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Conference Papers Year : 2015

Automatic graph cut segmentation of multiple sclerosis lesions

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Abstract

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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Dates and versions

inserm-01304109 , version 1 (19-04-2016)

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  • HAL Id : inserm-01304109 , version 1

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Laurence Catanese, Olivier Commowick, Christian Barillot. Automatic graph cut segmentation of multiple sclerosis lesions. ISBI Longitudinal Multiple Sclerosis Lesion Segmentation Challenge, Apr 2015, New York, United States. ⟨inserm-01304109⟩
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