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Erschienen in:
2005 | OriginalPaper | Buchkapitel
MR Diffusion-Based Inference of a Fiber Bundle Model from a Population of Subjects
verfasst von : V. El Kouby, Y. Cointepas, C. Poupon, D. Rivière, N. Golestani, J. -B. Poline, D. Le Bihan, J. -F. Mangin
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005
Verlag: Springer Berlin Heidelberg
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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.