Tensorlines: advection-diffusion based propagation through diffusion tensor fields
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Regularized Stochastic White Matter Tractography Using Diffusion Tensor MRI
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Mean q-Ball Strings Obtained by Constrained Procrustes Analysis with Point Sliding
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
A Statistical Model of White Matter Fiber Bundles Based on Currents
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Shape modeling and clustering of white matter fiber tracts using Fourier descriptors
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
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This paper proposes a method to infer a high level model of the white matter organization from a population of subjects using MR diffusion imaging. This method takes as input for each subject a set of trajectories stemming from any tracking algorithm. Then the inference results from two nested clustering stages. The first clustering converts each individual set of trajectories into a set of bundles supposed to represent large white matter pathways. The second clustering matches these bundles across subjects in order to provide a list of candidates for the bundle model. The method is applied on a population of eleven subjects and leads to the inference of 17 such candidates.