Difference between revisions of "NA"

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'''Objective:'''
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'''Objective:''' Developing new methods for statistical group tests of diffusion tensor data. Our goal is to be able to detect subtle white matter differences between schizophrenics and normal controls beyond what can be detected today using current methods.
 
 
Semi Automatic Segmentation and parcellation for the Basal Ganglia.
 
  
 
'''Progress:'''
 
'''Progress:'''
  
A Semi-Automatic algorithm for delineation of the striatum into the 5 desired regions was implemented into Slicer. Ramsey's Matlab program facilitates the subdivision of the striatum based on Jim Fallon's rules (UCI). Matlab interface allows for the simple definition of the regions of interest. Changed the interface from drawing on the segmentation to drawing on the gray-level images. Future work: Integration of the rule-based subdivision scheme into Slicer.
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* We are applying our methods to the cingulum bundle data from Harvard. First, we have developed a new measure of anisotropy, called geodesic anisotropy (GA), that we are comparing with the standard fractional anisotropy (FA) to see if it gives more statistical power in group tests. Our results on the cingulum bundle data have shown similar results using FA or GA, that is, they show no advantage to using GA over FA. Another method that we are developing compares distributions of data within regions of interest rather than just a single summary measurement. Our preliminary results have not shown differences that are detectable using the mean FA, and we are working to improve upon the methodology. Finally, we are building DTI processing tools to help Core 3 researchers, including methods for interpolating, filtering, and segmenting DTI.
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* March 25, 2005. University of Utah visit of Harvard VA for collaborative work on DTMRI.
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** Presentation of non linear statistics for tensors by Tom Fletcher.
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** Possible collaboration on comparing new and old anisotropy measures in the context of Schizophrenia.
  
 
'''Key Investigators:'''
 
'''Key Investigators:'''
  
* GTech: Ramsey Al-Hakim, Delphine Nain, Allen Tannenbaum.
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* Utah: Tom Fletcher, Ross Whitaker.
* PNL: Sylvain Bouix, James Levitt, Marc Niethammer, Martha Shenton.
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* PNL: Sylvain Bouix, Marek Kubicki, Martha Shenton.
* UCI: James Fallon
 
* Kitware: Luis Ibanez
 
* Isomics: Steve Pieper
 
  
 
'''Links:'''
 
'''Links:'''
  
* [[DBP:Harvard:Collaboration:GTech|Harvard - Rule-based Segmentation]]
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* http://pnl.bwh.harvard.edu/index.html
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*
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*

Revision as of 13:28, 18 December 2006

Home < NA

Objective: Developing new methods for statistical group tests of diffusion tensor data. Our goal is to be able to detect subtle white matter differences between schizophrenics and normal controls beyond what can be detected today using current methods.

Progress:

  • We are applying our methods to the cingulum bundle data from Harvard. First, we have developed a new measure of anisotropy, called geodesic anisotropy (GA), that we are comparing with the standard fractional anisotropy (FA) to see if it gives more statistical power in group tests. Our results on the cingulum bundle data have shown similar results using FA or GA, that is, they show no advantage to using GA over FA. Another method that we are developing compares distributions of data within regions of interest rather than just a single summary measurement. Our preliminary results have not shown differences that are detectable using the mean FA, and we are working to improve upon the methodology. Finally, we are building DTI processing tools to help Core 3 researchers, including methods for interpolating, filtering, and segmenting DTI.
  • March 25, 2005. University of Utah visit of Harvard VA for collaborative work on DTMRI.
    • Presentation of non linear statistics for tensors by Tom Fletcher.
    • Possible collaboration on comparing new and old anisotropy measures in the context of Schizophrenia.

Key Investigators:

  • Utah: Tom Fletcher, Ross Whitaker.
  • PNL: Sylvain Bouix, Marek Kubicki, Martha Shenton.

Links: