NAMIC Wiki - User contributions [en]

2012 Summer Project Week:DTIRegistration

2012-06-22T15:00:57Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
Image:View ant before.png|Fiber Geometry Registration Before.
Image:View ant after.png|Fiber Geometry Registration After.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]
* [[File:Test-output-test2.zip]] test output of tractography registration
* [[File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans deformed wFA Y01 OutputFiberBundle.vtk.zip]] Fiber bundle of intermediate output.

==Updates==
Discussed and initial work on different methods to obtain registration:
* Geometric Metamorphosis - worked on implementation of Matlab code.
* Fiber geometry based registration with Lauren Donnell. Figures before and after registration attached on top of page.
* Feature Map improvements:
- Crossing Fibers.
- Fiber Density.
- Weighting Function.
* TumorSim.

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-22T14:59:21Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
Image:View ant before.png|Fiber Geometry Registration Before.
Image:View ant after.png|Fiber Geometry Registration After.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]
* [[File:Test-output-test2.zip]] test output of tractography registration
* [[File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans deformed wFA Y01 OutputFiberBundle.vtk.zip]] Fiber bundle of intermediate output.

==Updates==
Discussed and initial work on different methods to obtain registration:
* Geometric Metamorphosis - worked on implementation of Matlab code.
* Fiber geometry based registration with Lauren Donnell.
* Feature Map improvements:
- Crossing Fibers.
- Fiber Density.
- Weighting Function.
* TumorSim.

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

File:View ant after.png

2012-06-22T14:57:30Z

AGupta:

File:View ant before.png

2012-06-22T14:53:53Z

AGupta:

2012 Summer Project Week:DTIRegistration

2012-06-22T14:30:16Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]
* [[File:Test-output-test2.zip]] test output of tractography registration
* [[File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans deformed wFA Y01 OutputFiberBundle.vtk.zip]] Fiber bundle of intermediate output.

==Updates==
Discussed and initial work on different methods to obtain registration:
* Geometric Metamorphosis - worked on implementation of Matlab code.
* Fiber geometry based registration with Lauren Donnell.
* Feature Map improvements:
- Crossing Fibers.
- Fiber Density.
- Weighting Function.
* TumorSim.

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans deformed wFA Y01 OutputFiberBundle.vtk.zip

2012-06-22T14:27:22Z

AGupta:

2012 Summer Project Week:DTIRegistration

2012-06-22T14:17:47Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]
* [[File:Test-output-test2.zip]] test output of tractography registration

==Updates==
Discussed and initial work on different methods to obtain registration:
* Geometric Metamorphosis - worked on implementation of Matlab code.
* Fiber geometry based registration with Lauren Donnell.
* Feature Map improvements:
- Crossing Fibers.
- Fiber Density.
- Weighting Function.
* TumorSim.

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-22T14:11:49Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]
* [[File:Test-output-test2.zip]] test output of tractography registration

==Updates==
Discussed and initial work on different methods to obtain registration:
* Geometric Metamorphosis - worked on implementation of Matlab code.
* TumorSim.
* Feature Map improvements:
- Crossing Fibers.
- Fiber Density.
- Weighting Function.
* Fiber geometry based registration with Lauren Donnell.

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-21T21:13:57Z

AGupta: /* Data */

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]
* [http://wiki.na-mic.org/Wiki/index.php/File:11067_012511_FullBrainTractography_New.vtk.zip Full brain tractography of Krabbe subject regenerated vtk files]

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

File:11067 012511 FullBrainTractography New.vtk.zip

2012-06-21T21:11:58Z

AGupta:

2012 Summer Project Week:DTIRegistration

2012-06-21T19:17:19Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

==Data==
* [http://wiki.na-mic.org/Wiki/index.php/File:Tractography.zip Full brain tractography of normal control and Krabbe vtk files]

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

File:Tractography.zip

2012-06-21T19:04:33Z

AGupta:

2012 Summer Project Week:DifficultRegistration

2012-06-20T20:26:24Z

AGupta: /* Links for Data */

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

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

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

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

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

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

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

<h3>Progress</h3>TBA

</div>
</div>

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

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

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

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

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

</div>

File:Krabbe Controls DWI.zip

2012-06-20T20:10:45Z

AGupta: DWI files of Krabbe and the normal controls.

DWI files of Krabbe and the normal controls.

2012 Summer Project Week:DifficultRegistration

2012-06-18T20:58:42Z

AGupta:

File:EnlargedLVCase Normal.zip

2012-06-18T20:54:15Z

AGupta: Zip File contains: DTI images for a normal control and an enlarged lateral ventricle Krabbe Case

Zip File contains: DTI images for a normal control and an enlarged lateral ventricle Krabbe Case

File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans.raw.gz

2012-06-18T18:47:31Z

AGupta: Normal neonate control - for registration with enlarged LV Krabbe case

Normal neonate control - for registration with enlarged LV Krabbe case

File:Neo-0011-2-1-1year dwi 35 all DTI AffTrans.nhdr

2012-06-18T18:46:21Z

AGupta: Normal neonate control - for registration with enlarged LV Krabbe case

Normal neonate control - for registration with enlarged LV Krabbe case

File:11066 082310 DTI QCed AffTrans.raw.gz

2012-06-18T18:45:09Z

AGupta: Enlarged LV Krabbe Case

Enlarged LV Krabbe Case

File:11066 082310 DTI QCed AffTrans.nhdr

2012-06-18T18:43:42Z

AGupta: Enlarged LV Krabbe case

Enlarged LV Krabbe case

2012 Summer Project Week:DTIRegistration

2012-06-18T18:19:43Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:18:41Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Subject Control1.png|EnlargedLV Reg
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

File:Subject Control1.png

2012-06-18T18:17:09Z

AGupta: Registration of enlarged LV cases with normal controls

Registration of enlarged LV cases with normal controls

2012 Summer Project Week:DTIRegistration

2012-06-18T18:15:40Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:EnlargedLV Reg.png|EnlargedLV Reg
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:14:59Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
[[File:EnlargedLV Reg.png|EnlargedLV Reg]]
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:13:32Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:EnlargedLV Reg.png|Registration of enlarged lateral ventricle cases to normal controls.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:11:41Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:EnlargedLV_Reg.png|Registration of enlarged lateral ventricle cases to normal controls.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:11:03Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
[[File:EnlargedLV_Reg.png]]|Registration of enlarged lateral ventricle cases to normal controls.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:05:14Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
File:EnlargedLV Reg.png|Registration of enlarged lateral ventricle cases to normal controls.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:04:43Z

AGupta:

<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
File:EnlargedLV_Reg.png|Registration of enlarged lateral ventricle cases to normal controls.
Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
</gallery>

==Key Investigators==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-06-18T18:04:04Z

AGupta:

2012 Summer Project Week:DTIRegistration

2012-06-18T18:01:16Z

AGupta:

[[File:EnlargedLV Reg.png|thumb|Add caption here]]
<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: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week

2012-05-17T19:43:12Z

AGupta: /* General Registration */

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:''' Slicer4 (Jean-Christophe Fillion-Robin)
'''10-11am''' Slicer4 Breakout (Continued) <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>----------------------------------------<br>
'''11-12pm: <font color="#4020ff">Breakout Session:'''</font> )<br>
[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''9am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Project Week Breakout Session: ITK|ITK]] (Luis Ibanez)
<br>[[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>
<br>Star Room
|'''9am-4pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:OpenIGTLink|OpenIGTLink]]
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva Room]]
<br>'''10:30am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> <br>
<br>[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''10am-12pm:''' [[#Projects|Project Progress Updates]]
<br>[[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)
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''3:30-4:15pm''' Slicer4 Developers Session (Pieper) <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Slicer4 Developer Session Continued <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Breakout Session: TBD <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Right)]]
|'''1-3pm: <font color="#4020ff">Breakout Session:'''</font><br> TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
<br>----------------------------------------<br>
'''3-4pm:''' [[2012_Tutorial_Contest|Tutorial Contest Presentations]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''4-5pm:''' Breakout Session:TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
|'''12:45-1pm:''' [[Events:TutorialContestJune2012|Tutorial Contest Winner Announcement]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]

|'''1-4pm: <font color="#4020ff">Breakout Session:'''</font><br>
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva 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==

This is where the list of projects goes...

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'''===

# [[2012_Summer_Project_Week:Early_Dementia_Diagnostic |Early Dementia Diagnostic Tools]] (Marcel Koek, Sonia Pujol)
# Intraoperative White Matter Tract Detection Module (Lauren O'Donnell, Isaiah Norton)
# [[Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury]] (Andrei Irimia, Danielle Pace, Micah Chambers, Stephen Aylward)
# [[2012_Summer_Project_Week:Radnostics |Spine Segmentation & Osteoporosis Detection In CT Imaging Studies]] (Anthony Blumfield)
# [[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)

==='''Radiation Therapy'''===

#Dose Calculation for Interstitial Brachytherapy (Tina Kapur, Greg Sharp)
#[[2012_Summer_Project_Week:Overlapping_structures|Overlapping structures]] (Greg Sharp, Steve Pieper)
#[[2012_Summer_Project_Week:Atlas_based_segmentation_for_head_and_neck|Atlas-based segmentation for head and neck]] (Greg Sharp, Nadya Shusharina, James Shackleford, Polina Golland)
#[[2012_Summer_Project_Week:SlicerRT|Radiotherapy extensions for Slicer 4]] (Andras Lasso, Csaba Pinter, Kevin Wang)

==='''Huntington's Disease'''===
# [[2012_Summer_Project_Week:DTIPrep|DTIPrep]] (David Welch)
# [[2012_Summer_Project_Week:Fast Fiducial Registration|Fast Fiducial Registration Module]] (David Welch)
# [[2012_Summer_Project_Week:ANTS Registation|ANTS Registation Module]] (David Welch)
# [[2012_Summer_Project_Week:Nipype Integration|Slicer/Nipype Integration]] (Hans Johnson)
# [[2012_Summer_Project_Week:DicomToNrrd|DicomToNrrdConverter Integration]] (Kent Williams)
# [[2012_Summer_Project_Week:4D shape analysis|4D shape analysis]] (James Fishbaugh, Marcel Prastawa, Guido Gerig)

==='''Atrial Fibrillation'''===
# Model-based segmentation of left Atrium using Graph-cuts (Gopal Veni, Ross Whitaker)
# [[DBP3:Utah:SlicerModuleCardiacRegistration|Cardiac MRI Registration Module]] (Alan Morris, Danny Perry, Josh Cates, Greg Gardner, Rob MacLeod)
# [[DBP3:Utah: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)
# [[DBP3:Utah:SlicerModuleAutoScar|Automatic Left Atrial Scar Detection]] (Danny Perry, Alan Morris, Josh Cates, Rob MacLeod)
# [[DBP3:Utah:SlicerModuleInhomogeneity|MRI Inhomogeneity Correction Filter]] (Alan Morris, Eugene Kholmovski, Josh Cates, Danny Perry, Rob MacLeod)
# OpenIGT for realtime MRI-guided RF ablation (Rob MacLeod, Junichi Tokuda)

==='''Device Integration with Slicer and General Image Guided Therapy'''===
# [[2012_Summer_Project_Week:iGyne|iGyne for Gyne Brachytherapy]] (Xiaojun Chen, Jan Egger, Tina Kapur, Steve Pieper)
# [[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:LiveUltrasound|Live Ultrasound]] (Tamas Ungi, Junichi Tokuda)
# [[2012_Summer_Project_Week:TransformRecorder|Transform Recorder]] (Simrin Nagpal, Tamas Ungi)
# [[2012_Summer_Project_Week:VertebraCTUSReg|Single Vertebra CT-US Registration]] (Samira Sojoudi, Saman Nouranian, Simrin Nagpal, Tamas Ungi, David Welch)

==='''General Segmentation'''===
#Semi-automated airway segmentation from 0.64mm lung CT datasets (Padraig Cantillon-Murphy, Pietro Nardelli)
# [[2012_Summer_Project_Week:QuantitativePETImageAnalysisModule|Quantitative PET Image Analysis Module]] (Markus Van Tol)
#Segmentation with Label Fusion (Ramesh Sridharan, Christian Wachinger, Polina Golland)

==='''General Registration'''===
# Interactive registration (Kunlin Cao GRC, Guillaume Pernelle BWH, Simrin Nagpal Queens)
# [[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 Toes)

==='''General Diffusion Tractography'''===
#
#

==='''Vessels'''===
#
#
==='''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)
# Multivolume, nrrd, .... (Andriy, Jim)
# Python CLI modules (Demian, JC, Julien)
# Charting (Jim)
# [[2012_Summer_Project_Week:SimpleITK Integration|SimpleITK Integration]] (Hans Johnson, Bradley Lowekamp)
# GPU Editor Effects
# XTK/WebGL Exporter (Daniel, Nicolas - Children's Hospital Boston)
# General Usability issues (e.g. LM,FG,BG blending)
# Callback/Events/Observation best practice + Performance bottleneck discussion (Julien, Steve,...)
# XNAT/Slicer implementation (Sunil, Dan, Steve,...)
# Pilot QIN use cases for Slicer/XNAT integration (Sunil, Steve, Dan, Andriy, Jayashree,...)
# [[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]

==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.

