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.
Bibliographical noteFunding Information:
This study was supported by NIH R01 grants MH097268 , NS080655 , AG040060 , and EB008432 . Additional support was provided by the National Health and Medical Research Council (NHMRC 486682 , 1009064 ), Australia. Genotyping was supported by NHMRC ( 389875 ).
- Curve registration
- Geodesic distance
- Longest path
- Maximum density path
- Shortest path