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

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