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Conference papers
Multiple Sclerosis lesion segmentation using an automated multimodal Graph Cut
Abstract : In this paper, we present an algorithm for Multiple Sclerosis (MS) lesion segmentation. Our method is fully automated and includes three main steps: 1. the computation of a rough total lesion load in order to optimize the parameter set of the following step; 2. the detection of lesions by graph cut initialized with a robust Expectation-Maximization (EM) algorithm; 3. the application of rules to remove false positives and to adjust the contour of the detected lesions. Our algorithm will be tested on the FLI 2016 MSSEG challenge data.
Cited literature [11 references]
https://www.hal.inserm.fr/inserm-01417378
Contributor : Nathalie Duchange <>
Submitted on : Thursday, December 15, 2016 - 3:41:46 PM
Last modification on : Friday, July 10, 2020 - 4:03:10 PM
Document(s) archivé(s) le : Thursday, March 16, 2017 - 6:02:15 PM
Contributor : Nathalie Duchange <>
Submitted on : Thursday, December 15, 2016 - 3:41:46 PM
Last modification on : Friday, July 10, 2020 - 4:03:10 PM
Document(s) archivé(s) le : Thursday, March 16, 2017 - 6:02:15 PM
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Beaumont et al, MSSEG_Challeng...
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