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Abstract #1983

Integration of Probabilistic Atlas and Graph Cuts for Automated Segmentation of Multiple Sclerosis lesions

Francesca Galassi1, Olivier Commowick1, and Christian Barillot1

1Univ Rennes, Inria, CNRS, IRISA UMR 6074, VISAGES ERL U-1228, F-35000, Rennes, France

We propose a framework for automated segmentation of Multiple Sclerosis (MS) lesions from MR brain images. It integrates a priori tissues and MS lesions information into a Graph-Cuts algorithm for improved segmentation results. We formulate the energy terms to include a priori information as well as the information derived directly from the MR images. We validate our method on a dataset of 37 MS subjects with a broad range of lesion loads. Results indicate that integrating a priori information with the information derived from the images can improve the segmentation outcome.

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