Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging
Journal of Biomedical Imaging - Recent Advances in Neuroimaging Methodology
Probabilistic clustering and quantitative analysis of white matter fiber tracts
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Probabilistic fiber tracking using particle filtering
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
MR diffusion-based inference of a fiber bundle model from a population of subjects
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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The idea underpinning the work we present herein is to design robust and objective tools for brain white matter (WM) morphometry. We focus on WM tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (HARDI). The definition of the tract mean line derives directly from the geometry of the tract fibres. We determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average HARDI models along the tract mean lines. This way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.