2012 Summer Project Week:DTIRegistration

2012-05-17T19:41:32Z

AGupta: /* References */

__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: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diffusion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Jaray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-05-17T19:40:54Z

AGupta: /* 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==
* UNC: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diffusion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fiber geometry and is robust against variations in WM fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation field computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diff�usion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Ja�ray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week:DTIRegistration

2012-05-17T19:40:08Z

AGupta: Created page with '__NOTOC__ <gallery> Image:PW-MIT2012.png|Projects List Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus…'

__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: Aditya Gupta, Martin Styner
* MIT: Matthew Toes

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

<h3>Objective</h3>
We are developing methods for fiber feature map based landmark initialization for highly deformable DTI registration. The goal is to register diff�usion tensor images with large pathological variations as compared to normal controls with the use of a feature map based on white matter (WM) �fiber tracts. Our final objective is to have an accurate registration to enable analysis of properties such as fractional anisotropy even on cases with large pathological variations.

</div>

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

<h3>Approach, Plan</h3>

Our approach is to develop a novel feature map that represents fi�ber geometry and is robust against variations in WM �fiber tract integrity. From this novel feature map, we plan to develop
landmark correspondence using a 3D point correspondence algorithm. This correspondence forms the basis of a deformation fi�eld computed using Gaussian radial basis functions(RBF) or a registration defined by landmarks and intensity.

Our plan for the project week is to first try to improve our current feature map by taking into consideration the features most useful to develop strong correspondence. Having determined strong correspondence points, we would look into methods that would best give us a strong initialization field, so that any scalar registration and DTI registration can then be used for these highly deformable cases.

</div>

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

<h3>Progress</h3>
We have developed a novel feature map that is partially immune to WM fiber tract integrity. The landmarks from this feature map used with gaussian radial basis function gives us an initial vector field which when used with demons gives us a good registration. But there is need for a more robust and more accurate method of deriving landmarks and generating a strong initialization field.

</div>
</div>

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

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

==References==
1. Fornefett, M., Rohr, K., Stiehl, H.S.: Elastic registration of medical images using radial basis functions with compact support. Proc. Computer Vison and Pattern Recognition (1999) 402407
2. Escolar, M., Poe, M., Smith, J., Gilmore, J., Kurtzberg, J., Lin, W., Styner, M.: Diff�usion tensor imaging detects abnormalities in the corticospinal tracts of neonates with infantile krabbe disease. American Journal of Neuroradiology 30(5) (May 2009) 1017-1021.
3. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004) 91-110.
4. Allaire, S., Kim, J., Breen, S., Ja�ray, D., Pekar, V.: Full orientation invariance and improved feature selectivity of 3d sift with application to medical image analysis. In: MMBIA. (2008)
</div>

2012 Summer Project Week

2012-05-17T19:12:17Z

AGupta:

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:''' Slicer4 (Jean-Christophe Fillion-Robin)
'''10-11am''' Slicer4 Breakout (Continued) <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>----------------------------------------<br>
'''11-12pm: <font color="#4020ff">Breakout Session:'''</font> )<br>
[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''9am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Project Week Breakout Session: ITK|ITK]] (Luis Ibanez)
<br>[[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>
<br>Star Room
|'''9am-4pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:OpenIGTLink|OpenIGTLink]]
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva Room]]
<br>'''10:30am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> <br>
<br>[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''10am-12pm:''' [[#Projects|Project Progress Updates]]
<br>[[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)
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''3:30-4:15pm''' Slicer4 Developers Session (Pieper) <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Slicer4 Developer Session Continued <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Breakout Session: TBD <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Right)]]
|'''1-3pm: <font color="#4020ff">Breakout Session:'''</font><br> TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
<br>----------------------------------------<br>
'''3-4pm:''' [[2012_Tutorial_Contest|Tutorial Contest Presentations]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''4-5pm:''' Breakout Session:TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
|'''12:45-1pm:''' [[Events:TutorialContestJune2012|Tutorial Contest Winner Announcement]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]

|'''1-4pm: <font color="#4020ff">Breakout Session:'''</font><br>
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva 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==

This is where the list of projects goes...

