NAMIC Wiki - User contributions [en]

Leadership:Publications Database 2007

2007-09-04T16:52:27Z

Dsjen: /* September 1 2007 */

=September 1 2007=

*[http://www.na-mic.org/publications/?text=005149 Papers view]
*[http://www.na-mic.org/Special:PubDB_Gallery%3Fsponsors%3D005149 Image Gallery view]

During the last few months we have rolled out a publications database framework, based on infrastructure developed by Kitware.

The two links above provide you views into this database that are specific to NA-MIC.

Highlights:

*Uploading follows a self-serve model. If you have problems with an upload (button on the same row as the search), our webmaster, Marianna Jakab, marianna at bwh.harvard.edu can help.
*The database can import from medline and export in formats that are compatible with endnote and bibtex.
*The database is not limited to medline papers but can also accommodate other peer reviewed publications.
*the database can hold files and data (pdf, jpg, gif, png, .tgz, etc.)
*the database holds information about the grants acknowledged by a paper

Checked:
*Utah no
*MIT yes
*UNC/CS no
*Georgia Tech no
*MGH yes
*Kitware no
*GE no
*UCLA no
*UCSD no
*Isomics yes
*PNL no
*UNH/Indiana no
*UCI no
*CAMH no
*MIND no
*Queens no
*UNC/Psych no
*Kubiki no

Algorithm:MGH:DTI POIStats

2007-07-31T16:01:48Z

Dsjen:

= Path of Interest =

[[Image:Poistats.png|thumb]] The goal of the POIStats (Path-of-Interest Statistics) algorithm is to calculate the highest probability path between two user-defined seed regions from magnetic resonance diffusion tensor data. The best path is determined by minimizing the energy of the entire path through randomization of the position of the control points of a spline curve drawn through the data and of the position of the endpoints. The energy of each point in the path is given by the negative natural logarithm of the scaled orientation density function at that point. The magnitude of the perturbation is time-step dependent – the magnitude is decreased exponentially with time step number. A set of replicates are used to explore the path parameter space and minimization of the path energy is achieved using a Metropolis algorithm with a constant percentage reduction of the temperature. The Metropolis algorithm accepts a path if its energy is less than that of the current lowest energy path; otherwise it accepts the path with a probability based on the difference in energy between the current path and the current best path normalized by the current temperature. Replicates can be exchanged between temperature baths and the exchange is determined also using a Metropolis algorithm.

== Project Weeks ==
*[[Media:2007_Project_Half_Week_PoistatsSlicerItkIntegration.ppt| ITK/Slicer3 Implementation of POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]
*[[Media:2007_Project_Half_Week_PoistatsImageFormatDartmouth.ppt| Supporting Dartmouth Data for POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]

== Additional Links ==
* http://www.na-mic.org/Wiki/index.php/Algorithm:MGH
* http://www.na-mic.org/Wiki/index.php/AHM_2006:ProjectsDTIPathOfInterest

File:Poistats.png

2007-07-31T15:56:02Z

Dsjen: Image of saggital slice and path.

Image of saggital slice and path.

Projects/Diffusion/Contrasting Tractography Measures

2007-07-31T15:39:43Z

Dsjen: /* Overview */

=Overview=
{| border="1" cellpadding="5"
|- style="background:#c2c2c2; color:black" align="left"
| style="width:20%" | Site
| style="width:30%" | Streamline Tractography Algorithm
| style="width:10%" | Input
| style="width:10%" | Volumetric Output
| style="width:10%" | Geometric Output
| style="width:20%" | Other Information
|-
| style="background:#ffffdd; color:black"|UNC
| style="background:#cbe2e5; color:black"|Streamline (Fiber Viewer)
| style="background:#fff6a6; color:black"|DTI
| style="background:#c4f4af; color:black"|None
| style="background:#cbe2e5; color:black"|Tracts
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|Iowa
| style="background:#cbe2e5; color:black"|Streamline (GTract)
| style="background:#fff6a6; color:black"|DTI
| style="background:#c4f4af; color:black"|None
| style="background:#cbe2e5; color:black"|Tracts
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|BWH
| style="background:#cbe2e5; color:black"|Streamline (Slicer)
| style="background:#fff6a6; color:black"|DWI
| style="background:#c4f4af; color:black"|None
| style="background:#cbe2e5; color:black"|Tracts
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|JHU
| style="background:#cbe2e5; color:black"|Streamline (DTI Studio)
| style="background:#fff6a6; color:black"|DWI
| style="background:#c4f4af; color:black"|None
| style="background:#cbe2e5; color:black"|Tracts
| style="background:#fff6a6; color:black"| see here
|}

{| border="1" cellpadding="5"
|- style="background:#c2c2c2; color:black" align="left"
| style="width:20%" | Site
| style="width:30%" | Volumetric Conectivity Filter Algorithm
| style="width:10%" | Input
| style="width:10%" | Volumetric Output
| style="width:10%" | Geometric Output
| style="width:20%" | Other Information
|-
| style="background:#ffffdd; color:black"|GaTech
| style="background:#cbe2e5; color:black"|Geodesic Active Contours (Finsler/Riemannian)
| style="background:#fff6a6; color:black"|DWI or DTI
| style="background:#c4f4af; color:black"|Labelmap per bundle
| style="background:#cbe2e5; color:black"|Optimal path
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|BWH
| style="background:#cbe2e5; color:black"|Stochastic
| style="background:#fff6a6; color:black"|DTI
| style="background:#c4f4af; color:black"|Probability Map
| style="background:#cbe2e5; color:black"|None
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|Utah
| style="background:#cbe2e5; color:black"|Volumetric Connectivity (Riemannian)
| style="background:#fff6a6; color:black"|DWI or DTI
| style="background:#c4f4af; color:black"|Tract label map
| style="background:#cbe2e5; color:black"|Isosurface of tract
| style="background:#fff6a6; color:black"| see here
|-
| style="background:#ffffdd; color:black"|MGH
| style="background:#cbe2e5; color:black"|Path of Interest (POI stats)
| style="background:#fff6a6; color:black"|DTI
| style="background:#c4f4af; color:black"|Tracts
| style="background:#cbe2e5; color:black"|Tracts
| style="background:#fff6a6; color:black"| may not be available for testing
|}

{| border="1" cellpadding="5"
|- style="background:#c2c2c2; color:black" align="left"
| style="width:20%" | Site
| style="width:30%" | Other
| style="width:10%" | Input
| style="width:10%" | Volumetric Output
| style="width:10%" | Geometric Output
| style="width:20%" | Other Information
|-
| style="background:#ffffdd; color:black"|BWH
| style="background:#cbe2e5; color:black"|Atlas Cluster
| style="background:#fff6a6; color:black"|Tracts
| style="background:#c4f4af; color:black"|Labelmap per bundle
| style="background:#cbe2e5; color:black"|Bundles
| style="background:#fff6a6; color:black"| see here
|}

== UNC ==

[[ Algorithm:UNC:DTI#Quantitative_Analysis_of_Fiber_Tract_Bundles | Overview of UNC Tractography Methods ]]

The UNC tractography measure methodology produces fiber bundles using a standard streamline tractography algorithm [http://www.ia.unc.edu/dev/download/fibertracking/index.htm FiberTracking]. The fiber bundles are attributed with tensor data at each point along the bundle. The user uses clustering and manual editing tools in [http://www.ia.unc.edu/dev/download/fiberviewer/index.htm FiberViewer] to identify the fiber bundle and remove outliers. The user identifies an origin on the fiber bundle and computes statistics of the bundle as a function of arc-length along the bundle.

* Inputs
** DWI or DTI
** ROI for seed regions for tractography
* Outputs
** Fiber bundle tracts viewable in FiberViewer or Slicer3
** Summary statistics of fiber bundle as function of arc length (text file)

== Iowa ==
The University of Iowa tractography program [http://mri.radiology.uiowa.edu/mediawiki/index.php/GTRACT_Users_Guide GTRACT] is based on a modified streamlines algorithm. The advantage of this algorithm is that it helps to resolve fibers in regions where there are crossing or fanning fibers. We have also instrumented a fast marching based algorithm into GTRACT that we are currently evaluating. These algorithms require a seed region as input and will generate a VTK file representing the fiber tracts. Data associated with anisotropy, curvature or cost of the tract can be included as point data associated with the fiber tract. Tools are also available for computing the distance between fiber tracts.

*Inputs
** DWI or DTI data (DICOM or other ITK supported format)
** Parameters defining the diffusion directions
** Binary image representing the regions of interest for seeds

*Outputs
** Tensor image
** ADC and anisotropy images as defined by the user
** Fiber tracts in VTK format

== GATech ==

[[ Algorithm:GATech:DWMRI_Geodesic_Active_Contours | Geodesic Active Contours for Fiber Tractography and Fiber Bundle Segmentation ]]

These algorithms find the optimal path (i.e. "the anchor tract") connecting two ROIs, which is equivalent to finding a geodesic on a manifold (which may be any Finsler manifold, such as the Riemannian manifold). Then, the associated fiber bundles is segmented from the data via a region-based flow adapted for DW-MRI direction-dependent data.

* Inputs
** DWI or DTI
** ROI for seed regions (i.e. the endpoints of the fiber bundle, which most likely correspond to the associated gray matter regions)
* Outputs
** VTK files of the anchor tracts
** VTK files of the volumetric fiber bundle
** Summary statistics of fiber bundle as function of arc length (text file)

Note, I've put this together which may have some educational and/or thought provoking value. It is certainly biased towards the ideas entertained at Georgia Tech over the past few years and could be greatly extended/enhanced with more input from others in the community. Check it out here: [[Algorithm:GATech:DWMRI_Musings | DW-MRI Musings]].

== BWH ==
'''Stochastic Tractography'''

[http://www.na-mic.org/Wiki/index.php/Algorithm:MIT:DTI_StochasticTractography Stochastic Tractography] is a Bayesian approach to estimating nerve fiber tracts from DWMRI (Diffusion Weighted Magnetic Imaging) images. The Bayesian framework provides a measure of confidence regarding the estimated tracts. This measure of confidence allows the algorithm to generate tracts which pass through regions with uncertain fiber directions, revealing more details about structural connectivity than non-Bayesian tractography algorithm.

*Inputs
** DWI and associated parameters (b-values, gradient directions)
** Posterior White Matter probability map

*Outputs
** Brain Connectivity Map
** Tract-Averaged FA Distribution
** Tract Length Distribution

== UTAH ==
This is a PDE-based approach to white matter connectivity from DTI that is founded on the principal of minimal paths through the tensor volume. Our method computes a volumetric representation of a white matter tract given two endpoint regions. We have also developed statistical methods for quantifying the full tensor data along these pathways, which should be useful in clinical studies using DT-MRI.

*Input
**DWI or DTI
**ROIs of tract endpoints
*Output
**Labelmap of tract
**Parameterization along tract
**Regression of tensor data along tract (tensors, FA, MD, etc)

== BWH ==
[[Image:CingulumSlicer.png|thumb|right|250px| Cingulum Bundle (case D00917)]]
The DT-MRI module of [http://www.slicer.org/ Slicer] uses a streamline tractography algorithm with a mutilple-ROI approach (AND and NOT operators).

*Inputs
** DWI or DTI data
** ROI
*Outputs
** Fiber tracts in VTK format

Example: Cingulum bundle generated from the [http://wiki.na-mic.org/Wiki/index.php/Projects/Diffusion/2007_Project_Week_Contrasting_Tractography_Measures/ROI_Definitions validation data ROIs].

== BWH ==
Clustering information to be entered here

== MGH ==
The goal of the [http://www.na-mic.org/Wiki/index.php/Algorithm:MGH:DTI_POIStats POIStats] (Path-of-Interest Statistics) algorithm is to calculate the highest probability path between two user-defined seed regions from DTI. The best path is determined by minimizing the energy of the entire path through randomization of the position of the control points of a spline curve drawn through the data and of the position of the endpoints.

*Input
**DTI
**ROIs of tract endpoints and/or intermediate points
*Output
**Volume label map of tracts
**Probability optimal path goes through voxels
**Coordinates of optimal path

Return to [[Projects/Diffusion/2007_Project_Week_Contrasting_Tractography_Measures | ContrastingTractography Project Page]]

Algorithm:MGH:DTI POIStats

2007-07-31T15:19:04Z

Dsjen:

= Path of Interest =

The goal of the POIStats (Path-of-Interest Statistics) algorithm is to calculate the highest probability path between two user-defined seed regions from magnetic resonance diffusion tensor data. The best path is determined by minimizing the energy of the entire path through randomization of the position of the control points of a spline curve drawn through the data and of the position of the endpoints. The energy of each point in the path is given by the negative natural logarithm of the scaled orientation density function at that point. The magnitude of the perturbation is time-step dependent – the magnitude is decreased exponentially with time step number. A set of replicates are used to explore the path parameter space and minimization of the path energy is achieved using a Metropolis algorithm with a constant percentage reduction of the temperature. The Metropolis algorithm accepts a path if its energy is less than that of the current lowest energy path; otherwise it accepts the path with a probability based on the difference in energy between the current path and the current best path normalized by the current temperature. Replicates can be exchanged between temperature baths and the exchange is determined also using a Metropolis algorithm.

== Project Weeks ==
*[[Media:2007_Project_Half_Week_PoistatsSlicerItkIntegration.ppt| ITK/Slicer3 Implementation of POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]
*[[Media:2007_Project_Half_Week_PoistatsImageFormatDartmouth.ppt| Supporting Dartmouth Data for POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]

== Additional Links ==
* http://www.na-mic.org/Wiki/index.php/Algorithm:MGH
* http://www.na-mic.org/Wiki/index.php/AHM_2006:ProjectsDTIPathOfInterest

SanteFe.Tractography.Conference

2007-07-31T14:56:44Z

Dsjen: /* Conference Attendees */

= Goals =
We in NA-MIC, and our collaborating colleagues from BIRN, NAC and UIowa, are in a unique position to make a substanital contribution to the field of knowledge concerning the validation of medical image processing of Diffusion Tensor Image data. Among our faculty are leaders in the field of not only DTI analysis algorithm development, but also of validation and calibration. We seek to use our unique opportunity for multi-site collaboration to advance knowledge in this area for the benefit of clinical and computational scientists.

* To compare and contrast the results of tractography algorithms included in or supported by the NA-MIC Toolkit on a benchmark dataset of Diffusion Tensor Imaging (DTI) data. 
* To develop a framework for systematically and statistically comparing and contrasting these outcome measures mapped to specific manuscript preparation. 
* To map out appropriate leadership for each of the proposed manuscripts. 
* To initiate development of tutorials for tractography algorithms not yet in the NAMIC Training Compendium. 
* To propose methods for NA-MIC benchmarks of calibration and validation of tractography algorithms for further discussion at the 2008 AHM. 

== Conference Logistics ==

* October 1-2, 2007, 8:00 AM- 5:00 PM 
* The workshop is being held in the Governors Room at the Inn of the Governors, 101 W. Alameda, Sante Fe, NM 87501, 1-800-234-4534, http://www.innofthegovernors.com/ 
* We have booked a block of rooms for $169.00/night for single or double occupancy September 30- October 3, 2007 (Sunday through Tuesday nights). Our reservation code will be posted shortly. The price includes a full breakfast buffet, wireless internet access in the lobby, meeting room and sleeping rooms at no additional cost. 
* Fly into Albuquerque, NM. Information about shuttles from the airport to the hotel can be found here http://www.sandiashuttle.com/.

Many grateful thanks to John Rasure and Debbie Lynch of the MIND Institute for their assistance in making these arrangements.

==Registration==
* '''To register, add your name to the list of attendees below and make your flight and hotel reservations'''

* Questions about logistics and the content of the Conference should be addressed to Randy Gollub (rgollub at partners.org).

* '''This Conference is supported by the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics'''.

== Conference Attendees ==

* Ross Whitaker, PhD
* Guido Gerig, PhD
* Carl Fredrick Westin, PhD
* Marek Kubicki, MD, PhD
* Sylvain Bouix, PhD
* [[User:Randy|Randy Gollub, MD, PhD]], Harvard Medical School (Department of Psychiatry and Martinos Center, Department of Radiology, Massachussets General Hospital)
* [[User:SPujol|Sonia Pujol, PhD]], Harvard Medical School (Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital)
* H. Jeremy Bockholt, The MIND Institute
* [[User:Melonakos|John Melonakos]], Georgia Tech
* Ron Kikinis, MD
* Tom Fletcher, Utah
* Dennis Jen, MGH

== Preparation for Workshop -- ''Important Information for all attendees'' ==

Suggested background reading for workshop: 

Suggestions:

#[[Media:AHM2006-validation-DTI-gg.ppt| Guido's 2006 AHM presentation on Validation strategies for DTI analysis]]
#[[Media:DWI.reproducibility.pdf]]
#[[http://cds.ismrm.org/protected/DiffusionWorkshop05 If any of you attended the 2005 ISMRM Workshop on Methods for Quantitative Diffusion of MRI of Human Brain and can get us access to the detailed summary, I have seen it and it might be very useful]]
#Presentations by and Fitzpatrick from the [http://idm.univ-rennes1.fr/VMIP/miccai2003/presentations.html MICCAI 2003 Tutorial on Validation in Medical Image Processing]
#Peruse the webpages associated with the [http://www.vuse.vanderbilt.edu/~image/registration/ Retrospective Image Registration Evaluation project]
#[http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/10818/34114/01624925.pdf anyone have access to this?]

Please complete the following items prior to the workshop.
'''This is hands-on Conference. All participants must come with their own computer loaded with the calibration data and the results of their own algorithm analysis. ''' 

'''Benchmark Datasets'''

== Agenda ==

=== '''October 1, Meeting 8:30 AM - 5 PM''' ===
* 7:30- 8:30 AM Enjoy the breakfast buffet at the hotel
* 8:30 - 8:40 AM '''Goals of Conference'''
* 8:40 - 9:40 AM '''Presentations of Results from each of the participants'''
* 9:40 - 10:15 AM '''Discussion'''
* 10:15 -10:30 Coffee Break
* 10:30 - 11:45 AM '''Expert speaker presentation on methods of statistical comparison of similar data, who?'''
* 11:45 - 1:00 Lunch together at local restaurant
* 1:00 - 3:00 PM '''?'''
* 3:00 - 3:15 PM Coffee Break
* 3:15 - 5:00 PM '''?'''

* 7:00 PM Dinner at local resturant(s) to be found by wandering around town

=== '''October 2, 8:30 AM - 5 PM''' ===
* 7:30- 8:30 AM Enjoy the breakfast buffet at the hotel
* 8:30 - 8:40 AM '''Synopsis of yesterday's accomplishments'''
* 8:40 - 10:15 ''''''
* 10:15 -10:30 Coffee Break
* 10:30 - 11:45 '''?'''
* 11:45 - 1:00 PM Lunch together at local restaurant
* 1:00 - 3:00 PM '''?'''
* 3:00 - 3:15 PM Coffee Break
* 3:15 - 5:00 PM Formulation of action plan and assignment of tasks

 

Return to [[Projects/Diffusion/2007_Project_Week_Contrasting_Tractography_Measures | Contrasting Tractography Project Page]]

2007 Core 1 Meeting

2007-05-15T15:25:21Z

Dsjen: /* Attendees */

== Agenda ==

*May 30 -
** 8:30am Remarks (Whitaker)
*** Introductions
*** Discuss goals and agenda
** 9:00am Driving Biological problems '''[[2007_Core_1_Meeting_DBP_Guidlines|(Guidelines for talks)]]'''
*** Marek Kubicki - Harvard/B&W
*** Gabor Fichtinger - Johns Hopkins
*** (break)
*** H. Jeremy Bockholt - Mind Institute
*** Heather Cody - UNC
**12:00pm Lunch
** 1:00pm Invited Talk: Daniel Rueckert
** 2:00pm Break out sessions with DPBs
** 3:30pm Break
** 3:45-6:00pm Core 1 presentations
*** Georgia Tech (name)
*** MGH (name)
*** MIT (name)
*** UNC (name)
*** Tom Fletcher (Utah), "Volumetric Connectivity for analysis of DTI"
*May 31
** 8:30am Core 1 presentations
*** Utah "Nonparametric Shape Modeling of Object Complexes" (Speaker TBD)
*** UNC (name)
*** (break)
*** MIT (name)
*** MGH (name)
*** Georgia Tech (name)
** 12:30pm Lunch
** 1pm Strategic planning, software
*** Progress/interactions with DBPs
*** Software contributions and Core 2 interactions
*** Performance assessment and renewal
** 5pm Finish

== Logistics ==

'''Dates:''' May 30-31, 2007.

