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Abstract #2845

Cerebral white matter lesions in multiple sclerosis: optimized automated segmentation and longitudinal follow-up

Philippe Tran1,2, Domitille Dempuré1, Ludovic Fillon2,3, Marie Chupin2,3, Urielle Thoprakarn1, and Jean-Baptiste Martini1

1Qynapse, Paris, France, 2Sorbonne Universités, UPMC Univ Paris 06, Inserm, CNRS, Institut du cerveau et de la moelle épinière (ICM) - Hôpital Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Inria Paris, Aramis project-team, Paris, France, 3CATI, Paris, France

In Multiple Sclerosis (MS), detection of T2-hyperintense white matter lesions on MRI has become a crucial criterion for early diagnosis and monitoring. In this study, we propose an accurate and reliable automated method for lesion segmentation and longitudinal follow-up, using color-scaled maps of lesion evolution depicting increasing and decreasing patterns. Validation of the cross-sectional segmentation has been performed on large samples of MS patients and shows good agreement with manual tracing. Through its reliability and robustness, the measures provided by our automated method of lesion quantification could be a valuable tool for clinical routine and clinical trials.

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