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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'''Key Investigators:'''
 
'''Key Investigators:'''
  
* Virginia Tech: Chris Wyatt
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* Virginia Tech: Chris Wyatt, Vidya Rajagopalan
 
* NAMIC: Kilian Pohl  
 
* NAMIC: Kilian Pohl  
  
 
'''Links:'''
 
'''Links:'''
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* A tutorial for EMSegment (in Slicer2.X) was developed for non-human primate data. The tutorial and the images are available [http://bsl.ece.vt.edu/download/NHP-EMSTut.zip here]

Latest revision as of 03:45, 13 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, Vidya Rajagopalan
  • NAMIC: Kilian Pohl

Links:

  • A tutorial for EMSegment (in Slicer2.X) was developed for non-human primate data. The tutorial and the images are available here