Automatic graph cut segmentation of multiple sclerosis lesions
Résumé
A fully automated segmentation algorithm for Multiple Sclerosis (MS) lesions is presented. Our method includes two main steps: the detection of lesions by graph cut initialized with a robust Expectation-Maximization (EM) algorithm and the application of rules to remove false positives. Our algorithm will be tested on the ISBI 2015 challenge longitudinal data. For each patient, a unique parameter set is used to run the algorithm.
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