Difference between revisions of "Rhesus EM Segmentation"

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* LEMS was used to segment 7 subjects imaged in alcohol naive and post induction states. No significant changes in the GM-WM volume ratio was obseved.  
 
* LEMS was used to segment 7 subjects imaged in alcohol naive and post induction states. No significant changes in the GM-WM volume ratio was obseved.  
  
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Revision as of 20:47, 6 February 2008

Home < Rhesus EM Segmentation

Objective:

  • Use the EM segmentation algorithm in slicer to segment Rhesus images.

Progress:

  • Results from 2007 Project Week
  • Followingup on a recommendation by Martin Syner, we have extended the algorithm from the project week to use a lobular parcellation map to automate the splitting of regions. We are calling this Lobulated EM Segmentation (LEMS). We are testing this method on a N=7 subject data set currently and a paper is in preparation.
  • LEMS was used to segment 7 subjects imaged in alcohol naive and post induction states. No significant changes in the GM-WM volume ratio was obseved.

MeanGmWmRatio.jpg IndGmWmRatio.jpg


Key Investigators:

  • Virginia Tech: Chris Wyatt
  • NAMIC: Kilian Pohl

Links: