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Abstract #0039

Fast and accurate white matter bundle segmentation

Jakob Wasserthal1,2, Peter F. Neher1, and Klaus H. Maier-Hein1

1Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Medical Faculty, University of Heidelberg, Heidelberg, Germany

Automatic white matter fiber bundle segmentation in diffusion-weighted MRI brain scans enables detailed studies of white matter characteristics in healthy and diseased brains. Existing approaches combine processing steps such as tractography, atlas registration and cortical parcellation, resulting in pipelines that are computationally intensive and tedious to set up. We present a novel convolutional neural network-based approach that incorporates or circumvents most of the usually required processing steps (no registration, no tracking, no parcellation). We demonstrate in 105 subjects from the Human Connectome Project that the proposed approach is much faster than existing methods while providing more accurate results.

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