Abstract
White matter segmentation is an essential step to study whole-brain structural connectivity via diffusion MRI white matter tractography. One important goal of segmentation methods is to improve consistency of the white matter segmentations across multiple subjects. In this study, we quantitatively compare two popular white matter segmentation strategies, i.e., a cortical-parcellation-based method and a groupwise fiber clustering method, to investigate their performance on consistency. Our experimental results indicate that the groupwise fiber clustering generated more consistent segmentations with lower variability across subjects. This suggests that the fiber clustering strategy could provide a potential alternative to the traditional cortical-parcellation-based brain connectivity modeling methods.
Published Version
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