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. | ||
− | [[Image:MeanGmWmRatio.jpg| | + | [[Image:MeanGmWmRatio.jpg|300pix|]] |
− | [[Image:IndGmWmRatio.jpg| | + | [[Image:IndGmWmRatio.jpg|300pix|]] |
Revision as of 20:47, 6 February 2008
Home < Rhesus EM SegmentationObjective:
- 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.
Key Investigators:
- Virginia Tech: Chris Wyatt
- NAMIC: Kilian Pohl
Links: