Difference between revisions of "2008 Winter Project Week:Resampling DTIs with Slicer3"
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<h1>Objective</h1> | <h1>Objective</h1> | ||
| − | The goal of this project is to develop a command line module for slicer 3 to resample DT images. This module | + | The goal of this project is to develop a command line module for slicer 3 to resample DT images. This module is compatible with several ITK 3D transforms (rigid, affine and non-rigid). These transforms can be pass as an ITKTransformFile using the command line, or directly as a transform in Slicer3. It also allows change the spacing, the orientation, the size or the origin of the image. This module implements different diffusion tensor interpolations and the structure of the program makes it easy to add new interpolations or new transformations. |
</div> | </div> | ||
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<h1>Approach, Plan </h1> | <h1>Approach, Plan </h1> | ||
| − | Our approach is to build the ITK infrastructure (ITK diffusion tensor interpolators and ITK diffusion tensor transforms) to support this module. | + | Our approach is to build the ITK infrastructure (ITK diffusion tensor interpolators and ITK diffusion tensor transforms) to support this module. Our main purpose at the Project Week is to implement a non-rigid transform for diffusion tensor images. |
</div> | </div> | ||
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<h1>Progress</h1> | <h1>Progress</h1> | ||
| − | The module currently | + | ====Jan 2008 Project Week==== |
| − | + | ||
| − | + | The project week allowed to integrate the module into Slicer3. It is now available in Slicer3 TransformIO branch. The support of the non-rigid transforms has been added. The list of the currently supported transforms is the following: | |
| − | + | *Rigid3D | |
| − | + | *Affine - Finite Strain | |
| − | + | *Affine - Preservation of Principal Direction | |
| − | + | *Non-rigid transforms (not tested yet) | |
| − | + | ||
| − | + | Several blockwise diffusion tensor interpolations are also available: | |
| − | + | *Nearest Neighborhood | |
| − | * | + | *Linear |
| − | * | + | *BSpline |
| + | *Windowed Sinc | ||
| + | |||
| + | The next step is to implement new interpolations (ie separating the shape and the orientation of the tensors). | ||
| + | |||
</div> | </div> | ||
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</div> | </div> | ||
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===References=== | ===References=== | ||
* D.C. Alexander, C. Pierpaoli, P.J. Basser, J.C. Gee. Spatial Transformations of Diffusion Tensor Magnetic Resonance Images, IEEE Transactions on medical imaging, vol. 20, No. 11, November 2001 | * D.C. Alexander, C. Pierpaoli, P.J. Basser, J.C. Gee. Spatial Transformations of Diffusion Tensor Magnetic Resonance Images, IEEE Transactions on medical imaging, vol. 20, No. 11, November 2001 | ||
Latest revision as of 22:21, 14 February 2008
Home < 2008 Winter Project Week:Resampling DTIs with Slicer3 Return to 2008_Winter_Project_Week |
Key Investigators
- BWH: Francois Budin, Sylvain Bouix
- GE: Xiaodong Tao
Objective
The goal of this project is to develop a command line module for slicer 3 to resample DT images. This module is compatible with several ITK 3D transforms (rigid, affine and non-rigid). These transforms can be pass as an ITKTransformFile using the command line, or directly as a transform in Slicer3. It also allows change the spacing, the orientation, the size or the origin of the image. This module implements different diffusion tensor interpolations and the structure of the program makes it easy to add new interpolations or new transformations.
Approach, Plan
Our approach is to build the ITK infrastructure (ITK diffusion tensor interpolators and ITK diffusion tensor transforms) to support this module. Our main purpose at the Project Week is to implement a non-rigid transform for diffusion tensor images.
Progress
Jan 2008 Project Week
The project week allowed to integrate the module into Slicer3. It is now available in Slicer3 TransformIO branch. The support of the non-rigid transforms has been added. The list of the currently supported transforms is the following:
- Rigid3D
- Affine - Finite Strain
- Affine - Preservation of Principal Direction
- Non-rigid transforms (not tested yet)
Several blockwise diffusion tensor interpolations are also available:
- Nearest Neighborhood
- Linear
- BSpline
- Windowed Sinc
The next step is to implement new interpolations (ie separating the shape and the orientation of the tensors).
References
- D.C. Alexander, C. Pierpaoli, P.J. Basser, J.C. Gee. Spatial Transformations of Diffusion Tensor Magnetic Resonance Images, IEEE Transactions on medical imaging, vol. 20, No. 11, November 2001
