NAMIC Wiki - User contributions [en]

File:AHM 2014 Engineering Now.pptx

2014-01-09T20:28:37Z

Aylward:

AHM2014-Engineering Updates

2014-01-09T20:26:41Z

Aylward:

[[AHM_2014#Agenda|Back to AHM_2014 Agenda]]

[http://cdn.knightlab.com/libs/timeline/latest/embed/index.html?source=0Aigzw56l1ZC-dHMwYWEzLW9tRFM1Sk5vbmZLU1FvNFE&font=Bevan-PotanoSans&maptype=TERRAIN&lang=en&hash_bookmark=true&height=850#0 NA-MIC Timeline]

* Retrospective from the entire program (Jim, [[Media:AHM 2014 Engineering Retrospective.pptx | Slides]])
** Highlights and watershed moments
* Accomplishments from the last year (Stephen, [[Media:AHM 2014 Engineering Now.pptx | Slides]])
** Highlights from 2013
* Plans for next 6 months (Steve)
** Mini-retreats: git big data, speed up slicer, overall cleanup of bug tracker
* Plans for after NA-MIC (Steve)

Engineering:Kitware

2013-04-03T23:41:31Z

Aylward: /* Overview of Kitware Projects (PI: Will Schroeder) */

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Stephen Aylward) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.jpg|200px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.jpg|200px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

File:NAMIC-Kit-Overview.png

2013-04-03T23:40:18Z

Aylward: uploaded a new version of "File:NAMIC-Kit-Overview.png"

Engineering:Main

2013-04-03T23:35:31Z

Aylward: /* Engineering Overview */

Back to [[Cores|NA-MIC Cores]]
__NOTOC__
= Engineering Overview =

The Engineering core, led by PI Will Schroeder (Kitware), is responsible for the software architecture, development, integration, and process for the center. Many software tools are being used and created by the engineering core, and a detailed discussion of these tools can be found [[NA-MIC-Kit|'''here''']]. Some of the licenses currently governing these tools are available here: [http://slicer.org/pages/License Slicer license], [http://www.itk.org/HTML/Copyright.htm VTK/ITK license].

{| style="background: #FFFFFF" cellspacing="10" align="right"
|
{| style="background: #cccccc" border="00" cellspacing="3" cellpadding="3"
|
{|
|+ <b>[http://wiki.na-mic.org/Wiki/index.php/NA-MIC-Kit NA-MIC Kit Architecture]</b>
|-
|
{|
| colspan="2" width="350px" align="left" valign="top" | [[Image:NAMIC-Kit-Overview.png|400px|Overall architecture of NAMIC Kit and key components.]]
|}
|}
{|
|+ <b>[http://wiki.na-mic.org/Wiki/index.php/NA-MIC-Kit Brain connectivity and tumor visualization for radiosurgery using 3D Slicer]</b>
|-
|
{|
| colspan="2" width="350px" align="left" valign="top" | [[Image:SlicerImage.png|400px|3D Slicer used for radiosurgery analysis.]]
|}
|}
|}
|}

= Engineering Projects - Organized by Site =

* [[Engineering:Kitware|Engineering Activities at Kitware]]
* [[Engineering:Isomics|Engineering Activities at Isomics]]
* [[Engineering:GE|Engineering Activities at GE]]
* [[Engineering:UCLA|Engineering Activities at UCLA]]
* [[Engineering:UCSD|Engineering Activities at UCSD]]
* [[Engineering:WUSTL|Engineering Activities at Washington University]]

= Engineering Projects - Joint Activities =

* [[Engineering:Core_Level_Activities|TCons and meetings]]

SlicerSummary

2013-04-03T23:34:18Z

Aylward: /* Development */

__NOTOC__
This page provides a summary of Slicer's role in the NA-MIC Toolkit. To learn more about Slicer or to download Slicer, click here to visit the [http://www.slicer.org Slicer Website].

[[Image:3DSlicerLogo-V-Color-201x204.png|right]]

== Overview ==
Slicer is a "point and click" end-user application. Slicer is used as a vehicle for delivering algorithms to computer scientists, biomedical researchers and clinical investigators. Slicer is distributed under an open source license without a reciprocity requirement and without restrictions on use. For a sampling of the portfolio of applications, please see the [http://www.slicer.org/pages/Slicer_Community '''Slicer Gallery'''] page. To get a list of the key features of slicer, please visit [[Slicer_Features|this page]].

== Slicer 4.1 (Current Release of Slicer) ==
[http://www.slicer.org/ '''Slicer 4.1'''] is a general purpose biomedical computing application with extensive built-in visualization and analysis capabilities, accessible through an easy to use graphical interface. For advanced users, Slicer may be extended at run-time with user-defined plug-in modules.

== Downloading Slicer ==
Visit [http://download.slicer.org Slicer.org] to download Slicer.

== Documentation, Tutorials and Examples ==
Visit the Slicer [http://wiki.slicer.org/slicerWiki/index.php/Training '''training'''] page to find tutorials for Slicer.

== History ==
The '''[http://www.slicer.org 3D Slicer]''' (or simply '''[http://www.slicer.org Slicer]''') software was initially developed as a joint effort between the [http://spl.harvard.edu/ Surgical Planning Lab at Brigham and Women's Hospital] and at the [http://csail.mit.edu/ MIT AI Lab]. The program has been extensively refactored by Kitware and Isomics under the direction of Ron Kikinis, and it has evolved into a national plattform, supported by a variety of federal funding sources. This versatile research environment has resulted in a wide array of functionality, supporting a variety of medical imaging projects.

[[Image:3DSlicer.png|right|100px]]

Legacy Slicer versions (including Slicer2) are available [[Slicer:Workshops:User_Training_101|here]].

== Development ==
Slicer is expected to evolve dynamically in architecture and implementation by drawing on the expertise and effort of a [[Engineering:Main | core engineering team]] as well as the wider [http://www.na-mic.org NA-MIC], NAC, [http://www.na-mic.org/Wiki/index.php/Collaboration:Harvard_CTSC Harvard Catalyst] and [http://www.ncigt.org NCIGT] communities. The NA-MIC software engineering methodology, as applied to the problems which Slicer has historically addressed, is expected to result in a cleaner architecture that is easier for developers to support and extend.

== Funding ==
Major funding for Slicer was provided through a variety of federal and private funding sources, including [http://www.ncrr.nih.gov/ NCRR], [http://www.nibib.nih.gov/ NIBIB], [http://nihroadmap.nih.gov/ Roadmap], [http://www.cancer.gov/ NCI], [http://www.nsf.gov/ NSF], [http://www.defenselink.mil/ DOD] and others.

== Role in NAMIC ==
NA-MIC is focused on developing Slicer, a multi-platform, free open source software (FOSS) for visualization and image computing.

== Platforms ==
Slicer runs on most Mac OS X, Linux and Windows platforms.

== Slicer Mailing lists ==
*'''slicer-users@bwh.harvard.edu'''

Questions about running Slicer can be sent to the [mailto:slicer-users@bwh.harvard.edu Slicer User's Mailing List]. Archives of slicer-users and subscription management tools are available at:

http://massmail.spl.harvard.edu/mailman/listinfo/slicer-users

*'''slicer-devel@bwh.harvard.edu'''

Slicer compilation/development questions can be sent to the [mailto:slicer-devel@bwh.harvard.edu Slicer Developer's Mailing List]. Archives of slicer-devel and subscription management tools are available at:

http://massmail.spl.harvard.edu/mailman/listinfo/slicer-devel

SlicerSummary

2013-04-03T23:31:12Z

Aylward: /* History */

__NOTOC__
This page provides a summary of Slicer's role in the NA-MIC Toolkit. To learn more about Slicer or to download Slicer, click here to visit the [http://www.slicer.org Slicer Website].

[[Image:3DSlicerLogo-V-Color-201x204.png|right]]

== Overview ==
Slicer is a "point and click" end-user application. Slicer is used as a vehicle for delivering algorithms to computer scientists, biomedical researchers and clinical investigators. Slicer is distributed under an open source license without a reciprocity requirement and without restrictions on use. For a sampling of the portfolio of applications, please see the [http://www.slicer.org/pages/Slicer_Community '''Slicer Gallery'''] page. To get a list of the key features of slicer, please visit [[Slicer_Features|this page]].

== Slicer 4.1 (Current Release of Slicer) ==
[http://www.slicer.org/ '''Slicer 4.1'''] is a general purpose biomedical computing application with extensive built-in visualization and analysis capabilities, accessible through an easy to use graphical interface. For advanced users, Slicer may be extended at run-time with user-defined plug-in modules.

== Downloading Slicer ==
Visit [http://download.slicer.org Slicer.org] to download Slicer.

== Documentation, Tutorials and Examples ==
Visit the Slicer [http://wiki.slicer.org/slicerWiki/index.php/Training '''training'''] page to find tutorials for Slicer.

== History ==
The '''[http://www.slicer.org 3D Slicer]''' (or simply '''[http://www.slicer.org Slicer]''') software was initially developed as a joint effort between the [http://spl.harvard.edu/ Surgical Planning Lab at Brigham and Women's Hospital] and at the [http://csail.mit.edu/ MIT AI Lab]. The program has been extensively refactored by Kitware and Isomics under the direction of Ron Kikinis, and it has evolved into a national plattform, supported by a variety of federal funding sources. This versatile research environment has resulted in a wide array of functionality, supporting a variety of medical imaging projects.

[[Image:3DSlicer.png|right|100px]]

Legacy Slicer versions (including Slicer2) are available [[Slicer:Workshops:User_Training_101|here]].

== Development ==
Slicer is expected to evolve dynamically in architecture and implementation by drawing on the expertise and effort of the wider [http://www.na-mic.org NA-MIC], NAC, [http://www.na-mic.org/Wiki/index.php/Collaboration:Harvard_CTSC Harvard Catalyst] and [http://www.ncigt.org NCIGT] communities. The NA-MIC software engineering methodology, as applied to the problems which Slicer has historically addressed, is expected to result in a cleaner architecture that is easier for developers to support and extend.

== Funding ==
Major funding for Slicer was provided through a variety of federal and private funding sources, including [http://www.ncrr.nih.gov/ NCRR], [http://www.nibib.nih.gov/ NIBIB], [http://nihroadmap.nih.gov/ Roadmap], [http://www.cancer.gov/ NCI], [http://www.nsf.gov/ NSF], [http://www.defenselink.mil/ DOD] and others.

== Role in NAMIC ==
NA-MIC is focused on developing Slicer, a multi-platform, free open source software (FOSS) for visualization and image computing.

== Platforms ==
Slicer runs on most Mac OS X, Linux and Windows platforms.

== Slicer Mailing lists ==
*'''slicer-users@bwh.harvard.edu'''

Questions about running Slicer can be sent to the [mailto:slicer-users@bwh.harvard.edu Slicer User's Mailing List]. Archives of slicer-users and subscription management tools are available at:

http://massmail.spl.harvard.edu/mailman/listinfo/slicer-users

*'''slicer-devel@bwh.harvard.edu'''

Slicer compilation/development questions can be sent to the [mailto:slicer-devel@bwh.harvard.edu Slicer Developer's Mailing List]. Archives of slicer-devel and subscription management tools are available at:

http://massmail.spl.harvard.edu/mailman/listinfo/slicer-devel

File:AHM2013-Engineering-ExtensionFramework.pptx

2013-01-10T13:59:16Z

Aylward: uploaded a new version of "File:AHM2013-Engineering-ExtensionFramework.pptx"

File:AHM2013-Engineering-ExtensionFramework.pptx

2013-01-10T13:48:46Z

Aylward:

AHM2013-Engineering Updates

2013-01-10T13:48:28Z

Aylward: /* Presentation Schedule */

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward, [[media:AHM2013-Engineering-Introduction.pptx|Slides]])
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward, [[media:AHM2013-Engineering-ExtensionFramework.pptx|Slides]])
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes from 2012 and for 2013 ==

These themes summarize engineering impact from the perspective of users and developers.

* Data handling
** DICOM
** Integration with Clinical Environments
* Components for development and deployment
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic,
* review changes since 2012 AHM
* summarize plans for 2013

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

AHM2013-Engineering Updates

2013-01-10T12:31:25Z

Aylward: /* Presentation Schedule */

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward, [[media:AHM2013-Engineering-Introduction.pptx|Slides]])
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward)
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes from 2012 and for 2013 ==

These themes summarize engineering impact from the perspective of users and developers.

* Data handling
** DICOM
** Integration with Clinical Environments
* Components for development and deployment
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic,
* review changes since 2012 AHM
* summarize plans for 2013

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

File:AHM2013-Engineering-Introduction.pptx

2013-01-10T12:27:47Z

Aylward:

AHM2013-Engineering Updates

2013-01-10T12:27:07Z

Aylward: /* Presentation Schedule */

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward, [[media:AHM2013-Engineering-Introduction.pptx|Slides]])
** Users and Developers
** Outline
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward)
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes from 2012 and for 2013 ==

These themes summarize engineering impact from the perspective of users and developers.

* Data handling
** DICOM
** Integration with Clinical Environments
* Components for development and deployment
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic,
* review changes since 2012 AHM
* summarize plans for 2013

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

AHM2013-Engineering Updates

2013-01-10T11:05:17Z

Aylward: /* Themes from 2012 */

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward)
** Users and Developers
** Outline
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward)
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes from 2012 and for 2013 ==

These themes summarize engineering impact from the perspective of users and developers.

* Data handling
** DICOM
** Integration with Clinical Environments
* Components for development and deployment
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic,
* review changes since 2012 AHM
* summarize plans for 2013

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

AHM2013-Engineering Updates

2013-01-10T11:04:34Z

Aylward: /* Themes */

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward)
** Users and Developers
** Outline
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward)
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes from 2012 ==

These themes summarize engineering impact from the perspective of users and developers.

* Data handling
** DICOM
** Integration with Clinical Environments
* Components for development and deployment
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic,
* review changes since 2012 AHM
* summarize plans for 2013

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

AHM2013-Engineering Updates

2013-01-10T10:59:10Z

Aylward:

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

== Presentation Schedule ==

* Introduction: (2min., Stephen Aylward)
** Users and Developers
** Outline
* Data and Clinical Interfaces (10 min., Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min., Jim Miller)
* Extension Framework (10 min., Stephen Aylward)
* Dynamic Coding: (10 min., Steve Pieper)
* Statistics and Summary (5 min.,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Themes ==

These themes can be addressed from both a user and developer perspective:
* Data
** DICOM
** Integration with Clinical Environments
* Components
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic:
* cover status and plans for the next year

== Areas of advancement in 2012 ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

== Metrics ==

* From bug tracker
*# open
*# closed
*# commits
*# bugs by type
*## category
*## type
*## severity
* From mailing list
** posts / activity
** users
** popular topics
* From svn/git
** contributors
** commits / commit timeline
** lines of code changed

AHM2013-Engineering Updates

2013-01-10T10:53:13Z

Aylward:

[[AHM_2013#Agenda|Back to AHM_2013 Agenda]]

==Schedule==
* Introduction: (2min, Stephen Aylward)
** Users and Developers
** Outline
* Data and Clinical Interfaces (10 min, Steve Pieper, [[media:AHM2013-Data+Clinical.ppt|Slides]])
* Components (10 min, Jim Miller)
* Extension Framework (10 Min, Stephen Aylward)
* Dynamic Coding: (10 Min, Steve Pieper)
* Statistics and Summary (5 Min,: Steve Pieper)
** Releases
** Statistics
** Lead into Extensions

== Discussion Topics ==

* Bug Squashing
* General Stability
* OpenCL
* Self Test
** Tutorials for RSNA
* Qt Testing
* Charting
* Multivolume
* Wizards (Python)
* Extensions
* MRBs
* Scene Views
* Annotations
* DICOM
* Linking Behavior
* Crosshairs
* Diffusion Interfaces
* Slice resolution pipeline
* Slice controller popups
* Volume Rendering
** GPU
** Interfaces

How these improvements were motivated by DBPs

Get metrics from bug tracker
# open
# closed
# commits
# bugs by type
## category
## type
## severity

Metrics on mailing list activity
Metrics from svn/git

==Themes==
These themes can be addressed from both a user and developer perspective:
* Data
** DICOM
** Integration with Clinical Environments
* Components
** User Experience Capabilities
** Extension Framework
* Code: Dynamic Coding Environment
** Coding Primitives
** Python

For each topic:
* cover status and plans for the next year

==Schedule==
* 2 min introduction: Stephen
** Users and Developers
** Outline
* 10 min Data and Clinical Interfaces: Steve [[media:AHM2013-Data+Clinical.ppt|Slides]]
* 10 min Components: Jim
* 10 min Extension Framework: Stephen
* 10 min Dynamic Coding: Steve
* 5 min Statistics and Summary: Steve (plus lead into Extensions)
** Releases
** Statistics

DBP3:UCLA

2012-11-19T17:17:40Z

Aylward: /* Completed */

Back to [[DBP3:Main|NA-MIC DBPs]] | [[Cores|NA-MIC Cores]]

=Introduction=

==What is traumatic brain injury?==
[[File:MP_RAGE_PRECONTRAST.png|200px|thumb|right|An example T1 weighted image from a patient with TBI]]
Traumatic brain injury, often referred to as "TBI", is most often an acute event that results in severe damage to portions of the brain. TBI results when the head suddenly and violently hits an object, or when an object pierces the skull and enters brain tissue. Symptoms of can be mild, moderate, or severe, depending on the extent of the damage to the brain. Common disabilities include cognitive deficits, sensory processing, communication, and behavior or mental health. Severe TBI may result in stupor where an individual can be aroused briefly by a strong stimulus (e.g. sharp pain); coma, where an individual is totally unconscious, unresponsive, unaware, and un-arousable; vegetative state, where an individual is unconscious and unaware of his or her surroundings, but continues to have a sleep-wake cycle and periods of alertness; and a persistent vegetative state, where an individual remains unresponsive for more than a month.

