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

Prasad, Gautam, Joshi, Shantanu H., Jahanshad, Neda, Villalon-Reina, Julio, Aganj, Iman, Lenglet, Christophe, Guillermo Sapiro, McMahon, Katie L., de Zubicaray, Greig I., Martin, Nicholas G., Wright, Margaret J., Toga, Arthur W. and Thompson, Paul M. (2014) Automatic clustering and population analysis of white matter tracts using maximum density paths. NeuroImage, 97 284-295. doi:10.1016/j.neuroimage.2014.04.033

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Author Prasad, Gautam
Joshi, Shantanu H.
Jahanshad, Neda
Villalon-Reina, Julio
Aganj, Iman
Lenglet, Christophe
Guillermo Sapiro
McMahon, Katie L.
de Zubicaray, Greig I.
Martin, Nicholas G.
Wright, Margaret J.
Toga, Arthur W.
Thompson, Paul M.
Title Automatic clustering and population analysis of white matter tracts using maximum density paths
Journal name NeuroImage   Check publisher's open access policy
ISSN 1095-9572
1053-8119
Publication date 2014
Sub-type Article (original research)
DOI 10.1016/j.neuroimage.2014.04.033
Open Access Status File (Author Post-print)
Volume 97
Start page 284
End page 295
Total pages 12
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2015
Language eng
Abstract 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.
Keyword Atlas
Brain
Clustering
Connectivity
Curve registration
Dijkstra
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Psychology Publications
Centre for Advanced Imaging Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 10 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 11 times in Scopus Article | Citations
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Created: Wed, 21 May 2014, 16:49:05 EST by Sandrine Ducrot on behalf of Centre for Advanced Imaging