Automatic clustering and population analysis of white matter tracts using maximum density paths.

Published

Journal Article

We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.

Full Text

Duke Authors

Cited Authors

  • Prasad, G; Joshi, SH; Jahanshad, N; Villalon-Reina, J; Aganj, I; Lenglet, C; Sapiro, G; McMahon, KL; de Zubicaray, GI; Martin, NG; Wright, MJ; Toga, AW; Thompson, PM

Published Date

  • August 2014

Published In

Volume / Issue

  • 97 /

Start / End Page

  • 284 - 295

PubMed ID

  • 24747738

Pubmed Central ID

  • 24747738

Electronic International Standard Serial Number (EISSN)

  • 1095-9572

International Standard Serial Number (ISSN)

  • 1053-8119

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2014.04.033

Language

  • eng