According to the CDC (United States Centers for Disease Control and Prevention), there are approximately 1.7 million people in the U.S. who suffer from a traumatic brain injury each year. 50,000 people die from TBI each year and 85,000 people suffer long term disabilities. In the U.S., more than 5.3 million people live with disabilities caused by TBI. Patients admitted to a hospital for TBI are included in this count, while those treated in an emergency room or doctor's office are not counted.
The causes of TBI are diverse. The top three causes are: car accident, firearms and falls. Firearm injuries are often fatal: 9 out of 10 people die from such injuries. Young adults and the elderly are the age groups at highest risk for TBI. Along with a traumatic brain injury, persons are also susceptible to spinal cord injuries which is another type of traumatic injury that can result out of vehicle crashes, firearms and falls. Prevention of TBI is the best approach since there is no cure or way to reverse brain damage of this kind.

==Mechanisms of TBI==
Understanding the various mechanisms of TBI can be helpful for the development of robust and reliable computational algorithms for neuroimage data processing. These mechanisms are the highest causes of brain injury: Open head Injury, Closed Head Injury, Deceleration Injuries, Chemical/Toxic, Hypoxia, Tumors, Infections and Stroke.

1. Open Head Injury
* Results from bullet wounds, etc.
* Largely focal damage
* Penetration of the skull
* Effects can be just as serious as closed brain injury

2. Closed Head Injury
* Resulting from a slip and fall, motor vehicle crashes, etc.
* Focal damage and diffuse damage to axons
* Effects tend to be broad (diffuse)
* No penetration to the skull

3. Deceleration Injuries (Diffuse Axonal Injury)
The skull is hard and inflexible while the brain is soft with the consistency of gelatin. The brain is encased inside the skull. During the movement of the skull through space (acceleration) and the rapid discontinuation of this action when the skull meets a stationary object (deceleration) causes the brain to move inside the skull. The brain moves at a different rate than the skull because it is soft. Different parts of the brain move at different speeds because of their relative lightness or heaviness. The differential movement of the skull and the brain when the head is struck results in direct brain injury, due to diffuse axonal shearing, contusion and brain swelling.

Diffuse axonal shearing: when the brain is slammed back and forth inside the skull it is alternately compressed and stretched because of the gelatinous consistency. The long, fragile axons of the neurons (single nerve cells in the brain and spinal cord) are also compressed and stretched. If the impact is strong enough, axons can be stretched until they are torn. This is called axonal shearing. When this happens, the neuron dies. After a severe brain injury, there is massive axonal shearing and neuron death.

4. Chemical/Toxic
* Also known as metabolic disorders
* This occurs when harmful chemicals damage the neurons
* Chemicals and toxins, e.g. insecticides, solvents, carbon monoxide poisoning, lead poisoning, etc.

5. Hypoxia (Lack of Oxygen)
* If the blood flow is depleted of oxygen, then irreversible brain injury can occur from anoxia (no oxygen) or hypoxia (reduced oxygen)
* This condition may be caused by heart attacks, respiratory failure, drops in blood pressure and a low oxygen environment
* This type of brain injury can result in severe cognitive and memory deficits

6. Tumors
* Tumors caused by cancer can grow on or over the brain
* Tumors can cause brain injury by invading the spaces of the brain and causing direct damage
* Damage can also result from pressure effects around an enlarged tumor
* Surgical procedures to remove the tumor may also contribute to brain injury

7. Infections
* The brain and surrounding membranes are very prone to infections if the special blood-brain protective system is breached
* Viruses and bacteria can cause serious and life-threatening diseases of the brain (encephalitis) and meninges (meningitis)

8. Stroke
* If blood flow is blocked through a cerebral vascular accident (stroke), cell death in the area deprived of blood will result
* If there is bleeding in or over the brain (hemorrhage or hematoma) because of a tear in an artery or vein, loss of blood flow and injury to the brain tissue by the blood will also result in brain damage

In this DBP, we will be primarily concentrating on #'s 1, 2, and 3.

==Neurological Concomitants of TBI==
Following TBI, a cascade of neuroanatomical alterations initiate, with diffuse alterations in cortical structure peripheral to the point of injury but also distributed throughout the brain. Notably, there is ventricular enlargement and cortical thickness changes remote from the site of the TBI. White matter connectivity can be significantly altered with greatly reduced efficiency of signal transduction over affected pathways or complete cessation of inter-regional communication due to axonal damage. This can have profound effects on speech, motor, and cognitive processes. The extent of change is putatively related to the severity of TBI, location, subject age, and post-injury treatment, among other factors.

==Challenges of TBI Neuroimaging==
On anatomical MRI scans, TBI-related insults can appear as hyper-intensities, varying in magnitude and extent the degree to which tends to correlate with clinical symptoms. Additionally, in severe TBI, sections of skull, fractured during the injury or removed during surgical intervention, may not form a contiguous boundary enabling efficient digital removal of bone and other non-brain tissues, complicating tissue segmentation, regional parcellation, the measurement of ventricular size, cortical thickness, and other metrics. Computational algorithms require refinement to include constraints to account for TBI related signal alterations in anatomical scans; e.g. users may have to manually indicate regions encompassing the site of injury on the scans to guide local processing around the site and to reduce the weight of these regions on other, non-affected brain areas. Alternatively, probabilistic classifiers may need to include an extra classification for voxels whose tissue properties have been altered by TBI. This is particularly the case in diffusion weighted imaging (DWI) where the presence of TBI-related alterations in signal may reflect specific damage to white matter proximal to the lesion as well as long reaching effects along tracts to peripherally connected regions of cortex.

=Project Goals and Specific Aims=

==Project Goals==
An increasingly relevant means for the neurological assessment of traumatic brain injury (TBI) is with in vivo neuroimaging. However, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury. Multimodal quantification of brain insults and associating these with clinical and outcome metrics is a particular challenge. The emphasis in this DBP is placed on the feasibility of subject-specific analysis, as opposed to population-based averaging, to examine the influence of TBI on time-dependent alteration of gray and white matter integrity with accompanying change in clinical outcome variables to be used in subsequent TBI assessment. This DBP [http://www.na-mic.org/pages/DBP:TBI] seeks to:

1. Develop end-to-end processing approaches using the NA-MIC Kit to investigate alterations in cortical thickness, and subsequent ventricular and white matter changes in patients with TBI and in age-matched controls. Image processing will include segmentation of lesions, hemorrhage, edema, and other pathology relevant to TBI. Longitudinal changes will be assessed by registration and joint segmentation of baseline and follow-up data.

2. Develop robust workflows for diffusion weighted imaging (e.g. DTI, HARDI) datasets from TBI patients, by using the NA-MIC Kit and Slicer to obtain reliable and robust metrics of white matter pathology and of white matter changes due to therapy and/or recovery.

3. Using the NA-MIC Kit, cross-correlate multimodal metrics of cortical thickness, complexity, ventricular volume, and lesions from structural imaging and white matter fiber integrity from diffusion tensor imaging, with clinical outcome variables, i.e., time since injury, age, gender and other potential factors predictive of recovery.

==Specific Aims==
In this NA-MIC DBP, we seek to develop the means for guided and semi-automatic TBI analysis and quantification with a view toward assessing clinical improvement under the following Specific Aims:

===Aim 1===
How can multimodal assessment of altered brain anatomy speak directly to questions of brain plasticity and to secondary neuroanatomical effects of TBI?

We will develop end-to-end processing approaches using the NA-MIC Kit to investigate alterations in cortical thickness, subsequent ventricular, and white matter changes in patients with TBI and in age-matched controls.

===Aim 2===
Can multimodal workflows be developed to guide clinicians in the analysis and display of white matter fiber tract pathology that frequently accompanies brain insult?

In diffusion weighted imaging (e.g. DTI, HARDI) datasets from TBI patients, we will develop robust workflows using the NA-MIC Kit and Slicer to obtain reliable and robust metrics of white matter pathology.

===Aim 3===
How can multimodal metrics of TBI grey and white matter pathology be utilized to inform and guide clinical assessment?

Under this DBP, using sophisticated NA-MIC tools, we will develop end-to-end processing solutions by which to examine TBI neuroimaging data. The NA-MIC Kit encompasses a collection of tools for automated or semi-automated processing of medical imaging data. Notable is the Insight Toolkit (http://www.itk.org) for use in brain registration and segmentation via the 3D Slicer (http://www.slicer.org) software platform. These software tools may be linked to form data processing workflows that can process data via end-to-end solutions that may be shared with others, posted on websites, and used in training materials. They form an excellent platform for user-guided, patient-specific analysis, however, require additional development to inform the program about regions where TBI-related signal changes may necessitate alteration of model parameters or search volumes. Using the NA-MIC Kit, multimodal metrics of cortical thickness, complexity, and ventricular-volume from structural imaging and white matter fiber integrity from diffusion tensor imaging will be cross-correlated with clinical outcome variables, time since injury, age, gender and other potential factors predictive of recovery. We will emphasize the feasibility of subject-specific analysis, as opposed to population-based averaging, to examine the influence of TBI on time-dependent alteration of gray and white matter integrity with accompanying change in clinical outcome variables to be used in subsequent TBI assessment.

This DBP directly pertains to stated scientific and funding objectives of the NIBIB and other NIH institutes conducting (e.g. NINDS) and supporting (e.g. NCRR) research on the mechanisms underlying CNS injury; to develop intervention strategies to limit the primary and secondary brain damage occurring within days of a TBI; and to devise therapies to treat TBI and help in long-term recovery of function. DBP results will have important implications for national health policy concerning TBI awareness, treatment and brain plasticity. Thus, this DBP is directly in-line with the NIH mission for greater assessment of neurological insults and factors that predict long-term outcomes in individual patients.

=Methods=

==Software and Analysis Protocol==
We will specifically adopt the NA-MIC kit open source software platform consisting of Slicer, tools and toolkits such as VTK and ITK, and software engineering methodologies for multiplatform implementation. Using ITK, data will be intensity normalized and bias-field corrected; tissue types will be segmented interactively to assist probabilistic classification; cortical thickness will be determined along the entire cortical sheet as the linear distance between the outer edge of the cortical surface and the grey-white matter boundary. Ventricular size will be determined by a space filling algorithm, while shape will be characterized using LONI tools for shape decomposition and quantitative description. DWI processing routines will be developed to better account for TBI-related changes in diffusion metrics. Results from multimodal analyses will be visualized using VTK, Slicer, and other suitable platforms.

==Anatomical Data==
To rigorously assess workflows using the NA-MIC Kit, we will examine neuroimaging data obtained from TBI patients. MRI volumes from 202 subjects will be drawn from the LONI Image Data Archive (IDA), a comprehensive neuroimaging data archive comprised of a number of funded projects. Samples will include patients who have suffered from TBI (N=160; 22F:138M) and age-matched normal controls (N=42; 13F:29M). Mean±sd ages for males is 33.8±9.2 and for females is 33.6±9.9. T1-weighted whole brain MPRAGE volumes, T2, and, in subjects with available data sets, diffusion weighted imaging (DTI/HARDI) collected at 1.5 and 3.0T will be utilized. Additional data include a variety of MR imaging modalities and NA-MIC workflows will be crafted to accommodate them.

==Expected Results==
Multimodal results will be obtained using Slicer software tools, specifically developed under NA-MIC using ITK, VTK, for the analysis of neurological concomitants of TBI. Metrics will be extracted and imported into purpose built software for univariate and multivariate modeling to provide additional insights to that of previous work on the role of neuroanatomical changes occurring in TBI on outcome variables predicting degree of change and/or recovery. Several primary hypotheses using individual and repeated imaging include:

1. Cerebral atrophy (regional and global) occurs at a faster rate in diffuse vs. focal TBI;

2. Rates are dependent upon initial injury severity

3. Ongoing or progressive change continues up to 1 yr post-TBI

4. Secondary insults increase the rate and extent of the initial TBI

We will also examine age-at-lesion effects, since these factors are likely to impact on measures of the degree of loss of developmental and life-span neuroplasticity believed to follow TBI. Using DWI data, we will assess the effects of TBI on mean diffusivity, fractional anisotropy, and their potential as clinical outcome correlates. Complete multimodal data processing solutions using the NA-MIC Kit and associated tools will be made openly available, with accompanying training materials via the NA-MIC web site, and comply with the NA-MIC open-source policies.

==Clinical Utility==
The emphasis from the NA-MIC KIT workflows developed under this program will be on the application of the NA-MIC tools to TBI clinical practice and patient monitoring. With knowledge of general location, extent, and degree of change, such metrics can be associated with clinical measures and used to suggest viable treatment options for a subject against patterns typical of TBI patients.

=Current Tasks=
Considerable interactions presently exist between the NA-MIC project and LONI, resulting in numerous peer-reviewed publications. This shows the suitability of these teams to work jointly under this proposed project. Computational outcomes from this DBP will also directly contribute to other NA-MIC DBPs involving

1. mapping head and neck radiation therapy

2. tracking MRI brain changes in Huntington’s Disease

3. segmenting cardiac MR atrial wall ablations in arrhythmia patients.

UCLA investigators will interact directly with NA-MIC Core 1 and 2 PIs in developing new and refining existing processing algorithms for addressing the issues inherent to neuroimaging data from TBI patients (YR1). DBP activities at UCLA will occur in consultation with the Primary Technical NA-MIC DBP Contact and the Algorithm and Engineering Contact. Once completed and rigorously validated these workflows will

1. be applied to the TBI patient data described above (YR1-2)

2. be made available for open dissemination via the NA-MIC website (YR3)

3. form the basis for training and educational materials for NA-MIC investigators and the TBI community (YR3)

Results will be featured in presentations at scientific conferences, organized training events/workshops, etc., as a way to disseminate tool capabilities and, where possible, tutorials on how to use the NA-MIC technology for other TBI-related projects. We will attend each NA-MIC All-Hands-Meeting to discuss the DBP with NA-MIC PIs, report on developments, and progress. NA-MIC will benefit from this DBP by exposure to a unique community that often possesses multisite neuroimaging clinical trials data.