Please plan to travel on May 29, so that we can start in the morning of May 30.
The meeting will be two full days; please plan to stay until 5pm on May31.

'''Location:''' MIT.

The meeting will take place in the Kiva conference room, on the 4th floor of Stata Center. We will post signs in the building, directing you to the conference room.

'''Food:''' Breakfast and lunch will be provided on May 30-31. We will also organize people into groups to go out for dinner on May 30. There are plenty of restaurants around Central Square and MIT.

'''Hotel:''' There is no official hotel for the meeting. Here is some information about Boston area hotels that are convenient to NA-MIC events: [[Boston_Hotels|Boston_Hotels]]. Please book your rooms early.

== Attendees ==

* Ross Whitaker
* Polina Golland
* Ron Kikinis
* Guido Gerig(UNC)
* Heather Cody (UNC Autism DBP)
* Allen Tannenbaum
* John Melonakos
* H. Jeremy Bockholt (MIND/UNM)
* Harvard Core 3: Marek Kubicki
* Mert R Sabuncu (MIT CSAIL)
* Lilla Zollei (NMR, MGH)
* Serdar K Balci (MIT CSAIL)
* Tom Fletcher (Utah)
* Josh Cates (Utah - tentative)
* Gabor Fichtinger (JHU)
* Jim Miller (GE Research)
* Dennis Jen

Projects:DTIPathOfInterest

2007-05-03T19:32:49Z

Dsjen:

'''Project''': DTI path of interest (POI) analysis

'''Use case''': "I'd like to be able to find the optimal path between two regions in a tensor image." - Saykin

'''Impact''': Medium (Saykin)

'''Difficulty''': Low (Snyder)
----

'''Vision''': Software tool which can find optimal and sub-optimal paths between regions of interest in a tensor image, and produce associated statistics and probability density images. Should work on output of Slicer DTI analysis and ROI drawing tools. Tool should generate probability density image, sample statistics from this image, and from user defined image w/ same geometry.

'''Goal''': Provide software deliverable with robust support for input images with varying slice prescription, voxel size, tensor measurement frame, etc. Ensure compatibility with Slicer file formats and Dartmouth tensor data conventions.

'''Test Data''': Six healthy individuals from the [https://portal.nbirn.net/BIRN/cgi-bin/DataGrid/browse.cgi?browseloc=/home/Projects/NAMIC__0003/Files/Dartmouth/HealthyControls6/DTIdata Dartmouth DTI data set].

'''Team members''': Fischl, Yendiki, Helmer, Saykin, West, Jen

* DTI Coordinate System Support: Gordon Kindlmann, Raul San Jose, Steve Pieper

'''Win conditions'''

'''MGH''': Improved robustness and portability of existing POI tool.

'''Dartmouth''': Software deliverable.
----

'''Steps''':

# Requirements extraction (Snyder/Saykin): '''done'''
# Create Wiki project page (Snyder): '''done'''
# Port MGH POI tool to Dartmouth compatible version (Snyder/Tuch): '''done'''
# Test output visualization in Slicer (Snyder): '''done'''
# Process test data with MGH tensor reconstruction and POI analysis tools; use for port validation (Snyder): '''done'''
# Software deliverable installation at Dartmouth (West/Snyder): '''done'''
# Port to ITK (Jen): '''done'''
# Test on expanded data set (West/Jen): '''in queue'''
# Develop path initialization (Jen): '''in progress'''
# Develop model selection for selecting optimal number of control points (Yendiki): '''in queue'''
# Develop algorithm for perturbing control points based on neighboring tensors (Yendiki): '''in progress'''
# Submit to the Insight Journal (Jen): '''in queue'''

----

'''Progress notes''':

* Dartmouth Dicom series -> NIFTI image conversion toolset completed.
* Tensor reconstruction workflow identified and tested.
* Path of interest tool ported.
* Installed at Dartmouth
* Currently in testing/use by John West
*[[Media:2007_Project_Half_Week_PoistatsSlicerItkIntegration.ppt| ITK/Slicer3 Implementation of POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]
*[[Media:2007_Project_Half_Week_PoistatsImageFormatDartmouth.ppt| Supporting Dartmouth Data for POIStats, Progress at Project Half Week, Jan 2007 (4-Block PPT)]]

2007 Scientific Report Timeline

2007-04-23T18:42:33Z

Dsjen: /* Timeline Modifications */

= Introduction =

This section of the report gives the milestones for years 1 through 3 that are associated with the timelines in the original proposal. We have organized the milestones by core. For each milestone we have indicated the proposed year of completion and a very brief description of the current status. In some cases the milestones include ongoing work, and we have try to indicate that in the status. We have also included tables that list any significant changes to the proposed timelines. On the wiki page, we have links to the notes from the various PIs that give more details on their progress and the status of the milestones.

'''These tables demonstrate that the project is, on the whole, proceeding according to the originally planned schedule.'''

= Core 1 =

== Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''MIT'''
| 1
| '''Shape-based segmentation'''
|
|
|-
| '''MIT'''
| 1.1
| Methods to learn shape representations
| Year 2
| Completed
|-
| '''MIT'''
| 1.2
| Shape in atlas-driven segmentation
| Year 4
| Partially completed - preliminary results
|-
| '''MIT'''
| 1.3
| Validate and refine approach
| Year 5
| Partially completed - preliminary validation
|-
| '''MIT'''
| 2
| '''Shape analysis'''
|
|
|-
| '''MIT'''
| 2.1
| Methods to compute statistics of shapes
| Year 4
| Partially completed -software framework
|-
| '''MIT'''
| 3
| '''Analysis of DTI data'''
|
|
|-
| '''MIT'''
| 3.2
| Fiber statistics
| Year 4
| Partially completed --- tract clustering
|-
| '''Utah'''
| 1
| '''Processing of DTI data'''
|
|
|-
| '''Utah'''
| 1.1
| Filtering of DTI
| Year 2
| Completed
|-
| '''Utah'''
| 1.2
| Quantitative analysis of DTI
| Year 3
| Completed partially, ongoing
|-
| '''Utah'''
| 1.3
| Segmentation of cortex/WM
| Year 3
| Completed partially, ongoing
|-
| '''Utah'''
| 1.4
| Segmentation analysis of white matter tracts
| Year 3
| Algorithms complete/published, refining and applying to Core 3 data.
|-
| '''Utah'''
| 2
| Nonparametric Shape Analysis
| Year 5
| Incomplete, ongoing.
|-
| '''Utah'''
| 2.1
| Framework in place
| Year 3
| Complete
|-
| '''Utah'''
| 2.2
| Demonstration on shape of neuranatomy (from Core 3)
| Year 4
| Complete
|-
| '''Utah'''
| 2.3
| Development for multiobject comlexes
| Year 4
| Complete
|-
| '''Utah'''
| 2.4
| Demonstration of NP shape representations on clinical hypotheses from Core 3
| Year 5
| Incomplete, ongoing
|-
| '''UNC'''
| 1
| '''Statistical shape analysis'''
|
|
|-
| '''UNC'''
| 1.1
| Comparative anal. of shape anal. schemes
| Year 2
| Completed
|-
| '''UNC'''
| 1.3
| Statistical shape analysis incl. patient variable
| Year 5
| Incomplete, ongoing
|-
| '''UNC'''
| 2
| '''Structural analysis of DW-MRI'''
|
|
|-
| '''UNC'''
| 2.1
| DTI tractography tools
| Year 4
| Completed
|-
| '''UNC'''
| 2.2
| Gometric characterization of fiber tracts
| Year 5
| Completed
|-
| '''UNC'''
| 2.3
| Quant. anal. of diffusion along fiber tracts
| Year 5
| Completed
|-
| '''GaTech'''
| 1.1
| ITK Implementation of PDEs
| Year 2
| Completed
|-
| '''GaTech'''
| 1.1
| Applications to Core 3 data
| Year 4
| Completed
|-
| '''GaTech'''
| 1.2
| New statistic models
| Year 4
| Completed
|-
| '''GaTech'''
| 1.2
| Shape anaylsis
| Year 4
| Preliminary results and ongoing
|-
| '''GaTech'''
| 2.0
| Integration in to Slicer
| Year 4-5
| Preliminary results and ongoing
|-
| '''MGH'''
| 1
| '''Registration'''
|
|
|-
| '''MGH'''
| 1.1
| Collect DTI/QBALL data
| Year 2
| Completed
|-
| '''MGH'''
| 1.2
| Develop registration method
| Year 2
| Completed
|-
| '''MGH'''
| 1.3
| Test/optimize registration method
| Year 3
| In Progress
|-
| '''MGH'''
| 1.4
| Apply registration on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 2
| '''Group DTI Statistics'''
|
|
|-
| '''MGH'''
| 2.1
| Develop group statistic method
| Year 2
| Partially Complete
|-
| '''MGH'''
| 2.2
| Apply on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 3
| '''Diffusion Segmentation '''
|
|
|-
| '''MGH'''
| 3.1
| Collect DTI/QBALL data
| Year 2
| Completed
|-
| '''MGH'''
| 3.2
| Develop/optimize segmentation algorithm
| Year 3
| In Progress
|-
| '''MGH'''
| 3.3
| Integrate w/ tractography
| Year 4
| In Progress
|-
| '''MGH'''
| 3.4
| Apply on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 4
| '''Group Morphometry Statistics'''
|
|
|-
| '''MGH'''
| 4.1
| Develop/optimize statistics algorithms
| Year 3
| Complete
|-
| '''MGH'''
| 4.2
| Develop GUI for Linux
| Year 3
| Partially Complete
|-
| '''MGH'''
| 4.3
| Slicer integration
| Year 3
| In Queue
|-
| '''MGH'''
| 4.4
| Compile application on Windows
| Year 4
| In Queue
|-
|}

== Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| '''MIT'''
| 2.4
| Plan to develop software infrastructure to integrate shape analysis tools into the pipeline for population studies.
| New
|-
| '''MIT'''
| 4
| Plans to for fMRI development including local and atlas-based priors for quantifying activation.
| New
|-
| '''Utah'''
| 2.2 (removed)
| Feature-based brain image registration.
| Shift emphasis to shape-based analysis/registration
|-
| '''Utah'''
| 2.1 (removed)
| Cortical filtering and feature detection
| Effort is subsumed by other Core 1 partners (e.g. see MGH/Freesurfer)
|-
| '''Utah'''
| 3.0 (removed)
| Fast implmentations of PDEs
| Real-time filtering is demphasized in favor of shape/DTI analysis
|-
| '''Utah'''
| 2.1-2.3 (added, in place of cortical analysis)
| Shape analysis
| Nonparametric shape analysis added to address needs of core 3.
|-
| '''UNC'''
| 1.2
| Develop medially-based shape representation
| Remove
|-
| '''UNC'''
| 1.4
| Develop generic cortical correspondence framework (Years 3-5)
| New
|-
| '''UNC'''
| 2.4
| DTI Atlas Building (Years 2--4)
| New
|-
| '''GaTech'''
| 2.1
| FA analysis
| New
|-
| '''MGH'''
| 4.1 - 4.4 added
| Group morphometry statistics
| New
|-
|}

== [[Core_1_Timeline_Notes|Core 1 Timeline Notes ]] ==

= Core 2 =

== Core 2 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''GE'''
| 1
| '''Define software architecture'''
|
|
|-
| '''GE'''
| 1
| Object design
| Yr 1
| Completed
|-
| '''GE'''
| 1
| Identify patterns
| Yr 3
| Patterns for processing scalar and vector images, models, fiducials complete. Patterns for diffusion weighted imageryand fMRI ongoing.
|-
| '''GE'''
| 1
| Create frameworks
| Yr 3
| Frameworks for processing scalar and vector images, models, fiducials complete. Frameworks for diffusion weighted imageryand fMRI ongoing.
|-
| '''GE'''
| 2
| '''Software engineering process'''
|
|
|-
| '''GE'''
| 2
| Extreme programming
| Yr 1-5
| On schedule, ongoing
|-
| '''GE'''
| 2
| Process automatiion
| Yr 3
| On schedule, ongoing
|-
| '''GE'''
| 2
| Refactoring
| Yr 3
| Complete
|-
| '''GE'''
| 3
| '''Automated quality system'''
|
|
|-
| '''GE'''
| 3
| DART deployment
| Yr 2
| Complete
|-
| '''GE'''
| 3
| Persistent testing system
| Yr 5
| Incomplete
|-
| '''GE'''
| 3
| Automatic defect detection
| Yr 5
| Incomplete
|-
| '''Kitware'''
| 1
| '''Cross-platform development'''
|
|
|-
| '''Kitware'''
| 1
| Deploy environment (CMake, CTest)
| Yr 1
| Complete
|-
| '''Kitware'''
| 1
| DART Integration and testing
| Yr 1
| Complete
|-
| '''Kitware'''
| 1
| Documentation tools
| Yr 2
| Complete
|-
| '''Kitware'''
| 2
| '''Integration tools'''
|
|
|-
| '''Kitware'''
| 2
| File Formats/IO facilities
| Yr 2
| Complete (ongoing)
|-
| '''Kitware'''
| 2
| CableSWIG deployment
| Yr 3
| Complete (integration ongoing)
|-
| '''Kitware'''
| 2
| Establish XML schema
| Yr 4
| Incomplete
|-
| '''Kitware'''
| 3
| '''Technology delivery'''
|
|
|-
| '''Kitware'''
| 3
| Deploy applications
| Yr 1
| Complete (ongoing)
|-
| '''Kitware'''
| 3
| Establish plug-in repository
| Yr 2
| Incomplete
|-
| '''Kitware'''
| 3
| Cpack
| Yr 4-5
| Incomplete
|-
| '''Isomics'''
| 1
| NAMIC builds of slicer
| Years 2--5
| Complete
|-
| '''Isomics'''
| 1
| Schizophrenia and DBP intefaces
| Year 3---5
| Partially completed, ongoing
|-
| '''Isomics'''
| 2
| ITK Integration tools
| Year 1---3
| Completed
|-
| '''Isomics'''
| 2
| Experiment Control Interfaces
| Year 2---5
| Migration from LONI to BatchMake Underway
|-
| '''Isomics'''
| 2
| fMRI/DTI algorithm support
| Year 2---5
| Completed DTI, fMRI Ongoing
|-
| '''Isomics'''
| 2
| New DBP algorithm support
| Year 2---5
| Ongoing
|-
| '''Isomics'''
| 3
| Compatible build process
| Year 1---3
| Completed
|-
| '''Isomics'''
| 3
| Dart Integration
| Year 1---2
| Completed, upgrades ongoing
|-
| '''Isomics'''
| 3
| Test scripts for new code
| Year 2---5
| Ongoing
|-
| '''UCSD'''
| 1
| Grid computing---base
| Year 1
| Completed
|-
| '''UCSD'''
| 1
| Grid enabled algorithms
| Year 3
| Ongoing
|-
| '''UCSD'''
| 1
| Testing infrastructure
| Year 4
| Initiated
|-
| '''UCSD'''
| 2
| Data grid --- compatibility
| Year 2
| Completed
|-
| '''UCSD'''
| 2
| Data grid --- slicer access
| Year 2
| In progress
|-
| '''UCSD'''
| 3
| Data mediation --- deploy
| Year 1
| Incomplete (modfication below)
|-
| '''UCLA'''
| 1
| Debabeler functionality
| Year 1
| Continued Progress
|-
| '''UCLA'''
| 2
| SLIPIE Interpretation (Layer 1)
| Year 1--Year2
| In Progress
|-
| '''UCLA'''
| 3
| SLIPIE Interpretation (Layer 2)
| Year 1--Year2
| On Schedule
|-
| '''UCLA'''
| 3
| Developing ITK Modules
| Year2
| In Progress
|-
| '''UCLA'''
| 4
| Integrating SRB (GSI-enabled)
| Year2
| Completed
|-
| '''UCLA'''
| 5
| Integrating IDA
| Year2
| Completed
|-
| '''UCLA'''
| 5
| Integrating External Visualization Applications
| Year2
| Completed
|}

== Core 2 Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| '''Isomics'''
| 3
| Data mediation
| Delayed pending integration of databases into NAMIC infractructure
|}

== [[Core_2_Timeline_Notes|Core 2 Timeline Notes ]] ==

= Core 3 =

The Core 3 projects submitted R01 style proposals, as specified in the RFA, and did not submit timelines.

= Core 4 =

== Core 4 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''Kitware'''
| 1
| '''Implement Development Farms'''
|
|
|-
| '''Kitware'''
| 1
| Deploy platforms
| Yrs 1
| Complete
|-
| '''Kitware'''
| 1
| Communications
| Yrs 1
| Complete, ongoing
|-
| '''Kitware'''
| 2
| '''Establish software process'''
|
|
|-
| '''Kitware'''
| 2
| Secure developer database
| Yr 1
| Complete, ongoing
|-
| '''Kitware'''
| 2
| Collect guidelines
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Manage software submission process
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Configure process tools
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Survey community
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| '''Deploy NAMIC Tools'''
|
|
|-
| '''Kitware'''
| 3
| Toolkits
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Integration tools
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Applications
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Integrate new computing resources
| Yr 1
| Complete
|-
| '''Kitware'''
| 4
| '''Provide support'''
|
|
|-
| '''Kitware'''
| 4
| Esablish support infrastructure
| Yrs 1--5
| On schedule, ongoing
|-
| '''Kitware'''
| 4
| NAMIC support
| Yr 1
| Complete
|-
| '''Kitware'''
| 5
| Manage NAMIC Software Releases
| Yrs 1--5
| On schedule, ongoing
|}

== Core 4 Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| Kitware
| 2-5
| Various
| Refined/modified the sub aims
|}

== [[Core_4_Timeline_Notes|Core 4 Timeline Notes ]] ==

= Core 5 =

== Core 5 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''Harvard'''
| 1
| '''Formal Training Guidllines'''
|
|
|-
| '''Harvard'''
| 1
| Functional neuroanatomy
| Yr 1
| Complete
|-
| '''Harvard'''
| 1
| Clinical correlations
| Yr 1
| Complete
|-
| '''Harvard'''
| 2
| '''Mentoring'''
|
|
|-
| '''Harvard'''
| 2
| Programming workshops
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 2
| One-on-one mentoring, Cores 1, 2, 3
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 3
| '''Collaborative work environment'''
|
|
|-
| '''Harvard'''
| 3
| Wiki
| Yrs 1
| Complete
|-
| '''Harvard'''
| 3
| Mailing lists
| Yrs 1
| Complete
|-
| '''Harvard'''
| 3
| Regular telephone conferences
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 4
| '''Educational component for tools'''
|
|
|-
| '''Harvard'''
| 4
| Slicer training modules
| Yr 2-5
| Many complete for Slicer 2.x, Slicer 3 ongoing
|-
| '''Harvard'''
| 5
| '''Demonstrations and hands-on training'''
|
|
|-
| '''Harvard'''
| 5
| Various workshops and conferences
| Yrs 1--5
| On schedule, ongoing (see also link)
|}

== Core 5 Timeline Modifications ==

None.

== [[Core_5_Timeline_Notes|Core 5 Timeline Notes ]] ==

= Core 6 =

== Core 6 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| Isomics
| 1
| Create a collaboration metholdology for NA-MIC
|
|
|-
| Isomics
| 1.1
| develop a selection process
| Yr 1
| Done
|-
| Isomics
| 1.2
| guidelines to govern the collaborations
| Yr 1-2
| Done
|-
| Isomics
| 1.3
| Provide on-site training
| Yr 1-5
| On Schedule
|-
| Isomics
| 1.4
| develop a web site infrastructure
| Yr 1
| Done
|-
| Isomics
| 2
| Facilitate communication between NA-MIC developers and wider research community
|
|
|-
| Isomics
| 2.1
| develop materials describing NAMIC technology
| Yr 1-5
| On Schedule
|-
| Isomics
| 2.2
| participate in scientific meetings
| Yr 2-5
| On Schedule
|-
| Isomics
| 2.3
| Document interactions with external researchers
| Yr 2-5
| On Schedule
|-
| Isomics
| 2.4
| Coordinate publication strategies
| Yr 3-5
| On track
|-
| Isomics
| 3
| Develop a publicly accessible internet resource of data, software, documentation, and publication of new discoveries
|
|
|-
| Isomics
| 3.1
| On-line repository of NAMIC related publications and presentations
| Yr 1-2-3
| On Schedule
|-
| Isomics
| 3.2
| On-line repository of NAMIC tutorial and training material
| Yr 1-5
| On Schedule
|-
| Isomics
| 3.3
| Index and a searchable database
| Yr 1-2
| Done
|-
| Isomics
| 3.4
| Automated feedback systems that track software downloads
| Yr 3
| On track
|}

== Core 6 Timeline Modifications ==

== [[Core_6_Timeline_Notes|Core 6 Timeline Notes ]] ==
|}

2007 Scientific Report Timeline

2007-04-23T18:39:40Z

Dsjen: /* Timelines and Milestones */

= Introduction =

This section of the report gives the milestones for years 1 through 3 that are associated with the timelines in the original proposal. We have organized the milestones by core. For each milestone we have indicated the proposed year of completion and a very brief description of the current status. In some cases the milestones include ongoing work, and we have try to indicate that in the status. We have also included tables that list any significant changes to the proposed timelines. On the wiki page, we have links to the notes from the various PIs that give more details on their progress and the status of the milestones.

'''These tables demonstrate that the project is, on the whole, proceeding according to the originally planned schedule.'''

= Core 1 =

== Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''MIT'''
| 1
| '''Shape-based segmentation'''
|
|
|-
| '''MIT'''
| 1.1
| Methods to learn shape representations
| Year 2
| Completed
|-
| '''MIT'''
| 1.2
| Shape in atlas-driven segmentation
| Year 4
| Partially completed - preliminary results
|-
| '''MIT'''
| 1.3
| Validate and refine approach
| Year 5
| Partially completed - preliminary validation
|-
| '''MIT'''
| 2
| '''Shape analysis'''
|
|
|-
| '''MIT'''
| 2.1
| Methods to compute statistics of shapes
| Year 4
| Partially completed -software framework
|-
| '''MIT'''
| 3
| '''Analysis of DTI data'''
|
|
|-
| '''MIT'''
| 3.2
| Fiber statistics
| Year 4
| Partially completed --- tract clustering
|-
| '''Utah'''
| 1
| '''Processing of DTI data'''
|
|
|-
| '''Utah'''
| 1.1
| Filtering of DTI
| Year 2
| Completed
|-
| '''Utah'''
| 1.2
| Quantitative analysis of DTI
| Year 3
| Completed partially, ongoing
|-
| '''Utah'''
| 1.3
| Segmentation of cortex/WM
| Year 3
| Completed partially, ongoing
|-
| '''Utah'''
| 1.4
| Segmentation analysis of white matter tracts
| Year 3
| Algorithms complete/published, refining and applying to Core 3 data.
|-
| '''Utah'''
| 2
| Nonparametric Shape Analysis
| Year 5
| Incomplete, ongoing.
|-
| '''Utah'''
| 2.1
| Framework in place
| Year 3
| Complete
|-
| '''Utah'''
| 2.2
| Demonstration on shape of neuranatomy (from Core 3)
| Year 4
| Complete
|-
| '''Utah'''
| 2.3
| Development for multiobject comlexes
| Year 4
| Complete
|-
| '''Utah'''
| 2.4
| Demonstration of NP shape representations on clinical hypotheses from Core 3
| Year 5
| Incomplete, ongoing
|-
| '''UNC'''
| 1
| '''Statistical shape analysis'''
|
|
|-
| '''UNC'''
| 1.1
| Comparative anal. of shape anal. schemes
| Year 2
| Completed
|-
| '''UNC'''
| 1.3
| Statistical shape analysis incl. patient variable
| Year 5
| Incomplete, ongoing
|-
| '''UNC'''
| 2
| '''Structural analysis of DW-MRI'''
|
|
|-
| '''UNC'''
| 2.1
| DTI tractography tools
| Year 4
| Completed
|-
| '''UNC'''
| 2.2
| Gometric characterization of fiber tracts
| Year 5
| Completed
|-
| '''UNC'''
| 2.3
| Quant. anal. of diffusion along fiber tracts
| Year 5
| Completed
|-
| '''GaTech'''
| 1.1
| ITK Implementation of PDEs
| Year 2
| Completed
|-
| '''GaTech'''
| 1.1
| Applications to Core 3 data
| Year 4
| Completed
|-
| '''GaTech'''
| 1.2
| New statistic models
| Year 4
| Completed
|-
| '''GaTech'''
| 1.2
| Shape anaylsis
| Year 4
| Preliminary results and ongoing
|-
| '''GaTech'''
| 2.0
| Integration in to Slicer
| Year 4-5
| Preliminary results and ongoing
|-
| '''MGH'''
| 1
| '''Registration'''
|
|
|-
| '''MGH'''
| 1.1
| Collect DTI/QBALL data
| Year 2
| Completed
|-
| '''MGH'''
| 1.2
| Develop registration method
| Year 2
| Completed
|-
| '''MGH'''
| 1.3
| Test/optimize registration method
| Year 3
| In Progress
|-
| '''MGH'''
| 1.4
| Apply registration on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 2
| '''Group DTI Statistics'''
|
|
|-
| '''MGH'''
| 2.1
| Develop group statistic method
| Year 2
| Partially Complete
|-
| '''MGH'''
| 2.2
| Apply on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 3
| '''Diffusion Segmentation '''
|
|
|-
| '''MGH'''
| 3.1
| Collect DTI/QBALL data
| Year 2
| Completed
|-
| '''MGH'''
| 3.2
| Develop/optimize segmentation algorithm
| Year 3
| In Progress
|-
| '''MGH'''
| 3.3
| Integrate w/ tractography
| Year 4
| In Progress
|-
| '''MGH'''
| 3.4
| Apply on core 3 data
| Year 5
| In Queue
|-
| '''MGH'''
| 4
| '''Group Morphometry Statistics'''
|
|
|-
| '''MGH'''
| 4.1
| Develop/optimize statistics algorithms
| Year 3
| Complete
|-
| '''MGH'''
| 4.2
| Develop GUI for Linux
| Year 3
| Partially Complete
|-
| '''MGH'''
| 4.3
| Slicer integration
| Year 3
| In Queue
|-
| '''MGH'''
| 4.4
| Compile application on Windows
| Year 4
| In Queue
|-
|}

== Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| '''MIT'''
| 2.4
| Plan to develop software infrastructure to integrate shape analysis tools into the pipeline for population studies.
| New
|-
| '''MIT'''
| 4
| Plans to for fMRI development including local and atlas-based priors for quantifying activation.
| New
|-
| '''Utah'''
| 2.2 (removed)
| Feature-based brain image registration.
| Shift emphasis to shape-based analysis/registration
|-
| '''Utah'''
| 2.1 (removed)
| Cortical filtering and feature detection
| Effort is subsumed by other Core 1 partners (e.g. see MGH/Freesurfer)
|-
| '''Utah'''
| 3.0 (removed)
| Fast implmentations of PDEs
| Real-time filtering is demphasized in favor of shape/DTI analysis
|-
| '''Utah'''
| 2.1-2.3 (added, in place of cortical analysis)
| Shape analysis
| Nonparametric shape analysis added to address needs of core 3.
|-
| '''UNC'''
| 1.2
| Develop medially-based shape representation
| Remove
|-
| '''UNC'''
| 1.4
| Develop generic cortical correspondence framework (Years 3-5)
| New
|-
| '''UNC'''
| 2.4
| DTI Atlas Building (Years 2--4)
| New
|-
| '''GaTech'''
| 2.1
| FA analysis
| New
|}

== [[Core_1_Timeline_Notes|Core 1 Timeline Notes ]] ==

= Core 2 =

== Core 2 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''GE'''
| 1
| '''Define software architecture'''
|
|
|-
| '''GE'''
| 1
| Object design
| Yr 1
| Completed
|-
| '''GE'''
| 1
| Identify patterns
| Yr 3
| Patterns for processing scalar and vector images, models, fiducials complete. Patterns for diffusion weighted imageryand fMRI ongoing.
|-
| '''GE'''
| 1
| Create frameworks
| Yr 3
| Frameworks for processing scalar and vector images, models, fiducials complete. Frameworks for diffusion weighted imageryand fMRI ongoing.
|-
| '''GE'''
| 2
| '''Software engineering process'''
|
|
|-
| '''GE'''
| 2
| Extreme programming
| Yr 1-5
| On schedule, ongoing
|-
| '''GE'''
| 2
| Process automatiion
| Yr 3
| On schedule, ongoing
|-
| '''GE'''
| 2
| Refactoring
| Yr 3
| Complete
|-
| '''GE'''
| 3
| '''Automated quality system'''
|
|
|-
| '''GE'''
| 3
| DART deployment
| Yr 2
| Complete
|-
| '''GE'''
| 3
| Persistent testing system
| Yr 5
| Incomplete
|-
| '''GE'''
| 3
| Automatic defect detection
| Yr 5
| Incomplete
|-
| '''Kitware'''
| 1
| '''Cross-platform development'''
|
|
|-
| '''Kitware'''
| 1
| Deploy environment (CMake, CTest)
| Yr 1
| Complete
|-
| '''Kitware'''
| 1
| DART Integration and testing
| Yr 1
| Complete
|-
| '''Kitware'''
| 1
| Documentation tools
| Yr 2
| Complete
|-
| '''Kitware'''
| 2
| '''Integration tools'''
|
|
|-
| '''Kitware'''
| 2
| File Formats/IO facilities
| Yr 2
| Complete (ongoing)
|-
| '''Kitware'''
| 2
| CableSWIG deployment
| Yr 3
| Complete (integration ongoing)
|-
| '''Kitware'''
| 2
| Establish XML schema
| Yr 4
| Incomplete
|-
| '''Kitware'''
| 3
| '''Technology delivery'''
|
|
|-
| '''Kitware'''
| 3
| Deploy applications
| Yr 1
| Complete (ongoing)
|-
| '''Kitware'''
| 3
| Establish plug-in repository
| Yr 2
| Incomplete
|-
| '''Kitware'''
| 3
| Cpack
| Yr 4-5
| Incomplete
|-
| '''Isomics'''
| 1
| NAMIC builds of slicer
| Years 2--5
| Complete
|-
| '''Isomics'''
| 1
| Schizophrenia and DBP intefaces
| Year 3---5
| Partially completed, ongoing
|-
| '''Isomics'''
| 2
| ITK Integration tools
| Year 1---3
| Completed
|-
| '''Isomics'''
| 2
| Experiment Control Interfaces
| Year 2---5
| Migration from LONI to BatchMake Underway
|-
| '''Isomics'''
| 2
| fMRI/DTI algorithm support
| Year 2---5
| Completed DTI, fMRI Ongoing
|-
| '''Isomics'''
| 2
| New DBP algorithm support
| Year 2---5
| Ongoing
|-
| '''Isomics'''
| 3
| Compatible build process
| Year 1---3
| Completed
|-
| '''Isomics'''
| 3
| Dart Integration
| Year 1---2
| Completed, upgrades ongoing
|-
| '''Isomics'''
| 3
| Test scripts for new code
| Year 2---5
| Ongoing
|-
| '''UCSD'''
| 1
| Grid computing---base
| Year 1
| Completed
|-
| '''UCSD'''
| 1
| Grid enabled algorithms
| Year 3
| Ongoing
|-
| '''UCSD'''
| 1
| Testing infrastructure
| Year 4
| Initiated
|-
| '''UCSD'''
| 2
| Data grid --- compatibility
| Year 2
| Completed
|-
| '''UCSD'''
| 2
| Data grid --- slicer access
| Year 2
| In progress
|-
| '''UCSD'''
| 3
| Data mediation --- deploy
| Year 1
| Incomplete (modfication below)
|-
| '''UCLA'''
| 1
| Debabeler functionality
| Year 1
| Continued Progress
|-
| '''UCLA'''
| 2
| SLIPIE Interpretation (Layer 1)
| Year 1--Year2
| In Progress
|-
| '''UCLA'''
| 3
| SLIPIE Interpretation (Layer 2)
| Year 1--Year2
| On Schedule
|-
| '''UCLA'''
| 3
| Developing ITK Modules
| Year2
| In Progress
|-
| '''UCLA'''
| 4
| Integrating SRB (GSI-enabled)
| Year2
| Completed
|-
| '''UCLA'''
| 5
| Integrating IDA
| Year2
| Completed
|-
| '''UCLA'''
| 5
| Integrating External Visualization Applications
| Year2
| Completed
|}

== Core 2 Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| '''Isomics'''
| 3
| Data mediation
| Delayed pending integration of databases into NAMIC infractructure
|}

== [[Core_2_Timeline_Notes|Core 2 Timeline Notes ]] ==

= Core 3 =

The Core 3 projects submitted R01 style proposals, as specified in the RFA, and did not submit timelines.

= Core 4 =

== Core 4 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''Kitware'''
| 1
| '''Implement Development Farms'''
|
|
|-
| '''Kitware'''
| 1
| Deploy platforms
| Yrs 1
| Complete
|-
| '''Kitware'''
| 1
| Communications
| Yrs 1
| Complete, ongoing
|-
| '''Kitware'''
| 2
| '''Establish software process'''
|
|
|-
| '''Kitware'''
| 2
| Secure developer database
| Yr 1
| Complete, ongoing
|-
| '''Kitware'''
| 2
| Collect guidelines
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Manage software submission process
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Configure process tools
| Yr 1
| Complete
|-
| '''Kitware'''
| 2
| Survey community
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| '''Deploy NAMIC Tools'''
|
|
|-
| '''Kitware'''
| 3
| Toolkits
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Integration tools
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Applications
| Yr 1
| Complete
|-
| '''Kitware'''
| 3
| Integrate new computing resources
| Yr 1
| Complete
|-
| '''Kitware'''
| 4
| '''Provide support'''
|
|
|-
| '''Kitware'''
| 4
| Esablish support infrastructure
| Yrs 1--5
| On schedule, ongoing
|-
| '''Kitware'''
| 4
| NAMIC support
| Yr 1
| Complete
|-
| '''Kitware'''
| 5
| Manage NAMIC Software Releases
| Yrs 1--5
| On schedule, ongoing
|}

== Core 4 Timeline Modifications ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Modification'''
|-
| Kitware
| 2-5
| Various
| Refined/modified the sub aims
|}

== [[Core_4_Timeline_Notes|Core 4 Timeline Notes ]] ==

= Core 5 =

== Core 5 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| '''Harvard'''
| 1
| '''Formal Training Guidllines'''
|
|
|-
| '''Harvard'''
| 1
| Functional neuroanatomy
| Yr 1
| Complete
|-
| '''Harvard'''
| 1
| Clinical correlations
| Yr 1
| Complete
|-
| '''Harvard'''
| 2
| '''Mentoring'''
|
|
|-
| '''Harvard'''
| 2
| Programming workshops
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 2
| One-on-one mentoring, Cores 1, 2, 3
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 3
| '''Collaborative work environment'''
|
|
|-
| '''Harvard'''
| 3
| Wiki
| Yrs 1
| Complete
|-
| '''Harvard'''
| 3
| Mailing lists
| Yrs 1
| Complete
|-
| '''Harvard'''
| 3
| Regular telephone conferences
| Yrs 1-5
| On schedule, ongoing
|-
| '''Harvard'''
| 4
| '''Educational component for tools'''
|
|
|-
| '''Harvard'''
| 4
| Slicer training modules
| Yr 2-5
| Many complete for Slicer 2.x, Slicer 3 ongoing
|-
| '''Harvard'''
| 5
| '''Demonstrations and hands-on training'''
|
|
|-
| '''Harvard'''
| 5
| Various workshops and conferences
| Yrs 1--5
| On schedule, ongoing (see also link)
|}

== Core 5 Timeline Modifications ==

None.

== [[Core_5_Timeline_Notes|Core 5 Timeline Notes ]] ==

= Core 6 =

== Core 6 Timelines and Milestones ==

{| border="1"
| '''Group'''
| '''Aim'''
| '''Milestone'''
| '''Proposed time of completion'''
| '''Status'''
|-
| Isomics
| 1
| Create a collaboration metholdology for NA-MIC
|
|
|-
| Isomics
| 1.1
| develop a selection process
| Yr 1
| Done
|-
| Isomics
| 1.2
| guidelines to govern the collaborations
| Yr 1-2
| Done
|-
| Isomics
| 1.3
| Provide on-site training
| Yr 1-5
| On Schedule
|-
| Isomics
| 1.4
| develop a web site infrastructure
| Yr 1
| Done
|-
| Isomics
| 2
| Facilitate communication between NA-MIC developers and wider research community
|
|
|-
| Isomics
| 2.1
| develop materials describing NAMIC technology
| Yr 1-5
| On Schedule
|-
| Isomics
| 2.2
| participate in scientific meetings
| Yr 2-5
| On Schedule
|-
| Isomics
| 2.3
| Document interactions with external researchers
| Yr 2-5
| On Schedule
|-
| Isomics
| 2.4
| Coordinate publication strategies
| Yr 3-5
| On track
|-
| Isomics
| 3
| Develop a publicly accessible internet resource of data, software, documentation, and publication of new discoveries
|
|
|-
| Isomics
| 3.1
| On-line repository of NAMIC related publications and presentations
| Yr 1-2-3
| On Schedule
|-
| Isomics
| 3.2
| On-line repository of NAMIC tutorial and training material
| Yr 1-5
| On Schedule
|-
| Isomics
| 3.3
| Index and a searchable database
| Yr 1-2
| Done
|-
| Isomics
| 3.4
| Automated feedback systems that track software downloads
| Yr 3
| On track
|}

== Core 6 Timeline Modifications ==

== [[Core_6_Timeline_Notes|Core 6 Timeline Notes ]] ==
|}

Projects:AutomaticFullBrainSegmentation

2007-04-17T15:47:42Z

Dsjen:

'''Project''': Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

'''Team''': Xiao Han and Bruce Fischl

----

'''Status''': Prototype

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': Atlas-based approaches have demonstrated the ability to automatically identify detailed brain structures from 3-D magnetic resonance (MR) brain images. Unfortunately, the accuracy of this type of method often degrades when processing data acquired on a different scanner platform or pulse sequence than the data used for the atlas training. In this paper, we improve the performance of an atlas-based whole brain segmentation method by introducing an intensity renormalization procedure that automatically adjusts the prior atlas intensity model to new input data. Validation using manually labeled test datasets has shown that the new procedure improves the segmentation accuracy (as measured by the Dice coefficient) by 10% or more for several structures including hippocampus, amygdala, caudate, and pallidum. The results verify that this new procedure reduces the sensitivity of the whole brain segmentation method to changes in scanner platforms and improves its accuracy and robustness, which can thus facilitate multicenter or multisite neuroanatomical imaging studies.

Projects:TopologyCorrectionNonSeparatingLoops

2007-04-17T15:47:34Z

Dsjen:

'''Project''': Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops

'''Team''': Florent Ségonne, Jenni Pacheco, and Bruce Fischl

----

'''Status''': Prototype

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': In this paper, we focus on the retrospective topology correction of surfaces. We propose a technique to accurately correct the spherical topology of cortical surfaces. Specifically,we construct a mapping from the original surface onto the sphere to detect topological defects as minimal nonhomeomorphic regions. The topology of each defect is then corrected by opening and sealing the surface along a set of nonseparating loops that are selected in a Bayesian framework. The proposed method is a wholly self-contained topology correction algorithm, which determines geometrically accurate, topologically correct solutions based on the magnetic resonance imaging (MRI) intensity profile and the expected local curvature. Applied to real data, our method provides topological corrections similar to those made by a trained operator.

Projects:CorticalSurfaceShapeAnalysisUsingSphericalWavelets

2007-04-17T15:47:10Z

Dsjen:

'''Project''': Cortical Surface Shape Analysis Based on Spherical Wavelets

'''Team''': Peng Yu, P. Ellen Grant, Yuan Qi, Xiao Han, Florent Ségonne, Rudolph Pienaar, Evelina Busa, Jenni Pacheco, Nikos Makris, Randy L. Buckner, Polina Golland, and Bruce Fischl

----

'''Status''': Prototype

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': In vivo quantification of neuroanatomical shape variations is possible due to recent advances in medical imaging and has proven useful in the study of neuropathology and neurodevelopment. In this paper, we apply a spherical wavelet transformation to extract shape features of cortical surfaces reconstructed from
magnetic resonance images (MRIs) of a set of subjects. The spherical wavelet transformation can characterize the underlying functions in a local fashion in both space and frequency, in contrast to spherical harmonics that have a global basis set. We perform principal component analysis (PCA) on these wavelet shape features to study patterns of shape variation within normal population from coarse to fine resolution. In addition, we study the development of cortical folding in newborns using the Gompertz model in the wavelet domain, which allows us to characterize the order of development of large-scale and finer folding patterns independently. Given a limited amount of training data, we use a regularization framework to estimate the parameters of the Gompertz model to improve the prediction performance on new data. We develop an efficient method to estimate this regularized Gompertz model based on the Broyden–Fletcher–Goldfarb–Shannon (BFGS) approximation. Promising results are presented using both PCA and the folding development model in the wavelet domain. The cortical folding development model provides quantitative anatomic information regarding macroscopic cortical folding development and may be of potential use as a biomarker for early diagnosis of neurologic deficits in newborns.

Projects:AutomaticFullBrainSegmentation

2007-04-17T15:38:02Z

Dsjen:

'''Project''': Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

'''Team''': Xiao Han and Bruce Fischl

----

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': Atlas-based approaches have demonstrated the ability to automatically identify detailed brain structures from 3-D magnetic resonance (MR) brain images. Unfortunately, the accuracy of this type of method often degrades when processing data acquired on a different scanner platform or pulse sequence than the data used for the atlas training. In this paper, we improve the performance of an atlas-based whole brain segmentation method by introducing an intensity renormalization procedure that automatically adjusts the prior atlas intensity model to new input data. Validation using manually labeled test datasets has shown that the new procedure improves the segmentation accuracy (as measured by the Dice coefficient) by 10% or more for several structures including hippocampus, amygdala, caudate, and pallidum. The results verify that this new procedure reduces the sensitivity of the whole brain segmentation method to changes in scanner platforms and improves its accuracy and robustness, which can thus facilitate multicenter or multisite neuroanatomical imaging studies.

Algorithm:MGH

2007-04-17T15:36:26Z

Dsjen:

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''QDEC: An easy to use GUI for group morphometry studies'''
* Difficulty: Medium
* Impact: High
* '''Use cases''': See [http://surfer.nmr.mgh.harvard.edu/fswiki/QdecProject Qdec project page]

* '''Use case'''<nowiki>: 'Compare the primary eigendirection in two groups to see if they are the same' </nowiki>
* Difficulty: Low
* Impact: Medium

See: [http://surfer.nmr.mgh.harvard.edu/fswiki/Qdec Qdec user page]

 ''''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See: [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Teich): '''queued'''
# Automate header generation when possible (Teich): '''queued'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

See: [[Algorithm:MGH:Development:SphericalWavelets|Algorithm:MGH:SphericalWavelets]]

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

See: [[Algorithm:MGH:Development:TopologyCorrection|Algorithm:MGH:Development:TopologyCorrection]]

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

See: [[Algorithm:MGH:FreeSurferNumericalRecipiesReplacement|Numerical Recipies Replacement]]

 '''Atlas Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

See: [[Algorithm:MGH:Development:AutoBrainSeg|Algorithm:MGH:Development:AutoBrainSeg]]

Projects:CorticalSurfaceShapeAnalysisUsingSphericalWavelets

2007-04-17T15:34:41Z

Dsjen:

'''Project''': Cortical Surface Shape Analysis Based on Spherical Wavelets

'''Team''': Peng Yu, P. Ellen Grant, Yuan Qi, Xiao Han, Florent Ségonne, Rudolph Pienaar, Evelina Busa, Jenni Pacheco, Nikos Makris, Randy L. Buckner, Polina Golland, and Bruce Fischl

----

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': In vivo quantification of neuroanatomical shape variations is possible due to recent advances in medical imaging and has proven useful in the study of neuropathology and neurodevelopment. In this paper, we apply a spherical wavelet transformation to extract shape features of cortical surfaces reconstructed from
magnetic resonance images (MRIs) of a set of subjects. The spherical wavelet transformation can characterize the underlying functions in a local fashion in both space and frequency, in contrast to spherical harmonics that have a global basis set. We perform principal component analysis (PCA) on these wavelet shape features to study patterns of shape variation within normal population from coarse to fine resolution. In addition, we study the development of cortical folding in newborns using the Gompertz model in the wavelet domain, which allows us to characterize the order of development of large-scale and finer folding patterns independently. Given a limited amount of training data, we use a regularization framework to estimate the parameters of the Gompertz model to improve the prediction performance on new data. We develop an efficient method to estimate this regularized Gompertz model based on the Broyden–Fletcher–Goldfarb–Shannon (BFGS) approximation. Promising results are presented using both PCA and the folding development model in the wavelet domain. The cortical folding development model provides quantitative anatomic information regarding macroscopic cortical folding development and may be of potential use as a biomarker for early diagnosis of neurologic deficits in newborns.

Projects:TopologyCorrectionNonSeparatingLoops

2007-04-17T15:29:54Z

Dsjen:

'''Project''': Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops

'''Team''': Florent Ségonne, Jenni Pacheco, and Bruce Fischl

----

'''Submitted''': IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 26, NO. 4, APRIL 2007

'''Abstract''': In this paper, we focus on the retrospective topology correction of surfaces. We propose a technique to accurately correct the spherical topology of cortical surfaces. Specifically,we construct a mapping from the original surface onto the sphere to detect topological defects as minimal nonhomeomorphic regions. The topology of each defect is then corrected by opening and sealing the surface along a set of nonseparating loops that are selected in a Bayesian framework. The proposed method is a wholly self-contained topology correction algorithm, which determines geometrically accurate, topologically correct solutions based on the magnetic resonance imaging (MRI) intensity profile and the expected local curvature. Applied to real data, our method provides topological corrections similar to those made by a trained operator.

Algorithm:MGH

2007-04-17T15:25:24Z

Dsjen:

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''QDEC: An easy to use GUI for group morphometry studies'''
* Difficulty: Medium
* Impact: High
* '''Use cases''': See [http://surfer.nmr.mgh.harvard.edu/fswiki/QdecProject Qdec project page]

* '''Use case'''<nowiki>: 'Compare the primary eigendirection in two groups to see if they are the same' </nowiki>
* Difficulty: Low
* Impact: Medium

See: [http://surfer.nmr.mgh.harvard.edu/fswiki/Qdec Qdec user page]

 ''''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See: [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Teich): '''queued'''
# Automate header generation when possible (Teich): '''queued'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

See: [[Algorithm:MGH:Development:SphericalWavelets|Algorithm:MGH:SphericalWavelets]]

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

See: [[Algorithm:MGH:Development:TopologyCorrection|Algorithm:MGH:Development:TopologyCorrection]]

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

See: [[Algorithm:MGH:FreeSurferNumericalRecipiesReplacement|Numerical Recipies Replacement]]

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

See: [[Algorithm:MGH:Development:AutoBrainSeg|Algorithm:MGH:Development:AutoBrainSeg]]

Algorithm:MGH

2007-04-17T15:16:32Z

Dsjen: /* In Development */

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''QDEC: An easy to use GUI for group morphometry studies'''
* Difficulty: Medium
* Impact: High
* '''Use cases''': See [http://surfer.nmr.mgh.harvard.edu/fswiki/QdecProject Qdec project page]

* '''Use case'''<nowiki>: 'Compare the primary eigendirection in two groups to see if they are the same' </nowiki>
* Difficulty: Low
* Impact: Medium

See [http://surfer.nmr.mgh.harvard.edu/fswiki/Qdec Qdec user page]

 ''''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Teich): '''queued'''
# Automate header generation when possible (Teich): '''queued'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

See [[AHM_2006:ProjectsDTIPathOfInterest|Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops]]

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

See: [[Algorithm:MGH:FreeSurferNumericalRecipiesReplacement|Numerical Recipies Replacement]]

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

Projects:FreeSurferNumericalRecipiesReplacement

2007-04-16T21:21:48Z

Dsjen:

== FreeSurfer Numerical Recipies Replacement ==

''Objective:'' Replace algorithms using proprietary numerical recipes in FreeSurfer in efforts to open source FreeSurfer.

''Status:'' Completed.
#12 numerical recipes replaced with open source alternatives, mainly using VXL.
#14 unit tests run nightly.

Algorithm:MGH

2007-04-16T19:12:20Z

Dsjen:

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''QDEC: An easy to use GUI for group morphometry studies'''
* Difficulty: Medium
* Impact: High
* '''Use cases''': See [http://surfer.nmr.mgh.harvard.edu/fswiki/QdecProject Qdec project page]

* '''Use case'''<nowiki>: 'Compare the primary eigendirection in two groups to see if they are the same' </nowiki>
* Difficulty: Low
* Impact: Medium

See [http://surfer.nmr.mgh.harvard.edu/fswiki/Qdec Qdec user page]

 ''''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Teich): '''queued'''
# Automate header generation when possible (Teich): '''queued'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

See: [[Algorithm:MGH:FreeSurferNumericalRecipiesReplacement|Numerical Recipies Replacement]]

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

Algorithm:MGH

2007-04-02T17:16:40Z

Dsjen:

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Snyder): '''queued'''
# Automate header generation when possible (Snyder): '''queued'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

Projects:DTIPathOfInterest

2007-04-02T16:10:43Z

Dsjen:

'''Project'''<nowiki>: DTI path of interest (POI) analysis </nowiki>

'''Use case'''<nowiki>: "I'd like to be able to find the optimal path between two regions in a tensor image." - Saykin </nowiki>

'''Impact'''<nowiki>: Medium (Saykin) </nowiki>

'''Difficulty'''<nowiki>: Low (Snyder) </nowiki>

----

 '''Vision'''<nowiki>: Software tool which can find optimal and sub-optimal paths between regions of interest in a tensor image, and produce associated statistics and probability density images. Should work on output of Slicer DTI analysis and ROI drawing tools. Tool should generate probability density image, sample statistics from this image, and from user defined image w/ same geometry. </nowiki>

'''Goal'''<nowiki>: Provide software deliverable with robust support for input images with varying slice prescription, voxel size, tensor measurement frame, etc. Ensure compatibility with Slicer file formats and Dartmouth tensor data conventions. </nowiki>

'''Test Data'''<nowiki>: Six healthy individuals from the </nowiki>[https://portal.nbirn.net/BIRN/cgi-bin/DataGrid/browse.cgi?browseloc=/home/Projects/NAMIC__0003/Files/Dartmouth/HealthyControls6/DTIdata Dartmouth DTI data set].

'''Team members'''<nowiki>: Snyder, Tuch, Saykin </nowiki>

* DTI Coordinate System Support: Gordon Kindlmann, Raul San Jose, Steve Pieper

 '''Win conditions'''<nowiki>: </nowiki>

'''MGH'''<nowiki>: Improved robustness and portability of existing POI tool. </nowiki>

'''Dartmouth'''<nowiki>: Software deliverable. </nowiki>

----

 '''Steps'''<nowiki>: </nowiki>

# Requirements extraction (Snyder/Saykin): '''done'''
# Create Wiki project page (Snyder): '''done'''
# Port MGH POI tool to Dartmouth compatible version (Snyder/Tuch): '''done'''
# Test output visualization in Slicer (Snyder): '''done'''
# Process test data with MGH tensor reconstruction and POI analysis tools; use for port validation (Snyder): '''done'''
# Software deliverable installation at Dartmouth (West/Snyder): '''done'''
# Port to ITK (Jen): '''done'''
# Test on expanded data set (West/Jen): '''in progress'''
# Submit to the Insight Journal (Jen): '''in progress'''

----

 '''Progress notes'''<nowiki>: </nowiki>

* Dartmouth Dicom series -> NIFTI image conversion toolset completed.
* Tensor reconstruction workflow identified and tested.
* Path of interest tool ported.
* Installed at Dartmouth
* Currently in testing/use by John West

Algorithm:MGH

2007-04-02T16:02:51Z

Dsjen: /* Done */

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Automatic segmentation of DTI using Spectral Clustering'''

* '''Use case'''<nowiki>: 'Automatically segment DTI image.' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implement algorithm in Matlab (Ziyan) : '''done'''
# Test/optimize on group data (Ziyan): '''in progress'''
# Port to diffusion toolkit (Tuch) : '''queued'''

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Snyder): '''queued'''
# Automate header generation when possible (Snyder): '''queued'''

 '''Replacing FreeDiffusion components with NA-MIC equivalents'''

* Difficulty: Medium-High
* Impact: Low

# Write regression tests: '''done'''
# Identify componenets to replace: '''queued'''
# Replace and test: '''queued'''

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

 '''Replacing Numerical Recipes in FreeSurfer (for open sourcing)'''

* '''Use case'''<nowiki>: 'Unit tests pass with all replacements.' </nowiki>
* Difficulty: Medium-High
* Impact: High

# Write test cases for each algorithm (Snyder, Jen): '''done'''
# Identify replacements (Snyder, Jen): '''done'''
# Integrate required libraries into FreeSurfer build process (Snyder, Jen): '''done'''
# Iteratively replace recipes with substitutes and run tests (Snyder, Jen): '''done'''

Algorithm:MGH

2007-04-02T16:02:20Z

Dsjen: /* In Development */

== Coordination ==

[[Algorithm:MGH:Coordination:Meeting_2004-11-17|2004-11-17 meeting @ MGH]]

[[Algorithm:MGH:Coordination:Meeting_2005-1-21|2005-1-21 meeting @ BWH]]

== Projects ==

=== In Development ===

'''Optimal path calculator (Poistats)'''

* '''Use case'''<nowiki>: 'Specify 2 points in a diffusion image and tell how connected they are.' </nowiki>
* Difficulty: High
* Impact: High

See [[AHM_2006:ProjectsDTIPathOfInterest|AHM 2006:ProjectsDTIPathOfInterest]]

 '''Statistical power benefit of ITK nonlinear registration'''

* '''Use case'''<nowiki>: 'Evaluate benefit of using ITK nonlinear registration for group FA comparisons' </nowiki>
* Difficulty: Low-Medium
* Impact: Medium

See: [[Engineering:Project:Non-rigid_EPI_registration|Engineering:Project:Non-rigid_EPI_registration]]

 '''Automatic segmentation of DTI using Spectral Clustering'''

* '''Use case'''<nowiki>: 'Automatically segment DTI image.' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implement algorithm in Matlab (Ziyan) : '''done'''
# Test/optimize on group data (Ziyan): '''in progress'''
# Port to diffusion toolkit (Tuch) : '''queued'''

 '''Adding NRRD I/O to Freesurfer'''

* '''Use case'''<nowiki>: 'Open a NRRD volume in FreeSurfer.' </nowiki>
* '''Use case'''<nowiki>: 'Convert an MGH volume to a NRRD volume with Freesurfer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Write unit tests for new IO functions (Snyder): '''in progress'''
# Add NrrdIO libraries from Teem to FS source tree, build with autoconf (Snyder): '''done'''
# Write and test FS NRRD IO functions (Snyder, Kindlmann): '''in progress'''
# Develop approriate headers for MGH DWI data (Snyder): '''queued'''
# Automate header generation when possible (Snyder): '''queued'''

 '''Replacing FreeDiffusion components with NA-MIC equivalents'''

* Difficulty: Medium-High
* Impact: Low

# Write regression tests: '''done'''
# Identify componenets to replace: '''queued'''
# Replace and test: '''queued'''

 '''Intensity Renormalization for Improved Brain MR Image Segmentation across Scanner Platforms'''

* '''Use Case'''<nowiki>: 'Atlas-based fully automated whole brain segmentation' </nowiki>
* Difficulty: Medium-High
* Impact: Medium-High

# Implemented in C and distribute with the FreeSurface Package: '''done'''

 '''Cortical Surface Shape Analysis Based on Spherical Wavelets'''

 '''Geometrically-Accurate Topology-Correction of Cortical Surfaces using Non-Separating Loops'''

 

* '''queued''' - step identified/specd
* '''in progress''' - step in progress
* '''done''' - step complete

=== Done ===

'''QBALL visualization'''

* '''Use case'''<nowiki>: 'Visualize q-ball data in Slicer.' </nowiki>
* Difficulty: Low
* Impact: Medium

# Implement ODF polygon decimation algorithm (Tuch) : '''done'''
# Port decimation fileformat into FreeDiffusion Visualizer (Snyder) : '''done'''
# Port QBALL/ODF visualization into [[Slicer|Slicer]] (Estepar/Snyder/Kindlmann/Tuch/Westin): '''done'''
## Implement (Estepar): '''done'''
## Test on mock data set (Estepar): '''done'''
## Demo for real data set (Estepar/Snyder/Kindlmann): '''done'''

'''Tensor-based group comparison (Cramer test)'''

* '''Use case'''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki>
* Difficulty: Medium
* Impact: Medium-High

# Implement in R (Whitcher/Tuch) : '''done'''
# Power analysis (Whitcher) : '''done'''
# Port to Matlab (Whitcher) : '''done'''
# Validate Matlab version against R (Whitcher) : '''done'''
# Test on group data : '''done'''
# Release bootstrap-only version to test group: '''done'''
# Port FFT method from R to matlab (Whitcher): '''done'''
# Implement FFT method in diffusion development environment (Tuch): '''done'''

See [[Algorithm:MGH:Development:GroupComp|Algorithm:MGH:Development:GroupComp]]

Slicer3:Execution Model Documentation

2007-01-16T20:21:16Z

Dsjen: /* Using GenerateCLP */

== Introduction ==

The Slicer 3 Execution Model is designed to improve the acceptance and productivity of Slicer application developers. The Execution Model provides a simple mechanism for incorporating command line programs as Slicer modules. These command line modules are self-describing, emitting an XML description of its command line arguments. Slicer uses this XML description to construct a GUI for the module.

[[Image:ExecutionModelPlugins.png|[[Image:ExecutionModelPlugins.png|Image:ExecutionModelPlugins.png]]]]

[[Image:CommandLineModule.png|[[Image:CommandLineModule.png|Image:CommandLineModule.png]]]] [[Image:ModuleFactory.png|[[Image:400px-ModuleFactory.png]]]]

[[Image:Class_parser_state_coll_graph.png|[[Image:Class_parser_state_coll_graph.png|Image:Class_parser_state_coll_graph.png]]]]

== Module Description ==

Modules are described using XML. The XML is used to generate the C++ command line code and the GUI for the application.

=== XML Schema ===

At a minimum, each module description must contain:

<?xml version="1.0" encoding="utf-8"?>
<executable>
<title>A title</title>
<description>A description</description>
<parameters>
At least one parameter
</parameters>
</executable>

In the following descriptions of each XML tag, CLP means command line processing and GUI means graphical user interface. Unless otherwise specified, tags are optional.

; <executable> (required)

;; <category> (required)
:: Classifies the executable (e.g. Filtering, Segmentation). Category can be a ''dot'' sepearted string.
:: ''for CLP'', not used.
:: ''for GUI'', used on the menu selector to group executables. ''Dot'' separated strings can be used to generate sub-menus.
;; </category>

;; <title> (required)
:: A word or two describing the executable (e.g. Median Filter, Anisotropic Diffusion
:: ''for CLP'', not used.
:: ''for GUI'', used to label the frame containing the GUI for the executable. Also, GUI names for volumes use this label as a prefix.
;; </title>

;; <description> (required)
:: A long description of the executable. Any double quotes will be converted to single quotes.
:: ''for CLP'', appears at the end of the --help.
:: ''for GUI'', appears in the help frame.
;; </description>

;; <version>
:: The version of the command line executable. A suggested format is:
::: ''major''.''minor''.''patch''.''build''.''status''
::: where status is
:::: vc: version controlled (pre-alpha), build can be a serial revision number, if any (like svn might have).
:::: a: alpha
:::: b: beta
:::: rc: release candidate
:::: fcs: first customer ship
:: ''for CLP'', reported in response to --version.
:: ''for GUI'', not used.
;; </version>

;; <documentation-url>
:: The location of extended documentation for the executable, (e.g. http://www.na-mic.org/foo.html).
;; </documentation-url>

;; <license>
:: The type of license or a url containing the license, (e.g. Berkeley, Apache, http://www.slicer.org/copyright/copyright.txt).
:: ''for CLP'', not used.
:: ''for GUI'', may show up in the Help or About section.
;; </license>

;; <contributor>
:: The author(s) of the command line executable (e.g. Pieper, Jim Miller).
:: for ''CLP'', appears as part of --help
:: for ''GUI'', may show up in the Help or About section.
;; </contributor>

;; <acknowledgements>
:: Acknowledgements for funding agency, employer, colleague, (e.g. This work is part of the National Alliance for Medical Image Computing NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149).
:: for ''CLP'', appears as part of --help
:: for ''GUI'', may show up in the Help of About section.
;; </acknowledgements>

;; <parameters> [advanced="true|''false''"] (required for each group of parameters)
:: Starts a group of parameters.
:: for ''CLP'', not used.
:: for ''GUI'', defines a widget (in tk, a frame) that contains other widgets. If ''advanced'' is true, the frame will be closed initially.

;;; <label> (required)
::: A short string that summarizes a parameter group, (e.g. I/O, Diffusion)
::: for ''CLP'', not used.
::: for ''GUI'', used to label the frame.
;;; </label>

;;; <description> (required)
::: A short descriprion of the parameter group, (e.g. Input/Output Parameters, Anitostropic Diffusion Parameters). Any double quotes will be converted to single quotes.
::: ''for CLP'', not used.
::: ''for GUI'', used in balloon help for the frame containing the parameter group.
;;; </description>

;;; <integer> | <float> | <double> | <boolean> | <string> | <integer-vector> | <float-vector> | <double-vector> | <string-vector> | <integer-enumeration> | <float-enumeration> | <double-enumeration> | <string-enumeration> | <file> | <directory> | <image> | <geometry> | <point>[multiple="true|''false''"] [coordinateSystem="lps|ras|''ijk''"]
::: The type of the parameter. The scalar types ('''integer''', '''float''', etc.) correspond to the usual programmming language types. The '''-vector''' types are representaed by comma separated values of the scalar type. The '''-enumeration''' types use the '''<element>''' tag to enumerate choices of the scalar type. '''<image>''' is a special type that indicates that the parameter is a file name that specifies images. If the attribute multiple is "true", multiple arguments are allowed for '''scalar''', '''file''', '''directory''', '''image''', '''geometry''' and '''point''' parameters. The attribute coordinateSystem is allowed for the parameter '''point'''. If the parameter has a ''flag'' or ''longflag'', then the flag may be specified multiple times on the command line. The resulting C++ variable will be a std::vector of the scalar type. If the multiple parameter does not have a flag, then multiple arguments can appear on the command line. However, a multiple parameter with no flags must be the last parameter specified.

;;;; <name> (required if longflag is not specified)
:::: The name of a command line argument. If name is not specified, longflag will be used (e.g. conductance, numberOfIterations). The name must be usable as a C++ variable. For example, it CANNOT have spaces or special characters and must start with a letter.
:::: ''for CLP'', the name of the C++ variable.
:::: ''for GUI'', used internally.
;;;; </name>

;;;; <description> (required)
:::: A brief description of the parameter. Any double quotes will be converted to single quotes.
:::: ''for CLP'', describes the parameter for --usage and --help.
:::: ''for GUI'', describes the parameter when the cursor is placed over the widget for the parameter (balloon help).
;;;; </description>

;;;; <label> (required)
:::: A label for parameter (e.g. Dicom Directory, Conductance).
:::: ''for'' CLP, not used.
:::: ''for'' GUI, the label for the parameter widget.
;;;; </label>

;;;; <default>
:::: A default value for the parameter. The default must be a type that is compatible with the parameter type. The vector parameters are specified as comma separated values of the atomic parameter type.
:::: ''for CLP'', contains the default for the parameter unless the parameter is a ''boolean''. The default for ''boolean'' parameters is always set to ''false''.
:::: ''for GUI'', contains the default for the parameter.
;;;; </default>

;;;; <flag> (not required if longflag is present)
:::: A single character command line flag (e.g. s, W)
:::: ''for CLP'', used as the short flag on the command line.
:::: ''for GUI'', used when running the module.
;;;; </flag>

;;;; <longflag> (not required if flag is present)
:::: A command line flag (e.g. spacing, Watcher).
:::: ''for CLP'', used as the long flag on the command line.
:::: ''for GUI'', used when running the module.
;;;; </longflag>

;;;; <constraints>
:::: Encloses constraints on the value of a non-vector, non-enumerated parameter.
:::: ''for CLP'', not used.
:::: ''for GUI'', if present, a slider will be created using the minimum, maximum and step specified.

;;;;; <minimum>
::::: The minimum allowed value for the parameter. If not specified, the minimum is the smallest possible value for the parameter type.
;;;;; </minimum>

;;;;; <maximum>
::::: The maximum allowed value for the parameter. If not specified, the maximum is the largest possible value for the parameter type.
;;;;; </maximum>

;;;;; <step>
::::: The increment for the parameter.
;;;;; </step>

;;;; </constraints>

;;;; <channel> (required for file, directory and image parameters)
:::: Specifies whether the parameter is an input or output parameter.
:::: ''for CLP'', not used.
:::: ''for GUI'', selects the proper widget for file handling.
;;;; </channel>

;;;; <index> (required if there are no flags specified)
:::: An integer starting at 0, that specifies a command line argument that has no flags.
:::: ''for CLP'', specifies the order of an argument that has no flags.
:::: ''for GUI'', used when running the module.
;;;; </index>

;;;; <enumeration> (required for enumeration parameters)
:::: Encloses elements for the parameter. The parameter is restricted one and only one element.
:::: ''for CLP'', not used.
:::: ''for GUI'', defines a radio button with choices.

;;;;; <element>
::::: Defines the choice. Must be of the proper type for a parameter.
::::: ''for CLP'', not used.
::::: ''for GUI'', used as the label for the raido button.
;;;;; </element>

;;;; </enumeration>

;;; </integer> | </float> | </double> | </boolean> | </string> | </integer-vector> | </float-vector> | </double-vector> | </string-vector> | </integer-enumeration> | </float-enumeration> | </double-enumeration> | </string-enumeration> | </file> | </directory> | </image> | </geometry> | </point>
;; </parameters>

; </executable>

== Slicer3 GUI Generation ==

Slicer 3 generates GUI's for each executable discovered during the startup process. Slicer 3 searches directories stored in the Slicer3 Module Path. This path is set from the Slicer3 application in View->Applicaton Settings->Module Settings. For Windows, the Module Path contains ";" separated directories while for Unix, the directories are spearated by ":"'s. Slicer3 attempts to run every executable in the prescribed directores and look for a valid XML file in response to a "--xml" command line.

Here are a few representative examples.

=== A tour of the Execution Model XML ===

This example is a sampler of the parameters available in the Execution Model.

<div class="floatright">[[Image:ExectionModelTourGUI.png|[[Image:ExectionModelTourGUI.png]]]]</div>

<?xml version="1.0" encoding="utf-8"?>
<executable>
<category>Tours</category>
<title>Execution Model Tour</title>
<description>
Shows one of each type of parameter.
</description>
<version>1.0</version>
<documentationurl></documentationurl>
<license></license>
<contributor>Daniel Blezek</contributor>

<parameters>
<label>Scalar Parameters</label>
<description>
Variations on scalar parameters
</description>
<integer>
<name>integerVariable</name>
<flag>i</flag>
<longflag>integer</longflag>
<description>
An integer without constraints
</description>
<label>Integer Parameter</label>
<default>30</default>
</integer>
<label>Scalar Parameters With Constraints</label>
<description>Variations on scalar parameters</description>
<double>
<name>doubleVariable</name>
<flag>d</flag>
<longflag>double</longflag>
<description>An double with constraints</description>
<label>Double Parameter</label>
<default>30</default>
<constraints>
<minimum>0</minimum>
<maximum>1.e3</maximum>
<step>0</step>
</constraints>
</double>
</parameters>

<parameters>
<label>Vector Parameters</label>
<description>Variations on vector parameters</description>
<float-vector>
<name>floatVector</name>
<flag>f</flag>
<description>A vector of floats</description>
<label>Float Vector Parameter</label>
<default>1.3,2,-14</default>
</float-vector>
<string-vector>
<name>stringVector</name>
<longflag>string_vector</longflag>
<description>A vector of strings</description>
<label>String Vector Parameter</label>
<default>"foo",bar,"foobar"</default>
</string-vector>
</parameters>

<parameters>
<label>Enumeration Parameters</label>
<description>Variations on enumeration parameters</description>
<string-enumeration>
<name>stringChoice</name>
<flag>e</flag>
<longflag>enumeration</longflag>
<description>An enumeration of strings</description>
<label>String Enumeration Parameter</label>
<default>foo</default>
<element>foo</element>
<element>"foobar"</element>
<element>foofoo</element>
</string-enumeration>
</parameters>
</executable>

=== Module with an integer-vector, one input image and one output image ===

Here is the XML that describes the MedianImageFilter. The image on the right shows the generated Slicer 3 GUI. The help frame has been expanded by the user.

<div class="floatright">[[Image:MedianFilterGUI.png|[[Image:MedianFilterGUI.png]]]]</div>
<pre>
<?xml version="1.0" encoding="utf-8"?>
<executable>
<category>
Filtering.Denoising
</category>
<title>
Median Filter
</title>
<description>
The MedianImageFilter is commonly used as a robust approach for
noise reduction. This filter is particularly efficient against
"salt-and-pepper" noise. In other words, it is robust to the presence
of gray-level outliers. MedianImageFilter computes the value of each output
pixel as the statistical median of the neighborhood of values around the
corresponding input pixel.
</description>
<version>0.1.0.$Revision: 2085 $(alpha)</version>
<documentation-url></documentation-url>
<license></license>
<contributor>Bill Lorensen</contributor>
<acknowledgements>This command module was derived from
Insight/Examples/Filtering/MedianImageFilter (copyright) Insight Software Consortium
</acknowledgements>
<parameters>
<label>Median Filter Parameters</label>
<description>Parameters for the median filter</description>

<integer-vector>
<name>neighborhood</name>
<longflag>--neighborhood</longflag>
<description>The size of the neighborhood in each dimension</description>
<label>Neighborhood Size</label>
<default>1,1,1</default>
</integer-vector>

</parameters>

<parameters>
<label>IO</label>
<description>Input/output parameters</description>
<image>
<name>inputVolume</name>
<label>Input Volume</label>
<channel>input</channel>
<index>0</index>
<description>Input volume to be filtered</description>
</image>
<image>
<name>outputVolume</name>
<label>Output Volume</label>
<channel>output</channel>
<index>1</index>
<description>Output filtered</description>
</image>
</parameters>

</executable>
</pre>

=== Module with a multiple scalars, one Input image and one output image ===

A module with

<div class="floatright">[[Image:AnisotropicDiffusionFilterGUI.png|[[Image:AnisotropicDiffusionFilterGUI.png]]]]</div>

<?xml version="1.0" encoding="utf-8"?>
<executable>
<category>filtering</category>
<title>Anisotropic Diffusion</title>
<description>
Runs anisotropic diffusion on a volume
</description>
<version>1.0</version>
<documentationurl></documentationurl>
<license></license>
<contributor>Bill Lorensen</contributor>

<parameters>
<label>
Anisotropic Diffusion Parameters
</label>
<description>
Parameters for the anisotropic
diffusion algorithm
</description>

<double>
<name>conductance</name>
<longflag>conductance</longflag>
<description>Conductance</description>
<label>Conductance</label>
<default>1</default>
<constraints>
<minimum>0</minimum>
<maximum>10</maximum>
<step>.01</step>
</constraints>
</double>

<double>
<name>timeStep</name>
<longflag>timeStep</longflag>
<description>Time Step</description>
<label>Time Step</label>
<default>0.0625</default>
<constraints>
<minimum>.001</minimum>
<maximum>1</maximum>
<step>.001</step>
</constraints>
</double>

<integer>
<name>numberOfIterations</name>
<longflag>iterations</longflag>
<description>Number of iterations</description>
<label>Iterations</label>
<default>1</default>
<constraints>
<minimum>1</minimum>
<maximum>30</maximum>
<step>1</step>
</constraints>
</integer>

</parameters>

<parameters>
<label>IO</label>
<description>Input/output parameters</description>
<image>
<name>inputVolume</name>
<label>Input Volume</label>
<channel>input</channel>
<index>0</index>
<description>Input volume to be filtered</description>
</image>
<image>
<name>outputVolume</name>
<label>Output Volume</label>
<channel>output</channel>
<index>1</index>
<description>Output filtered</description>
</image>
</parameters>

</executable>

== Command Line Parsing ==

The Slicer 3 Execution Model has support for parsing executable command lines. The C++ code to parse the command line arguments is generated automatically from the same XML description that generates the GUI. ''GenerateCLP,'' located in ''Slicer3/Libs/GenerateCLP'' reads the XML Module Description and creates an include file "''Executable"CLP.h'' in the build tree. The executable includes this header file and accesses the code with the macro PARSE_ARGS.

GenerateCLP provides the following to the executable:

# A brief usage command if required arguments are missing
# A full help command if ''-h'' or ''--help'' is specified on the command line
# A copy of the xml description if ''--xml'' is specified on the command line
# An echo of the command line parameters and their values if ''--echo'' is specified

GenerateCLP provides the following source code:

# A C++ declaration of the proper type for each parameter assiging the default value if specified by the XML
# For ''-vector'' parameters, a ''std::vector'' containing the proper C++ type fo the parameter. The generated code parses the comma separated strings to generate the ''std::vector''

=== Using GenerateCLP ===

GenerateCLP is normally used via CMake where it is implemented as a CUSTOM_COMMAND. To use GenerateCLP from CMake include the following in your CMakeLists.txt file:

INCLUDE(${Slicer3_SOURCE_DIR}/Libs/GenerateCLP/UseGenerateCLP.cmake)

For each executable, include the following, replacing '''MyFilter''' with the name of your C++ source:

SET ( '''MyFilter'''_SOURCE '''MyFilter'''.cxx )
GENERATECLP('''MyFilter'''_SOURCE '''MyFilter'''.xml)

To generate a stand-alone executable add the lines:

ADD_EXECUTABLE ( '''MyFilter''' ${'''MyFilter'''_SOURCE})
TARGET_LINK_LIBRARIES ( '''MyFilter''' ITKIO ITKBasicFilters ITKCommon)

To generate a pluggable library add the lines:

ADD_LIBRARY('''MyFilter'''Lib SHARED ${'''MyFilter'''_SOURCE})
SET_TARGET_PROPERTIES ('''MyFilter'''Lib PROPERTIES COMPILE_FLAGS "-Dmain=SlicerModuleEntryPoint")
TARGET_LINK_LIBRARIES ('''MyFilter'''Lib ITKIO ITKBasicFilters)

 The ADD_EXECUTABLE target creates a stand-alone executable that can be run from a command line. The ADD_LIBRARY target creates a shared library that is discovered at Slicer 3 startup.

Although this example linked to ITK libraries, other libraries can be specified.

=== Short Example ===

This example uses the XML for the [[Slicer3:Execution_Model_Documentation#Module_with_an_integer-vector.2C_one_input_image_and_one_output_image|Median Image Filter example]].
 
'''Note:''' The program '''MUST NOT''' write anything to stdout before the ''PARSE_ARGS'' statement. If something is written, the plugin discovery mechanism will not recognize the program as a plugin.

<nowiki>#include "MedianImageFilterCLP.h"
int main (int argc, char * argv[])
{
PARSE_ARGS;
std::cout << "The size of the neighborhood is: " << neighborhood.size()
<< " and the first element of the neighborhood is: " << neighborhood[0]
<< std::endl;
std::cout << "The input volume is: " << inputVolume << std::endl;
std::cout << "The output volume is: " << outputVolume << std::endl;
return EXIT_SUCCESS;
}
</nowiki>

Here is the output --help:

<pre>

USAGE:

./MedianImageFilter [--processinformationaddress <std::string>] [--xml]
[--echo] [--neighborhood <std::vector<int>>] [--]
[--version] [-h] <std::string> <std::string>

Where:

--processinformationaddress <std::string>
Address of a structure to store process information (progress, abort,
etc.). (default: 0)

--xml
Produce xml description of command line arguments (default: 0)

--echo
Echo the command line arguments (default: 0)

--neighborhood <std::vector<int>>
The size of the neighborhood in each dimension (default: 1,1,1)

--, --ignore_rest
Ignores the rest of the labeled arguments following this flag.

--version
Displays version information and exits.

-h, --help
Displays usage information and exits.

<std::string>
(required) Input volume to be filtered

<std::string>
(required) Output filtered

The MedianImageFilter is commonly used as a robust approach for noise
reduction. This filter is particularly efficient against
'salt-and-pepper' noise. In other words, it is robust to the presence of
gray-level outliers. MedianImageFilter computes the value of each output
pixel as the statistical median of the neighborhood of values around the
corresponding input pixel.

Author(s): Bill Lorensen

Acknowledgements: This command module was derived from
Insight/Examples/Filtering/MedianImageFilter (copyright) Insight
Software Consortium

</pre>

=== Parameters and C++ code ===

This table shows how parameters are defined in the C++ code and how they are specified on the command line.

{| border="1"
! XML
! C++ Declaration
! Command Line
|-
|
<integer> <name>count</name> <flag>c</flag> </integer>
|
int count;
|
''prog'' -c 10
|-
|
<float> <name>stepSize</name> <default>.0625</default> <longflag>stepSize</longflag> </float>
|
float stepSize=.0625;
|
''prog'' --stepSize .003
|-
|
<integer multiple="true"> <name>iterations</name> <flag>i</flag> <default>100</default> </integer>
|
std::vector<int> iterations; iterations.push_back(100); 
|
''prog'' -i 20 -i 30 -i 100
|-
|
<float-vector> <name>variation</name> <flag>v</flag> <default>1,2,3</default> </float-vector>
|
std::vector<float> variation; iterations.push_back(1); iterations.push_back(2); iterations.push_back(3); 
|
''prog'' -v 10,20,3
|-
|
<string-vector> <name>sites</name> <longflag>sites</longflag> </string-vector>
|
std::vector<std::string> sites;
|
''prog'' --names BWH,GE,Kitware,UNC,MIT,UTAH,GT
|-
|
<string-enumeration> <name>leaders</name> <default>Bill</default> <element>Ron</element> <element>Bill</element> <element>Steve</element> </string-enumeration>
|
std::string leaders = "Bill";
|
''prog'' --leaders Ron
|-
|
<boolean> <name>debugSwitch</name> <flag>d</flag> <default>true</default> </boolean>
|
bool debugSwitch = false;
|
''prog'' -d
|-
|
<file> <longflag>file1</longflag> <file>
|
std::string file1;
|
''prog'' --file1 mytext.txt
|-
|
<image> <name>image</name> <index>0</index> </image>
|
std::string image;
|
''prog'' c:/lorensen/Data/ct.nrrd
|-
|
<file multiple="true"> <name>args</name> <index>1</index> </file>
|
std::vector<std::string> args;
|
''prog'' --otherFlags file1 file2 ... filen
|-
|
<point multiple="true" coordinateSystem="ras"> <name>seed</name> <longflag>--seed</longflag>
|
std::vector<std::vector<float> > seed;
|
''prog'' --seed 10,100,23 --seed 5,240,17
|}

== Error Handling ==

GenerateCLP attempts to do error checking so that the generated C++ code will compile. These errors will show up as custom command errors during the build process.

* XML Errors
** ''mismatched tag at line xx'' : The closing tag (a tag with </ >) does not have a matching opening tag.
** ''not well-formed (invalid token) at line xx'' : Probably a blank in the token name.
* ModuleDescriptionParser Errors
** ''<executable> must be the outer most tag''
** ''<executable> was found inside another tag''
** ''<parameters> can only be inside <executable>''
** ''<xxx> can only be used inside <parameters>''
** ''<flag> can only contain one character''
** ''<longname> can only contain letters, numbers and underscores and must start with a _ or letter''
** ''<name> can only contain letters, numbers and underscores and must start with an _ or letter''

* ModuleDescriptionParser Warnings
** ''<xxx> is an unknown parameter tag'' : Probably a misspelled parameter type.

* Compiler Errors
** The generated C++ code may have syntax errors if invalid defaults are specified. These will show up during the C++ compilation.

== Interfacing Legacy Executables ==

GenerateCLP is only provided as a convenience. Users can use the same XML Module Description to interface C++, shell scripts, tcl programs and even Matlab!

* C++ Example
* Tcl Example
* Shell Script Example
* Matlab Example
* [[Slicer3:FiberTrackingIntegration|FiberTracking Integration Example]]

== Showing Progress in an Application ==

Programs can communicate progress to the user in two ways. If the program is running an a stand-alone executable, it communicates with a simple XML syntax. If the program is loaded at run-time as a plugin library, it communicates through a C structure.

The XML syntax is:

<filter-start>
<filter-name>
''name of program section or algorithm''
</filter-name>
<filter-comment>
''description of program section or algrotihm''
</filter-comment>
</filter-start>

<filter-progress>
''floating number from 0 to 1''
</filter-progress>

<filter-end>
<filter-name>
''name of program section or algorithm''
</filter-name>
<filter-time>
''execution time''
</filter-time>
</filter-end>

The C structure that library plugins use is:

extern "C" {
struct ModuleProcessInformation
{
/** Inputs from calling application to the module **/
unsigned char Abort;
/** Outputs from the module to the calling application **/
float Progress;
char ProgressMessage[1024];
void (*ProgressCallbackFunction)(void *);
void *ProgressCallbackClientData;
double ElapsedTime;
}
}

Details on how to use this mechanism are illustrated in [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FitkPluginFilterWatcher.h&rev=0&sc=0 itkPluginFilterWatcher.h].

