NA-MIC/Projects/External Collaboration/Measuring Alcohol and Stress Interaction
- BWH: Kilian Pohl
- Virginia Tech: Chris Wyatt, Vidya Rajagopalan
- Kitware: Luis Ibanez
The objectives of this project are to:
- Optimize the EM Brain Classifier in Slicer on MRI images of vervets.
- Segment data from N subjects.
- Optimize GM/WM/CSF segmentation so that calculation of GM/WM volume and ratios between the two states can be automated.
- Optimize hippocampus, putamen and caudate segmentation so that volume comparison between states can be performed.
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.
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
- Developed an ITK utility for multiresolution demons registration. (Source code available for download from the NAMIC sandbox)