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Abstract #4294

White Matter Inter-tract Connectivity Using Cosine Similarity between Population Kernel Densities of Diffusion Measures

David Lee1, Ashish Sahib1, Antoni Kubicki1, Katherine Narr1, and Shantanu Joshi1
1UCLA, Los Angeles, CA, United States

Pairwise inter-tract correlations of the mean diffusion measures have been used to infer structural connectivity among major white matter (WM) fiber tract pathways. Instead of using the mean, we propose a novel approach of constructing kernel density distributions to represent population variability of fractional anisotropy. We also propose the cosine similarity metric between the full shapes of the kernel densities to investigate inter-tract connectivity among the fiber tracts. Our representation and the shape similarity measure is a better predictor of the short- and long-range connectivity disruptions in WM tracts in major depressive disorder patients compared to the conventional mean-based approach.

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