Difference between revisions of "NA-MIC/Projects/External Collaboration/Measuring Alcohol and Stress Interaction"

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<h1>Progress</h1>
 
<h1>Progress</h1>
 
Prior to the project week:
 
Prior to the project week:
# Study data on 8 subjects at two time points (alcohol naive and post-induction) organized
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* Study data on 8 subjects at two time points (alcohol naive and post-induction) organized
# GM/WM/CSF atlas will be constructed for the study data.  
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* GM/WM/CSF atlas will be constructed for the study data.  
  
 
During Project Week
 
During Project Week
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1 Optimized segmentation parameters for vervet data
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* Optimized segmentation parameters for vervet data
2 Improved accuracy of subcortical segmentation in rhesus data set
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* Improved accuracy of subcortical segmentation in rhesus data set
  
 
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3 Developed an ITK utility for multiresolution demons registration. (Source code available for download from the NAMIC sandbox)
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* Developed an ITK utility for multiresolution demons registration. (Source code available for download from the NAMIC sandbox)
 
   {|
 
   {|
 
|[[Image:CheckerB4Reg_Screenshot.jpg |thumb|320px|Checker Image of source and target before registration ]]
 
|[[Image:CheckerB4Reg_Screenshot.jpg |thumb|320px|Checker Image of source and target before registration ]]

Revision as of 21:54, 26 June 2008

Home < NA-MIC < Projects < External Collaboration < Measuring Alcohol and Stress Interaction



Key Investigators

  • Wake Forest: Bob Kraft, Jim Daunais
  • BWH: Kilian Pohl
  • Virginia Tech: Chris Wyatt, Vidya Rajagopalan
  • Kitware: Luis Ibanez

Objective

The objectives of this project are to:

  1. Optimize the EM Brain Classifier in Slicer on MRI images of vervets.
  2. Segment data from N subjects.
  3. Optimize GM/WM/CSF segmentation so that calculation of GM/WM volume and ratios between the two states can be automated.
  4. Optimize hippocampus, putamen and caudate segmentation so that volume comparison between states can be performed.


Approach, Plan

We will use the current implementation of the EM Segmenter in Slicer. Using a manual segmentation as an estimate of ground truth in a single subject, we will optimize the EM segmenter parameters over the classification error and running time.

Progress

Prior to the project week:

  • Study data on 8 subjects at two time points (alcohol naive and post-induction) organized
  • GM/WM/CSF atlas will be constructed for the study data.

During Project Week


  • Optimized segmentation parameters for vervet data
  • Improved accuracy of subcortical segmentation in rhesus data set
Segmentation of major tissue classes in for vervet subject
Subcortical Segmentation of Rhesus subject
  • Developed an ITK utility for multiresolution demons registration. (Source code available for download from the NAMIC sandbox)
Checker Image of source and target before registration
Checker Image of source and target after registration




References