Projects:ShapeAnalysisOfCaudateAndCorpusCallosum

Shape Analysis for the caudate and corpus callosum data

Back to NA-MIC_Collaborations, Georgia Tech Algorithms, UNC Algorithms

Objective

To improve shape analysis of the caudate and to parcellate the corpus callosum based on function.

Progress

• UNC applied shape analysis pipeline to a dataset of manually segmented caudates of males with and without schizoptypal personality disorders. Differences were found mainly on the right caudates. No differences were found for regional parcellations of the corpus callosum.
• The open source shape analysis pipeline was transfered and installed at Harvard PNL.
• Harvard applied the UNC shape analysis software to a new dataset of manually segmented caudates of females with and without schizotypal personality disorder. The results confirmed previous findings in the male dataset. Statistically significant shape differences for the right caudate were found (see Fig 1).
• A less stringent method to correct for multiple comparisons (false discovery rate; FDR) was implemented (UNC) and applied to the the male and female caudata datasets (see Fig 2).

Key Investigators

• BWH: Sylvain Bouix, Marek Kubicki, James Levitt, Marc Niethammer, Martha Shenton
• UNC: Martin Styner, Isabelle Corouge, Guido Gerig
• Georgia Tech: Delphine Nain, Allen Tannenbaum

Fig 1. Right female caudate results

Medial

Lateral

p value

Fig 2. Right female caudate results, corrected for multiple comparisons (FDR)

Medial

Lateral

p value

Links

• Shape Analysis Progress Report
• DBP:Harvard:Collaboration:UNC
• Male caudate data