==Case Analysis Goals==
* Multimodal registration within and between scan sessions separated by ~6 months
* Computation of neuroanatomical measures of change per unit time in each case
* Visualization of 3D models and their degree of change
* Quantification of alterations in ventricle and WM/GM volume, surface, cortical thickness, and other morphological metrics at time 1 and time 2
* Ability to quantify changes in diffusion local to the lesions as well as overall mean FA and fiber patterns between scan sessions
* Generation of a clinical report for each TBI patient. The clinician should have the ability to store such a report and use it in conjunction with their neurological assessments to gain insight about the case. It would be nice if that report could be generated not only in printer-friendly format but also in XML (or similar format) so that it can be read without much trouble into Matlab, R, or other secondary analysis frameworks or databases.
* Semi-automatic segmentation. Certain aspects of image segmentation segmentation may need to be user-guided (e.g. to conditionalize segmentation given the presence of a lesion), though in a way that is easy for clinicians to use. The user might point and click on an area exhibiting a bleed, or some other type of hypo-/hyperintesity. A boundary contour could then be found around that area, and the segmentation model would then be weighted by the presence of that area as some unique tissue type.
* Creation of population-based atlases from multiple TBI subjects or at least reference to standardized coordinate systems

==Software Requests==
* The UCLA team would like to have Windows compilations of (1) the Longitudinal Lesion Comparison and (2) the Lesion Segmentation Applications Modules.

==Specific Tasks In Progress==
Specific tasks include the following, in reverse chronological order:

* There is some interest in a macro capability to record selections for later playback
* Full brain fiber tractography
* NIFTI 4D file read/write, external gradient information importation, and a gradient table editor for DTI
* Better interoperability between LPS/RAS file organization in Slicer vs. vTK
* Ability to set direction cosines directly in Slicer volumes module
* Timed autosave functionality of scene files and other filetypes fundamental to Slicer (saved for several time steps)
* Welcome screen should be a pop-up window in the middle of screen that could be disabled
* Integration of volume render with slice displays (rendering set aside as an option)
* Import tools for DTIStudio and TrackVis tractography files
* Creating 3D ROIs using the edge detection routine
* Use of customizable toolbars for commonly used operations/features/modules/workflows/etc
* Volumes shouldn’t be loaded differently from “other data”
* Screen shot functionality shouldn’t force a re-render
* Being able to record video sequences (at least we couldn’t readily find this capability)
* NIFTI fMRI processing capability (3D+time)

==Completed==
* 2010-Dec-20. ABC module has been successfully compiled for Windows and tested (use Slicer nightly build for best results). Our thanks to Marcel and to the Utah team!
* 2011-Jan. TubeTK implementation of slicing organ registration made available in Slicer4 at AHM in Salt Lake City
* 2011-Oct. Geometric Metamorphosis presentation at MICCAI 2011
* 2011-Oct. Sliding organ registration presented at Abdominal Imaging workshop at MICCAI 2011
* 2012-Jan. CalaTK implementation of geometric metamorphosis for registration in the presence of lesion infiltration/recession released
* 2012-Oct. Sliding organ journal article submitted to IEEE Transactions on Medical Imaging

==Data==
* Need to obtain CT and PET for each example case (Jack Van Horn, UCLA TBI team)

=Results=

==Sample Data Sets==
[[File:ThreeSubjects.png|200px|thumb|right|Sample images from the three TBI cases]] '''IMPORTANT NOTE: Use of these data for inclusion in peer-reviewed publication is provided contingent on appropriate recognition of the following UCLA investigators as study co-authors: Andrei Irimia, Micah C Chambers, Jeffry R Alger, Paul M Vespa, John D Van Horn.'''
* [[File:TBI Patient1 nrrd3.zip]]
* [[File:TBI Patient2 nrrd2.zip]]
* [[File:Patient3_DTI_nrrd_files.zip]]
* [[File:Patient1 UCLA 3T.zip]]
* [[File:Patient2 UCLA 3T.zip]]
* [[File:Patient3 UCLA 3T.zip]]
* [[File:Patient3_UCLA_CT.zip]]
* [[File:UCLA_1_5T.zip]]
* [[File:UCLA_3T.zip]]

==Sample Slicer Results==
[[File:Slicer_TBI_render1.png|200px|thumb|right|Example TBI results from Slicer]]
The following PDF contains a presentation prepared by Dr. Guido Gerig which showcases some example results on the above TBI data sets obtained using existing and newly developed Slicer processing modules.

*[[File:NAMIC-TBI-Nov-2010-compr.pdf]]

==TBI Results at UCLA==
[[File:2010-01-05-P3-collage.JPG|200px|thumb|right|ABC segmentation results for TBI Patient No. 3 from UCLA.]]
The ABC module in 3D Slicer has been applied to segment the anatomic MR volumes for Patients 1-3 in the Sample Data Sets section. In the adjacent figures, sample images of the segmentations for Patient 3 (both acute baseline and follow-up) are shown. In the first image, the WM and GM segmentations are shown for the acute baseline and follow up scans of Patient 3. We have found that, for this TBI patient, the ABC segmentation is superior to that of the EMSegmenter Module and we are excited about the ability of ABC to capture the neuroanatomical outliers of these challenging data. Many of the items of concern that remain concerning the quality of the segmentation might be addressed using suitable modifications of input parameters to ABC. For example, there seems to be some inconsistency between scans in the reconstructed gyrification of the cortex and extent of the GM/WM interface (see arrows, first and third columns). We are looking forward to learning more about the effective use of ABC to avoid these problems.

[[File:2010-01-05-P3-slicer.JPG|200px|thumb|right|Comparison of TBI acute baseline and follow-up MR volumes and segmentations for UCLA Patient No. 3.]]
From the second figure it can be inferred that, in the case of the acute baseline scan, ABC may have failed to include the lesion in the temporal lobe as part of the WM volume. This did not occur during the segmentation of the volume acquired during the follow-up scan, where this region seems to have been more appropriately segmented (see arrows).

===Longitudinal comparison of TBI using Slicer 3.6===
Few non-commercial software tools are available to help clinicians analyze and solve problems of quantitative analysis and visualization. Problems on which there has been significant progress up to this point include data processing challenges, problems recognizing acute versus chronic phases of traumatic brain injury, establishing the means of performing more sensitive quantification of change, and determining extent of cortical and ventricular injury, amount of white matter injury and axonal damage and the means of associating change TBI morphometry over time with clinical outcome.

To date, the UCLA team has successfully performed co-registration of several baseline and follow-up TBI volumes, classification of healthy and injured tissues, as well as longitudinal analysis of TBI cases. Specifically, we have introduced the combined the use of multimodal TBI segmentation and longitudinal analysis using 3D Slicer. For three representative TBI cases, semi-automatic tissue classification and 3D model generation have been performed to assess longitudinal TBI evolution using multimodal volumetrics and clinical atrophy measures. Identification and quantitative assessment of extra- and intra-cortical bleeding, lesions, edema and diffuse axonal injury was also performed. 3D Slicer tools have been used to perform cross-correlation of multimodal metrics from structural imaging (structural volume, atrophy measurements, etc.) and with clinical outcome variables (time since injury, age, gender, etc.) and other potential factors predictive of recovery.

3D Slicer workflows have been found to be suitable for TBI clinical practice and patient monitoring, particularly for assessing damage extent as well as for the measurement of neuroanatomical change over time. With knowledge of general location, extent, and degree of change, such metrics computed in 3D Slicer can be associated with clinical measures and subsequently used to suggest viable treatment options for individual subjects against patterns that are typical TBI populations. Thus, the methodology that has been demonstrated up to this point using the 3D Slicer platform has the potential for significant impact upon the state of the art in TBI neuroimaging as well as upon the added benefit of TBI neuroimaging techniques from the standpoint of clinical monitoring, diagnosis and treatment.

Shown below are four images that are illustrative of this procedure for Patient 3 (MR and CT data available for download from above). A more comprehensive description of this analysis will very soon be made available in a manuscript to be submitted for peer review.
[[File:Patient3_acute_baseline.png|170px|thumb|left|Segmentation of acute baseline volume for UCLA Patient 3. Legend: Gray matter - blue (transparent); ventricular system - purple; extracerebral lesions - green; nonhemorrhagic cerebral lesions - yellow; hemorrhagic cerebral lesions - red.]]
[[File:Patient3_chronic_followup.png|170px|thumb|left|Segmentation of chronic follow-up volume for UCLA Patient 3. Legend as in acute baseline figure.]]
[[File:Patient3_GM_comparison.png|170px|thumb|left|Longitudinal comparison of acute baseline (red) and chronic follow-up (red) gray matter volumes. Swelling of the left hemisphere is apparent in the acute baseline compared to follow-up.]]
[[File:Patient3_ventricles_comparison.png|170px|thumb|left|Longitudinal comparison of acute baseline (AB, red) and chronic follow-up (CF, red) volumes associated with the ventricular system. As illustrated by the relative positioning of the AB and CF ventricular 3D volumes, swelling due to the primary injury in the left hemisphere has shifted the ventricles to the right in the AB.]]

In conclusion, although the UCLA team is only 4 months into the first year of participating in the NA-MIC project, we have not only already fulfilled all specific aims for Year 1, but also made a significant amount of progress beyond these aims.

===3D Slicer as a software platform for TBI===

To address the urgent need for clinician-friendly TBI analysis tools, we have combined the use of multimodal, semi-automatic TBI analysis methods within 3D Slicer. To showcase the ability of the UCLA team to perform quantitative longitudinal analysis of TBI in 3D Slicer, we have analyzed three cases of semi-automatic TBI volume segmentation and 3D brain model generation while also highlighting the added clinical insight which 3D Slicer can offer.

Slicer 3 has the capability of providing visual assessment of multimodality imaging of 3D fiber tracts and morphometry in TBI. It provides the possibility for potential identification of specific targets for neurological testing enabling the clinician or researcher to deploy tests based on hypotheses derived from image analysis. Ultimately, through a more principled approach, quantitative assessments can be made.

Over the past 4 months, the UCLA team has developed a sophisticated protocol for image segmentation and model generation, which has been applied to three representative TBI patients with spectacular results. This standard protocol has been confirmed to be optimal for TBI case analysis in 3D Slicer. Specifically, brain lesions adjacent to CSF were segmented from volumes acquired using FLAIR, GRE imaging, TSE T2-weighted volumes as well as DWI. Because SWI is generally superior to GRE and T2-weighted imaging to detect hemorrhagic lesions, volumes acquired using the former modality were used to identify micro-hemorrhages. Images that were additionally available in the context of our protocol were used to confirm segmentation accuracy as well as to illustrate the additional capabilities of 3D Slicer to segment images from a variety of MR data sets and combination of sequences.
Throughout the past several months, the UCLA team has demonstrated the usefulness of semi-automatic segmentation tools available in 3D Slicer software, including the Atlas Based Classification (ABC) segmenter. As opposed to other specialized segmenters where access is often restricted from outside users, the ABC segmenter is freely available as a segmentation module in 3D Slicer. The method is automatic, its execution requires minimal user supervision, and its appropriateness for TBI case analysis is excellent. In addition, the ABC segmenter possesses the ability to perform co-registration of an arbitrary number of MR volumes acquired using various sequences. This makes ABC highly suitable to the UCLA multimodal TBI imaging paradigm, where as many as 12 distinct sequence types are employed in the context of a sophisticated TBI analysis protocol.
At UCLA, tissue-type segmentation has already been used to calculate the total volumes of selected structure types (ventricular system, non-hemorrhagic lesions, and hemorrhagic lesions, white matter and gray matter). Volume changes have been computed as the ratio of the difference in volume between the follow-up and acute baseline time points, to the volume at the latter time point. In addition to these measures, the UCLA team has also computed five measures of atrophy, namely the bifrontal index, the bicaudate index, Evan’s index, the ventricular index and Huckman’s index. These measures as computed in Slicer have been found to be in excellent agreement with previous results available in the TBI literature.

In conclusion, over the past 4 months, we have used Slicer 3 to perform multimodal data fusion (linear co-registration, segmentation using ABC, etc.). Tissue classification with normal atlas prior, deformable (fluid) atlas to subject registration, as well as segmentation of lesions, bleedings, shunts has also been performed.

===Resolving the temporal evolution of TBI-related brain atrophy in 3D Slicer===

Despite appreciable recent efforts to integrate advanced neuroimaging analysis with existing methodologies for TBI treatment, there has been insufficient progress in combining personalized case description and characterization with surgical and neuro-intensive care methods. Specifically, an important challenge encountered in the attempt of performing such integration is the difficulty of determining how each subject’s lesion profile modulates brain atrophy, and how these changes lead to behavioral, cognitive and neural dysfunction. In TBI, significant additional difficulties exist because (1) damage is often inflicted upon more than a single functional area, and additionally because (2) injuries can affect brain regions and structures whose detailed functions have not been studied and quantified as rigorously as those mentioned above. The pervasive presence of diffuse axonal injury (DAI) in TBI can lead to additional functional changes which are strongly modulated by white matter (WM) connectivity and which can be very difficult to quantify. For these reasons, TBI is considerably more challenging to study than many other conditions of the diseased brain, both methodologically and conceptually. One area of progress for the UCLA DBP group involves a methodological framework for patient-tailored structural characterization of TBI-related brain atrophy which combines magnetic resonance imaging (MRI) with image processing methods to perform patient-specific longitudinal analysis of TBI brain morphometry. These methods can be used to determine how atrophy differentially affects the TBI brain depending on injury location, and how such atrophy evolves longitudinally compared to normative samples of healthy adults. This contribution provides proof of concept in favor of the fact that our methods implemented via 3D Slicer can substantially aid in the process of pursuing such hypothesis-driven research.

===EEG/MRI source localization in TBI patients===

Though an appreciable number of traumatic brain injury (TBI) patients with post-traumatic epilepsy (PTE) may benefit from epileptogenic focus removal, the localization of epileptic foci remains difficult in PTE. This difficulty is partly due to the complexity of TBI-related structural brain changes, and is currently seen as deterrent to surgery. One area of progress by the UCLA DBP group involves determining the effects of TBI-related pathology upon EEG source localization accuracy in acute TBI. Realistic models of the head with 25 tissue types (including 6 types accounting for TBI pathology) are generated using 3D Slicer based on multimodal MRI via the finite element method (FEM). This research involving 3D Slicer has helped us to determine that TBI-related changes in the conductivity profile of the head can have appreciable effects upon EEG source localization, and that such changes should therefore be accounted for when performing forward/inverse modeling.

=Outreach=
Our outreach goals include:
* [[media:TBIDataAnalysis_SoniaPujol.pdf | TBI Cases]] [http://www.na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C31 TBI Registration Case Library]
* Develop comprehensive tutorial/how-to guide
* Design user friendly TBI workflow interface for Slicer
* Presentations/posters at OHBM, SFN, and other (inter)national meetings in year 2
* Hands-on teaching event for the DBP scientific community for year 3
* Peer reviewed publications

==Outreach Events==

===UCLA Neurology Science Day (January 2011)===

The UCLA Department of Neurology held its Third Annual Neurology Science Day on Wednesday, January 26, 2011. During the Poster Session, Andrei Irimia presented a poster to the Neurology Faculty at UCLA.

[[File:Irimia-UCLA-Neurology-Day-poster.pdf|200px|thumb|right|UCLA Neurology Science Day Poster]]

===TBI DBP Meeting at NA-MIC AHM (January 2011)===

The UCLA and SCI teams had several fruitful and friendly meetings during the All Hands Meeting in Salt Lake City. The first of these meetings was attended by about 30 researchers, including Guido Gerig, Marcel Prastawa, Bo Wang, Sylvain Gouttard, Andrei Irimia, Micah Chambers, Stephen Aylward, Hans Johnson, and their teams. This part of the meeting focused on how Slicer tools can be used to study pathology, with a focus on Huntington Disease and TBI. In the opening of the meeting, Guido raised the question of what Slicer tools are already available to assess longitudinal changes. Hans Johnson expressed his interest in Slicer and commented on the possible activity of using the platform for the development of clinical trials.

For the TBI project, the Utah team is interested in obtaining radiological TBI case descriptions from UCLA radiologists and in having more input from UCLA as to how various types of TBI images (e.g. Flair, GRE bleed, etc.) should be interpreted. Such radiological case descriptions would allow one to better interpret TBI data and to determine the class of pathology to which various features belong, based on a comparative examination of different scans. Another request from the Utah team is to have patient histories for the subjects that we provide for them. They would like to use this information in conjunction with the case descriptions to learn more about the type of lesions that they are studying, and to obtain a sense of how the patient history and case evolution is reflected in the anatomical changes that are apparent from the scans.

One concern that was expressed regards the ability of this project's time frame to accommodate both algorithm development as well as the development of clinically oriented tools and measures which require the output of the former from the very beginning. For example, we need to develop longitudinal analysis tools but the algorithms to do TBI segmentation are a prerequisite to this, although it may take years to develop the latter. Andrei pointed out to the possibility of using mild TBI cases in the beginning in order to develop longitudinal analysis tools, while the Utah team is developing more complex and robust methods that can handle difficult cases.

Five goals of clinical interest were discussed during the meetings, namely (1) the ability to do TBI tissue classification, (2) the ability to perform volumetric analysis to allow for neuroanatomic assessment, (3) the ability to track the fate of lesions and pathology using automatic segmentation, (4) the ability to generate quantitative output in the form of a report to demonstrate that the use of imaging correlates with improvement in outcome scores, and (5) the ability to easily quantify WM tract distortion and change, as well as how this distortion evolves over time.

One item that was pointed out to the entire audience is that the focus of Slicer is on subject-level rather than population-level analysis, in spite of existing clinical interest in performing statistical studies of population groups. However, one item which clinicians would find appealing is precisely the ability to compute anatomical measures at the subject level, particularly because these subject-level measures can then be used for population-level statistical analysis outside Slicer. Although such population-level analyses may not be within the scope of Slicer, it may be useful to take their specifications into account in the context of formulating goals and strategies for the collaboration.

ABC segmentations of TBI volumes were reviewed in a separate session at the meeting, and a number of plans for the future were formulated. One item that was discussed was the selective use of image channels to perform TBI segmentation. Depending on the type of pathology that is the subject of focus, it may be of interest to include in the segmentation process only those scans in which the pathology is most obvious. The two teams decided to collaborate on how best to accomplish this.

A number of technicalities related to ABC and to segmentation in general were discussed, with the end conclusion being that the results thus far generated with ABC can probably be much improved upon after some exploratory analysis. Team members agreed to keep in touch by email, phone, teleconference, etc. It was agreed upon that there should be some type of periodical face-to-face interaction between the teams at UCLA and SLC, possibly every several months.

===TBI DBP Conference Call with Utah Team (September 9, 2011)===

The UCLA and Utah teams had a productive conference call on September 9, 2011. All progress up to this date was reviewed, including (1) integration of MRI Watcher into Slicer, (2) the upcoming version of Slicer in QT, (3) the conference paper that was submitted to SPIE, and (4) the availability of CT data for TBI patients. The two teams also reviewed various technical items, including (5) the calculation and display of Jacobian deformation maps for TBI between acute and chronic time points for use by clinicians, (6) the issue of how to address changes in topology between time points, (7), possible relaxation of diffeomorphic constraints for the purpose of quantifying the deformation field, (8), the step-by-step TBI tutorial that was presented by Andrei Irimia at the Boston June Meeting, (9) possible future coordination between the Utah and UNC/Kitware/GA Tech teams. The overall conclusion from the meeting was that much progress has been achieved this year and that we are looking forward to presenting our accomplishments in Salt Lake City at the Annual All-Hands Meeting.

===NA-MIC Conference Call (October 27, 2011)===

During the NA-MIC conference call with Dr. Kikinis and his team at BWH, Dr. Van Horn highlighted our excellent research progress throughout the past year, including publication of a paper in the Journal of Neurotrauma that uses Slicer, one publication accepted for MICCAI 2012 based on a study directed by Guido Gerig at the University of Utah, two manuscripts on TBI geometric metamorphosis based on research directed by Stephen Aylward from Kitware, one paper based on research directed by Yifei Lou and Allen Tannenbaum on deformable registration, and other conference abstracts and posters.

===TBI DBP Conference Call (November 10, 2011)===
A conference call was held with the Kitware, GA Tech and Utah teams regarding activities planned for the NA-MIC All Hands Meeting in Salt Lake City. While there, the three teams will collaborate on atlas based classification, nonrigid registration algorithms, and on several manuscripts in progress.

===NA-MIC Conference Call (November 16, 2011)===
Dr. Van Horn had a conference call with Tina Kapur regarding the upcoming meeting in January. Our recent progress was highlighted, including the publication of a paper in the Journal of Neurotrauma, conference abstracts and proceedings, posters and other activities.

===UCLA visit by Dr. Guido Gerig from Univ. of Utah (May 22, 2012)===
Dr. Guido Gerig visited UCLA and presented his group's research to members of LONI as well as to Dr. Paul Vespa and to his colleagues at the Neurointensive Care Unit (NICU) of the UCLA Ronald Reagan Medical Center. The two groups discussed the application of Dr. Gerig's TBI registration algorithms to the UCLA data, and brainstormed with regard to possible avenues for future collaboration. It was decided to share additional data between the two groups as they become available. Dr. Gerig also met with Dr. Arthur Toga at the LONI and with Dr. Jeff Alger at the Brain Mapping Center. This was a very welcome and excellent visit that resulted in much progress with regard to future work by the two groups.

=Investigators=
UCLA
* John Darrell Van Horn, M.Eng., Ph.D. - Principal Investigator of the DBP
* Andrei Irimia, Ph.D. (DBP engineer, postdoctoral scholar) [http://www.andrei-irimia.com]
* Micah Chambers, M.S. (graduate student)
* David Hovda, Ph.D. (investigator)
* Paul Vespa, M.D., F.C.C.M., F.A.A.N. (investigator)
* Arthur W. Toga, Ph.D. (investigator)
* Jeffry Alger, Ph.D. (investigator)
University of Utah
* Guido Gerig, Ph.D. (lead technical contact)
* Marcel Pastrawa, Ph.D. (research scientist)
* Sylvain Gouttard, M.S. (postdoctoral scholar)
* Bo Wang, B.S. (graduate student)
Kitware/UNC Chapel Hill
* Stephen Aylward, Ph.D. (director of medical imaging)
* Danielle Pace
* Martin Styner, Ph.D. (lead algorithm and engineering contact)
Boston University
* Allen Tannebaum, Ph.D. (Principal Investigator of the Algorithm Core)
Harvard Medical School
* Ron Kikinis, M.D. (Principal Investigator)
* Sonja Pujol, Ph.D.

=Awards, Honors and Accomplishments=

* Research using 3D Slicer was honored with the Mazziotta Prize awarded to Andrei Irimia for excellence in postdoctoral research in the field of neurology
* Review on the use of 3D Slicer for TBI outcome prediction was selected as the inaugural article published by NeuroImage: Clinical
* Over 10,000 downloads of the PLoS ONE research article co-authored on Phineas Gage by the UCLA group and featuring 3D Slicer
* Research involving 3D Slicer performed by the UCLA group on Phineas Gage was featured extensively as main article by Discover Magazine
* Andrei Irimia received the Young Investigator Award from the American College of Neuropsychopharmacology (ACNP) for work in 3D Slicer (given to only 10 out of 200 applicants in 2012)
* Connectomics visualization and work in 3D Slicer by the UCLA group was featured at the Ars Electronica 2012 Conference in Linz, Austria
* Andrei Irimia was awarded a research travel fellowship by the Brain Injury Research Center at UCLA for his TBI research in Slicer
* Travel scholarship was awarded to Andrei Irimia for presenting 3D Slicer research at the Dynamics Days 2012 conference in Baltimore, MD
* Scientific visualizations based on 3D Slicer featured in the 2012 and 2013 calendars of the UCLA Brain Research Institute
* TBI work in 3D Slicer is recognized at the research competition finalist stage (top 15 of 400 participants) at the Neurotrauma Symposium, Phoenix, AZ
* Andrei Irimia was awarded a scholarship to attend the Neurotrauma Symposium in Phoenix, AZ to present his Slicer research (top 10 of 390 applicants)
* Article by UCLA group on 3D Slicer was featured in the top 12 most downloaded articles published by the journal NeuroImage
* Andrei Irimia was selected as research competition finalist for his TBI research in Slicer from among 390 participants at the Neurotrauma Symposium
* Andrei Irimia obtained the First Prize in the Summer Tutorial Contest of the National Alliance for Medical Image Computing [http://www.na-mic.org/Wiki/index.php/TBISegmentation_TutorialContestSummer2011]
* Andrei Irimia's visualization of TBI using Slicer has been selected to be featured on the cover of the Journal of Neurotrauma for a special issue on bioengineering for TBI
* Andrei Irimia was awarded the first prize in the Fine Science Award Competition by the Brain Research Institute at UCLA for excellence in postdoctoral neuroscience research
* Andrei Irimia obtained a competitive travel award to present TBI research at a Keystone Symposium on the Molecular and Clinical Biology of TBI to be held in Keystone, Colorado in February 2012
* Andrei Irimia obtained a travel scholarship to present a TBI-related poster at the Dynamic Days 2012 conference to be held in Baltimore, MD in January 2012

=Publications=

==Journal Articles==

* Andrei Irimia and John D. van Horn (2012) The structural, connectomic and network covariance of the human brain NeuroImage (accepted) [http://www.sciencedirect.com/science/article/pii/S1053811912010695]
* Andrei Irimia, Bo Wang, Stephen R. Aylward, Marcel W. Prastawa, Danielle F. Pace, Marc Niethammer, Guido Gerig, David A. Hovda, Ron Kikinis, Paul M. Vespa and John D. van Horn (2012) Multimodal neuroimaging of structural pathology and connectomics in traumatic brain injury: toward personalized outcome prediction Neuroimage: Clinical volume 1, pages 1-17 [http://www.sci.utah.edu/~prastawa/papers/NIClinical2012_Irimia_TBISurvey.pdf]
* John D. van Horn, Andrei Irimia, Carinna M. Torgerson, Micah C. Chambers, Arthur W. Toga (2012) Mapping connectivity damage in the case of Phineas Gage. Plos ONE [http://dx.plos.org/10.1371/journal.pone.0037454]
* Andrei Irimia, Micah C. Chambers, Carinna M. Torgerson and John D. van Horn (2012) Circular representation of human cortical networks for subject and population-level connectomic visualization NeuroImage volume 60, pages 1340-1351
* Andrei Irimia, Micah C Chambers, Carinna M Torgerson, Maria Filippou, David A Hovda, Jeffry R Alger, Guido Gerig, Arthur W Toga, Paul M Vespa, Ron Kikinis, John D Van Horn (2012) Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury. Frontiers in Neurology [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3275792/]
* Andrei Irimia, Micah C. Chambers, Jeffry R. Alger, Maria Filippou, Marcel W. Prastawa, Bo Wang, David A. Hovda, Guido Gerig, Arthur W. Toga, Ron Kikinis, Paul M. Vespa, John D. van Horn (2011) Comparison of acute and chronic traumatic brain injury using semi-automatic multimodal segmentation of MR volumes. Journal of Neurotrauma [http://www.ncbi.nlm.nih.gov/pubmed/21787171]

==Proceedings==

* Bo Wang, Marcel W. Prastawa, Andrei Irimia, Micah C. Chambers, Paul M. Vespa, John D. van Horn and Guido Gerig (2012) Segmentation of MRI presenting pathology and inconsistent multimodal information. Proceedings of the Fifteenth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2012), October 1-5, 2012, Nice, France.
* Bo Wang, Marcel W. Prastawa, Suyash P. Awate, Andrei Irimia, Micah C. Chambers, Paul M. Vespa, John D. Van Horn and Guido Gerig (2012) Segmentation of serial MRI of TBI patients using personalized atlas construction and topological change estimation Proceedings of the Tenth International Symposium on Biomedical Imaging (ISBI 2012), May 2-5, 2012, Barcelona, Catalonia, Spain
* Bo Wang, Marcel W. Prastawa, Andrei Irimia, Micah C. Chambers, Paul M. Vespa, John D. van Horn, Guido Gerig (2012) A patient-tailored segmentation framework for longitudinal MR images of traumatic brain injury Proceedings of the Twenty-Fifth International Conference of SPIE—The International Society for Optical Engineering, February 4-9, 2012, San Diego, California, USA
* Marc Niethammer, Gabriel L. Hart, Danielle F. Pace, Micah C. Chambers, Andrei Irimia, John D. van Horn, Stephen R. Aylward (2011) Geometric metamorphosis. Proceedings of the Fourteenth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), September 18-22, 2011, Toronto, Ontario, Canada

==Abstracts==

* Micah C. Chambers, Andrei Irimia and John D. van Horn (2012) Combined functional and structural connectivity for an improved look at the brain Proceedings of the Nineteenth Joint Symposium on Neural Computation, June 2, 2012, University of California, Riverside, California, USA
* Andrei Irimia, S. Y. Matthew Goh, Carinna M. Torgerson, Micah C. Chambers, David A. Hovda, Jeffry R. Alger, Paul M. Vespa, Guido Gerig, Arthur W. Toga, Ron Kikinis and John D. van Horn (2012) Impact of neurotrauma upon the network architecture and information processing capabilities of the human cortex Proceedings of the Nineteenth Joint Symposium on Neural Computation, June 2, 2012, University of California, Riverside, California, USA
* Andrei Irimia, Micah C. Chambers, Marcel W. Prastawa, Paul M. Vespa, David A. Hovda, Jeffry R. Alger, Guido Gerig, Stephen R. Aylward, Arthur W. Toga, Ron Kikinis, John D. van Horn (2012) Systematic connectomic analysis of white matter atrophy associated with severe traumatic brain injury Proceedings of the Thirtieth Neurotrauma Symposium, July 22-25, 2012, Arizona Biltmore Resort and Spa, Phoenix, Arizona, USA
* Andrei Irimia, John D. van Horn, Micah C. Chambers, Marcel W. Prastawa, Silvain Gouttard, Paul M. Vespa, David A. Hovda, Jeffry R. Algers, Sonia M. A. Pujol, Guido Gerig, Stephen R. Aylward, Arthur W. Toga and Ron Kikinis (2011) Connectome-level evaluation of neurodegeneration caused by traumatic brain injury Proceedings of the Eighteenth Annual Meeting of the Organization on Human Brain Mapping (OHBM 2012), June 10-14, 2012, Beijing, China
* Andrei Irimia, SY Matthew Goh, Carinna M. Torgerson, Micah C. Chambers, Jeffry R. Alger, David A. Hovda, Paul M. Vespa, Arthur W. Toga, Ron Kikinis and John D. van Horn (2012) Connectome-level quantification of longitudinal changes in brain circuitry: a study of human neurodegeneration caused by traumatic brain injury Accepted for publication in the Proceedings of the Annual Keystone Conference on Synapses and Circuits: From Formation to Disease, April 1-6, 2012, Steamboat Resort, Steamboat Springs, Colorado, USA
* Andrei Irimia, Micah C. Chambers, Jeffry R. Alger, David A. Hovda, Paul M. Vespa, Arthur W. Toga, Ron Kikinis and John D. van Horn (2012) Patient-tailored longitudinal quantification of brain atrophy in chronic traumatic encephalopathy using multimodal neuroimaging Proceedings of the Annual Keystone Conference on the Clinical and Molecular Biology of Acute and Chronic Traumatic Encephalopathies, February 26-March 2, 2012, Keystone Resort, Keystone, Colorado, USA
* Andrei Irimia, Micah C. Chambers, Maria Filippou, Paul M. Vespa, Jeffry R. Alger, David A. Hovda, Arthur W. Toga, Ron Kikinis, John D. van Horn (2012) Impact of traumatic brain injury upon the architecture and longitudinal dynamics of cortical networks Proceedings of the Thirtieth Annual International Conference on Chaos and Nonlinear Dynamics (Dynamics Days 2012), January 4-7, 2012, Baltimore, Maryland, USA
* Andrei Irimia, Micah C. Chambers, Maria Filippou, Jeffry R. Alger, Marcel W. Prastawa, Bo Wang, Silvain Gouttard, Sonia M. A. Pujol, Stephen R. Aylward, David A. Hovda, Guido Gerig, Arthur W. Toga, Ron Kikinis, Paul M. Vespa and John D. van Horn (2011) Quantification of morphometric and volumetric changes associated with recovery from traumatic brain injury using clinical atrophy measures Neuroscience Poster Session, Brain Research Institute, Ackerman Student Union Grand Ballroom, University of California, Los Angeles, November 29, 2011, Los Angeles, California, USA
* Andrei Irimia, Micah C. Chambers, Paul M. Vespa, Arthur W. Toga, John D. van Horn (2011) Cortical network visualization and analysis in traumatic brain injury using multimodal neuroimaging Proceedings of the Eighteenth Joint Symposium on Neural Computation, June 4, 2011, Institute of Neural Computation, University of California, San Diego, La Jolla, California, USA
* Andrei Irimia, Micah C. Chambers, Maria Filippou, Jeffry R. Alger, Marcel W. Prastawa, Bo Wang, Silvain Gouttard, Sonia M. A. Pujol, Stephen R. Aylward, David A. Hovda, Guido Gerig, Arthur W. Toga, Ron Kikinis, Paul M. Vespa, John D. van Horn (2011) Three‐dimensional calculation and quantification of morphometric and volumetric cortical atrophy indices of widespread clinical use from MRI volumes of traumatic brain injury using 3D Slicer Proceedings of the Forty‐First Annual Meeting of the Society for Neuroscience (SfN 2011), November 12-16, 2011, Washington, District of Columbia, USA
* Andrei Irimia, John D. van Horn, Micah C. Chambers, Marcel W. Prastawa, Silvain Gouttard, Paul M. Vespa, David A. Hovda, Jeffry R. Algers, Sonia M. A. Pujol, Guido Gerig, Stephen R. Aylward, Arthur W. Toga, Ron Kikinis (2011) Automatic multimodal MR image segmentation for the clinical assessment of traumatic brain injury in 3D Slicer Proceedings of the Seventeenth Annual Meeting of the Organization on Human Brain Mapping (OHBM 2011), June 26-30, 2011, Quebec City, Canada

