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The understanding of neurodegenerative diseases undoubtedly passes throughthe study of human brain white matter fiber tracts. To date, diffusion magneticresonance imaging (dMRI) is the unique technique to obtain information aboutthe neural architecture of the human brain, thus permitting the study of whitematter connections and their integrity. However, a remaining challenge of thedMRI community is to better characterize complex fiber crossing configurations,where diffusion tensor imaging (DTI) is limited but high angular resolutiondiffusion imaging (HARDI) now brings solutions. This paper investigates thedevelopment of both identification and classification process of the localwater diffusion phenomenon based on HARDI data to automatically detect imagingvoxels where there are single and crossing fiber bundle populations. Thetechnique is based on knowledge extraction processes and is validated on a dMRIphantom dataset with ground truth.

Local Water Diffusion Phenomenon Clustering From High Angular Resolution Diffusion Imaging (HARDI)