NAMIC Wiki - User contributions [en]

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T15:18:39Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:CTUSDiagram.png|Sequence diagram
Image:CTUSModule.png|Module interface
Image:CTUSTools.png|Slicer plug-ins
Image:CTUSReg.png|Registered phantom(L3)
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Entire procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
** loading complete ultrasound volume of the lumbar phantom
** cropping ultrasound volume using "Crop Volume" module
** Segmentation of the cropped CT volume using "Editor" module
** Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation conflicts
* Improving animated visualization of the transform evolution on each iteration
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T14:05:52Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:CTUSDiagram.png|Sequence diagram
Image:CTUSModule.png|Module interface
Image:CTUSTools.png|Slicer plug-ins
Image:CTUSReg.png|Registered phantom(L3)
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

File:CTUSDiagram.png

2012-06-22T14:05:28Z

Samann:

File:CTUSReg.png

2012-06-22T13:58:41Z

Samann:

File:CTUSModule.png

2012-06-22T13:58:18Z

Samann:

File:CTUSTools.png

2012-06-22T13:57:56Z

Samann:

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T13:57:03Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:CTUSDiagram.jpg|Sequence diagram
Image:CTUSModule.png|Module interface
Image:CTUSTools.png|Slicer plug-ins
Image:CTUSReg.png|Registered phantom(L3)
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T13:54:08Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]

Image:CTUSDiagram.jpg|Sequence Diagram
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T13:53:49Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]

Image:CTUSDiagram.png|Sequence Diagram
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T13:51:07Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
[[File:CTUSDiagram.jpg]]
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T13:49:42Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
[[File:CTUSDiagram.jpg]]
</gallery>
[[File:CTUSDiagram.jpg]]
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

File:PW-MIT2012.png

2012-06-22T13:49:06Z

Samann: Blanked the page

File:PW-MIT2012.png

2012-06-22T13:48:53Z

Samann:

[[File:CTUSDiagram.jpg]]

File:CTUSDiagram.jpg

2012-06-22T13:46:28Z

Samann: uploaded a new version of "File:CTUSDiagram.jpg"

File:CTUSDiagram.jpg

2012-06-22T12:51:22Z

Samann:

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:49:10Z

Samann:

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:48:09Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:43:24Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

[[File:Diagram.png]]
[[File:Diagram1.png]]
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:38:07Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

[[File:Diagram.png]]
==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:37:37Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">
[[File:Diagram.png]]
<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

File:Diagram.png

2012-06-22T12:36:07Z

Samann:

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T12:35:11Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University
[[File:c:\diagram.png]]
<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T05:05:05Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
<h3>Progress during project week</h3>
* MATLAB core is compiled and exported as shared libraries to be used in external projects.
* A wrapper project is added to the slicer solution to provide an interface with compiled MATALB dlls.
* Whole procedure for single vertebra registration is implemented using slicer interface and current plugin modules:
- loading complete ultrasound volume of the lumbar phantom
- cropping ultrasound volume using Crop Volume module
- Segmentation of the cropped CT volume using Editor module
- Passing model and volume nodes to "SpineCTUSRegistration" module and calling the registration commands
<h3>Works to do</h3>
* Still there is a need to initialize model and volume inputs regarding LPS/RAS orientation
* Improving animated visualization of the transform evolution on each iteration
* Cropping a larger area and reviewing the results
* Algorithm modification by using original MHA files instead of reconstructed VTK files
* Performing entire procedure for a real patient data.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-22T04:49:40Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory: Saman Nouranian, Samira Sojoudi
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week

2012-06-22T04:48:28Z

Samann:

Back to [[Events]]

[[image:PW-MIT2012.png|200px]]