==Presentations and Dissemination Events==

* Andrei Irimia, Micah C. Chambers, Sheng-Yang Matthew Goh, Carinna M. Torgerson, Marcel W. Prastawa, Paul M. Vespa, David A. Hovda, Jeffry R. Alger, Guido Gerig, Stephen R. Aylward, Arthur W. Toga, Ron Kikinis and John D. van Horn (2012) Large scale calculation of the connectomic and network covariance of the human brain (N = 110) Poster Session of the National Alliance for Medical Image Computing, National Institute of Biomedical Imaging and Bioengineering, November 7-9, 2012, Bethesda, Maryland, USA
* Micah C. Chambers, Andrei Irimia, Lori L. Altshuler and John D. van Horn (2012) Structural and functional connectivity representation in euthymic bipolar disorder via connectogram representations Neuroscience Poster Session, Brain Research Institute, Ackerman Student Union Grand Ballroom, University of California, Los Angeles, December 4, 2012, Los Angeles, California, USA
* Andrei Irimia and John D. van Horn (2012) Multimodal neuroimaging for the personalized assessment of structural and connectomic brain changes prompted by traumatic brain injury Mazziotta Prize Presentation at the Work in Progress Meeting, Hermann Conference Center, Department of Neurology, University of California, Los Angeles, September 26, 2012, Los Angeles, California, USA
* Andrei Irimia, Micah C. Chambers and John D. van Horn (2012) Large-scale calculation of population-level connectomics using 3D Slicer and the connectogram. Presentation at “Big Data Computational Neuroscience using the Pipeline: LONI Resource Advisory Board Meeting”, Neurosciences Research Building Auditorium, Department of Neurology, University of California, Los Angeles, September 25, 2012, Los Angeles, California, USA
* Andrei Irimia, Micah C. Chambers, Bo Wang, Marcel W. Prastawa, Danielle F. Pace, Stephen R. Aylward, John D. van Horn, Guido Gerig (2012) Semi-automatic longitudinal segmentation of magnetic resonance imaging volumes in traumatic brain injury Invited Presentation at the Seventh Annual Project Week of the National Alliance for Medical Image Computing (NA-MIC), June 18-22, 2012, Greer Hall, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
* Andrei Irimia, Micah C. Chambers, Paul M. Vespa, David A. Hovda, Arthur W. Toga and John D. Van Horn (2012) Multimodal structural neuroimaging for patient-tailored longitudinal quantification of brain atrophy in traumatic brain injury Invited Presentation at the weekly Research Seminar of the Neural Dynamics and Data Analysis Laboratory, Department of Mathematics and Statistics, Boston University, June 15, 2012, Boston, Massachusetts, USA
* S. Y. Matthew Goh, Andrei Irimia, Paul M. Vespa and John D. van Horn (2012) Atlas-based automatic segmentation of MRI volumes from patients with traumatic brain injury Presentation at the Annual Science Day, University of California, Los Angeles, May 15, 2012, Los Angeles, California, USA
* Andrei Irimia, Micah C. Chambers, Paul M. Vespa, David A. Hovda, Arthur W. Toga and John D. Van Horn (2012) Connectomic visualization using the LONI Pipeline Invited Presentation at “Big Data Analysis using the LONI Pipeline” Advanced Neuroimaging, Informatics and Genomics Computing, Neurosciences Research Building Auditorium, Department of Neurology, University of California, Los Angeles, April 17, 2012, Los Angeles, California, USA
* Andrei Irimia, Micah C. Chambers and John D. van Horn (2012) The connectogram: a circular representation of human cortical networks Presentation at the Research Seminar of the Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, February 9, 2012, Los Angeles, California, USA
* Bo Wang, Marcel W. Prastawa, Andrei Irimia, Micah C. Chambers, Paul M. Vespa, John D. van Horn and Guido Gerig (2012) Segmentation of longitudinal MR images of traumatic brain injury using a patient-specific framework Presentation at the Twenty-Fifth International Conference of SPIE—The International Society for Optical Engineering, February 4-9, 2012, San Diego, California, USA
* S. M. Matthew Goh, Andrei Irimia and John D. van Horn (2012) Semi-automatic segmentation and cortical mesh generation for traumatic brain injury MR volumes Presentation at the Fourth Annual Neurology Science Day, Department of Neurology, University of California, Los Angeles, January 25, 2012, Los Angeles, California, USA
* Micah C. Chambers, Andrei Irimia and John D. van Horn (2012) Full-brain functional connectivity using mutual information Presentation at the Fourth Annual Neurology Science Day, Department of Neurology, University of California, Los Angeles, January 25, 2012, Los Angeles, California, USA
* Andrei Irimia, SY Matthew Goh, Carinna M. Torgerson, Micah C. Chambers, Jeffry R. Alger, David A. Hovda, Paul M. Vespa, Arthur W. Toga, Ron Kikinis and John D. Van Horn (2012) Quantification of changes in cortical network topology caused by traumatic brain injury Presentation at the Fourth Annual Neurology Science Day, Department of Neurology, University of California, Los Angeles, January 25, 2012, Los Angeles, California, USA (the research outlined in this poster was awarded the Mazziotta Prize)
* John D. van Horn, Andrei Irimia and Micah C. Chambers (2012) Driving biological project on traumatic brain injury: an annual update Invited presentation at the Brain Injury Research Center, Ronald Reagan Medical Center, University of California, Los Angeles, January 17, 2012, Los Angeles, California, USA
* John D. van Horn, Andrei Irimia and Micah C. Chambers (2012) Traumatic brain injury Presentation at the Eighth All Hands Meeting of the National Alliance for Medical Image Computing, January 8-14, 2012, Salt Lake City, Utah, USA
* Andrei Irimia, Micah C. Chambers, Maria Filippou, Paul M. Vespa, Jeffry R. Alger, David A. Hovda, Arthur W. Toga, Ron Kikinis, John D. van Horn (2012) Impact of traumatic brain injury upon the architecture and longitudinal dynamics of cortical networks Presentation at the Thirtieth Dynamics Days 2012 International Conference on Chaos and Nonlinear Dynamics, January 4-7, 2012, Baltimore, Maryland, USA
* Marc Niethammer, Gabriel L. Hart, Danielle F. Pace, Micah C. Chambers, Andrei Irimia, John D. van Horn and Stephen R. Aylward (2011) Geometric metamorphosis for traumatic brain injury Presentation at the Fourteenth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), September 18-22, 2011, Toronto, Ontario, Canada
* Andrei Irimia, Micah C. Chambers, John D. van Horn (2011) Automatic segmentation of traumatic brain injury MRI volumes using atlas based classification and 3D Slicer Tutorial Presentation Session of the Seventh Annual Project Week of the National Alliance for Medical Image Computing, June 20-24, 2011, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
* Andrei Irimia, Micah C. Chambers, John D. van Horn (2011) Analysis and visualization of traumatic brain injury using 3D Slicer within the NA-MIC Collaboration Invited Presentation at the Seventh Annual Project Week of the National Alliance for Medical Image Computing, June 20-24, 2011, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
* Andrei Irimia, Micah C. Chambers, John D. van Horn (2011) Traumatic brain injury processing, analysis and visualization. Laboratory of Neuro Imaging, University of California, Los Angeles, June 3, 2011, Los Angeles, California, USA
* Andrei Irimia, John D. van Horn, Micah C. Chambers (2011) Longitudinal analysis of traumatic brain injury using 3D Slicer. Brain Injury Research Center, University of California, Los Angeles, March 25, 2011, Los Angeles, California, USA
* Andrei Irimia, John D. van Horn, Micah C. Chambers, Marcel W. Prastawa, Bo Wang, Silvain Gouttard, Paul M. Vespa, David A. Hovda, Jeffry R. Alger, Sonia M. A. Pujol, Guido Gerig, Stephen R. Aylward, Arthur W. Toga, Ron Kikinis (2011) Clinically-driven multimodal imaging of traumatic brain injury using semi-automatic segmentation in 3D Slicer. Third Annual Neurology Science Day, University of California, Los Angeles, January 26, 2011, Los Angeles, California, USA
* John D. van Horn, Andrei Irimia, Micah C. Chambers, Arthur W. Toga, Jeffry R. Alger, Paul M. Vespa, David A. Hovda (2011) UCLA Traumatic Brain Injury. Seventh All Hands Meeting of the National Alliance for Medical Image Computing (NA-MIC AHM), January 10-14 2011, Salt Lake City, Utah, USA

=Press Releases=

* Graziella Marturano (2012) Svelato il mistero di Phineas Gage [The mystery of Phineas Gage unveiled] (in Italian) Featured by Controcampus (Accessed May 30, 2012)
* Michael Robinson (2012) The 152-year-old brain that changed the course of science. Featured by The Market Oracle (Accessed May 29, 2012)
* British Psychological Society (2012) Neuroscience still haunted by Phineas Gage. Featured by Research Digest (Accessed May 23, 2012)
* Phineas Gage vivio 12 anos con una varilla en el cerebro [Phineas Gage lived for 12 years with a hole in his brain] (2012) Featured by Actualidad.com (Accessed May 22, 2012)
* Lauren Davis (2012) 164 years later, researchers map Phineas Gage’s pierced brain. Featured by io9 (Accessed May 20, 2012)
* Caroline Kraaijvanger (2012) Brein van onfortuinlijke Phineas Gage gereconstrueerd [Brain of unfortunate Phineas Gage reconstructed, in Dutch] Featured by Scientias.nl (Accessed May 21, 2012)
* Lancia gli trafigge la testa e cambia personalità. Svelato il «giallo medico» di Phineas Gage [A rod pierces his head and his personality changes. The ‘yellow doctor’ of Phineas Gage is unveiled, in Italian] (2012) Featured by Corriere della Sera (Accessed May 18, 2012)
* Без мозгов можно жить [You can live without a brain, in Russian] (2012) Featured by Siteua.org (Accessed May 18, 2012)
* Müfit Yılmaz Gökmen (2012) 164 yıllık mucizenin sırrı çözüldü [The secret of the miracle was solved after 164 years, in Turkish) Featured by MSNBC Turkey (Accessed May 17, 2012)
* David Freeman (2012) Phineas Gage brain map study spotlights neuroscience’s most celebrated case. Featured by The Huffington Post (Accessed May 18, 2012).
* Phineas Gage’s brain imaged for the first time (sic) (2012) Featured by Planetsave (Accessed May 17, 2012)
* Kyle Wagner (2012) Watch how a rod impaled a 19th century man’s skull without killing him Featured by Gizmodo (Accessed May 17, 2012)
* Clay Dillow (2012) Phineas Gage, neurology’s most interesting case, gets his head re-examined with new neural map Featured by Popular Science (Accessed May 17, 2012)
* Неврологи объяснили изменения психики Финеаса Гейджа после травмы головы [Neuroscientists explain Phineas Gage’s mental changes after head injury, in Russian] (2012) Med Portal (Accessed May 17, 2012)
* Lancia gli buca testa e diventa bad guy, svelato giallo del 1848 [Rod pierces his head and he becomes a bad guy, in Italian] (2012) Featured by Sassari Notizie (Accessed May 17, 2012)
* Omul care a uimit medicii timp de 200 de ani [The man who has astonished doctors for 200 (sic) years] (in Romanian) (2012) Realitatea (Accessed May 17, 2012)
* Kate Taylor (2012) Researchers map damage to Phineas gage’s brain. Featured by TG Daily, Free Republic, Science Blog (Accessed May 17, 2012)
* Helen Thomson (2012) Phineas Gage brain pathways mapped for the first time. Featured by New Scientist Health (Accessed May 17, 2012)
* Live Science Staff (2012) Phineas Gage’s missing brain mapped. Featured by Life Science (Accessed May 17, 2012)
* Robin Wulffson (2012) UCLA researchers study man with horrific brain injury. Featured by Examiner.com (Accessed May 16, 2012)
* Jacy Young (2012) Mapping Phineas Gage’s brain 150+ years later Featured by Advances in the History of Psychology (Accessed May 16, 2012)
* Lindsay Morton (2012) Modeling neurological damage of a traumatic brain injury survivor. Featured by EurekAlert!, Medical Xpress (Accessed May 16, 2012)
* Elizabeth Landau (2012) The curious brain impalement of Phineas Gage. Featured by CNN Health, Science Daily, Local 10, CNN Mexico (Accessed May 16, 2012)
* Thomas H. Maugh II (2012) Rod through Phineas Gage’s brain caused more damage than thought. Featured by Los Angeles Times (Accessed May 16, 2012)
* Mo Constandi (2012) Phineas Gage’s connectome Featured by The Guardian (Accessed on May 16, 2012)
* Mark Wheeler (2012) UCLA researchers map damaged connections in Phineas Gage’s brain. Featured by UCLA Newsroom, Science Codex, India Times, e! Science News, Newsodrome, SciTech Daily (Accessed on May 16, 2012)
* In Statu Nascendi (2012) Human brain becomes prettier [http://x-positor.blogspot.com/ 2012/02/human-brain-becomes-prettier.html] February 9, 2012
* Circos (2012) Circos tackles the connectome [http://circos.ca] February 14, 2012
* Neuroskeptic (2012) Visualizing the connected brain http://neuroskeptic.blogspot.com February 8, 2012
* Michelle C. LaPlaca, David F. Meaney (2011) Perspectives on the role of bioengineering in neurotrauma research Journal of Neurotrauma volume 28, pages 2201-2202

=Links=

*[http://loni.ucla.edu UCLA Laboratory of Neuro Imaging(LONI)]
*[http://www.ucnia.org/ Utah Center for NeuroImage Analysis]
*[http://www.traumaticbraininjury.com/ Traumatic Brain Injury Portal]
*[http://www.tbi-impact.org/ TBI IMPACT Mission]

Engineering:Kitware

2012-11-19T17:12:41Z

Aylward: /* TubeTK for geometry-inspired image analysis */

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Will Schroeder) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.jpg|200px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.jpg|200px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

Engineering:Kitware

2012-11-19T17:12:27Z

Aylward: /* CDash, CTest, CPack Software Process Tools */

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Will Schroeder) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.jpg|200px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.jpg|100px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

File:CalaTK.jpg

2012-11-19T17:12:11Z

Aylward:

File:TubeTK.jpg

2012-11-19T17:11:55Z

Aylward:

Engineering:Kitware

2012-11-19T17:11:39Z

Aylward: /* CDash, CTest, CPack Software Process Tools */

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Will Schroeder) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.jpg|100px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.jpg|100px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

Engineering:Kitware

2012-11-19T17:11:30Z

Aylward: /* TubeTK for geometry-inspired image analysis */

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Will Schroeder) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.gif|100px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.jpg|100px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

Engineering:Kitware

2012-11-19T17:07:29Z

Aylward:

Back to [[Engineering:Main|NA-MIC Engineering]]
__NOTOC__
= Overview of Kitware Projects (PI: Will Schroeder) =

{|
|width="120px" | [[Image:KitwareLogo.gif|220px]]
| |

== [http://Kitware.com/ Kitware, Inc.] ==

[http://www.kitware.com/ Kitware, Inc.] is teaming with NA-MIC to produce the NA-MIC Kit, high-quality software for solving medical image analysis and visualization challenges. Our contributions to NA-MIC and the NA-MIC Kit include providing software process and algorithms research consultation as well as support for open-source software design, development, and integration. Specific examples are featured below.

