Difference between revisions of "2010 Winter Project Week WM ATLAS"
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** export of cluster/structure based measurements (FA, etc) | ** export of cluster/structure based measurements (FA, etc) | ||
** some statistical analysis | ** some statistical analysis | ||
| − | + | * Clustering | |
| + | ** investigating options in python... | ||
The eventual goal is re-implementation of much of the above in the Slicer3 framework. This will enable use of the pipeline for neuroscience research and our future investigation of DTI+fMRI atlases for neurosurgery. | The eventual goal is re-implementation of much of the above in the Slicer3 framework. This will enable use of the pipeline for neuroscience research and our future investigation of DTI+fMRI atlases for neurosurgery. | ||
Revision as of 18:32, 4 January 2010
Home < 2010 Winter Project Week WM ATLAS
Automatically segmented fiber tracts.
Example whole-brain tract cluster mean fibers.
Key Investigators
- Lauren O'Donnell (Instructor, Harvard Medical School (BWH))
- Carl-Fredrik Westin (Professor, Harvard Medical School (BWH) )
- William Wells (Professor, Harvard Medical School (BWH) )
- Alexandra J Golby (Professor of Neurosurgery, Harvard Medical School (BWH) )
Objective
Implement tract-based morphometry pipeline in 3D Slicer, including atlas-based WM (white matter) segmentation and whole-brain WM coordinate system generation. Investigate integration of FMRI+DTI into atlas pipeline, for neurosurgical planning applications.
This work is based on the papers Tract-Based Morphometry for White Matter Group Analysis. Lauren J. O'Donnell, Carl-Fredrik Westin, and Alexandra J. Golby NeuroImage 45(3):832-844, 2009 and Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas Lauren O'Donnell and Carl-Fredrik Westin IEEE Transactions in Medical Imaging 26(11):1562-1575, 2007
Approach, Plan
The original pipeline consists of (over a group):
- Preprocessing
- DTI and FA image calculation
- congealing registration of FA images
- whole-brain tract seeding
- application of registration to tractography
- EITHER atlas-based segmentation of tractography
- OR atlas generation
- clustering of (sample from) whole-brain tractography in group
- expert labeling of clusters to give anatomical structures
- the above produces an atlas that can be used to segment
- analysis of segmented WM
- optimal generation of tract-based coordinate systems per anatomical structure
- export of cluster/structure based measurements (FA, etc)
- some statistical analysis
- Clustering
- investigating options in python...
The eventual goal is re-implementation of much of the above in the Slicer3 framework. This will enable use of the pipeline for neuroscience research and our future investigation of DTI+fMRI atlases for neurosurgery.
Progress
- Preprocessing
- initial implementation of BatchMake modules for tensor calc, but ipython is preferable for overall pipeline
- tested congealing implementation in ITK from NAMIC SandBox to replace our current use of original code by Lilla Zollei
- implementation of initial seeding pipeline script in ipython
- current pipeline uses slicer command line modules that call teem/vtk
- Gordon has implemented some probing capability in teem, may allow more direct teem/itk/vtk dependencies
- discussions with Sandy, Lilla indicate ITK congealing broke with new ITK version, unclear when this was
