Section: New Results
Image processing on Diffusion Weighted Magnetic Resonance Imaging
Clustering and classification ofwhite matter fibers from Diffusion Tensor Imaging (DTI)
Participants : Meena Mani, Christian Barillot.
This project can be broken down into three major aspects:
Spectral clustering of DTI fibers using different distance metrics. Two distance metrics, a mean closest point (MCP) and a barymetric distance were found to give the best clustering results on data sets such as the corpus callosum.
Spectral clustering using the Nystrom approximation to handle large data sets. This included an investigation of the error involved when the Nystrom approximation is used.
Clustering and statistical quantitative analysis of DTI fibers using a comprehensive Riemannian framework that allows for a joint analysis of features in a consistent manner. This work was done with Professor Anuj Srivastava at Florida State University. A paper based on this work was submitted to the ISBI 2010 conference.