<hr>
|-
| | [[Image:VTK-logo-medium-res.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/VTKSummary The Visualization Toolkit VTK] ==

The Visualization Toolkit is an object-oriented toolkit for processing, viewing and interacting with a variety of data forms including images, volumes, polygonal data, and simulation datasets such as meshes, structured grids, and hierarchical multi-resolution forms. It also supports large-scale data processing and rendering. [http://wiki.na-mic.org/Wiki/index.php/VTKSummary More...]

<hr>
|-

| | [[Image:itkLogo.jpg|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/ITKSummary The Insight Toolkit ITK] ==

The Insight Segmentation and Registration Toolkit ([http://www.itk.org ITK]) is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in digitally sampled representations. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be registered with a MRI scan in order to combine the information contained in both. [http://wiki.na-mic.org/Wiki/index.php/ITKSummary More...]

<hr>
|-

| | [[Image:MIDASLogo.png|150px]]
| |

== [http://www.kitware.com/products/midas.html MIDAS and the Publications Database] ==

MIDAS is open-source software for hosting heterogeneous databases, e.g., databases of images, publications, meta-data, presentations, and more. MIDAS also provides interfaces so that its data can be easily accesses over the web and via C++/python/Java. MIDAS can also harvest data from other databases on the web, e.g., PubMed and genomics databases. NA-MIC has a MIDAS installation to serve as the [http://www.na-mic.org/publications NA-MIC Publications Database]. MIDAS is also being used to host [http://www.insight-journal.org/midas/community/view/17 NA-MIC data], the [http://www.insight-journal.org Insight Journal], the [http://www.midasjournal.org/ MIDAS Journal], and the [http://www.midasjournal.org/?journal=35 VTK Journal]. Direct access to MIDAS's data from within Slicer is being developed to support informatics analysis and visualization. Direct access to MIDAS's publications from within Slicer is being developed to provide documentation and integrative tutorials. [http://www.kitware.com/products/midas.html More...]

<hr>
|-

| | [[Image:CTKLogo.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CTKSummary CTK GUI Toolkit] ==

CTK is an Open Source library of GUI classes based on Qt, VTK, ITK, and DCMTK. This library is an international effort to simplify the development of medical image analysis applications. NAMIC is assisting in the architectural design, helping them establish software practices, contributing classes, and evaluating early developments. [http://wiki.na-mic.org/Wiki/index.php/CTKSummary More...]

<hr>

|-

| | [[Image:BatchMakeLogo.gif|100px]]
| |

== [http://batchmake.org Batchmake] ==

BatchMake is a cross platform tool for batch processing of large amount of data.
BatchMake can process datasets locally or on distributed systems using Condor (a grid computing tool that enables distributed computing across the network). Some of the key features of BatchMake include: 1) a BSD License, 2) CMake-like scripting language, 3) distributed scripting via Condor, 4) a centralized remote website for online statistical analysis. 4) a user Interface using FLTK, and 5) BatchMake is cross platform. [http://batchmake.org More...]

<hr>
|-

| | [[Image:CMake-logo-med-res.png|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CMake The Cross-platform Make Tool] ==

[http://www.cmake.org CMake] is used to control the software build process using simple platform, compiler and operating system independent configuration files. CMake generates native makefiles and workspaces that can be used in the development environment of your choice. That is, CMake does not attempt to replace standard development tools such as compilers and debuggers, rather it produces build files and other development resources that can benefit from automated generation. Further, once CMake configuration files are created, they can be used to produce developer resources across the many platforms that CMake supports. CMake is quite sophisticated: it is possible to support complex environments requiring system configuration, pre-processor generation, code generation, and template instantiation. [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary More...]

<hr>
|-

| | [[Image:Cdash.gif|100px]]
| |

== [http://wiki.na-mic.org/Wiki/index.php/CmakeSummary CDash, CTest, CPack Software Process Tools] ==

As an adjunct to [http://www.cmake.org CMake] the tools [http://wiki.na-mic.org/Wiki/index.php/CDashSummary CDash], [http://wiki.na-mic.org/Wiki/index.php/CTestSummary CTest], [http://wiki.na-mic.org/Wiki/index.php/CPackSummary CPack] are used to test and package all components of the NAMIC kit. CTest is a testing client that locally performs testing on a software repository, and then communicates the results of the testing to CDash (and other testing, dashboard servers such as DART2). CPack is a cross-platform tool for packaging, distributing and installing the NAMIC kit on various systems including Linux, Windows, and Mac OSX. [http://wiki.na-mic.org/Wiki/index.php/OverviewSoftwareProcessSummary More...]<br>

<hr>
|-

| | [[Image:TubeTK.gif|100px]]
| |

== [http://tubetk.org/ TubeTK for geometry-inspired image analysis] ==

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in areal photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK is implemented as a C++ library and makes extensive use of ITK and VTK. Select methods of TubeTK are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. [http://tubetk.org More...]<br>

<hr>
|-

| | [[Image:CalaTK.gif|100px]]
| |

== [http://calatk.org/ CalaTK for cross sectional and longitudinal atlas building] ==

CalaTK is an open-source toolkit for cross-sectional and longitudinal atlas building.

The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in macaque structural and diffusion tensor magnetic resonance (MR) images.

A number of algorithms are available including registration and atlas building based on LDDMM, growth model LDDMM, LDDMM with geodesic shooting and/or initial momentum, or geometric metamorphosis with LDDMM.

Unlike existing atlas-building methods, we explicitly use longitudinal (or temporal) information, both for the structural atlas as well as for the diffusion tensor atlas. This will be achieved directly within the registration framework by modeling expected changes in image intensity for the structural images (to handle contrast inversion at the early stage of brain development) and by using subject-specific growth models. The proposed atlas-building strategy is specifically tailored for the construction of longitudinal atlases. The longitudinal approach is expected to significantly improve estimation accuracy.

CalaTK is implemented as a C++ library and makes extensive use of ITK. Algorithms are provided as command-line applications and as extensions in 3D Slicer, an open-source medical imaging application. Algorithm configuration is performed with a system based on JSON files that is human-readable, machine-editable, and easily archived for reproducible analysis. [http://calatk.org More...]<br>

|}

Slicer4.2Planning

2012-08-20T15:05:03Z

Aylward:

[[Image:SlicerRt0.3_Screenshot_DVH_HeadNeck.png|thumb|right|320px]]
[[Image:AHM2012-JC.jpg|thumb|right|320px]]
Attendees: JC, Steve, Chris, Slicer Users, Slicer Developers, NA-MIC Engineers, and More!

Venue: Google hangout.

Hours: August 20th, 10am until ???

<b>To participate</b>, send your google+ account address to "Jean-Christophe Fillion-Robin" <JChris.FillionR@kitware.com> and he will invite you to the hangout. The invites and a link to the google hangout will be sent to various email lists 5 minutes before the hangout starts on August 20th.

<b>The goal</b> of this meeting is to review outstanding bugs, find volunteers to fix them, and define the features needed in future releases of Slicer!

<b>This meeting is open to the community!</b> All are welcome and encouraged to participate. Join us, contribute to Slicer, and participate in the meeting to make Slicer an even greater success!

Agenda:
http://na-mic.org/Mantis/roadmap_page.php

See also:
http://na-mic.org/Mantis/changelog_page.php

== Planning Considerations ==
* Goal is to have a robust set of features in a stable release to support dissemination efforts
** Prime target for 4.2 release is [http://www.rsna.org/Annual_Meeting.aspx RSNA Nov 25-30, 2012]
** Release must be available on Monday November 5, 2012 (3 weeks in advance) to support preparation of training materials and installation at RSNA.
The [http://www.na-mic.org/Wiki/index.php/RSNA_2012 courses we teach at RSNA] are hands-on sessions in classrooms equipped with Windows computers. The computers are provided by a company that pre-load all of the different software platforms used to teach at RSNA. The software installation is done by the company three weeks before the meeting. The RSNA release must be ready and all tutorials must be tested by that date. No dead-line extension is possible.
*[http://www.na-mic.org/Wiki/index.php/RSNA2012_Planning RNSA 2012 Planning Table]
* Developers need to make realistic estimates of time required and time available to address targeted issues. These estimates need to be taken into account when determining priorities. Your colleagues will be depending on you to make realistic estimates so that they can plan accordingly.

== Schedule ==
<em> JC, Nicole, Andras, Steve, JC, J2, Andrey, Chris, Greg, and Stephen</em>
* Nov 1 have executable ready for RSNA
* Oct 15 to Nov 1 fix errors found by tutorial testing
* Oct 1 to Oct 15 formal tutorial testing organized by Sonia
* Sept 1 to Oct 1 bug fixes driven by tutorial testing conducted by developers
* Sept 1: Feature freeze for 4.2.

== Tasks ==
<em>JC, Nicole, Andras, Steve, JC, J2, Andrey, Chris, Greg, and Stephen</em>
* Extensions are our #1 priority: Macs, dependencies, etc. These will be fixed for 4.2.
* ITKv4 is our #2 priority, but it isn't going to make it by Sept 1. Packaging and building generally works on all platforms according to Steve P, HOWEVER, it is extremely slow to load images and certain key modules still depend on ITKv3. Please check with Steve for details. Our fear is that this conversion is going to require extensive testing, and we don't have time for it. So, we have decided that ITKv4 won't be in 4.2.
* Annotation system will be addressed by bug fixes to the current implementation.
* Data Bundle will be in by Sept 1.
* SceneViews will be addressed by bug fixes.
* System-level python will not be in 4.2 - we will continue with the current implementation.

== To Do's ==
* Week of Aug 20
** JC is going to re-assign bugs and features to different releases in more details this week. We will all review and then move forward to getting it done.

Slicer4.2Planning

2012-08-13T15:10:38Z

Aylward:

Slicer4.2Planning

2012-08-13T15:09:41Z

Aylward:

Slicer4.2Planning

2012-08-13T15:09:24Z

Aylward:

[[Image:SlicerRt0.3_Screenshot_DVH_HeadNeck.png|thumb|right|320px]]
[[Image:AHM2012-JC.jpg|thumb|right|320px|Jc talking about extensions on Tuesday morning]]
Attendees: JC, Steve, Chris, Slicer Users, Slicer Developers, NA-MIC Engineers, and More!

Venue: Google hangout.

Hours: August 20th, 10am until ???

<b>To participate</b>, send your google+ account address to "Jean-Christophe Fillion-Robin" <JChris.FillionR@kitware.com> and he will invite you to the hangout. The invites and a link to the google hangout will be sent to various email lists 5 minutes before the hangout starts on August 20th.

<b>The goal</b> of this meeting is to review outstanding bugs, find volunteers to fix them, and define the features needed in future releases of Slicer!

This is going to be a community meeting - all are welcome and encouraged to participate. Join us, contribute to Slicer, and participate in the community to make Slicer an even greater success!

Agenda:
http://na-mic.org/Mantis/roadmap_page.php

See also:
http://na-mic.org/Mantis/changelog_page.php

Slicer4.2Planning

2012-08-13T15:07:01Z

Aylward:

[[Image:SlicerRt0.3_Screenshot_DVH_HeadNeck.png|thumb|right|320px]]

Attendees: JC, Steve, Chris, Slicer Users, Slicer Developers, NA-MIC Engineers, and More!

Venue: Google hangout.

Hours: August 20th, 10am until ???

<b>To participate</b>, send your google+ account address to "Jean-Christophe Fillion-Robin" <JChris.FillionR@kitware.com> and he will invite you to the hangout. The invites and a link to the google hangout will be sent to various email lists 5 minutes before the hangout starts on August 20th.

<b>The goal</b> of this meeting is to review outstanding bugs, find volunteers to fix them, and define the features needed in future releases of Slicer!

This is going to be a community meeting - all are welcome and encouraged to participate. Join us, contribute to Slicer, and participate in the community to make Slicer an even greater success!

Agenda:
http://na-mic.org/Mantis/roadmap_page.php

See also:
http://na-mic.org/Mantis/changelog_page.php

Slicer4.2Planning

2012-08-13T15:05:43Z

Aylward:

Attendees: JC, Steve, Chris, Slicer Users, Slicer Developers, NA-MIC Engineers, and More!

Venue: Google hangout.

Hours: August 20th, 10am until ???

<b>To participate</b>, send your google+ account address to "Jean-Christophe Fillion-Robin" <JChris.FillionR@kitware.com> and he will invite you to the hangout. The invites and a link to the google hangout will be sent to various email lists 5 minutes before the hangout starts on August 20th.

<b>The goal</b> of this meeting is to review outstanding bugs, find volunteers to fix them, and define the features needed in future releases of Slicer!

This is going to be a community meeting - all are welcome and encouraged to participate. Join us, contribute to Slicer, and participate in the community to make Slicer an even greater success!

Agenda:
http://na-mic.org/Mantis/roadmap_page.php

See also:
http://na-mic.org/Mantis/changelog_page.php

Slicer4.2Planning

2012-07-26T15:13:47Z

Aylward:

Attendees: JC, Steve, Chris

Venue: Google hangout.

Hours: 10am until ???

Agenda:
http://na-mic.org/Mantis/roadmap_page.php

See also:
http://na-mic.org/Mantis/changelog_page.php

2012 Summer Project Week:DifficultRegistration

2012-06-19T14:12:33Z

Aylward: /* Links for Data */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
A summary of results will be provided via this page, including algorithms, parameters, and additional findings.

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-19T14:11:55Z

Aylward: /* Links for Data */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
A summary of results will be provided via this page, including algorithms, parameters, and additional findings.

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* TumorSim longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-19T14:07:07Z

Aylward: /* Links for Papers */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
A summary of results will be provided via this page, including algorithms, parameters, and additional findings.

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* XCAT
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip Enlarged LV registration with normal control]

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-19T14:02:13Z

Aylward: /* Links for Tools & Methods */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
A summary of results will be provided via this page, including algorithms, parameters, and additional findings.

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* XCAT
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip Enlarged LV registration with normal control]

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==

</div>

2012 Progress Report Science Wiki Version Engineering

2012-04-21T18:05:43Z

Aylward: /* 5.3.3. Roadmap */

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png|500px|center]]
<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* ''DICOM-RT and QIN support:'' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* ''DICOM database and networking:'' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>

As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog: The NA-MIC community was introduced to the Slicer Catalog in Slicer 4.1. This system allows users to install, unstall, search, browse, and rank Slicer extensions. This user experience is available from within Slicer and over the web - much like the Android and Apple App Stores. Developers can contribute, update, document, and post screenshots on their modules and receive community feedback. We see this work as a launchpad for new levels and avenues for community involvement in Slicer.