*'''Dates:''' June 18-22, 2012
*'''Location:''' MIT

==Agenda==

{|border="1"
|-style="background:#b0d5e6;color:#02186f"
!style="width:10%" |Time
!style="width:18%" |Monday, June 18
!style="width:18%" |Tuesday, June 19
!style="width:18%" |Wednesday, June 20
!style="width:18%" |Thursday, June 21
!style="width:18%" |Friday, June 22
|-
|
|bgcolor="#dbdbdb"|'''Project Presentations'''
|bgcolor="#6494ec"|'''NA-MIC Update Day'''
|
|bgcolor="#88aaae"|'''IGT Day'''
|bgcolor="#faedb6"|'''Reporting Day'''
|-
|bgcolor="#ffffdd"|'''8:30am'''
|
|bgcolor="#ffffaa"|Breakfast
|bgcolor="#ffffaa"|Breakfast
|bgcolor="#ffffaa"|Breakfast
|bgcolor="#ffffaa"|Breakfast
|-
|bgcolor="#ffffdd"|'''9am-12pm'''
|
|'''9am-10am:''' [[2012 Project Week Breakout Session: Slicer4|What's new in Slicer4 (Charts - Jim, DICOM - Steve, Multivolume - Andrey)]] <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>----------------------------------------<br>
'''10-11am''' [[2012 Project Week Breakout Session:Slicer4 Python Q&A|Slicer4 Python Q&A]] <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
|'''9am-11pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Project Week Breakout Session: SimpleITK|Slicer and SimpleITK]] (Hans)
[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva Room]]
<br>----------------------------------------<br>
'''10am-12pm: <font color="#4020ff">Computation Core PIs: closed meeting with Ron:'''</font><br>
[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''9am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:Slicer in Networked Environment|Slicer in Networked Environment]] (Junichi)
[[MIT_Project_Week_Rooms#Kiva_32-G449|Grier Room]]
|'''10am-12pm:''' [[#Projects|Project Progress Updates]]
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
|-
|bgcolor="#ffffdd"|'''12pm-1pm'''
|bgcolor="#ffffaa"|Lunch
|bgcolor="#ffffaa"|Lunch
|bgcolor="#ffffaa"|Lunch
|bgcolor="#ffffaa"|Lunch
|bgcolor="#ffffaa"|Lunch boxes; Adjourn by 1:30pm
|-
|bgcolor="#ffffdd"|'''1pm-5:30pm'''
|'''1-1:05pm: <font color="#503020">Ron Kikinis: Welcome</font>'''
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''1:05-3:30pm:''' [[#Projects|Project Introductions]] (all Project Leads)
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''3:30-4:30pm''' [[2012 Summer Project Week Breakout Session:SlicerExtensions|Slicer4 Extensions]] (JC) <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Left)]]
|'''3-4pm:''' [[2012_Tutorial_Contest|Tutorial Contest Presentations]]
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''4-5pm:''' [[2012 Summer Project Week Breakout Session:Slicer DICOM|Breakout Session: DICOM, Networking, RT, Segmentations]] (Steve, Greg, Andras, Andre)
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
|'''12:45-1pm:''' [[Events:TutorialContestJune2012|Tutorial Contest Winner Announcement]]
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''3-30pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:QtTesting|QtTesting]] (JC)
|'''1-3pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:Ultrasound|Ultrasound]] (Tamas)
[[MIT_Project_Week_Rooms#Kiva_32-G449|Grier Room]]
<br>----------------------------------------<br>
'''3:00-4:00pm''' [[2012_Summer_Project_Week:LeanSlicer|Lean Slicer (Andras)]]<br>
[[MIT_Project_Week_Rooms#Kiva_32-G449|Grier Room]]
|
|-
|bgcolor="#ffffdd"|'''5:30pm'''
|bgcolor="#f0e68b"|Adjourn for the day
|bgcolor="#f0e68b"|Adjourn for the day
|bgcolor="#f0e68b"|Adjourn for the day
|bgcolor="#f0e68b"|Adjourn for the day
|
|}

==Projects==

Please use [http://wiki.na-mic.org/Wiki/index.php/Project_Week/Template THIS TEMPLATE] to create project pages for this event.

==='''Neurosurgery, Brain and Spine, Traumatic Brain Injury'''===

# [[Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury]] (Andrei Irimia, Micah Chambers, Bo Wang, Marcel Prastawa, Danielle Pace, Stephen Aylward, Jack van Horn, Guido Gerig)
# [[2012_Summer_Project_Week:4D_Segmentation_TBI|4D Segmentation of longitudinal MRI of TBI patients]] (Bo Wang, Marcel Prastawa, Andrei Irimia, Micah Chambers, Jack van Horn, Guido Gerig)
# [[2012_Summer_Project_Week:Intraoperative_Tract_Detection | Intraoperative White Matter Tract Detection Module]] (Lauren O'Donnell, Isaiah Norton)
# [[2012_Summer_Project_Week:Ultrasound_Aberration_Correction | An Ultrasound-based Method for Aberration Correction in TCFUS]] (Jason White, Greg Clement)
# [[2012_Summer_Project_Week:Early_Dementia_Diagnostic |Early Dementia Diagnostic Tools]] (Marcel Koek, Sonia Pujol)
# [[2012_Summer_Project_Week:Radnostics |Spine Segmentation & Osteoporosis Detection In CT Imaging Studies]] (Anthony Blumfield, Ron Kikinis)

==='''Radiation Therapy'''===
#[[2012_Summer_Project_Week:Atlas_based_segmentation_for_head_and_neck| Atlas-based segmentation for head and neck]] (Amelia Arbisser, Nadya Shusharina, James Shackleford, Greg Sharp, Polina Golland)
#[[2012_Summer_Project_Week:Overlapping_structures| First class structure set support in Slicer]] (Greg Sharp, James Shackleford, Steve Pieper)
#[[2012_Summer_Project_Week:PlastimatchIntegration| Plastimatch loadable module]] (James Shackleford, Greg Sharp)
#[[2012_Summer_Project_Week:Deformable_Registration_for_Head_and_Neck| Deformable Registration for Head and Neck ]] (Ivan Kolesov, Greg Sharp, Yi Gao, Allen Tannenbaum)
#[[2012_Summer_Project_Week:SlicerRT| Radiotherapy extensions for Slicer 4]] (Andras Lasso, Csaba Pinter, Kevin Wang)
#[[2012_Summer_Project_Week:PET_Image_Analysis | SUV Threshold Computation]] (Nadya Shusharina, Greg Sharp)

