Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics

Jin, Yan, Shi, Yonggang, Zhan, Liang, Gutman, Boris, de Zubicaray, Greig I., McMahon, Katie L., Wright, Margaret J., Toga, Arthur W. and Thompson, Paul M. (2014) Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics. NeuroImage, 100 75-90. doi:10.1016/j.neuroimage.2014.04.048


Author Jin, Yan
Shi, Yonggang
Zhan, Liang
Gutman, Boris
de Zubicaray, Greig I.
McMahon, Katie L.
Wright, Margaret J.
Toga, Arthur W.
Thompson, Paul M.
Title Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics
Journal name NeuroImage   Check publisher's open access policy
ISSN 1053-8119
1095-9572
Publication date 2014-10-15
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.neuroimage.2014.04.048
Volume 100
Start page 75
End page 90
Total pages 16
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2015
Language eng
Abstract To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion – a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.
Keyword HARDI
Tractography
Fiber clustering
Label fusion
Genetic heritability
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
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 25 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 31 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 21 May 2014, 16:38:10 EST by Sandrine Ducrot on behalf of Centre for Advanced Imaging