* CDash Package Manager: We have automated the nightly release of pre-compiled packages for Slicer on multiple platforms. This new process is built on CDash and allows executables and packages created during nightly regression testing to be submitted to a Midas system for download: http://slicer.kitware.com

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing is being offered in a maintenance release to follow Slicer 4.1 in May/June 2012. This work will allow user interactions with Slicer to be recorded on one machine and played back on another - and the results of those interactions can be compared. This GUI testing will be integrated into Slicer's nightly regression testing process. We propose to base the tests on the features demonstrated in the Slicer tutorials.

* DICOM Lollipops are a novel method for embedding entire Slicer (MRML) scenes into a DICOM object. Via this embedding, Slicer data can be read to/from PACS - enabling better integration of Slicer with clinical workflows.

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

<center>[[image:Slicer_4_1_MultiVolumeCharts.png|500px|center]]
<em>Figure 3. Slicer 4.1 introduced support for 4D images and charting.</em></center>

* Slicer 4.2: Plans (August, 2012)
** The next major release of Slicer 4.2 is still in the planning phase, but certain features are likely to be present. In particular, we anticipate the following will be released in Beta/1.0 format in Slicer 4.2:
*** QtTesting
*** DICOM Lollipops
*** ITKv4
*** SimpleITK
** Additionally, Slicer 4.2 will feature the maturation of two leading technologies:
*** Improved and stabilized Multi-Volume support, e.g., dynamic objects (4D surfaces/meshes)
*** Improved and stabilized Slicer Catalog integration
** As with prior releases, community involvement is key in determining and providing the final set of features to be included.

2012 Progress Report Science Wiki Version Engineering

2012-04-21T17:56:01Z

Aylward: /* 5.3.2. Expansion */

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png|500px|center]]
<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* ''DICOM-RT and QIN support:'' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* ''DICOM database and networking:'' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>

As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog: The NA-MIC community was introduced to the Slicer Catalog in Slicer 4.1. This system allows users to install, unstall, search, browse, and rank Slicer extensions. This user experience is available from within Slicer and over the web - much like the Android and Apple App Stores. Developers can contribute, update, document, and post screenshots on their modules and receive community feedback. We see this work as a launchpad for new levels and avenues for community involvement in Slicer.

* CDash Package Manager: We have automated the nightly release of pre-compiled packages for Slicer on multiple platforms. This new process is built on CDash and allows executables and packages created during nightly regression testing to be submitted to a Midas system for download: http://slicer.kitware.com

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing is being offered in a maintenance release to follow Slicer 4.1 in May/June 2012. This work will allow user interactions with Slicer to be recorded on one machine and played back on another - and the results of those interactions can be compared. This GUI testing will be integrated into Slicer's nightly regression testing process. We propose to base the tests on the features demonstrated in the Slicer tutorials.

* DICOM Lollipops are a novel method for embedding entire Slicer (MRML) scenes into a DICOM object. Via this embedding, Slicer data can be read to/from PACS - enabling better integration of Slicer with clinical workflows.

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

[[image:Slicer_4_1_MultiVolumeCharts.png|500px|center]]
<em>Figure 3. Slicer 4.1 introduced support for 4D images and charting.</em>

* Slicer 4.2: Plans (August, 2012)
** QtTesting
** DICOM Lollipops
** Slicer Catalog

2012 Progress Report Science Wiki Version Engineering

2012-04-21T17:40:11Z

Aylward: /* 5.3.1. Maturation */

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png|500px|center]]
<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* ''DICOM-RT and QIN support:'' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* ''DICOM database and networking:'' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>

As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog:

* CDash Package Manager:

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing

* DICOM Lollipops

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

[[image:Slicer_4_1_MultiVolumeCharts.png|500px|center]]
<em>Figure 3. Slicer 4.1 introduced support for 4D images and charting.</em>

* Slicer 4.2: Plans (August, 2012)
** QtTesting
** DICOM Lollipops
** Slicer Catalog

2012 Progress Report Science Wiki Version Engineering

2012-04-21T17:39:39Z

Aylward: /* Major Developments */

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png|500px|center]]
<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* ''DICOM-RT and QIN support:'' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* ''DICOM database and networking:'' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>
As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog:

* CDash Package Manager:

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing

* DICOM Lollipops

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

[[image:Slicer_4_1_MultiVolumeCharts.png|500px|center]]
<em>Figure 3. Slicer 4.1 introduced support for 4D images and charting.</em>

* Slicer 4.2: Plans (August, 2012)
** QtTesting
** DICOM Lollipops
** Slicer Catalog

2012 Progress Report Science Wiki Version Engineering

2012-04-21T17:39:13Z

Aylward:

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png|500px|center]]
<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* '''DICOM-RT and QIN support:''' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* '''DICOM database and networking:''' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>
As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog:

* CDash Package Manager:

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing

* DICOM Lollipops

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

[[image:Slicer_4_1_MultiVolumeCharts.png|500px|center]]
<em>Figure 3. Slicer 4.1 introduced support for 4D images and charting.</em>

* Slicer 4.2: Plans (August, 2012)
** QtTesting
** DICOM Lollipops
** Slicer Catalog

File:Slicer 4 1 MultiVolumeCharts.png

2012-04-21T17:35:16Z

Aylward:

2012 Progress Report Science Wiki Version Engineering

2012-04-21T17:34:38Z

Aylward:

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png]]

<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* '''DICOM-RT and QIN support:''' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* '''DICOM database and networking:''' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>
As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT 1.5.4 was release with support from NA-MIC. XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Thanks to its extensibility, XNAT can be used to support a wide range of imaging-based projects. The 1.5.4 release addressed security and DICOM handling as well as improved the overall stability of the system.

* BRAINSFit updated with NA-MIC support. BRAINSFIT is a collection of programs for registering images with with mutual information based metric. Several registration options are given for 3, 6, 9, 12, 16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program uses the Slicer execution model framework to define the command line arguments and can be fully integrated with Slicer using the module discovery capabilities of Slicer.

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit (discussed in Section 5.3.1) has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the NA-MIC Kit into new areas include:

* Slicer Catalog:

* CDash Package Manager:

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

* GUI Testing

* DICOM Lollipops

== 5.3.3. Roadmap ==

We are proposing to offer quarterly releases of the NA-MIC Kit and Slicer. Highlights from the recent releases and plans for future releases are given next.

* Slicer 4.0: Major Changes (November, 2011)
** Slicer 4.0 includes a major overhaul of the user interface, improved and simplified workflows for major tasks, simplified procedures for developers, and improved Python support.
** http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Announcements

* Slicer 4.0.1: Major Changes (January, 2011)
** Notable changes in Slicer 4.0.1 include new support for Ubuntu 11.04 and Fedora FC 13, and for DWI tractrography modules on Mac OS X. VTK GPU raycast method support of ATI GPU cards for Mac OS X is also included in this release, as well as major improvements to restoring scenes, which now provides significantly faster speeds. Additionally, in Slicer 4.0.1, users can now drag-and-drop files, including volumes, meshes, annotations, etc., into Slicer from Window Explorer, Mac Finder, and Linux Nautilus.
** http://www.slicer.org/slicerWiki/index.php/Slicer4:QtPort/Releases#Slicer_4.0.1

* Slicer 4.1: Major Changes (April, 2012)
** Charting support has been added with a new chart view in the 4.1 release, which is used by the MultiVolumeExplorer module. This new module introduces multi-volume (e.g. time series) support in Slicer. The Cache Settings panel has been ported from Slicer 3, to provide users with controls to display or clear the available cache space used when downloading sample data, and to store temporary filter outputs. Further support for importing VTK unstructured grids is also a new addition.
** Several other modules have been updated or added, including the OpenIGTLinks, Welcome, and DICOM modules. The CompareViews and View Controller GUI have been revised and improved. The Modules settings panel has also been enhanced, enabling users to set Prefer Executable CLI loading option to decrease memory consumption by modules and select which module(s) to skip at startup, as well as to customize their Favorite modules toolbar. Many of the icons for the Core Modules have also been updated.
** http://www.kitware.com/news/home/browse/401

[[image:Slicer_4_1_MultiVolumeCharts.png]]

* Slicer 4.2: Plans (August, 2012)
** QtTesting
** DICOM Lollipops
** Slicer Catalog

2012 Progress Report Science Wiki Version

2012-04-21T17:10:13Z

Aylward: /* Assignments: Short version */

Back to [[NAMIC_Annual_Reports|NAMIC_Annual_Reports]]<br>
Back to [[2012_Progress_Report|NAMIC_2012_Progress_Report]]<br>

This is where the outline for the 2012 scientific report for NA-MIC goes in. Ann will provide this outline by 4/1.
=Assignments: Short version=
Reporting Interval: 7/1/2011- 6/30/2012
{| class="wikitable sortable labelpage labelpagetable" border="1" width="100%" cellpadding="5"
|- style="background:#c2c2c2; color:black" align="left"
| style="width:20%" | Task
| style="width:20%" | Owner
| style="width:60%" | Title, comments
|-
| style="background:#ffffdd; color:black" align="center"|1. INTRODUCTION
| style="background:#c4f4af; color:black"|Ron
| style="background:#fff6a6; color:black"|Update Figure 1-1. Geo-anatomical Map of NA-MIC Collaborations, Recent changes and Center (administrative) highlights
|-
| style="background:#ffffdd; color:black" align="center"|2. [[2012_Progress_Report_HIGHLIGHTS | HIGHLIGHTS]]
| style="background:#c4f4af; color:black"|Will Schroeder, Kitware
| style="background:#fff6a6; color:black"|2.1 Algorithms, 2.2 Engineering, 2.3 NA-MIC Kit.
|-
| style="background:#ffffdd; color:black" align="center"|3. [[2012_Progress_Report_IMPACT | IMPACT AND VALUE TO BIOCOMPUTING]]
| style="background:#c4f4af; color:black"|Jim Miller, GE
| style="background:#b4e4d4; color:black"|3.1 Impact within the Center, 3.2 Impact within NIH-Funded Research, 3.3 National and International Impact
| style="background:#b4e4d4; color:black"|Submitted on 4/20/2012
|-
| style="background:#ffffdd; color:black" align="center"|4. RESEARCH PROGRESS SUMMARIES
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black"|
|-
| style="background:#ffffdd; color:black" align="center"|4.1 DRIVING BIOLOGICAL PROJECTS
| style="background:#c4f4af; color:black"|DBP PIs
| style="background:#fff6a6; color:black"|
|-
| style="background:#ffffdd; color:black" align="center"|4.1.1 [[2012_Progress_Report_DBP Atrial_Fibrillation | Atrial Fibrillation]]
| style="background:#c4f4af; color:black"|Rob MacLeod, Utah
| style="background:#b4ebd4; color:black"|A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC
| style="background:#b4e4d4; color:black"|Submitted on 4/20/2012
|-
| style="background:#ffffdd; color:black" align="center"|4.1.2 [[2012_Progress_Report_DBP Huntington's Disease | Huntington's Disease]]
| style="background:#c4f4af; color:black"|Hans Johnson, Iowa
| style="background:#b4e4d4; color:black"|A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC
| style="background:#b4e4d4; color:black"|Submitted on 4/18/2012
|-
| style="background:#ffffdd; color:black" align="center"|4.1.3 [[2012_Progress_Report_DBP Adaptive Radiotherapy | Adaptive Radiotherapy for Head and Neck Cancer]]
| style="background:#c4f4af; color:black"|Gregory C. Sharp, MGH
| style="background:#b4e4d4; color:black"|A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC
| style="background:#b4e4d4; color:black"|Submitted on 4/17/2012
|-
| style="background:#ffffdd; color:black" align="center"|4.1.4 [[2012_Progress_Report_DBP_TBI | Traumatic Brain Injury]]
| style="background:#c4f4af; color:black"|Jack Van Horn, UCLA
| style="background:#b4e4d4; color:black"|A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC
| style="background:#b4e4d4; color:black"|Submitted on 4/2/2012
|-
| style="background:#ffffdd; color:black" align="center"|5. COMPUTER SCIENCE CORE
| style="background:#c4f4af; color:black"|Ross Whitaker
| style="background:#fff6a6; color:black"|Brief Introduction: Algorithms, Engineering, NA-MIC Kit<br>
|-
| style="background:#ffffdd; color:black" align="center"|5.1 Algorithms
| style="background:#c4f4af; color:black"|Polina Golland, Guido Gerig, Allen Tannenbaum, Martin Styner
| style="background:#fff6a6; color:black"|5.1.1 Statistical Models of Anatomy and Pathology, Polina Golland<br>A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC<br>
|-
| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black"|5.1.2. Geometric Correspondence, Guido Gerig<br>A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC<br>
|-
| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black"|5.1.3. User Interactive Segmentation, Allen Tannenbaum<br>A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC<br>
|-
| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black"|5.1.4. Longitudinal and Time Series Analysis, Martin Styner<br>A. Introduction, B. Research Progress Report, C. Plans for the Coming Year, D. Papers that Acknowledge NA-MIC
|-
| style="background:#ffffdd; color:black" align="center"|5.2
| style="background:#c4f4af; color:black"|Will Schroeder, Steven Aylward, Steve Pieper, Jim Miller
| style="background:#b4e4d4; color:black"|5.2.1. [[2012_Progress_Report_Science_Wiki_Version_Engineering | End-user Platform, Steve Pieper]]
| style="background:#b4e4d4; color:black"|Submitted on 4/2/2012
|-
| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black" align="center"|5.2.2. [[2012_Progress_Report_Science_Wiki_Version_Engineering | Computational Platform, Jim Miller]]
| style="background:#b4e4d4; color:black"|Submitted on 4/20/2012
|-

| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black" align="center"|5.2.3. [[2012_Progress_Report_Science_Wiki_Version_Engineering | Data Management Platform, Dan Marcus]]
| style="background:#b4e4d4; color:black"|Submitted on 4/20/2012
|-
| style="background:#ffffdd; color:black" align="center"|
| style="background:#c4f4af; color:black"|
| style="background:#fff6a6; color:black" align="center"|5.2.4.[[2012_Progress_Report_Science_Wiki_Version_Engineering | Software Process, Stephen R. Aylward ]]
| style="background:#b4e4d4; color:black"|Submitted on 4/20/2012
|-
| style="background:#ffffdd; color:black" align="center"|5.3 [[2012_Progress_Report_Science_Wiki_Version_Engineering | NA-MIC Kit]]
| style="background:#c4f4af; color:black"|Will Schroeder, Steven Aylward, Steve Pieper, Jim Miller
| style="background:#fff6a6; color:black"|5.3.1. [[2012_Progress_Report_Science_Wiki_Version_Engineering | Expansion<br>5.3.2. Release<br>]]
| style="background:#b4e4d4; color:black"|Submitted on 4/21/2012
|-
| style="background:#ffffdd; color:black" align="center"|6. [[2012_Progress_Report_ARRA_Supplement| ARRA SUPPLEMENT]]
| style="background:#c4f4af; color:black"|Steve Aylward
| style="background:#b4e4d4; color:black"|6.1 Summary of Funded Activity
| style="background:#b4e4d4; color:black"|Submitted on 4/2/2012
|-
| style="background:#ffffdd; color:black" align="center"|7. [[2012_Progress_Report_Outreach| OUTREACH]]
| style="background:#c4f4af; color:black"|Sonia Pujol
| style="background:#b4e4d4; color:black"|7.1 Summary of Outreach Activities<br>
| style="background:#b4e4d4; color:black"|Submitted on 4/13/2012
|-
| style="background:#ffffdd; color:black" align="center"|8. NA-MIC PUBLICATIONS
| style="background:#c4f4af; color:black"|Marianna
| style="background:#fff6a6; color:black"|8.1 Papers that Acknowledge NA-MIC, 8.2. Conference Reports [[2012_Progress_Report#Dissemination|Go to All Papers List]]<br>
|-
| style="background:#ffffdd; color:black" align="center"|9. External Advisory Board (EAB) Report
| style="background:#c4f4af; color:black"|Bill Lorensen
| style="background:#fff6a6; color:black"|

2012 Progress Report Science Wiki Version Engineering

2012-04-21T11:06:48Z

Aylward: /* 5.3. NA-MIC Kit */

= 5.2. Engineering =
<em>Key Investigators </em>
* Will Schroeder, Kitware
* Stephen R. Aylward, Kitware
* Steve Pieper, Isomics
* Jim Miller, GE Research

The Engineering component of the Computer Science Core (Core 1b) has been focusing on the
infrastructure needed for the Algorithms component to implement their methods, and has been
working closely with them so that the functionality we provide can serve to inspire new methods
as well. Herein we provide more details regarding our accomplishments in those directions

== 5.2.1. End-user Platform: 3D Slicer ==
<em>Steve Pieper</em>
=== Release of 3D Slicer version 4.0 and 4.1 ===
As shown in Figure 1, 3D Slicer version 4.0 (commonly called Slicer4) is having an immediate world-wide impact. Version 4.0, released at the Radiology Society of North America (RSNA) meeting in late November 2011, is the result of a major effort by the NA-MIC engineering cores, in collaboration with the wider Slicer community, to re-implement and streamline the software in response to feedback from NA-MIC DBPs and algorithm developers. A new 3D Slicer version 4.1 release, being finalized at the time of this writing, adds back many of the advanced features of Slicer3, notably the Extension system by which new functionality can be downloaded and installed independent of the main executable. As described more fully below, these sweeping changes required touching not only most of the code in Slicer, but also feeding important feature and bug fix changes back into the rest of the NA-MIC Kit and upstream libraries. As a result of these efforts, 3D Slicer in now an improved reference implementation of a modern medical image computing package and a strong foundation for research.