==='''Huntington's Disease'''===
# [[2012_Summer_Project_Week:Nipype Integration|Slicer/Nipype Integration]] (Hans Johnson)
# [[2012_Summer_Project_Week:DicomToNrrd|DicomToNrrdConverter Integration]] (Kent Williams, Hans Johnson)
# [[2012_Summer_Project_Week:4D shape analysis|4D Shape Analysis: Software Tools]] (James Fishbaugh, Marcel Prastawa, Guido Gerig)
# [[2012_Summer_Project_Week:DTI-Reg|DTI atlas based fiber analysis]] (Francois Budin)

==='''Atrial Fibrillation'''===
# [[2012_Summer_Project_Week:UtahCardiacRegistration|Cardiac MRI Registration Module]] (Greg Gardner, Alan Morris, Danny Perry, Josh Cates, Rob MacLeod)
# [[2012_Summer_Project_Week:UtahAutoScar|Automatic Left Atrial Scar Detection]] (Greg Gardner, Danny Perry, Alan Morris, Josh Cates, Rob MacLeod)
# [[2012_Summer_Project_Week:UtahInhomogeneity|MRI Inhomogeneity Correction Filter]] (Greg Gardner, Alan Morris, Eugene Kholmovski, Josh Cates, Danny Perry, Rob MacLeod)
# [[2012_Summer_Project_Week:VecReg|Vector-Valued Cardiac MRI Registration]] (Yi Gao, Josh Cates, Liang-Jia Zhu, Alan Morris, Danny Perry, Greg Gardner, Rob MacLeod, Sylvain Bouix, Allen Tannenbaum)
# [[2012_Summer_Project_Week:RidgeExtractionAtrialWallSegmentation|Perceptual Ridge Extraction for Atrial Wall Segmentation in MRI]] (Arie Nakhmani, Allen Tannenbaum)

==='''Device Integration with Slicer and Image Guided Therapy'''===
# [[2012_Summer_Project_Week:SlicerWeb|Web Interface to Slicer 4]] (Steve Pieper)
# [[2012_Summer_Project_Week:OpenIGTLinkIF|Improvement of OpenIGTLink IF for Slicer 4]] (Junichi Tokuda, Laurent Chauvin)
# [[2012_Summer_Project_Week:LeanSlicer|Lean Slicer to facilitate regulatory approval]] (Andras Lasso, Chris Wedlake)
# [[2012_Summer_Project_Week:LiveUltrasound|Live Ultrasound]] (Tamas Ungi, Andinet Enquobahrie, Junichi Tokuda)
# [[2012_Summer_Project_Week:BK-PLUS_Integration|Integration of BK ProFocus US with Slicer via PLUS library]] (Andras Lasso, Andrey Fedorov, Isaiah Norton, Saman)
# [[2012_Summer_Project_Week:TransformRecorder|Transform Recorder and other IGT modules]] (Simrin Nagpal, Tamas Ungi)
# [[2012_Summer_Project_Week:Open_source_electromagnetic_trackers_using OpenIGTLink|Open-source electromagnetic trackers using OpenIGTLink]] (Peter Traneus Anderson, Tina Kapur, Sonia Pujol)
# [[2012_Summer_Project_Week:iGyne|iGyne for Gynecological Cancer Brachytherapy]] (Xiaojun Chen, Jan Egger, Tina Kapur, Steve Pieper)
#[[2012_Summer_Project_Week:Interactive_Needle_Segmentation|Interactive Needle Segmentation for Gynecological Cancer Brachytherapy]] (Nabgha Farhat, Neha Agrawal, Jan Egger, Tina Kapur, Steve Pieper)
# [[2012_Summer_Project_Week:VertebraCTUSReg|Single Vertebra CT-US Registration]] (Saman Nouranian, Samira Sojoudi, Simrin Nagpal, Tamas Ungi, David Welch)
# [[2012_Summer_Project_Week:Fast Fiducial Registration|Fast Fiducial Registration Module]] (David Welch, Hans Johnson, Nicole Aucoin, Ron Kikinis)
# [[2012_Summer_Project_Week:SteeredRegistration|Steered Registration for Image Guided Therapy]] (Guillaume Pernelle BWH, Jan Egger, Tina Kapur, Steve Pieper, Jim Miller, Kunlin Cao)
# [[2012_Summer_Project_Week:4D_Ultrasound_Slicer4|4D Ultrasound on Slicer4]] (Laurent Chauvin, Nobuhiko Hata)
# [[2012_Summer_Project_Week:Kinect4Slicer|Kinect4Slicer]] (Laurent Chauvin, Nobuhiko Hata)
# [[2012_Summer_Project_Week:Needle Tip Tracking |Needle Tip Tracking for complex MR images]] (Atsushi Yamada, Nobuhiko Hata)

==='''General Segmentation'''===
#[[2012_Summer_Project_Week:SemiAutomatedAirwaySegmentationfrom0.64mmLungCTDatasets|Semi-automated airway segmentation from 0.64mm lung CT datasets]] (Pietro Nardelli, Padraig Cantillon-Murphy, Raul San Jose Estepar)
#[[Loading and segmentation of histopathology imaging for radiological-pathological correlation]] (Tobias Penzkofer, Andrey Fedorov)
#[[2012_Summer_Project_Week:ABC_Slicer4|Porting ABC extension to Slicer 4]] (Marcel Prastawa, Bo Wang, Guido Gerig)
# [[2012_Summer_Project_Week:QuantitativePETImageAnalysisModule|Quantitative PET Image Analysis Module]] (Markus Van Tol)
#[[2012_Summer_Project_Week:SegmentationWithLabelFusion|Segmentation with Label Fusion]] (Ramesh Sridharan, Christian Wachinger, Polina Golland)

==='''General Registration'''===
# [[2012_Summer_Project_Week:NiftyReg|NiftyReg integration]] (Marc Modat, Sonia Pujol)
#[[2012_Summer_Project_Week:ElastixIntegration|Elastix integration]] (Stefan Klein, Sonia Pujol)
# [[2012_Summer_Project_Week:DTIRegistration| Highly Deformable DTI Registration for cases with large pathological variations]] (Aditya Gupta, Martin Styner, Matthew Toews)
# [[2012_Summer_Project_Week:DifficultRegistration| Registration of Difficult Images]] (Matthew Toews, Stefan Klein, Marc Modat, Aditya Gupta, Martin Styner, Petter Risholm, Dominik Meier, William Wells)

==='''Informatics'''===
# [[2012_Summer_Project_Week:AIM_for_QIN|Applicability of AIM to QIN use cases]] (Andrey Fedorov, Reinhard Beichel, Jayashree Kalpathy-Cramer, Pat Mongkolwat, Daniel Rubin)
# [[2012_Summer_Project_Week:Reporting|Reporting module]] (Andrey, Nicole, Steve, Ron, Pat)
# [[2012_Summer_Project_Week:CMake_for_AIM_API|CMake-fying AIM API]] (Pat Mongklowat, Vlad Kleper, Andrey Fedorov)

==='''Infrastructure'''===

# [[2012_Summer_Project_Week:SelfTesting|Built-In Self-Testing (BIST) for Slicer]] (Steve, Julien, Jc, Sonia)
# [[2012_Summer_Project_Week:AnnotationModule|Annotation module redesign for Slicer]] (Nicole)
# [[2012_Summer_Project_Week:MultiVolumeSupport|Multivolume support]] (Andrey, Jim, Brendan Moloney)
# [[2012_Summer_Project_Week:PythonCLIandWidget|Python CLI modules (Demian, JC, Julien, Steve)]].
# [[2012_Summer_Project_Week:Charting|Charting]] (Jim)
# [[2012_Summer_Project_Week:GPUEditor|GPU Editor Effects]] (Steve, Jim)
# [[2012_Summer_Project_Week:XTK|XTK/WebGL Exporter]] (Daniel, Nicolas - Boston Children's Hospital)
# [[2012_Summer_Project_Week:EventOptimization|Callback/Events/Observation best practice + Performance bottleneck discussion (Julien, Steve,...)]]
# [[2012_Summer_Project_Week:XNATSlicerIntegration|XNAT/Slicer Integration]] (Sunil, Dan, Steve,...)
# [[2012_Summer_Project_Week:ITKv4 Integration|ITKv4 Integration]] (Hans Johnson, Julien Finet, Jim). See [http://www.na-mic.org/Bug/view.php?id=2007 #2007]
# [[2012_Summer_Project_Week:SimpleITK Integration|SimpleITK Integration]] (Hans Johnson, Bradley Lowekamp)
# [[2012_Summer_Project_Week:Threat Modeling|Threat Modeling]] (JC, J2, Anthony, Steve)
# [[2012_Summer_Project_Week:CUDA Volume Rendering Extension|CUDA Volume Rendering as Extension]] (J2, Elvis)

==Background==

We are pleased to announce the 15th PROJECT WEEK of hands-on research and development activity for applications in Neuroscience, Image-Guided Therapy and several additional areas of biomedical research that enable personalized medicine. Participants will engage in open source programming using the [[NA-MIC-Kit|NA-MIC Kit]], algorithm design, medical imaging sequence development, tracking experiments, and clinical application. The main goal of this event is to move forward the translational research deliverables of the sponsoring centers and their collaborators. Active and potential collaborators are encouraged and welcome to attend this event. This event will be set up to maximize informal interaction between participants. If you would like to learn more about this event, please [http://public.kitware.com/cgi-bin/mailman/listinfo/na-mic-project-week click here to join our mailing list].

Active preparation begins on Thursday, April 26th at 3pm ET, with a kick-off teleconference. Invitations to this call will be sent to members of the sponsoring communities, their collaborators, past attendees of the event, as well as any parties who have expressed an interest in working with these centers. The main goal of the kick-off call is to get an idea of which groups/projects will be active at the upcoming event, and to ensure that there is sufficient coverage for all. Subsequent teleconferences will allow for more focused discussions on individual projects and allow the hosts to finalize the project teams, consolidate any common components, and identify topics that should be discussed in breakout sessions. In the final days leading upto the meeting, all project teams will be asked to fill in a template page on this wiki that describes the objectives and plan of their projects.

The event itself will start off with a short presentation by each project team, driven using their previously created description, and will help all participants get acquainted with others who are doing similar work. In the rest of the week, about half the time will be spent in breakout discussions on topics of common interest of subsets of the attendees, and the other half will be spent in project teams, doing hands-on project work. The hands-on activities will be done in 40-50 small teams of size 2-4, each with a mix of multi-disciplinary expertise. To facilitate this work, a large room at MIT will be setup with several tables, with internet and power access, and each computer software development based team will gather on a table with their individual laptops, connect to the internet to download their software and data, and be able to work on their projects. Teams working on projects that require the use of medical devices will proceed to Brigham and Women's Hospital and carry out their experiments there. On the last day of the event, a closing presentation session will be held in which each project team will present a summary of what they accomplished during the week.

This event is part of the translational research efforts of [http://www.na-mic.org NA-MIC], [http://www.ncigt.org NCIGT], [http://nac.spl.harvard.edu/ NAC], [http://catalyst.harvard.edu/home.html Harvard Catalyst], [http://www.cimit.org CIMIT], and OCAIRO. It is an expansion of the NA-MIC Summer Project Week that has been held annually since 2005. It will be held every summer at MIT and Brigham and Womens Hospital in Boston, typically during the last full week of June, and in Salt Lake City in the winter, typically during the second week of January.

A summary of all past NA-MIC Project Events is available [[Project_Events#Past|here]].

== Logistics ==
*'''Dates:''' June 18-22, 2012.
*'''Location:''' MIT. [[Meeting_Locations:MIT_Grier_A_%26B|Grier Rooms A & B: 34-401A & 34-401B]].
*'''REGISTRATION:''' Please click [https://www.regonline.com/namic2012summerprojweek HERE] to do an on-line registration for the meeting that will allow you to pay by credit card. No checks will be accepted.
*'''Registration Fee:''' $300 (covers the cost of breakfast, lunch and coffee breaks for the week).
*'''Hotel:''' No room blocks have been reserved in any area hotel. Please select a [http://web.mit.edu/institute-events/visitor/stay.html hotel of your choice] and make reservations as early as possible. Some area hotels are:
**marriott cambridge center
**marriott residence inn kendall square
**le meridien central square
**hotel marlowe cambridge
**royal sonesta hotel cambridge

== Preparation ==
# Please make sure that you are on the http://public.kitware.com/cgi-bin/mailman/listinfo/na-mic-project-week mailing list
# The NA-MIC engineering team will be discussing infrastructure projects in a kickoff TCON on April 26, 3pm ET. In the weeks following, new and old participants from the above mailing list will be invited to join to discuss their projects, so please make sure you are on it!
# By 3pm ET on Thursday May 10, all participants to add a one line title of their project to #Projects
# By 3pm ET on Thursday June 7, all project leads to complete [[Project_Week/Template|Complete a templated wiki page for your project]]. Please do not edit the template page itself, but create a new page for your project and cut-and-paste the text from this template page. If you have questions, please send an email to tkapur at bwh.harvard.edu.
# By 3pm on June 14: Create a directory for each project on the [[Engineering:SandBox|NAMIC Sandbox]] (Matt)
## 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. XNAT/MIDAS). 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.)
## Where possible, 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. (Matt)
# 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...
# People doing Slicer related projects should come to project week with slicer built on your laptop.
## See the [http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/Developers Developer Section of slicer.org] for information.
## Projects to develop extension modules should be built against the latest Slicer4 trunk.

==Registrants==

Do not add your name to this list- it is maintained by the organizers based on your paid registration. ([http://www.regonline.com/Register/Checkin.aspx?EventID=1089602 Please click here to register.])

