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Abstract #2370

Anatomical priors informed tractography. Evaluation on the DiSCo synthetic dataset

Thomas Durantel1, Julie Coloigner1, Emmanuel Caruyer1, Gabriel Girard2,3, and Olivier Commowick1
1Univ Rennes, INRIA, CNRS, INSERM, IRISA UMR 6074, Empenn ERL U-1228, F-35000, Rennes, France, 2Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 3Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada

Synopsis

Keywords: Data Processing, Tractography & Fibre ModellingWhite matter fiber tracking using diffusion magnetic resonance imaging (DWI) provides a powerful approach to map brain connections, but they are not completely reliable both in academic and clinical context. This is because most methods infer global connectivity from local information,leading to a high rate of false positive. We propose a method to include anatomical prior in the tractography algorithm. We show on synthetic DiSCo data that including this prior on two state-of-the-art tractography algorithms could improve the overall shape of the tractograms.

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