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'''===

# [[2012_Summer_Project_Week:Early_Dementia_Diagnostic |Early Dementia Diagnostic Tools]] (Marcel Koek, Sonia Pujol)
# Intraoperative White Matter Tract Detection Module (Lauren O'Donnell, Isaiah Norton)
# [[Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury]] (Andrei Irimia, Danielle Pace, Micah Chambers, Stephen Aylward)
# [[2012_Summer_Project_Week:Radnostics |Spine Segmentation & Osteoporosis Detection In CT Imaging Studies]] (Anthony Blumfield)
# [[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)

==='''Radiation Therapy'''===

#Dose Calculation for Interstitial Brachytherapy (Tina Kapur, Greg Sharp)
#[[2012_Summer_Project_Week:Overlapping_structures|Overlapping structures]] (Greg Sharp, Steve Pieper)
#[[2012_Summer_Project_Week:Atlas_based_segmentation_for_head_and_neck|Atlas-based segmentation for head and neck]] (Greg Sharp, Nadya Shusharina, James Shackleford, Polina Golland)
#[[2012_Summer_Project_Week:SlicerRT|Radiotherapy extensions for Slicer 4]] (Andras Lasso, Csaba Pinter, Kevin Wang)

==='''Huntington's Disease'''===
# [[2012_Summer_Project_Week:DTIPrep|DTIPrep]] (David Welch)
# [[2012_Summer_Project_Week:Fast Fiducial Registration|Fast Fiducial Registration Module]] (David Welch)
# [[2012_Summer_Project_Week:ANTS Registation|ANTS Registation Module]] (David Welch)
# [[2012_Summer_Project_Week:Nipype Integration|Slicer/Nipype Integration]] (Hans Johnson)
# [[2012_Summer_Project_Week:DicomToNrrd|DicomToNrrdConverter Integration]] (Kent Williams)
# [[2012_Summer_Project_Week:SimpleITK Integration|SimpleITK Integration]] (Hans Johnson, Bradley Lowekamp)
# [[2012_Summer_Project_Week:ITKv4 Integration|ITKv4 Integration]] (Hans Johnson, Julien Finet)
# [[2012_Summer_Project_Week:4D shape analysis|4D shape analysis]] (James Fishbaugh, Marcel Prastawa, Guido Gerig)

==='''Atrial Fibrillation'''===
# Model-based segmentation of left Atrium using Graph-cuts (Gopal Veni, Ross Whitaker)
# [[DBP3:Utah:SlicerModuleCardiacRegistration|Cardiac MRI Registration Module]] (Alan Morris, Danny Perry, Josh Cates, Greg Gardner, Rob MacLeod)
# [[DBP3:Utah: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)
# [[DBP3:Utah:SlicerModuleAutoScar|Automatic Left Atrial Scar Detection]] (Danny Perry, Alan Morris, Josh Cates, Rob MacLeod)
# [[DBP3:Utah:SlicerModuleInhomogeneity|MRI Inhomogeneity Correction Filter]] (Alan Morris, Eugene Kholmovski, Josh Cates, Danny Perry, Rob MacLeod)
# OpenIGT for realtime MRI-guided RF ablation (Rob MacLeod, Junichi Tokuda)

==='''Device Integration with Slicer and General Image Guided Therapy'''===
# [[2012_Summer_Project_Week:iGyne|iGyne for Gyne Brachytherapy]] (Xiaojun Chen, Jan Egger, Tina Kapur, Steve Pieper)
# [[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:LiveUltrasound|Live Ultrasound]] (Tamas Ungi, Junichi Tokuda)
# [[2012_Summer_Project_Week:TransformRecorder|Transform Recorder]] (Simrin Nagpal, Tamas Ungi)
# [[2012_Summer_Project_Week:VertebraCTUSReg|Single Vertebra CT-US Registration]] (Samira Sojoudi, Saman Nouranian, Simrin Nagpal, Tamas Ungi)

==='''General Segmentation'''===
#Semi-automated airway segmentation from 0.64mm lung CT datasets (Padraig Cantillon-Murphy, Pietro Nardelli)
# [[2012_Summer_Project_Week:QuantitativePETImageAnalysisModule|Quantitative PET Image Analysis Module]] (Markus Van Tol)
#Segmentation with Label Fusion (Ramesh Sridharan, Christian Wachinger, Polina Golland)

==='''General Registration'''===
# Interactive registration (Kunlin)
# [[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| DTI Registration for enlarged ventricles]] (Aditya Gupta, Martin Styner, Matthew Toes)

==='''General Diffusion Tractography'''===
#
#

==='''Vessels'''===
#
#
==='''Infrastructure'''===

# [[2012_Summer_Project_Week:SelfTesting|Built-In Self-Testing (BIST) for Slicer]] (Steve, Julien, Jc, Sonia)
# Annotation module redesign (Nicole)
# Multivolume, nrrd, .... (Andriy, Jim)
# Python CLI modules (Demian, JC, Julien)
# Charting (Jim)
# ITKv4
# SimpleITK
# GPU Editor Effects
# XTK/WebGL Exporter (Daniel, Nicolas - Children's Hospital Boston)
# General Usability issues (e.g. LM,FG,BG blending)
# Callback/Events/Observation best practice + Performance bottleneck discussion (Julien, Steve,...)
# XNAT/Slicer implementation (Sunil, Dan, Steve,...)
# Pilot QIN use cases for Slicer/XNAT integration (Sunil, Steve, Dan, Andriy, Jayashree,...)

==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.

2012 Summer Project Week

2012-05-17T19:11:06Z

AGupta:

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:''' Slicer4 (Jean-Christophe Fillion-Robin)
'''10-11am''' Slicer4 Breakout (Continued) <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>----------------------------------------<br>
'''11-12pm: <font color="#4020ff">Breakout Session:'''</font> )<br>
[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''9am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Project Week Breakout Session: ITK|ITK]] (Luis Ibanez)
<br>[[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>
<br>Star Room
|'''9am-4pm: <font color="#4020ff">Breakout Session:'''</font><br> [[2012 Summer Project Week Breakout Session:OpenIGTLink|OpenIGTLink]]
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva Room]]
<br>'''10:30am-12pm: <font color="#4020ff">Breakout Session:'''</font><br> <br>
<br>[[MIT_Project_Week_Rooms#Star|Star Room]]
|'''10am-12pm:''' [[#Projects|Project Progress Updates]]
<br>[[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)
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''3:30-4:15pm''' Slicer4 Developers Session (Pieper) <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Slicer4 Developer Session Continued <br>
[[MIT_Project_Week_Rooms|Grier Room (Left)]]
<br>---<br>
'''4:15-5:00pm''' Breakout Session: TBD <br>
[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Room (Right)]]
|'''1-3pm: <font color="#4020ff">Breakout Session:'''</font><br> TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
<br>----------------------------------------<br>
'''3-4pm:''' [[2012_Tutorial_Contest|Tutorial Contest Presentations]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]
<br>----------------------------------------<br>
'''4-5pm:''' Breakout Session:TBD
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Star Room]]
|'''12:45-1pm:''' [[Events:TutorialContestJune2012|Tutorial Contest Winner Announcement]]
<br>[[MIT_Project_Week_Rooms#Grier_34-401_AB|Grier Rooms]]

|'''1-4pm: <font color="#4020ff">Breakout Session:'''</font><br>
<br>[[MIT_Project_Week_Rooms#Kiva_32-G449|Kiva 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==

This is where the list of projects goes...

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'''===

# [[2012_Summer_Project_Week:Early_Dementia_Diagnostic |Early Dementia Diagnostic Tools]] (Marcel Koek, Sonia Pujol)
# Intraoperative White Matter Tract Detection Module (Lauren O'Donnell, Isaiah Norton)
# [[Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury]] (Andrei Irimia, Danielle Pace, Micah Chambers, Stephen Aylward)
# [[2012_Summer_Project_Week:Radnostics |Spine Segmentation & Osteoporosis Detection In CT Imaging Studies]] (Anthony Blumfield)
# [[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)

==='''Radiation Therapy'''===

#Dose Calculation for Interstitial Brachytherapy (Tina Kapur, Greg Sharp)
#[[2012_Summer_Project_Week:Overlapping_structures|Overlapping structures]] (Greg Sharp, Steve Pieper)
#[[2012_Summer_Project_Week:Atlas_based_segmentation_for_head_and_neck|Atlas-based segmentation for head and neck]] (Greg Sharp, Nadya Shusharina, James Shackleford, Polina Golland)
#[[2012_Summer_Project_Week:SlicerRT|Radiotherapy extensions for Slicer 4]] (Andras Lasso, Csaba Pinter, Kevin Wang)