For vtk and itk execution model programs, two classes are available that make it simple to add progress. The classes, ''vtkPluginFilterWatcher'' and ''itk::PluginFilterWatcher'' use the vtk and itk command/observer mechanism to report progress.

vtkPluginFilterWatcher (vtkAlgorithm *'''filter''', const char* '''comment''', ModuleProcessInformation *'''inf''', double '''fraction''', double '''start''') itk::PluginFilterWatcher (itk::ProcessObject '''filter''', const char* '''comment''', ModuleProcessInformation *'''inf''', double '''fraction''', double '''start''')

: where:
;; filter
:: is the vtkAlgorithm or itk::ProcessObject to be watched.
;; comment
:: is a string that describes the algorithm.
;; inf
:: is an optional pointer to a structure that is used to communicate with the invoking program when the called program is used as a library plugin. If the pointer is 0, this prgram will not report progress if it is run as a library plugin. Default is 0.
;; fraction
:: is the fraction (0-1) of progress that will be reported by this watcher. This is used when multiple filters are run and each filter represents a proportion of the total progress. Default is 1.
;; start
:: is the offset (0-1) of the progress for this filter. This is added to the progress of the filter. The reported progress of the watched filter is ''start + fraction * filter_progress''.

 The following example produces progress for a simple vtk program. The variable CLPProcessInformation is automatically declared and set in the program's ''program''CLP.h file.

<nowiki>#include "vtkPluginFilterWatcher.h"
...
vtkMarchingCubes *cubes = vtkMarchingCubes::New();
cubes->SetInput(reader->GetOutput());
vtkPluginFilterWatcher watchCubes(cubes, "Generate Isosurface", CLPProcessInformation, .5, 0.0);
vtkDecimatePro *decimate = vtkDecimatePro::New();
decimate->SetInput(cubes->GetOutput());
vtkPluginFilterWatcher watchDecimate(decimate, "Reduce Triangle Count", CLPProcessInformation, .5, 0.5);
decimate->Update();
</nowiki>

The following example produces progress for a simple itk program:

<nowiki>#include "itkPluginFilterWatcher.h
...
typedef itk::MedianImageFilter<ImageType,ImageType> FilterType;
FilterType::Pointer median = FilterType::New();
itk::PluginFilterWatcher watchMedian(median, "Denoise Image", CLPProcessInformation);
</nowiki>

== Adding Module Logos to Slicer3 ==
Slicer3 plugins, both libraries and executables, can specify plugin-specific logos. These appear in Slicer3 when a module is selected. The logos are specified in the KWWidget icon format. KWWidget icons are stored in the vtkKWIcon class. The vtkKWIcon::SetImage method supports images encoded in zlib compressed, base64 format. The KWWidget utility, KWConvertImageToHeader, converts a .png file into a .h header file containing the encoded image and additional information such as width, height and pixel size.

For Slicer3, execution model plugin logos are stored in Applications/CLI/Resources. The corresponding image in .png format should be stored in Applcations/CLI/ImageData. Othere plugins, created outside the Slicer3 tree, should store the logo and image in a similar location.

To add a logo to a plugin:
* Create a png image of the logo. The height of the logo should not exceed 40 pixels.
* Convert the logo to the KWWidget icon format as follows. '''NOTE:''' the prefix of the image and header file must be the same for a plugin logo.
<pre>
cd Slicer3/Applications/CLI
KWConvertImageToHeader --base64 --zlib Resources/ITKLogo.h ImageData/ITKLogo.png
</pre>
* Add the logo to the GENERATECLP macro in the CMakeLists.txt file for the plugin:
<pre>
#####################
SET (CLP foo)

SET ( ${CLP}_SOURCE ${CLP}.cxx)
GENERATECLP(${CLP}_SOURCE ${CLP}.xml ${CLI_SOURCE_DIR}/Resources/ITKLogo.h)
ADD_EXECUTABLE(${CLP} ${${CLP}_SOURCE})
TARGET_LINK_LIBRARIES (${CLP} ITKIO ITKBasicFilters)

ADD_LIBRARY(${CLP}Lib SHARED ${${CLP}_SOURCE})
SET_TARGET_PROPERTIES (${CLP}Lib PROPERTIES COMPILE_FLAGS "-Dmain=SlicerModuleEntryPoint")
TARGET_LINK_LIBRARIES (${CLP}Lib ITKIO ITKBasicFilters)
</pre>

== Using GenerateCLP Outside of Slicer3 ==

GenerateCLP can be built and used outside of the Slicer3 tree.

# First checkout the required directories from the Slicer3 repository.
## svn co http://www.na-mic.org:8000/svn/Slicer3/trunk/Libs/tclap
## svn co http://www.na-mic.org:8000/svn/Slicer3/trunk/Libs/ModuleDescriptionParser
## svn co http://www.na-mic.org:8000/svn/Slicer3/trunk/Libs/GenerateCLP
# Run cmake on tclap
# Run cmake on ModuleDescriptionParser
# make ModuleDescriptionParser
# Run cmake on GenerateCLP
# make GenerateCLP

To use '''GenerateCLP''' from CMake include the following in your ''CMakeLists.txt'' file:

FIND_PACKAGE(GenerateCLP REQUIRED)
INCLUDE(${GenerateCLP_SOURCE_DIR}/UseGenerateCLP.cmake)

To use '''GenerateCLP''' with an itk program, add the following to the ''CMakeLists.txt'' file for your project:

SET ( '''MyFilter'''_SOURCE '''MyFilter'''.cxx )
GENERATECLP('''MyFilter'''_SOURCE '''MyFilter'''.xml)
ADD_EXECUTABLE ( '''MyFilter''' ${'''MyFilter'''_SOURCE})
TARGET_LINK_LIBRARIES ( '''MyFilter''' ITKIO ITKBasicFilters ITKCommon)

To use '''GenerateCLP''' with a vtk program, add the following to the ''CMakeLists.txt'' file for your project:

SET ( '''MyFilter'''_SOURCE '''MyFilter'''.cxx )
GENERATECLP('''MyFilter'''_SOURCE '''MyFilter'''.xml)
LINK_DIRECTORIES(${vtkITK_LIB_DIR})
ADD_EXECUTABLE ( '''MyFilter''' ${'''MyFilter'''_SOURCE})
TARGET_LINK_LIBRARIES ( '''MyFilter''' vtkITK vtkImaging vtkGraphics vtkIO)
INCLUDE_DIRECTORIES(${vtkITK_SOURCE_DIR} ${vtkITK_BINARY_DIR})

 '''Windows Users Please Note:''' All packages that you use '''MUST''' be built with the same build type (Debug, Release or RelWithDebInfo).

== Accessing Module Information at Runtime ==

All of the information contained in the XML description of a module can be accessed at run-time by the command line program. The ''ModuleDescriptionParser'' class library can parse an XML module description and populate a ''ModuleDescription'' instance.
<pre>
// Module Description Parser Class Library
#include "ModuleDescriptionParser.h"
#include "ModuleDescription.h"
#include "ModuleParameterGroup.h"
#include "ModuleParameter.h"
.
.
.
// Create a module and a parser
ModuleDescription module;
ModuleDescriptionParser parser;
// Parse the XML
if (parser.Parse(GetXMLModuleDescription(), module))
{
std::cerr << argv[0] << ": One or more XML errors detected." << std::endl;
return EXIT_FAILURE;
}
// Access the module description information
std::cout << "Module Description Information" << std::endl;
std::cout << "\tCategory is: " << module.GetCategory() << std::endl;
std::cout << "\tTitle is: " << module.GetTitle() << std::endl;
std::cout << "\tDescription is: " << module.GetDescription() << std::endl;
std::cout << "\tVersion is: " << module.GetVersion() << std::endl;
std::cout << "\tDocumentationURL is: " << module.GetDocumentationURL() << std::endl;
std::cout << "\tLicense is: " << module.GetLicense() << std::endl;
std::cout << "\tContributor is: " << module.GetContributor() << std::endl;
</pre>

''GetXMLModuleDescription'' is automatically generated by ''GenerateCLP''. Information about parameter groups and parameters is also available [[Accessing_Module_Information_at_Runtime|here]].

The ''CMakeLists.txt'' file that creates the command line module should point to the ''ModuleDescriptionParser'' library.
<pre>
TARGET_LINK_LIBRARIES (${CLP}
ModuleDescriptionParser
)
</pre>

== Building the Slicer3 Command Line Programs Outside of Slicer3 ==

The command line programs developed for Slicer3 can be built without building Slicer3.

# First follow the directions in [[Slicer3:Execution_Model_Documentation#Using_GenerateCLP_Outside_of_Slicer3|Using GenerateCLP Outside of Slicer3]]
# Checkout the Slicer3 command line programs
## svn co http://www.na-mic.org:8000/svn/Slicer3/trunk/Applications/CLI
# Some of the programs in CLI rely on vtkITK. If you will e using these command line programs, then checkout vtkITK.
## svn co http://www.na-mic.org:8000/svn/Slicer3/trunk/Libs/vtkITK
## Run cmake on vtkITK.
# Run cmake on CLI.

CMake may ask you to locate the builds for packages that the CLI programs use.

'''Windows Users Please Note:''' All packages that you use '''MUST''' be built with the same build type (Debug, Release or RelWithDebInfo).

== Useful Examples ==

Slicer3 contains a growing list of command line programs. These reside in the [http://www.na-mic.org:8000/websvn/listing.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2F&rev=0&sc=0 Slicer3/Applications/CLI]directory. As with all command line programs, these can be run from the Slicer3 GUI or as independent executables. The command line programs fall into two general categories:

# ''Read/Single Filter/Write'' - These programs provide useful, single function operations. Examples include:
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FCheckerBoard.cxx&rev=0&sc=0 CheckerBoard] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FCheckerBoard.xml&rev=0&sc=0 xml]) - combines two volumes into a single volume with alternating images from each volume.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGradientAnisotropicDiffusion.cxx&rev=0&sc=0 Gradient Anisotropic Diffusion] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGradientAnisotropicDiffusion.xml&rev=0&sc=0 xml]) - classic Perona-Malik, gradient magnitude based equation
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGrayscaleFillHoleImageFilter.cxx&rev=0&sc=0 Grayscale Fill Hole] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGrayscaleFillHoleImageFilter.xml&rev=0&sc=0 xml]) - smooth over local minima without affecting the values of local maxima.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGrayscaleGrindPeakImageFilter.cxx&rev=0&sc=0 Grayscale Grind Peak] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FGrayscaleGrindPeakImageFilter.xml&rev=0&sc=0 xml]) - smooth over local maxima without affecting the values of local minima.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FMedianImageFilter.cxx&rev=0&sc=0 Median Image Filter] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FMedianImageFilter.xml&rev=0&sc=0 xml]) - classic non-linear median filter. This program is a modification of the Insight Example [http://www.itk.org/cgi-bin/viewcvs.cgi/Examples/Filtering/MedianImageFilter.cxx?rev=1.24&root=Insight&view=markup Median Image Filter].
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FOtsuThresholdImageFilter.cxx&rev=0&sc=0 Otsu Threshold] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FOtsuThresholdImageFilter.xml&rev=0&sc=0 xml]) - creates a binary thresholded image that separates an image into foreground and background components. This program is a modification of the Insight Example [http://www.itk.org/cgi-bin/viewcvs.cgi/Examples/Filtering/OtsuThresholdImageFilter.cxx?root=Insight&view=markup OtsuThresholdImageFilter].
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FVotingBinaryHoleFillingImageFilter.cxx&rev=0&sc=0 Voting Binary Hole Filling] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FVotingBinaryHoleFillingImageFilter.xml&rev=0&sc=0 xml]) - fills in holes and cavities by applying a voting operation on each pixel.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FResampleVolume.cxx&rev=0&sc=0 Resample Volume] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FResampleVolume.cxx&rev=0&sc=0 xml]) - resample a volume.
# ''Read/Multiple Filters/Write'' - These programs package a number of filters to accomplish a higher level task.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FModelMaker.cxx&rev=0&sc=0 Model Maker]([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FModelMaker.xml&rev=0&sc=0 xml]) - creates polygonal models from segmented volumes. This program uses vtk filters to creae isosurfaces, decimate and smooth them.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FImageReadDicomWrite.cxx&rev=0&sc=0 Image Read DICOM Write] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FImageReadDicomWrite.xml&rev=0&sc=0 xml]) - creates a DICOM series from a 3D volume.
## [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FOtsuThresholdSegmentation.cxx&rev=0&sc=0 Otsu Threshold Segmentation] ([http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FApplications%2FCLI%2FOtsuThresholdSegmentation.xml&rev=0&sc=0 xml]) - finds a threshold to separate foreground and background, then runs a connected component algorithm and produces a segmented volume with independent components.

=== Runtime specification of filter types ===

ITK filters are templated over the images they process. The following code snippet shows how an execution model program can select the image types for filters based on the input images.

First, include the utilites for plugin's:
<pre>
#include "itkPluginUtilities.h"
</pre>

Then, turn your main program into a templated procedure called ''DoIt'':
<pre>
template<class T> int DoIt( int argc, char * argv[], T )
{
PARSE_ARGS;

typedef itk::Image< T, 3 > InputImageType;
typedef itk::Image< T, 3 > OutputImageType;
.
.
.
}
</pre>
Then, create a main program that gets the native component type from one of the input file. Here that input file is ''inputVolume'':
<pre>
int main( int argc, char * argv[] )
{

PARSE_ARGS;

itk::ImageIOBase::IOPixelType pixelType;
itk::ImageIOBase::IOComponentType componentType;

try
{
itk::GetImageType (inputVolume, pixelType, componentType);

// This filter handles all types

switch (componentType)
{
case itk::ImageIOBase::UCHAR:
return DoIt( argc, argv, static_cast<unsigned char>(0));
break;
case itk::ImageIOBase::CHAR:
return DoIt( argc, argv, static_cast<char>(0));
break;
case itk::ImageIOBase::USHORT:
return DoIt( argc, argv, static_cast<unsigned short>(0));
break;
case itk::ImageIOBase::SHORT:
return DoIt( argc, argv, static_cast<short>(0));
break;
case itk::ImageIOBase::UINT:
return DoIt( argc, argv, static_cast<unsigned int>(0));
break;
case itk::ImageIOBase::INT:
return DoIt( argc, argv, static_cast<int>(0));
break;
case itk::ImageIOBase::ULONG:
return DoIt( argc, argv, static_cast<unsigned long>(0));
break;
case itk::ImageIOBase::LONG:
return DoIt( argc, argv, static_cast<long>(0));
break;
case itk::ImageIOBase::FLOAT:
return DoIt( argc, argv, static_cast<float>(0));
break;
case itk::ImageIOBase::DOUBLE:
return DoIt( argc, argv, static_cast<double>(0));
break;
case itk::ImageIOBase::UNKNOWNCOMPONENTTYPE:
default:
std::cout << "unknown component type" << std::endl;
break;
}
}
catch( itk::ExceptionObject &excep)
{
std::cerr << argv[0] << ": exception caught !" << std::endl;
std::cerr << excep << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}

</pre>

== Behind the Scenes ==

A primary goal of the execution model is to relieve developers from developing GUI code and command line parsing code. This section descibes the major components of the execution model implementation.

=== Command Line Processing ===

Command line processing parses command line arguments and populates internal program variables. Every Unix (and windows) program can receive an argument list through its main entry point. All C and C++ programmers are familiar with the ''int main (int argc, char *[] argv)'' entry point in their programs. Most computer languages including scripting languages provide a similar mechanism to retrieve command line arguments. Simple command line processing directly accesses the strings defined in argv.

This snippet shows simple commmand line processing:

int main (int argc, char *argv[])
{
if (argc < 2)
{
std::cout << "Usage: " << argv[0] << " filename" << std::endl;
return -1;
}
std::cout << "The File is " << argv[1] << std::endl;
return 0;
}

The simple approach works great for a small number of arguments. But larger numbers of arguments of varying types quickly make the processing code more complex and subject to error, both in coding and usage.

int main (int argc, char *argv[])
{
if (argc < 5)
{
std::cout << "Usage: " << argv[0] << " iterations epsilon inputfile outputfile " << std::endl;
return -1;
}
std::string inputfile(argv[3]);
std::string outputfile(argv[4]);
unsigned int iterations = atoi(argv[1]);
float epsilon = atof(argv[2]);
...
return 0;
}

Adding flags (or options) to the command line makes the program easier to use but places a larger burden on the program developer. Each developer must ''invent'' a command line argument syntax and implement code to parse the command line. Even a simple example of this is too long to include in this description. This code snippet looks for just two command line arguments.

int main (int argc, char *argv[])
{
if (argc < 3)
{
std::cout << "Usage: " << argv[0] << " [-i iterations] [-e epsilon] inputfile outputfile " << std::endl;
return -1;
}
std::string inputfile;
std::string outputfile;
unsigned int iterations = 10; /* a default */
float epsilon = .001; /* a defualt */
++argc; /* skip program name */
while (argc > 0)
{
if (strcmp(argv[argc], "-i")
{
iterations = atoi(argv[argc+1]);
argc+=2;
continue;

else if (strcmp(argv[argc], "-e")
{
epsilon = atof(argv[argc+1]);
argc+=2;
continue;
...
}

The code gets longer and longer as more options are added and must be rewritten every time a new programs is open.

To solve this complexity issue, people have developed command line argument libraries. There are dozens, if not hundreds, of command line processing tools. For Slicer3 we looked at argument processors in vxl, nrrd, meta, kwsys and tclap. Each has its strengths and weaknesses. We chose [http://tclap.sourceforge.net/ The Templatized C++ Command Line Parser Library], '''TCLAP'''. '''TCLAP''' is implemented in ''include'' files and does not require a separate library build. As you will see later, the particular command line processing tool is, for the most part, transparent to the Slicer3 developer or user.

But even these libraries require some work to use.

==== TCLAP ====

This example uses '''TCLAP''' to process a command line with 10 possible entries:

int main ( int argc, char* argv[] ) {
//
// Define default values
int HistogramBins = 30;
int RandomSeed = 1234567;
int SpatialSamples = 10000;
float TranslationScale = 100.0;
int Iterations = 200;
int SplineOrder = 3;
double MinimumStepSize = 0.00001;
double MaximumStepSize = 0.005;
bool PrintTransform = false;
string fixedImageFileName;
string movingImageFileName;
string resampledImageFileName;
//
// Setup command line parsing
try
{
TCLAP::CmdLine cl ( "Register2d", ' ', "$Revision: 1.1 $" );
TCLAP::ValueArg<int> HistogramBinsArg ( "b", "histogrambins", "Number of histogram bins", false, 30, "integer", cl );
TCLAP::ValueArg<int> IterationsArg ( "i", "iterations", "Number of Iterations", false, Iterations, "int", cl );
TCLAP::ValueArg<double> MinimumStepSizeArg ( "m", "minstepsize", "Minimum Step Size", false, MinimumStepSize, "double", cl );
TCLAP::ValueArg<double> MaximumStepSizeArg ( "x", "maxstepsize", "Maximum Step Size", false, MaximumStepSize, "double", cl );
TCLAP::ValueArg<int> RandomSeedArg ( "r", "randomseed", "Random Seed", false, RandomSeed, "int", cl );
TCLAP::ValueArg<int> SpatialSamplesArg ( "s", "spatialsamples", "Number of spatial samples", false, SpatialSamples, "int", cl );
TCLAP::ValueArg<int> SplineOrderArg ( "o", "splineorder", "Order of spline for registration", false, SplineOrder, "int", cl );
TCLAP::SwitchArg PrintTransformArg ( "p", "printtransform", "Print the final transform", PrintTransform, cl );
TCLAP::ValueArg<float> TranslationScaleArg ( "t", "translationscale", "Translation scale", false, TranslationScale, "float", cl );
TCLAP::UnlabeledValueArg<string> FixedImageArg ( "fixed", "Fixed image filename", "", "string", cl );
TCLAP::UnlabeledValueArg<string> MovingImageArg ( "moving", "Moving image filename", "", "string", cl );
TCLAP::UnlabeledValueArg<string> ResampledImageArg ( "resampled", "Resampled image filename", "", "string", cl );
//
// Parse the command line
cl.parse ( argc, argv );
//
// Access the variables
HistogramBins = HistogramBinsArg.getValue();
Iterations = IterationsArg.getValue();
MinimumStepSize = MinimumStepSizeArg.getValue();
MaximumStepSize = MaximumStepSizeArg.getValue();
RandomSeed = RandomSeedArg.getValue();
SpatialSamples = SpatialSamplesArg.getValue();
TranslationScale = TranslationScaleArg.getValue();
PrintTransform = PrintTransformArg.getValue();
fixedImageFileName = FixedImageArg.getValue();
movingImageFileName = MovingImageArg.getValue();
resampledImageFileName = ResampledImageArg.getValue();
}
catch ( ArgException e )
{
cerr << "error: " << e.error() << " for arg " << e.argId() << endl;
exit ( EXIT_FAILURE );
}

You do get a lot for your investment here. Good error handling and help.

=== Module Description Parser ===
The XML parsing is done by the ''ModuleDescriptionParser'' class library located in ''Slicer3/Libs/ModuleDescriptionParser''. ''GenerateCLP'' and Slicer3 use this class library to parse the module XML descriptions. The class ''ModuleDescrptionParser'' has one method, '''Parse''', that converts the XML description into an object model. The resulting object model has one ''ModuleDescription'', one or more ''ModuleParameterGroup'' each of which has one or more ''ModuleParameter''. Each instance has access methods to retrieve information from the XML.
* '''ModuleDescriptionParser''' - parser for command line module XML description.
*: ''Parse(std::string xml, ModuleDescription module)'' - parse an xml string and populate a ModuleDescription.
* '''ModuleDescription''' - contains information about a module
*: const std::string ''GetCategory()'' : returns the contents of '''<category>'''.
*: const std::string ''GetTitle()'' : returns the contents of '''<title>'''.
*: const std::string ''GetDescription()'' : returns the contents of '''<description>'''.
*: const std::string ''GetVersion()'' : returns the contents of '''<version>'''.
*: const std::string ''GetDocumentationURL()'' : returns the contents of '''<documentationURL>'''.
*: const std::string ''GetLicense()'' : returns the contents of '''<license>'''.
*: const std::string ''GetContributor()'' : returns the contents of '''<contributor>'''.
*: const std::vector<ModuleParameterGroup>& ''GetParameterGroups()'' : returns a vector of parameter groups.
* '''ModuleParameterGroup''' - contains ModuleParameters for each parameter group.
*: const std::string ''GetLabel'' - returns the contents of '''<label>'''.
*: const std::string ''GetDescription()'' - returns the contents of the parameter group's '''<description>'''.
*: const std::string ''GetAdvanced()'' - returns advanced attribute. Either "true" of "false".
* '''ModuleParameter''' - contains information for a parameter.
*:GetTag() - returns the parameter's tag, e.g. '''<integer>, <image>''', etc.
*:GetName() - returns the parameter's '''<name>'''.
*:GetLongFlag() - returns the parameter's '''<longflag>'''.
*:GetLabel() - returns the parameter's '''<label>'''.
*:GetMaximum() - returns the parameter's '''<maximum>''' constraint.
*:GetMinimum() - returns the parameter's '''<minimum>''' constraint.
*:GetStep() - returns the parameter's '''<step>'''.
*:GetDescription() - returns the parameter's '''<description>'''.
*:GetChannel() - returns the parameter's '''<channel>'''.
*:GetIndex() - returns the parameter's '''<index>'''.
*:GetDefault() - returns the parameter's '''<default>'''.
*:GetFlag() - returns the parameter's '''<flag>'''.
*:GetMultiple() - returns the parameter's multiple attribute, either "true" or "false".
*:GetCoordinateSystem() - returns the parameter's coordinate system attribute, one of "lps", "ras", or "ijk".

Engineering:Subversion Repository

2007-01-03T19:34:22Z

Dsjen: /* I get the following error when I try to commit... */

== What is NA-MIC Subversion ==

NA-MIC SandBox is a repository of untested and unstable code developed as a part of NA-MIC. For more information, check the [[NAMIC_Wiki:Software_Process#The_Sandbox|NA-MIC Software Development Process]]

See [http://svnbook.red-bean.com/ the SVN Book at red-bean.com]. In particular, check out the information about [http://svnbook.red-bean.com/en/1.1/ch03s05.html the Basic Work Cycle for svn].

The NA-MIC SVN is also used for the [[Slicer3|Slicer3]] development effort.

== How do I get NA-MIC SandBox ==

Use [http://subversion.tigris.org/ Subversion]. Checkout using the following command:

svn checkout http://www.na-mic.org:8000/svn/NAMICSandBox

Clients for subversion are avaialble for most operating systems. Please check if you already have Subversion on the system, or download apropriate one from http://subversion.tigris.org/project_packages.html.

== How do I commit to NA-MIC Subversion ==

Fill the form at https://www.kitware.com/Admin/SendPassword.cgi and under Comment type "Request password for NA-MIC Sandbox". Once you have access to write to NA-MIC SandBox, you can work with repository using the following commands:

To update repository:

svn update

To check current state of your edits:

svn status

To check the current state compared to the repository:

svn -u status

To add new file:

svn add filename

followed by (very important):

svn commit -m"ENH: Adding a new file" filename

To remove file:

svn remove filename

To rename file:

svn move oldname newname

If the update results in conflict, fix the file first before commiting it.

Once you have fixed the file:

svn resolved <filename>

== Can I see the files through the Web ==

Yes, check: [http://www.na-mic.org:8000/websvn/listing.php?repname=NAMICSandBox&path=%2F&sc=0 WebSVN].

Or for Slicer3, [http://www.na-mic.org:8000/websvn/listing.php?repname=Slicer3&path=%2F&sc=0 WebSVN].

== I get the following error when I try to commit... ==

If you want to enable this error reporting on your subversion repository, please follow instructions about [[Subversion_Input_Filters|Subversion Input Filters]].

=== Commit log error ===

The error would look like this:

<nowiki>---------------------------------------------------------------------
Subversion Commits to NA-MIC require commit type in the comment.
Valid commit types are:
BUG: - a change made to fix a runtime issue
(crash, segmentation fault, exception, or incorrect result,
COMP: - a fix for a compilation issue, error or warning,
ENH: - new functionality added to the project,
PERF: - a performance improvement,
STYLE: - a change that does not impact the logic or execution of the code.
(improve coding style, comments, documentation).

The Subversion command to commit the change is:

svn commit -m "BUG: fixed core dump when passed float data" filename

you can also use the syntax below which omits the -m flag. In this case
subversion will start up an editor for you to enter a comment on why you made
the change.

svn commit filename
----------------------------------------------------------------------</nowiki>

Make sure to start the commit message with one of the specified tags.

 

=== Tabs in the source file ===

<nowiki>----------------------------------------------------------------------
Problems in file "my baby.cxx":
The following line(s) contain tabs:
4: This line contains a tab--> <--

Found problems with 1 file(s). Cannot commit
----------------------------------------------------------------------</nowiki>

Make sure there is no tabs in the source files. You can remove them with

perl -pi .-e 's/\t/ /g' <FileName>

or

sed -i -e 's/\t/ /g' <FileName>

=== Missing new line at the end of file ===

<nowiki>----------------------------------------------------------------------
Problems in file "my baby.cxx":
The following line(s) do not contain new-line character:
5: another linex

Found problems with 1 file(s). Cannot commit
----------------------------------------------------------------------</nowiki>

Make sure there is a new line at the end of the source file. Most editors should fix this automatically.

=== Conflicts in the file ===

<nowiki>----------------------------------------------------------------------
Problems in file "test.cxx":
The following line(s) contain conflicts:
1: <<<<<<< .mine
11: =======
22: >>>>>>> .r13

Found problems with 2 file(s). Cannot commit
----------------------------------------------------------------------</nowiki>

Make sure to remove any conflicts before removing files.

Once resolved:

svn resolved test.cxx

=== Things missing from SVN that were in CVS ===

==== No cvs diff -w ====

Some workarounds here: http://kitt.hodsden.com/ignoring_whitespace_changes_with_svn_diff

==== No cvs update -C ====

Remove the file and then update (nothing more clean?) (mathieu). I believe this is describe here: http://svnbook.red-bean.com/nightly/en/svn.tour.cycle.html#svn.tour.cycle.resolve

...snip...

If you get a conflict, you need to do one of three things:

* Merge the conflicted text “by hand” (by examining and editing the conflict markers within the file).
* Copy one of the temporary files on top of your working file.
* Run svn revert <filename> to throw away all of your local changes.

Once you've resolved the conflict, you need to let Subversion know by running svn resolved. This removes the three temporary files and Subversion no longer considers the file to be in a state of conflict.

$ svn resolved <filename>

...snip...

User:Dsjen

2007-01-03T19:27:42Z

Dsjen:

Dennis Jen

2007 Project Half Week

2007-01-03T19:21:40Z

Dsjen: /* Projects */

Back to [[AHM_2007|AHM_2007]]

== Results ==
Results of this event will be summarized here after it is completed.

==Please note==
* Everyone should '''bring a laptop'''. We will have three or four projectors.
* About half the time will be spent working on projects and the other half in project related discussions.

== Projects ==
This is the list of projects discussed in the preparation tcons on [[Engineering:TCON_12_07_2006|December 7]] and [[Engineering:TCON_12_14_2006|December 14, 2006]]. Each project lead (first name in the list) needs to complete a [[Media:2007_Project_Half_Week_Template.ppt|new 4-block PPT]], and upload and link it to this page.

===Structural Analysis===
# [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]] (Delphine Nain - GT, Yi Gao - GT, Jim Miller - GE, Luis Ibanez - Kitware): [[Media:2006_Project_Week_MIT_SphericalWaveletInITK.ppt| 4-block PPT Summer 2006]],[[Media:2007_Project_Half_Week_SphericalWaveletInITK.ppt| 4-block PPT Jan 2007]]
#scripts to run UNC shape analysis (delphine, Martin)
#EMSegmenter Software Development(Kilian, Brad)
#SVM Shape Analysis (Brad, Polina, Martin)
#EMSegmenter for UNM use (Kilian, ?)
#[[Non_Rigid_Registration|Parallelization of ITK for deformable registration (Stephen, Jim, Ross)]]
## Driving problem: Congealing with B-spline (Lilla, Stephen)
## Driving problem: ? (Kilian, Stephen)
# Integrating KWMeshVisu into Slicer (Ipek, Martin, Sebastien), [[Media:2006_AHM_Programming_Half_week_MeshVisu.ppt|4-block PPT Jan 2006]], [[Media:2007_AHM_Programming_Half_week_MeshVisu.ppt |4-block PPT Jan 2007 ]]
#Group-wise Registration of Medical Images(Serdar, Polina, Mert, Sandy ), [[Media:2007_Project_Half_Week_GroupWiseRegistration.ppt| 4-block PPT Jan 2007]]

===Diffusion Image Analysis===
#Finsler Tractography (John Melonakos - GT, Luis Ibanez - Kitware): [[Media:2007_Project_Half_Week_FinslerTractography.ppt| 4-block PPT Jan 2007]]
#Finsler Levelsets (Vandana Mohan - GT, John Melonakos - GT, Luis Ibanez - Kitware): [[Media:2007_Project_Half_Week_FinslerLevelsets.ppt| 4-block PPT Jan 2007]]
#Rician Noise Remvoal in Diffusion Tensor MRI (McKay Davis - Utah, Tom Fletcher - Utah): [[Media:2007_Project_Half_Week_RicianNoiseDTI.ppt | 4-block PPT Jan 2007]]
#ITK implementation of POIStat, and Integration into Slicer3 (Dennis, Steve), [[Media:2007_Project_Half_Week_PoistatsSlicerItkIntegration.ppt| 4-block PPT Jan 2007]]
#Image Format issues in application of POIStats to Dartmouth data (Dennis, Steve, Luis, John West, Andy Saykin), [[Media:2007_Project_Half_Week_PoistatsImageFormatDartmouth.ppt| 4-block PPT Jan 2007]]

===NA-MIC Kit===
#[[Slicer3:Grid_Interface|Grid Execution]] (Neil, Bill, Jim) [[2007_Project_Half_Week_GridExecution.ppt]]
#Tractography in Slicer3 (Lauren, Raul)
#Model Hierarchies (Alex, Lauren, Kilian, Brad, Ron) -- generalize concepts from DTI and EM group nodes to support atlas hierachies like in slicer2.

===External Collaborations===
#Converting ITK Pipeline for Archip's, HPC based, deformable registration to Slicer3 Module (Daniel Goldberg, Stephen)
#Developing IGT workflow for Slicer3 (Simon DiMaio, Haiying Liu, Noby Hata, Stephen Aylward) [[IGT|IGT Project page in NA-MIC wiki]]
#Radiology Workstation Module for Slicer3 (Pat, Steve)
#vmtk module for Slicer(Luca Antiga, Jim Miller)
#Hexahedral Voxel Meshing Slicer Module (Nicole Grosland, Vincent Magnotta, Steve Pieper)

----
This following is a list of projects carried out at the last project week (summer 2006). For new attendees, these projects can be used as templates. For attendees involved in the last project week, please move projects from the list below to the list above if you intend to continue these projects. And please do add a [[Media:2007_Project_Half_Week_Template.ppt|new 4-block PPT for 2007]].

=== 2006 Structural Analysis ===

# [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]] (Xavier Le Faucheur, GT, Delphine Nain, GT, John Melonakos GT/GE, Jim Miller GE, Luis Ibanez, Kitware): [[Media:2006_Project_Week_MIT_SphericalWaveletInITK.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/ShapeStatisticsWithPermTestCorrectionAndFDR|ITK statistical analysis using non-parametric permutation analysis and false discovery rate]] (Martin Styner, UNC): [[Media:2006_06_PW_StatAnal.ppt| 4 block PPT 2006 ]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/Correspondence|Local curvature based correspondence in ITK]] (Ipek Oguz, Martin Styner, UNC): [[Media:2006_MIT_Project_Week_LocalCurvatureBasedCorrespondence.ppt| 4 block PPT 2006]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/FemaleSPDCaudates|Shape analysis of female SPD dataset]] (Jim Levitt, PNL, Marc Niethammer, PNL, Sylvain Bouix, PNL, Martin Styner, UNC): [[Media:2006_06_PW_female_SPD.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Structural/Mesh/Mesh_Untangling|Mesh Untangling]] (Gheorghe Postelnicu, MGH, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_Mesh_Untangling.ppt|4 block PPT 2006]]
# [[NA-MIC/Projects/Structural/Registration/Histology_MR_Registration|MR Histology Registration]] (Gheorghe Postelnicu MGH, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_MGH_Histology_MR_Registration.ppt|4 block PPT 2006]]

=== 2006 Diffusion Image Analysis ===

# [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|ITK DTI Image Processing Modules]] (Casey Goodlett UNC, Tom Fletcher Utah, Bill Lorensen GE, John Melonakos GT/GE): [[Media:2006_Summer_Project_Week_DTI_Processing.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fiber_Tools_Slicer_Integration|Fiber Tools / Slicer 3 Integration]] (Casey Goodlett UNC, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_FiberTracking_Slicer_Integration.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Stochastic_Fiber_Tracing_Applications|Stochastic Fiber Tracing Applications]] (C-F Westin, Marek Kubicki, Raul San-Jose, AW de Vries, All LMI):[[Media:2006_Summer_Project_Week_stochastictracking.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Slicer_Fiber_Anatomical_Labeling|Slicer Fiber (Model) Labeling Interface]] (Lauren O'Donnell MIT, Marek Kubicki BWH) :[[Media:2006_Summer_Project_Week_ModelLabel.ppt| 4-block PPT 2006]]

=== 2006 FMRI Image Analysis ===

# [[NA-MIC/Projects/Structural/Conformal_Flattening_in_ITK|Conformal Flattening in ITK]](Yi Gao GT, John Melonakos GT/GE, Jim Miller GE, Luis Ibanez Kitware, Marc Niethammer BWH): [[Media:2006_Summer_Project_Week_ConformalFlattening.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/fMRI_Analysis/Spatial_Regularization_for_fMRI_Detection|Spatial Regularization in fMRI Analysis]](Wanmei Ou, Polina Golland, Sandy Wells, and Carsten) [[Media:2006_Summer_Project_Week_fMRIMRF.ppt| 4-block PPT 2006]]

=== 2006 NA-MIC Kit ===

# [[2006_Project_Week_MIT_SlicerUI|Slicer3 Interface]] (Wendy Plesniak, Sebastien Barre, Steve Pieper, Mathieu Malaterre, Randy Gollub, Michael Halle), [[Media:2006_Summer_Project_Week_Slicer3UI.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_Migrating_Slicer2.x_Modules_to_Slicer3|Migrating Slicer2.x Modules to Slicer3]] (Nicole Aucoin, Mathieu Malaterre, Katie Hayes, Bill Lorensen): [[Media:2006_Summer_Project_Week_Migrating_Slicer2x_Modules_to_Slicer3.ppt|4-block PPT 2006]]
# [[2006_Project_Week_Kitware_Slicer3_Packaging|Slicer3 Packaging]] (Andy Cedilnik, Steve Pieper) [[Media:2006_Summer_Project_Week_Slicer3_Packaging.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_Grid_Integration|Slicer3 Grid Integration]] (Jeff Grethe, Brendan Faherty, Steve Pieper, Katie Hayes), [[Media:2006_Summer_Project_Week_Grid_Interface_for_Slicer3.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_LONIPipelineIntegration|Slicer3 Pipeline Integration ]] (Jagadeeswaran Rajendiran, Martin Styner, Steve Pieper), [[Media:2006_Summer_Project_Week_Jagadeeswaran_June30.ppt|4 block PPT 2006]]
# [[2006_Project_MGH_File_Format_Converter|2006 Project MGH File Format Converter]](Gheorghe Postelnicu, Bill Lorensen) [[Media:2006_Summer_Project_MIT_MGH_IO.ppt|4-block PPT 2006]]
# Volumetric Meshing (Kiran Shivanna, Vincent Magnotta, Nicole Grosland):[[Media:2006_Summer_Project_Week_Volumetric_Meshing.ppt|4-block PPT 2006]]
# Dicom Query/Retrieve (Eduardo Suárez, Rafael Nebot, Steve Pieper, Jim Miller):[[Media:2006_Summer_Project_Week_Slicer_Query_Retrieve.ppt|4-block PPT 2006]]
# A Translation Station for Imaging (Pat Mongkolwat, Alex Kogan, Tom Lechner, Steve Pieper, Wendy Plesniak):[[Media:2006_Project_Week_MIT_IntegrateSlicerWith_A_PACS_Workstation.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Slicer3_for_IGT/Converting_vtkFMRIEngine_and_vtkMRAblation_to_Slicer3_modules|Converting vtkFMRIEngine and vtkMRAblation to Slicer3 modules]] (Noby Hata, Haiying Liu, Steve Pieper, Jim Miller): [[Media:2006_Summer_Project_Week_Slicer3_IGT.ppt| 4-block ppt 2006]]

=== 2006 NA-MIC Kit Support for Non-Medical Data ===

# ITK IO support for reading astronomy data and coordinates from FITS files (Douglas Alan IIC, Michael Halle BWH/IIC, Luis Ibanez Kitware)[[Media:2006_Summer_Project_Week_Astronomy_FITS_Reader_Prelim_Results.ppt| 4-block PPT 2006]]

== Logistics ==

'''Dates:''' January 10 & 12, 2007 (There will be no project-week related events scheduled for Thursday, January 11th, the day of the AHM.)

'''Registration Fee:''' Registration fee is $215 for this event, and includes registration for the NA-MIC AHM. Separate registration, either for the AHM, or the project event are not available. To register and reserve hotel rooms, please [[AHM_2007#Registration_and_Hotel_Logistics|follow this link]].

== Background and Preparation ==

We continue to call this event "Project Week" or "Project Half Week", depending on how its duration, rather than by its original name of "Programming Week". Along with programming, a fair amount of algorithm design, and clinical application brainstorming also takes places and the name change reflects the broader scope of the event. What does this means for participants: if you are participating in a NA-MIC project or collaboration by providing algorithmic or clinical input, you are very welcome to attend. As always, participation is entirely voluntary.

=== Goals ===

The main goal of this week is to move forward the deliverables of NA-MIC. All NA-MIC participants and their collaborators are welcome.

* Members of all cores are welcome. This event involves programming, algorithm design, and clinical application development/testing.
* The event is open to people outside NA-MIC, subject to availability.
* You '''do''' need to be actively working on a NA-MIC related project in order to make this investment worthwhile for everyone.
* Participation in this event is voluntary -- if you don't think this will help you move forward in your work, there is no obligation to attend.
* Ideal candidates are those who want to contribute to the NA-MIC Kit, and those who can help make it happen.
* This is not an introduction to the components of the NA-MIC Kit.
* Submit any projects that you would like to work on during this week, and what type of help you might need for it.