#Anderson, Peter, retired, traneus@verizon.net
#Arbisser, Amelia, MIT, arbisser@mit.edu
#Aucoin, Nicole, BWH, Nicole@bwh.harvard.edu
#Aylward, Stephen, Kitware, stephen.aylward@kitware.com
#Blevins, Scott, BWH, stblevins@gmail.com
#Blumfield, Anthony, Radnostics, Anthony.Blumfield@Radnostics.com
#Budin, Francis, NIRAL-UNC, fbudin@unc.edu
#Cao, Kunlin, GE Research, cao@ge.com
#Chambers, Micah, UCLA, micahcc@ucla.edu
#Chauvin, Laurent, SPL, lchauvin@bwh.harvard.edu
#Chen, Elvis, Robarts, chene@robarts.ca
#Chen, Xiaojun, SPL, xiaojun@bwh.harvard.edu
#Datar, Manasi, Utah SCI, datar@sci.utah.edu
#Diedrich, Karl, AZE R&D, karl.diedrich@azeresearch.com
#Egger, Jan, BWH, egger@bwh.harvard.edu
#Farhat, Nabgha, SPL, nfarhat@bwh.harvard.edu
#Fedorov, Andriy, BWH, fedorov@bwh.harvard.edu
#Fillion-Robin, Jean-Christophe, Kitware, jchris.fillionr@kitware.com
#Finet, Julien, Kitware, julien.finet@kitware.com
#Fishbaugh, James, SCI, jfishbau@sci.utah.edu
#Gao, Yi, BWH, gaoyi@bwh.harvard.edu
#Gardner, Greg, SCI, ggardner@sci.utah.edu
#Golland, Polina, MIT CSAIL, polina@csail.mit.edu
#Gouaillard, Alexandre, A*STAR, agouaillard@gmail.com
#Gupta, Aditya, NIRAL UNC, aditya_gupta@med.unc.edu
#Irimia, Andrei, UCLA, andrei.irimia@loni.ucla.edu
#Jagadeesan, Jayender, SPL, jayender@bwh.harvard.edu
#Johnson, Hans, Univ Iowa, hans-johnson@uiowa.edu
#Kalpathy-Cramer, Jayashree, MGH, kalpathy@nmr.mgh.harvard.edu
#Kapur, Tina, BWH HMS, tkapur@bwh.harvard.edu
#Kikinis, Ron, HMS, kikinis@bwh.harvard.edu
#Klein, Stefan, (cancelled registration) Erasmus MC, s.klein@erasmusmc.nl
#Kleper, Vladimir, Northwestern Univ, vkleper@northwestern.edu
#Koek, Marcel, Erasmus MC, m.koek@erasmusmc.nl
#Kolesov, Ivan, GA Tech, ivan.kolesov@gatech.edu
#Kumar, Sunil, Washington Univ St Louis, kumars@mir.wustl.edu
#Lasso, Andras, Queen's Univ, lasso@cs.queensu.ca
#Lowekamp, Bradley, NLM/NIH, bradley.lowekamp@nih.gov
#Macule, Raul, AZE R&D, raul.macule@azeresearch.com
#Mastrogiacomo, Katie, SPL, BWH, kmast@bwh.harvard.edu
#Meier, Dominik, BWH, meier@bwh.harvard.edu
#Mercea, Paul, SPL, pmercea@bwh.harvard.edu
#Miller, Jim, GE Research, millerjv@ge.com
#Mizutani, Tatsushi, Nagoya Univ, tatsushi0207@me.com
#Modat, Marc, Univ College London, m.modat@ucl.ac.uk
#Moloney, Brendan, AIRC, moloney.brendan@gmail.com
#Mongkolwat, Pattanasak, Northwestern U, p-mongkolwat@northwestern.edu
#Montillo, Albert, GE Research, montillo@ge.com
#Nagpal, Simrin, Queen’s Univ, 7sn6@cs.queensu.ca
#Nakhmani, Arie, BU, nakhmani@gmail.com
#Nardelli, Pietro, Univ College Cork, pie.nardelli@gmal.com
#Norton, Isaiah, BWH, inorton@partners.org
#Nouranian, Saman, Univ BC, samann@ece.ubc.ca
#O'Donnell, Lauren, BWH, odonnell@bwh.harvard.edu
#Oyama, Rie, BWH, royama@bwh.harvard.edu
#Paniagua, Beatriz, Univ NC Chapel Hill, bpaniagua@gmail.com
#Penzkofer, Tobias, SPL, pt@bwh.harvard.edu
#Pernelle, Guillaume, BWH, gpernelle@gmail.com
#Pieper, Steve, Isomics, pieper@bwh.harvard.edu
#Pinter, Csaba, Queen's Univ, pinter@cs.queensu.ca
#Pujol, Sonia, BWH, spujol@bwh.harvard.edu
#Rannou, Nicolas, Childrens Hospital, nicolas.rannou@childrens.harvard.edu
#Razzaque, Sharif, InnerOptic Technology, sharif@inneroptic.com
#Risholm, Petter, Harvard, pettri@bwh.harvard.edu
#San Jose, Raul, BWH, rjosest@bwh.harvard.edu
#Schroeder, William, Kitware, will.schroeder@kitware.com
#Shackleford, James, MGH, jshackleford@partners.org
#Sharp, Greg, MGH, gcsharp@partners.org
#Shusharina, Nadya, MGH, nshusharina@partners.org
#Sojoudi, Samira, Univ BC, samiras@ece.ubc.ca
#Spindler, Wolf, Fraunhofer MEVIS, wolf.spindler@mevis.fraunhofer.de
#Sridharan, Ramesh, MIT CSAIL, rameshvs@MIT.EDU
#State, Andrei, InnerOptic Technology, andrei@inneroptic.com
#Tiwari, Pallavi, Rutgers, pallavi.tiwar@gmail.com
#Toews, Matthew, BWH HMS, mt@bwh.harvard.edu
#Tokuda, Junichi, BWH, tokuda@bwh.harvard.edu
#Ungi, Tamas, Queen's Univ, ungi@cs.queensu.ca
#Van Tol, Markus, Univ Iowa, mvantol@engineering.uiowa.edu
#Vosburgh, Kirby, BWH, kirby@bwh.harvard.edu
#Wang, Bo, SCI, bowang@sci.utah.edu
#Wang, Kevin, Princess Margaret Hospital, kevin.wang@rmp.uhn.on.ca
#Wedlake, Chris, Robarts, cwedlake@robarts.ca
#Welch, David, Univ Iowa, david-welch@uiowa.edu
#Wells, William, HMS BWH, sw@bwh.harvard.edu
#Whitaker, Ross, SCI, whitaker@cs.utah.edu
#White, Phillip, BWH HMS, white@bwh.harvard.edu
#Yamada, Atsushi, BWH, ayamada@bwh.harvard.edu
#Yarmakovich, Alex, Isomics, alexy@bwh.harvard.edu