[[image:2012_Engineering_EndUserPlatform_Fig1.png]]

<em>Figure 1: 3D Slicer version 4.0 end-user downloads during the first 3 months of 2012, a rate of 45,360 per year (over 100 downloads per day). Interactive geolocated download statistics are available at http://download.slicer.org/stats.</em>

===Major Developments and New Functionality in Slicer4===
* ''Modern Cross-Platform Design Patterns:'' As a by-product of the port of the user interface from KWWidgets to Qt, a comprehensive suite of non-GUI OS abstractions and utility functions from Qt became available to support core application functions such as preference settings, multi-processing, application resource data. This was a direct benefit from the GUI port supported by an ARRA supplement to the Neuroimage Analysis Center, a NA-MIC collaborating P41 grant. Slicer4 supports native windows 64 bit environments and can be bundled into a standard Mac OS X application bundle.
* ''Efficiency and Robustness:'' Careful review of core data management and processing pipeline steps allowed us to remove much redundant processing. The result is that Slicer is easier for developers to understand and debug, and end users experience faster startup and more responsive behavior.
* ''DICOM Networking:'' Slicer4 includes a DICOM listener and DICOM Query/Retrieve capabilities for integration with standard clinical image management environments and workflows. For example, intraprocedural imaging obtained during image guided procedures can now be auto-routed to Slicer for analysis and navigation.
* ''Additional Features:'' Slicer4 includes: an improved flexible view layout system; a revised implementation of the Expectation Maximization (EM) Segmenter; faster hardware accelerated volume rendering; improved markups and annotations; improved atlas and model hierarchy support; a streamlined and revised diffusion MRI implementation.

=== Plans ===
With the introduction of the Slicer4 Extension system we plan to stabilize the core slicer distribution and move to less frequent releases with more of the algorithm innovation becoming available through as Extensions. This will allow further stabilization and streamlining of the core while speeding up the delivery of new technologies to end users for testing.

== 5.2.2. Computational Platform ==
<em>Jim Miller</em>

Efforts in the Computational Platform have focused on developing a general and flexible computing architecture and analysis platform to meet the needs of NA-MIC scientists and engineers as well as the larger medical imaging community.
=== Major Developments ===
* ''Interactive methods:'' The Editor module has supported interactive segmentation techniques that were deeply integrated with the Editor codebase. We have broadened the Slicer Extension mechanisms to support Editor Extensions, allowing interactive segmentation techniques to be developed separately from the Slice codebase. We have also refined the interaction patterns for interactive segmentation within the Editor and are starting to develop interactive registration techniques.
* ''Multivolume analysis:'' The infrastructure for Diffusion Weighted MRI (DWI) IO and visualization has been generalized to be used for other time varying acquisitions like Dynamic Contrast Enhanced MRI (DCE) and Gated Cardiac CT. Massively univariate processing of DCE to produce parametric maps is being developed as a Slicer Extension.
* ''Distributed computing:'' Slicer Execution Model modules (also known as Command Line Modules) are now available as Nipype tools, enabling local and distributed scripted execution of processing pipelines.
* ''Exploratory image analysis:'' Infrastructure for the interactive exploration of images and the relationships of features calculated over regions of images was developed, including: feature libraries for Gabor, Haralick, entropy, polynomial, and histograms; and charting capabilities to display line, bar, and scatter plots within Slicer.
* ''Compatibility with ITK version 4:'' Compatibility with ITK version 4 was developed and continuously maintained over the past year as ITKv4 matured. Slicer will officially switch to ITKv4 in the coming months.
=== Plans ===
At the time of this writing, 3D Slicer 4.1 is being finalized. After the release of Slicer 4.1, the Slicer development codebase will migrate to using ITK version 4. This migration will enable new image registration methods, introduce SimpleITK APIs, and introduce GPU support for image analysis algorithms. Other plans for the Computational Platform include further developments for interactive analysis methods, infrastructure for private cloud computing, and interfaces for statistical analysis.

== 5.2.3. Data Management Platform ==
<em>Dan Marcus</em>

Efforts in the Data Management Platform have focused on (1) developing an ergonomic user interface and internal networking logical to efficiently exchange data between Slicer and XNAT and (2) expanding Slicer's support for importing from and exporting to local DICOM Objects and networked DICOM PACS.

=== Major Developments ===
* ''User Interface:'' The XNAT development team is working with a web usability firm (Integrity St. Louis) to design and implement a web interface that can be deployed in Slicer 4's Qt framework for exploring data hosted in a remote XNAT data repository. Prototypes have been implemented and are currently being reviewed by stakeholders with the goal of a functioning interface by June, 2012.
* ''Networking logic:'' An alpha implementation of the infrastructure for actually exchanging data between XNAT and Slicer has been developed and revealed that significant additional work is required to handle parsing of MRML files within Slicer in the context of remotely hosted data. This work is now underway and will require several months to complete.
* ''Use cases:'' Several use cases have been identified, including projects within the Quantitative Imaging Network (QIN), to drive the development of the Slicer/XNAT integration.
* '''DICOM-RT and QIN support:''' Via DCMTK and custom classes, Slicer is being extended to support RT Plans, Images, Annotations, etc. Much of the support is being driving by the head-and-neck cancer core. Additional developments are being driven by an ongoing effort to integrate Slicer as an annotation module in the Quantitative Imaging Network (QIN).
* '''DICOM database and networking:''' Slicer DICOM support is approaching clinical quality in terms of speed of searching and IO by maintaining a database that indexes previously loaded DICOM objects. Via this database, it is no longer necessary to parse each object in order to search and/or load an entire series, study, or patient into Slicer.

=== Plans ===
The bulk of the effort in the coming year will continue to focus on (1) the user interface and networking logic for remote data management in XNAT and (2) import and export of Slicer results (i.e., entire MRML scenes) as DICOM objects. Regarding XNAT, as the initial development completes, we will turn to developing more efficient mechanisms for caching data locally and synchronizing local caches with remote repositories. Regarding importing and exporting Slicer data as DICOM objects, we are pursuing the concept of a '''DICOM Lollipop.''' In a DICOM Lollipop, a complete Slicer (MRML) Scene, with annotations, segmentations, viewing conditions, etc, can be saved as a binary payload in a standard DICOM object. In this manner, Slicer's data can be pushed/pulled from PACS for integration with and sharing across hospital workflows.

== 5.2.4. Community Software Process ==
<em>Stephen R. Aylward</em>

The goal of the Community Software Process effort is to provide tools and processes that make it easy for algorithms developers to contribute methods to the NA-MIC Kit, while maintaining the NA-MIC Kit's high-quality software standards.

=== Major Developments ===

This year, we have seen massive expansion and significant stabilization of the NA-MIC Kit. While these two accomplishments may seem at odds, they actually represent the planned progression of our community software processes. The specific aims and approaches we pursued to achieve these accomplishments are as follows:

* <em>Provide a modern, stable platform:</em> Slicer 4.0 has been released. This is a major milestone in the NA-MIC community. Slicer 4.0 represents a re-write of the majority of the slicer core to achieve stability, remove redundancy, refactor inefficiencies, and provide new pathways for growth. The most noticeable change is the conversion of the user interface to Qt - which provided speed, stability, and support from the well established Qt community.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python has been adopted as the preferred scripting language, and it has been tightly integrated into Slicer 4.0. Python is a powerful scripting language with strong scientific computing support via add-on libraries such as SciPy, NumPy, and NiPy. We have tightly integrated it with Slicer so that python scripts can modify and extend the Slicer GUI, manipulate Slicer's data representations (i.e., the MRML Scene), and call other extensions in Slicer to specify novel workflows.
** Slicer Extension Manager is now the "Slicer Catalog." It is a new web-based system that builds upon the "App Store" concept that is familiar to Android and Apple users. Users can easily install, uninstall, rate, and comment on extensions. Developers can easily add new extensions, upload revisions, add screenshots, and respond to feedback from users.

* <em>Provide access to the best algorithms:</em> ITKv4 has been released by the Insight Software Consortium, and we have begun integrating this new version of ITK and its associated wrapping for Python (i.e., SimpleITK) into Slicer 4.0.

* <em>Provide easy access to clinical data:</em> Upgraded the version of the DICOM library (DCMTK) used by Slicer and provided improved DICOM RT support. We also have begun supporting Ultrasound (e.g., video) and 4D (e.g., gated CT) data in Slicer.

* <em>Provide easy-to-create and easy-to-access documentation:</em> We have integrated the extension writing and the documentation generation processes. The documentation created when an extension is written is now automatically ported to a web host for easier access from within and from outside of Slicer.

=== Plans ===

The planned efforts of the Community Software Processes are continuations of ongoing work:

* <em>Provide a modern, stable platform:</em> Slicer quality will continue to be improved via refactoring and via expanded emphasis on testing. Refactoring of the core is nearly complete and new efforts will be directed by the Algorithms team - to support their evolving needs and to inspire future research directions. Testing will evolve from code unit testing to GUI testing. Kitware's ParaView team has developed a semi-automated GUI testing system. It can record and then play-back user interactions. It can also verify that the user interface and Slicer output matches a pre-defined state. In this way, algorithm developers can more easily implement regression tests to ensure the continued operation of their modules.

* <em>Provide a simple interface for algorithm developers to extend Slicer:</em>
** Python: We will continue to promote Python as the preferred language for scripting in Slicer. It will be used for algorithm prototyping, parameter exploration, and workflow development and delivery. In particular, we expect future development to facilitate scripts that feature interactive algorithms running within Slicers 2D and 3D visualizations.
** Slicer Catalog: Future work will focus on extending the foundation introduced in Slicer 4.1. New developments will address hosting "extension packages" (e.g., the microscopy package or the DTI package of extensions) as well as hosting data, tutorials, videos, and other adjunct material.

* <em>Provide access to the best algorithms:</em> We will complete integration of ITKv4 and its associated SimpleITK (for python) into Slicer 4. Special attention will be given to ensuring that the upgrade will not disrupt the operation of existing modules.

* <em>Provide easy access to clinical data:</em> The OFFIS and CTK developers anticipate further updated to DCMTK and other clinical data systems used by Slicer. We will continue, in particular, to broaden and stabilize Slicer's support of DICOM, DICOM RT, Ultrasound, video, and 4D data.

= 5.3. NA-MIC Kit =
The NA-MIC Kit is designed to accelerate the pace of research and facilitate clinical evaluation. It provides (a) a flexible yet stable execution and visualization engine with strong support for clinical data (Slicer), (b) methods for extending that platform and sharing those extensions with others, and (c) tools for community software development. The major components of the NA-MIC Kit are illustrated in Fig. 2.

[[image:2012_Engineering_NAMICKit.png|500px|center]]
<em>Figure 2. The NA-MIC Kit is a collection of applications, libraries, and processes for bridging algorithm developers, engineers, and clinical researchers. Slicer is the primary vehicle for deploying algorithms. The other components of the NA-MIC Kit addresses the critical yet often overlooked elements of data sharing, integration into clinical workflows, code quality assurance, cross-platform development, and much more.</em>

== 5.3.1. Maturation ==
<em>Stephen R. Aylward</em>
As mentioned in Section 5.2., Slicer has undergone massive expansion while also achieving improved stability. The same is true for the NA-MIC Kit as a whole. This evolution represents a maturation of our tools as well as the community. Open-source software, good software practices, and our tools are becoming the leading standards in our fields. Large communities of users and developers are forming around many of the components that we have chosen to use and that we have created for the NA-MIC Kit. The many improvements and new features of Slicer are discussed in Section 5.2. Below we highlights the evolution of the other tools in the NA-MIC:

* CMake 2.8.7 was released with support from NA-MIC. CMake is the foundation of the Slicer build process. It greatly facilitates building Slicer on multiple platforms, using a wide range of support libraries within Slicer, and packaging Slicer for redistribution. CMake is downloaded over 2,000 times per day. It has become the industry standard for cross-platform development, and NA-MIC has played a key role in driving and funding its development.

* CDash 2.0.2 (with CTest) was released with support from NA-MIC. CDash and CTest are responsible for the nightly regression testing of the core code and extensions of Slicer. NA-MIC has driven more of the evolution of this project than nearly any other end-user application. In the CDash releases during this past project cycle, one of the most significant contributions to CDash from NA-MIC was the package upload process. This process allows the many machines that are used to test Slicer every night to upload the executables and packages they create during testing to the main CDash server. This, in turn, allows users to download those testing packages and run additional tests or use them in their research. This complete automation of the test-release cycle is a massive time-saver for the Service core and has greatly reduced the time to discover and resolve bugs and to improve the stability of Slicer. More details on this process is available in a blog at: http://www.kitware.com/blog/home/post/249

* DCMTK 3.6 was released with support from NA-MIC. DCMTK is the DICOM toolkit used in Slicer for local object IO and for networking Slicer with DICOM PACS. This release offers improved support for jpeg compressed DICOM images, for structured reports, for large file support, and for RT objects. Further details are available at http://www.kitware.com/blog/home/post/88

* XNAT

== 5.3.2. Expansion ==

The maturation of the foundation of the NA-MIC Kit has allowed NA-MIC to pursue new opportunities with less effort and greater confidence. Highlights regarding the expansion of the toolkit into new areas include:

* Slicer Catalog:

* Package Manager:

* CTK is the toolkit NA-MIC created in collaboration with other open-source toolkits (e.g., MITK from the German Cancer Research Center in Heidelberg, XIP from Siemens, GIMIAS from UPF in Spain, and OpenMAF from U of Bologna) to host custom Qt and DCMTK modules for crafting medical applications. CTK now provides several innovative GUI and DICOM elements that specifically save GUI space, user-time, and developer effort in medical applications. Examples of the widgets provided by CTK are discussed in the blog: http://www.kitware.com/blog/home/post/169

== 5.3.3. Roadmap ==

In addition to expanding into new areas, we

=== Progress ===
* Package Manager
* Updates to ITK, VTK, Qt, CMake, DCMTK, ...
* CTK
* GUI Testing

=== Plans ===
== 5.3.2. Release ==
<em>Stephen R. Aylward</em>
=== Release Schedule ===
=== Recent Change Logs ===

2012 Progress Report Science Wiki Version Engineering

2012-04-20T22:37:58Z

Aylward: /* 5.3. NA-MIC Kit */

2012 Progress Report Science Wiki Version Engineering

2012-04-20T21:42:30Z

Aylward: /* 5.2.3. Data Management Platform */

2012 Progress Report Science Wiki Version Engineering

2012-04-20T19:59:55Z

Aylward: /* 5.3. NA-MIC Kit */

2012 Progress Report Science Wiki Version Engineering

2012-04-20T19:39:55Z

Aylward: /* 5.2.4. Community Software Process */

2012 Progress Report Science Wiki Version Engineering

2012-04-20T19:27:48Z

Aylward: /* 5.2.4. Community Software Process */