==='''Huntington's Disease'''===
# [[2012_Summer_Project_Week:DTIPrep|DTIPrep]] (David Welch)
# [[2012_Summer_Project_Week:Fast Fiducial Registration|Fast Fiducial Registration Module]] (David Welch)
# [[2012_Summer_Project_Week:ANTS Registation|ANTS Registation Module]] (David Welch)
# [[2012_Summer_Project_Week:Nipype Integration|Slicer/Nipype Integration]] (Hans Johnson)
# [[2012_Summer_Project_Week:DicomToNrrd|DicomToNrrdConverter Integration]] (Kent Williams)
# [[2012_Summer_Project_Week:SimpleITK Integration|SimpleITK Integration]] (Hans Johnson, Bradley Lowekamp)
# [[2012_Summer_Project_Week:ITKv4 Integration|ITKv4 Integration]] (Hans Johnson, Julien Finet)
# [[2012_Summer_Project_Week:4D shape analysis|4D shape analysis]] (James Fishbaugh, Marcel Prastawa, Guido Gerig)

==='''Atrial Fibrillation'''===
# Model-based segmentation of left Atrium using Graph-cuts (Gopal Veni, Ross Whitaker)
# [[DBP3:Utah:SlicerModuleCardiacRegistration|Cardiac MRI Registration Module]] (Alan Morris, Danny Perry, Josh Cates, Greg Gardner, Rob MacLeod)
# [[DBP3:Utah: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)
# [[DBP3:Utah:SlicerModuleAutoScar|Automatic Left Atrial Scar Detection]] (Danny Perry, Alan Morris, Josh Cates, Rob MacLeod)
# [[DBP3:Utah:SlicerModuleInhomogeneity|MRI Inhomogeneity Correction Filter]] (Alan Morris, Eugene Kholmovski, Josh Cates, Danny Perry, Rob MacLeod)
# OpenIGT for realtime MRI-guided RF ablation (Rob MacLeod, Junichi Tokuda)

==='''Device Integration with Slicer and General Image Guided Therapy'''===
# [[2012_Summer_Project_Week:iGyne|iGyne for Gyne Brachytherapy]] (Xiaojun Chen, Jan Egger, Tina Kapur, Steve Pieper)
# [[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:LiveUltrasound|Live Ultrasound]] (Tamas Ungi, Junichi Tokuda)
# [[2012_Summer_Project_Week:TransformRecorder|Transform Recorder]] (Simrin Nagpal, Tamas Ungi)
# [[2012_Summer_Project_Week:VertebraCTUSReg|Single Vertebra CT-US Registration]] (Samira Sojoudi, Saman Nouranian, Simrin Nagpal, Tamas Ungi)

==='''General Segmentation'''===
#Semi-automated airway segmentation from 0.64mm lung CT datasets (Padraig Cantillon-Murphy, Pietro Nardelli)
# [[2012_Summer_Project_Week:QuantitativePETImageAnalysisModule|Quantitative PET Image Analysis Module]] (Markus Van Tol)
#Segmentation with Label Fusion (Ramesh Sridharan, Christian Wachinger, Polina Golland)

==='''General Registration'''===
# Interactive registration (Kunlin)
# [[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:DTI Registration for enlarged ventricles]] (Aditya Gupta, Martin Styner, Matthew Toes)

==='''General Diffusion Tractography'''===
#
#

==='''Vessels'''===
#
#
==='''Infrastructure'''===

# [[2012_Summer_Project_Week:SelfTesting|Built-In Self-Testing (BIST) for Slicer]] (Steve, Julien, Jc, Sonia)
# Annotation module redesign (Nicole)
# Multivolume, nrrd, .... (Andriy, Jim)
# Python CLI modules (Demian, JC, Julien)
# Charting (Jim)
# ITKv4
# SimpleITK
# GPU Editor Effects
# XTK/WebGL Exporter (Daniel, Nicolas - Children's Hospital Boston)
# General Usability issues (e.g. LM,FG,BG blending)
# Callback/Events/Observation best practice + Performance bottleneck discussion (Julien, Steve,...)
# XNAT/Slicer implementation (Sunil, Dan, Steve,...)
# Pilot QIN use cases for Slicer/XNAT integration (Sunil, Steve, Dan, Andriy, Jayashree,...)

==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.