Difference between revisions of "Projects:SulciOutlining"
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Latest revision as of 01:01, 16 November 2013
Home < Projects:SulciOutliningBack to NA-MIC Collaborations, MGH Algorithms, Stony Brook University Algorithms
Automatic Outlining of Sulci on a Brain Surface
Description
We present a method to automatically extract certain key features on a surface. We apply this technique to outline sulci on the cortical surface of a brain, where the data is taken to be a 3D triangulated mesh formed from the segmentation of MR image slices. The problem is posed as energy minimization using penalizing the arc-length of segmenting curve using conformal factor involving the mean curvature of the underlying surface. The computation is made practical for dense meshes via the use of a sparse-field method to track the level set interfaces and regularized least-squares estimation of geometric quantities.
Key Investigators
- Georgia Tech: Allen Tannenbaum
- MGH: Peter Karasev