2012 Summer Project Week:VertebraCTUSReg

2012-06-11T17:57:09Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume are provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-09T18:42:26Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics behind and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, we are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume is provided using existing slicer modules, like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk and scene.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-09T18:39:25Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, We are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume is provided using existing slicer modules like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk.
</div>

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

<h3>Progress</h3>
* A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
* Core implementation of the algorithm is MATLAB-based (The algorithm is quite fast and speed is not an issue). Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module to run on any machine.
* A spine phantom data (L1-5) is used for the experiment.
</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-09T18:37:23Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, We are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
We assume a single vertebra model and volume is provided using existing slicer modules like crop-volume and segmentation (editor).
From the CT model, a subset of visible points is extracted regarding position of the probe in ultrasound data acquisition step.
3D ultrasound volume (reconstructed before) is processed to generate a bone probability volume. <br/>
An iterative optimization algorithm is performed using Guassian Mixture Model method to solve for this surface to volume registration problem.
Results of each iteration step is visualaized in slicer to show the convergence of the algorithm.<br/>
Output from each step of the algorithm and all transforms from each iteration are saved to disk.
</div>

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

<h3>Progress</h3>
# A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs. All inputs need to be limited to region of interest (i.e. a single vertebra: L3)
# Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue. Re-distributable MATLAB Compiler Runtime (MCR) is a prerequisite for the slicer module.
# A spine phantom data (L1-5) is used for the experiment.
</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-09T18:25:37Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
To bring the realtime needle navigation for spine injections into 3D-slicer framework, a chain of tools are required.
Ultrasound machine is one of the most applicable devices for realtime guidance due to its non-poisonous physics and low cost availability.
Out of the patient's lumbar section of the spine, a 3D volume is reconstructed using tracked frames acquired from ultrasound machine. This volume needs to be registered to prior CT-image of the same area of the patient. At the end a realtime guidance is performed based on outputs generated.
<p>
In this phase, We are focused on developing a new module for slicer that performs a rigid registration between segmented CT (model) and ultrasound volumetric representation (reconstructed volume). Current algorithm is based on single vertebra inputs and will be extended to include mechanical characteristics of spine for a multi-vertebrae case.
</p>

</div>

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

<h3>Approach, Plan</h3>
A bone probability volume is generated from the original ultrasound volume.
From the CT image, a subset of visible points is extracted.
A guassian mixture model method is performed to solve for this surface to volume registration problem.

</div>

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

<h3>Progress</h3>
All implementations are based on a single vertebra registration for now.
A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs.
All inputs need to be limited to region of interest (i.e. a single vertebra: L3).
Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue.
A gaussian mixture model is used to register surface to volume. output of the module is the rigid transformation matrix obtained in this way.
A spine phantom data is used for validation. Patient recruitment is an ongoing task for this project.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-08T03:24:22Z

Samann: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
We are developing a new module as a puzzle block for a spine injection image-guided intervention.<br />
The ultimate goal is to plan for injection based on prior CT-image and perform the treatment using ultrasound-based needle guidance.
A volumetric representation of the patient's lumbar section is being reconstructed using tracked frames.
This volume should go through a registration algorithm to rigidly align with the model generated from CT image.

</div>

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

<h3>Approach, Plan</h3>
A bone probability volume is generated from the original ultrasound volume.
From the CT image, a subset of visible points is extracted.
A guassian mixture model method is performed to solve for this surface to volume registration problem.

</div>

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

<h3>Progress</h3>
All implementations are based on a single vertebra registration for now.
A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs.
All inputs need to be limited to region of interest (i.e. a single vertebra: L3).
Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue.
A gaussian mixture model is used to register surface to volume. output of the module is the rigid transformation matrix obtained in this way.
A spine phantom data is used for validation. Patient recruitment is an ongoing task for this project.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable --> Yes
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-08T03:23:43Z

Samann: /* References */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
We are developing a new module as a puzzle block for a spine injection image-guided intervention.<br />
The ultimate goal is to plan for injection based on prior CT-image and perform the treatment using ultrasound-based needle guidance.
A volumetric representation of the patient's lumbar section is being reconstructed using tracked frames.
This volume should go through a registration algorithm to rigidly align with the model generated from CT image.

</div>

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

<h3>Approach, Plan</h3>
A bone probability volume is generated from the original ultrasound volume.
From the CT image, a subset of visible points is extracted.
A guassian mixture model method is performed to solve for this surface to volume registration problem.

</div>

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

<h3>Progress</h3>
All implementations are based on a single vertebra registration for now.
A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs.
All inputs need to be limited to region of interest (i.e. a single vertebra: L3).
Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue.
A gaussian mixture model is used to register surface to volume. output of the module is the rigid transformation matrix obtained in this way.
A spine phantom data is used for validation. Patient recruitment is an ongoing task for this project.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable
#Other (Please specify)

2012 Summer Project Week:VertebraCTUSReg

2012-06-08T03:23:31Z

Samann:

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
We are developing a new module as a puzzle block for a spine injection image-guided intervention.<br />
The ultimate goal is to plan for injection based on prior CT-image and perform the treatment using ultrasound-based needle guidance.
A volumetric representation of the patient's lumbar section is being reconstructed using tracked frames.
This volume should go through a registration algorithm to rigidly align with the model generated from CT image.

</div>

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

<h3>Approach, Plan</h3>
A bone probability volume is generated from the original ultrasound volume.
From the CT image, a subset of visible points is extracted.
A guassian mixture model method is performed to solve for this surface to volume registration problem.

</div>

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

<h3>Progress</h3>
All implementations are based on a single vertebra registration for now.
A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs.
All inputs need to be limited to region of interest (i.e. a single vertebra: L3).
Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue.
A gaussian mixture model is used to register surface to volume. output of the module is the rigid transformation matrix obtained in this way.
A spine phantom data is used for validation. Patient recruitment is an ongoing task for this project.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable
#Other (Please specify)

==References==
*Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI.] Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
* Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. [http://www.na-mic.org/publications/item/view/292 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
* Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. [http://www.na-mic.org/publications/item/view/1122 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
* Goodlett C, Corouge I, Jomier M, Gerig G, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .

2012 Summer Project Week:VertebraCTUSReg

2012-06-08T03:22:51Z

Samann: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* University of British Columbia, Robotics & Control Laboratory
* Queen's University

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

<h3>Objective</h3>
We are developing a new module as a puzzle block for a spine injection image-guided intervention.<br />
The ultimate goal is to plan for injection based on prior CT-image and perform the treatment using ultrasound-based needle guidance.
A volumetric representation of the patient's lumbar section is being reconstructed using tracked frames.
This volume should go through a registration algorithm to rigidly align with the model generated from CT image.

</div>

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

<h3>Approach, Plan</h3>
A bone probability volume is generated from the original ultrasound volume.
From the CT image, a subset of visible points is extracted.
A guassian mixture model method is performed to solve for this surface to volume registration problem.

</div>

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

<h3>Progress</h3>
All implementations are based on a single vertebra registration for now.
A loadable module is created which accepts a CT model (polydata) and an ultrasound volume (scalar) as inputs.
All inputs need to be limited to region of interest (i.e. a single vertebra: L3).
Core implementation of the algorithm is MATLAB-based, since the algorithm is quite fast and speed is not an issue.
A gaussian mixture model is used to register surface to volume. output of the module is the rigid transformation matrix obtained in this way.
A spine phantom data is used for validation. Patient recruitment is an ongoing task for this project.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable
#Other (Please specify)

==References==
*Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI.] Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
* Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. [http://www.na-mic.org/publications/item/view/292 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
* Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. [http://www.na-mic.org/publications/item/view/1122 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
* Goodlett C, Corouge I, Jomier M, Gerig G, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .

2012 Summer Project Week:VertebraCTUSReg

2012-06-08T02:57:51Z

Samann: /* Instructions for Use of this Template */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
* Utah: Tom Fletcher, Ross Whitaker

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

<h3>Objective</h3>
We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.

</div>

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

<h3>Approach, Plan</h3>

Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below. The main challenge to this approach is <foo>.

Our plan for the project week is to first try out <bar>,...

</div>

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

<h3>Progress</h3>
Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.

</div>
</div>

==Delivery Mechanism==

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

#ITK Module
#Slicer Module
##Built-in
##Extension -- commandline
##Extension -- loadable
#Other (Please specify)

==References==
*Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI.] Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
* Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. [http://www.na-mic.org/publications/item/view/292 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
* Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. [http://www.na-mic.org/publications/item/view/1122 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
* Goodlett C, Corouge I, Jomier M, Gerig G, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .

2012 Summer Project Week

2012-05-10T19:59:24Z

Samann: Added project title