Automatic graph cut segmentation of multiple sclerosis lesions - Inserm - Institut national de la santé et de la recherche médicale
Communication Dans Un Congrès Année : 2015

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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Dates et versions

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

Identifiants

  • HAL Id : inserm-01304109 , version 1

Citer

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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