=== Preparation for the workshop ===

# Please make sure that you are on the [http://public.kitware.com/cgi-bin/mailman/listinfo/na-mic-programming-week na-mic-programming-week mailing list]
# [[Engineering:TCON_12_07_2006|December 7: Kickoff TCON]]
# December 14: Create a Wiki page per project (the participants must do this, hopefully jointly)
# [[Engineering:TCON_12_14_2006|December 14: TCON#2 to discuss projects and verify teams]]
# December: Create a directory for each project on the [[Engineering:SandBox|NAMIC Sandbox]] (Andy)
## Commit on each sandbox directory the code examples/snippets that represent our first guesses of appropriate methods. (Luis and Steve will help with this, as needed)
## Gather test images in any of the Data sharing resources we have (e.g. the BIRN). These ones don't have to be many. At least three different cases, so we can get an idea of the modality-specific characteristics of these images. Put the IDs of these data sets on the wiki page. (the participants must do this.)
## Setup nightly tests on a separate Dashboard, where we will run the methods that we are experimenting with. The test should post result images and computation time. (Andy)
# [[Engineering:TCON_2007#2007-Jan-04|January 4, 2007: TCON#3 last preparation tcon]]
# By January 9th: Complete the top half of [[Media:2007_Project_Half_Week_Template.ppt|this powerpoint template]] for each project. Upload and link to the right place.
# Please note that by the time we get to the project event, we should be trying to close off a project milestone rather than starting to work on one...

== A History in Wiki Links ==

A history of all the programming/project events in NA-MIC is available by following [[Engineering:Programming_Events|this link]].

File:2007 Project Half Week PoistatsImageFormatDartmouth.ppt

2007-01-03T17:43:41Z

Dsjen:

File:2007 Project Half Week PoistatsSlicerItkIntegration.ppt

2007-01-03T17:33:57Z

Dsjen:

2007 Project Half Week

2007-01-03T17:20:00Z

Dsjen:

Back to [[AHM_2007|AHM_2007]]

== Results ==
Results of this event will be summarized here after it is completed.

==Please note==
* Everyone should '''bring a laptop'''. We will have three or four projectors.
* About half the time will be spent working on projects and the other half in project related discussions.

== Projects ==
This is the list of projects discussed in the preparation tcons on [[Engineering:TCON_12_07_2006|December 7]] and [[Engineering:TCON_12_14_2006|December 14, 2006]]. Each project lead (first name in the list) needs to complete a [[Media:2007_Project_Half_Week_Template.ppt|new 4-block PPT]], and upload and link it to this page.

===Structural Analysis===
# [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]] (Delphine Nain - GT, Yi Gao - GT, Jim Miller - GE, Luis Ibanez - Kitware): [[Media:2006_Project_Week_MIT_SphericalWaveletInITK.ppt| 4-block PPT Summer 2006]],[[Media:2007_Project_Half_Week_SphericalWaveletInITK.ppt| 4-block PPT Jan 2007]]
#scripts to run UNC shape analysis (delphine, Martin)
#EMSegmenter Software Development(Kilian, Brad)
#SVM Shape Analysis (Brad, Polina, Martin)
#EMSegmenter for UNM use (Kilian, ?)
#[[Non_Rigid_Registration|Parallelization of ITK for deformable registration (Stephen, Jim, Ross)]]
## Driving problem: Congealing with B-spline (Lilla, Stephen)
## Driving problem: ? (Kilian, Stephen)
# Integrating KWMeshVisu into Slicer (Ipek, Martin, Sebastien), [[Media:2006_AHM_Programming_Half_week_MeshVisu.ppt|4-block PPT Jan 2006]], [[Media:2007_AHM_Programming_Half_week_MeshVisu.ppt |4-block PPT Jan 2007 ]]
#Group-wise Registration of Medical Images(Serdar, Polina, Mert, Sandy ), [[Media:2007_Project_Half_Week_GroupWiseRegistration.ppt| 4-block PPT Jan 2007]]

===Diffusion Image Analysis===
#Finsler Tractography (John Melonakos - GT, Luis Ibanez - Kitware): [[Media:2007_Project_Half_Week_FinslerTractography.ppt| 4-block PPT Jan 2007]]
#Finsler Levelsets (Vandana Mohan - GT, John Melonakos - GT, Luis Ibanez - Kitware): [[Media:2007_Project_Half_Week_FinslerLevelsets.ppt| 4-block PPT Jan 2007]]
#Rician Noise Remvoal in Diffusion Tensor MRI (McKay Davis - Utah, Tom Fletcher - Utah): [[Media:2007_Project_Half_Week_RicianNoiseDTI.ppt | 4-block PPT Jan 2007]]

===fMRI Analysis===
#ITK implementation of POIStat, and Integration into Slicer3 (Dennis, Steve), [[Media:2007_Project_Half_Week_PoistatsSlicerItkIntegration.ppt| 4-block PPT Jan 2007]]
#Image Format issues in application of POIStats to Dartmouth data (Dennis, Steve, Luis, John West, Andy Saykin), [[Media:2007_Project_Half_Week_PoistatsImageFormatDartmouth.ppt| 4-block PPT Jan 2007]]
===NA-MIC Kit===
#[[Slicer3:Grid_Interface|Grid Execution]] (Neil, Bill, Jim) [[2007_Project_Half_Week_GridExecution.ppt]]
#Tractography in Slicer3 (Lauren, Raul)
#Model Hierarchies (Alex, Lauren, Kilian, Brad, Ron) -- generalize concepts from DTI and EM group nodes to support atlas hierachies like in slicer2.

===External Collaborations===
#Converting ITK Pipeline for Archip's, HPC based, deformable registration to Slicer3 Module (Daniel Goldberg, Stephen)
#Developing IGT workflow for Slicer3 (Simon DiMaio, Haiying Liu, Noby Hata, Stephen Aylward) [[IGT|IGT Project page in NA-MIC wiki]]
#Radiology Workstation Module for Slicer3 (Pat, Steve)
#vmtk module for Slicer(Luca Antiga, Jim Miller)
#Hexahedral Voxel Meshing Slicer Module (Nicole Grosland, Vincent Magnotta, Steve Pieper)

----
This following is a list of projects carried out at the last project week (summer 2006). For new attendees, these projects can be used as templates. For attendees involved in the last project week, please move projects from the list below to the list above if you intend to continue these projects. And please do add a [[Media:2007_Project_Half_Week_Template.ppt|new 4-block PPT for 2007]].

=== 2006 Structural Analysis ===

# [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]] (Xavier Le Faucheur, GT, Delphine Nain, GT, John Melonakos GT/GE, Jim Miller GE, Luis Ibanez, Kitware): [[Media:2006_Project_Week_MIT_SphericalWaveletInITK.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/ShapeStatisticsWithPermTestCorrectionAndFDR|ITK statistical analysis using non-parametric permutation analysis and false discovery rate]] (Martin Styner, UNC): [[Media:2006_06_PW_StatAnal.ppt| 4 block PPT 2006 ]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/Correspondence|Local curvature based correspondence in ITK]] (Ipek Oguz, Martin Styner, UNC): [[Media:2006_MIT_Project_Week_LocalCurvatureBasedCorrespondence.ppt| 4 block PPT 2006]]
# [[NA-MIC/Projects/Structural/Shape_Analysis/FemaleSPDCaudates|Shape analysis of female SPD dataset]] (Jim Levitt, PNL, Marc Niethammer, PNL, Sylvain Bouix, PNL, Martin Styner, UNC): [[Media:2006_06_PW_female_SPD.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Structural/Mesh/Mesh_Untangling|Mesh Untangling]] (Gheorghe Postelnicu, MGH, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_Mesh_Untangling.ppt|4 block PPT 2006]]
# [[NA-MIC/Projects/Structural/Registration/Histology_MR_Registration|MR Histology Registration]] (Gheorghe Postelnicu MGH, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_MGH_Histology_MR_Registration.ppt|4 block PPT 2006]]

=== 2006 Diffusion Image Analysis ===

# [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|ITK DTI Image Processing Modules]] (Casey Goodlett UNC, Tom Fletcher Utah, Bill Lorensen GE, John Melonakos GT/GE): [[Media:2006_Summer_Project_Week_DTI_Processing.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fiber_Tools_Slicer_Integration|Fiber Tools / Slicer 3 Integration]] (Casey Goodlett UNC, Bill Lorensen GE): [[Media:2006_Summer_Project_Week_FiberTracking_Slicer_Integration.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Stochastic_Fiber_Tracing_Applications|Stochastic Fiber Tracing Applications]] (C-F Westin, Marek Kubicki, Raul San-Jose, AW de Vries, All LMI):[[Media:2006_Summer_Project_Week_stochastictracking.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/Diffusion_Image_Analysis/Slicer_Fiber_Anatomical_Labeling|Slicer Fiber (Model) Labeling Interface]] (Lauren O'Donnell MIT, Marek Kubicki BWH) :[[Media:2006_Summer_Project_Week_ModelLabel.ppt| 4-block PPT 2006]]

=== 2006 FMRI Image Analysis ===

# [[NA-MIC/Projects/Structural/Conformal_Flattening_in_ITK|Conformal Flattening in ITK]](Yi Gao GT, John Melonakos GT/GE, Jim Miller GE, Luis Ibanez Kitware, Marc Niethammer BWH): [[Media:2006_Summer_Project_Week_ConformalFlattening.ppt| 4-block PPT 2006]]
# [[NA-MIC/Projects/fMRI_Analysis/Spatial_Regularization_for_fMRI_Detection|Spatial Regularization in fMRI Analysis]](Wanmei Ou, Polina Golland, Sandy Wells, and Carsten) [[Media:2006_Summer_Project_Week_fMRIMRF.ppt| 4-block PPT 2006]]

=== 2006 NA-MIC Kit ===

# [[2006_Project_Week_MIT_SlicerUI|Slicer3 Interface]] (Wendy Plesniak, Sebastien Barre, Steve Pieper, Mathieu Malaterre, Randy Gollub, Michael Halle), [[Media:2006_Summer_Project_Week_Slicer3UI.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_Migrating_Slicer2.x_Modules_to_Slicer3|Migrating Slicer2.x Modules to Slicer3]] (Nicole Aucoin, Mathieu Malaterre, Katie Hayes, Bill Lorensen): [[Media:2006_Summer_Project_Week_Migrating_Slicer2x_Modules_to_Slicer3.ppt|4-block PPT 2006]]
# [[2006_Project_Week_Kitware_Slicer3_Packaging|Slicer3 Packaging]] (Andy Cedilnik, Steve Pieper) [[Media:2006_Summer_Project_Week_Slicer3_Packaging.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_Grid_Integration|Slicer3 Grid Integration]] (Jeff Grethe, Brendan Faherty, Steve Pieper, Katie Hayes), [[Media:2006_Summer_Project_Week_Grid_Interface_for_Slicer3.ppt|4-block PPT 2006]]
# [[2006_Project_Week_MIT_LONIPipelineIntegration|Slicer3 Pipeline Integration ]] (Jagadeeswaran Rajendiran, Martin Styner, Steve Pieper), [[Media:2006_Summer_Project_Week_Jagadeeswaran_June30.ppt|4 block PPT 2006]]
# [[2006_Project_MGH_File_Format_Converter|2006 Project MGH File Format Converter]](Gheorghe Postelnicu, Bill Lorensen) [[Media:2006_Summer_Project_MIT_MGH_IO.ppt|4-block PPT 2006]]
# Volumetric Meshing (Kiran Shivanna, Vincent Magnotta, Nicole Grosland):[[Media:2006_Summer_Project_Week_Volumetric_Meshing.ppt|4-block PPT 2006]]
# Dicom Query/Retrieve (Eduardo Suárez, Rafael Nebot, Steve Pieper, Jim Miller):[[Media:2006_Summer_Project_Week_Slicer_Query_Retrieve.ppt|4-block PPT 2006]]
# A Translation Station for Imaging (Pat Mongkolwat, Alex Kogan, Tom Lechner, Steve Pieper, Wendy Plesniak):[[Media:2006_Project_Week_MIT_IntegrateSlicerWith_A_PACS_Workstation.ppt|4-block PPT 2006]]
# [[NA-MIC/Projects/Slicer3_for_IGT/Converting_vtkFMRIEngine_and_vtkMRAblation_to_Slicer3_modules|Converting vtkFMRIEngine and vtkMRAblation to Slicer3 modules]] (Noby Hata, Haiying Liu, Steve Pieper, Jim Miller): [[Media:2006_Summer_Project_Week_Slicer3_IGT.ppt| 4-block ppt 2006]]

=== 2006 NA-MIC Kit Support for Non-Medical Data ===

# ITK IO support for reading astronomy data and coordinates from FITS files (Douglas Alan IIC, Michael Halle BWH/IIC, Luis Ibanez Kitware)[[Media:2006_Summer_Project_Week_Astronomy_FITS_Reader_Prelim_Results.ppt| 4-block PPT 2006]]

== Logistics ==

'''Dates:''' January 10 & 12, 2007 (There will be no project-week related events scheduled for Thursday, January 11th, the day of the AHM.)

'''Registration Fee:''' Registration fee is $215 for this event, and includes registration for the NA-MIC AHM. Separate registration, either for the AHM, or the project event are not available. To register and reserve hotel rooms, please [[AHM_2007#Registration_and_Hotel_Logistics|follow this link]].

== Background and Preparation ==

We continue to call this event "Project Week" or "Project Half Week", depending on how its duration, rather than by its original name of "Programming Week". Along with programming, a fair amount of algorithm design, and clinical application brainstorming also takes places and the name change reflects the broader scope of the event. What does this means for participants: if you are participating in a NA-MIC project or collaboration by providing algorithmic or clinical input, you are very welcome to attend. As always, participation is entirely voluntary.

=== Goals ===

The main goal of this week is to move forward the deliverables of NA-MIC. All NA-MIC participants and their collaborators are welcome.

* Members of all cores are welcome. This event involves programming, algorithm design, and clinical application development/testing.
* The event is open to people outside NA-MIC, subject to availability.
* You '''do''' need to be actively working on a NA-MIC related project in order to make this investment worthwhile for everyone.
* Participation in this event is voluntary -- if you don't think this will help you move forward in your work, there is no obligation to attend.
* Ideal candidates are those who want to contribute to the NA-MIC Kit, and those who can help make it happen.
* This is not an introduction to the components of the NA-MIC Kit.
* Submit any projects that you would like to work on during this week, and what type of help you might need for it.

=== Preparation for the workshop ===

# Please make sure that you are on the [http://public.kitware.com/cgi-bin/mailman/listinfo/na-mic-programming-week na-mic-programming-week mailing list]
# [[Engineering:TCON_12_07_2006|December 7: Kickoff TCON]]
# December 14: Create a Wiki page per project (the participants must do this, hopefully jointly)
# [[Engineering:TCON_12_14_2006|December 14: TCON#2 to discuss projects and verify teams]]
# December: Create a directory for each project on the [[Engineering:SandBox|NAMIC Sandbox]] (Andy)
## Commit on each sandbox directory the code examples/snippets that represent our first guesses of appropriate methods. (Luis and Steve will help with this, as needed)
## Gather test images in any of the Data sharing resources we have (e.g. the BIRN). These ones don't have to be many. At least three different cases, so we can get an idea of the modality-specific characteristics of these images. Put the IDs of these data sets on the wiki page. (the participants must do this.)
## Setup nightly tests on a separate Dashboard, where we will run the methods that we are experimenting with. The test should post result images and computation time. (Andy)
# [[Engineering:TCON_2007#2007-Jan-04|January 4, 2007: TCON#3 last preparation tcon]]
# By January 9th: Complete the top half of [[Media:2007_Project_Half_Week_Template.ppt|this powerpoint template]] for each project. Upload and link to the right place.
# Please note that by the time we get to the project event, we should be trying to close off a project milestone rather than starting to work on one...

== A History in Wiki Links ==

A history of all the programming/project events in NA-MIC is available by following [[Engineering:Programming_Events|this link]].

People

2007-01-02T21:25:48Z

Dsjen:

== Personnel at least partially funded by NA-MIC ==

# Core 7: Leadership
## [[User:Kikinis|Ron Kikinis]], Harvard (BWH SPL) PI
## [[User:Wong|Stephen Wong]], Harvard (BWH) PI
# Core 1 (Algorithms)
## [[User:Lzollei|Lilla Zollei]], MIT
## [[Eric_Grimson|Eric Grimson]], MIT PI
## [[Polina_Golland|Polina Golland]], MIT
## Lauren O'Donnell, MIT
## Wanmei Ou, MIT
## [[Mahnaz_Maddah|Mahnaz Maddah]], MIT
## Guido Gerig, UNC PI
## [[User:Styner|Martin Styner]], UNC
## [[User:Gcasey|Casey Goodlett]], UNC
## Ipek Oguz, UNC
## Allen Tannenbaum, Georgia Tech PI
## Oleg Michailovich, Georgia Tech
## Ramsey Al-Hakim, Georgia Tech
## [[User:Melonakos|John Melonakos]], Georgia Tech
## [[User:Lankton|Shawn Lankton]], Georgia Tech
## [[User:Nain|Delphine Nain]], Georgia Tech
## Xavier Le Faucheur, Georgia Tech
## Tom Fletcher, Utah
## [[User:Whitaker]], Utah, Algorithms Core PI
## Tolga Tasdizen, Utah
## Saurav Basu, Utah
## Dave Kennedy, Harvard (MGH) PI
## Bruce Fischl, Harvard (MGH)
## [[User:DavidTuch|David Tuch]], Harvard (MGH)
## Josh Snyder, Harvard (MGH)
## [[User:dsjen|Dennis Jen]], Harvard (MGH)
# Core 2 (Engineering)
## [[User:Lorensen|Bill Lorensen]], Core PI
## [[User:Millerjv|Jim Miller]], GE PI
## [[User:Taox|Xiaodong Tao]], GE
## Dan Blezek, GE
## [[User:Will|Will Schroeder]], Kitware PI
## [[User:Ibanez|Luis Ibanez]],Kitware
## [[User:Mathieu|Mathieu Malaterre]],Kitware
## [[User:Barre|Sebastien Barre]],Kitware
## [[User:Karthik|Karthik Krishnan]],Kitware
## Andy Cedilnik, Kitware
## [[User:Pieper|Steve Pieper]], Isomics PI
## Alex Yarmakovich, Isomics
## Art Toga, UCLA PI
## [[User:Dinov|Dinov]], UCLA
## [[User:MichaelPan|Michael Pan]], UCLA
## [[User:Jags|Jagadeeswaran Rajendiran]], UCLA
## Mark Ellisman, UCSD PI
## Jeff Grethe, UCSD
## Brendan Flaherty, UCSD
# Core 3: DBP
## [[User:Adamc|Adam Cohen]] Harvard (BWH PNL)
## [[User:Markd|Mark Dreusicke]] Harvard (BWH PNL)
## Martha Shenton, Harvard (BWH PNL) PI
## Sylvain Bouix, Harvard (BWH PNL)
## Marc Neithammer, Harvard (BWH PNL)
## Andy Saykin, Dartmouth PI
## Bob Roth, Dartmouth
## Laura Flashman, Dartmouth
## Thomas McAllister, Dartmouth
## Alan Green, Dartmouth
## John West, Dartmouth
## Tara McHugh, Dartmouth
## Heather Pixley, Dartmouth
## Stephen Guerin, Dartmouth
## John MacDonald, Dartmouth
## Steve Potkin, UCI PI
## [[User:Jfallon|James Fallon]], UCI
## Jessica Turner, UCI
## Martina Panzenboeck, UCI
## David Medina, UCI
## Padhraic Smyth, UCI
## Hal Stern, UCI
## Diane Highum, UCI
## Yi Jin, UCI
## Liv Trondsen, UCI
## Fabio Macciardi, Toronto
## Jim Kennedy, Toronto
## Aristotle Voineskos, Toronto
# Core 4: Service
## [[User:Andy|Andy Cedilnik]], Kitware
## [[User:Will|Will Schroeder]], Kitware PI
# Core 5: Training
## [[User:Randy|Randy Gollub]], Harvard (MGH), PI
## Guido Gerig, UNC
## [[User:Whitaker]], Utah
## Martha Shenton, Harvard (BWH PNL) PI
## Sonia Pujol, Harvard (BWH SPL)
# Core 6: Dissemination
## [[User:Tkapur|Tina Kapur]], Epiphany Medical, co-PI
## [[User:Pieper|Steve Pieper]], Isomics, co-PI

 

== NA-MIC alumni ==

== "Friends and Family" ==

=== NIH ===

* [[User:Lysterp|Peter M. Lyster]]

=== mBIRN ===

* [[User:Akolasny|Anthony Kolasny]]
* [[User:Dmarcus|Dan Marcus]]
* [[User:Kikinis|Ron Kikinis]]

=== fBIRN ===

* [[User:Kikinis|Ron Kikinis]]

=== IGT ===

* [[User:Ibanez|Luis Ibanez]]

=== other ===