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* Corresponding author 1 VisAGeS - Vision, Action et Gestion d-informations en Santé INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE 2 CREATIS - Centre de recherche en applications et traitement de l-image pour la santé 3 CHU Lyon

Abstract : This proceedings book gathers methodological papers of segmentation methods evaluated at the first MICCAI Challenge on Multiple Sclerosis Lesions Segmentation Challenge Using a Data Management and Processing Infrastructure. This challenge took place as part of an effort of the OFSEP French registry on mul- tiple sclerosis aiming at gathering, for research purposes, imaging data, clinical data and biological samples from the French population of multiple sclerosis sub- jects and FLI France Life Imaging, devoted to setup a national distributed e-infrastructure to manage and process medical imaging data. These joint ef- forts are directed towards automatic segmentation of MRI scans of MS patients to help clinicians in their daily practice. This challenge took place at the MICCAI 2016 conference, on October 21st 2016.More precisely, the goals of this challenge were multiple. It first aimed at evaluating state-of-the-art and advanced segmentation methods from the participants on a database following a standard protocol. For this, both lesion detection how many lesions are detected and lesion segmentation how pre- cise the lesions are delineated were evaluated on a multi-centric database 38 patients from four different centers, imaged on 1.5 or 3T scanners, each patient being manually annotated by seven experts from three different French centers, located in Bordeaux, Lyon and Rennes.This challenge was also the occasion to perform this advanced evaluation on a common infrastructure, provided by FLI. As such, challengers were asked to provide their pipeline as a Docker container image. After integration in the VIP platform, the challengers pipelines were then evaluated independently by the challenge organization team, the testing data and evaluation results being queried and stored in a Shanoir database. This infrastructure enabled a fair comparison of the algorithms in terms of running time comparison and ensuring all algorithms were run with the same parameters for each patient which is required for a truly automatic segmentation. These proceedings do not include results of the evaluation, rather the evaluated methods descriptions. Evaluation results are available on the challenge website6 from the day of the challenge.As a conclusion note, the organizers of the challenge are welcoming new pipelines to be evaluated after the challenge itself. Interested teams may go on the challenge website to register their new method and evaluate it on our data.





Autor: Olivier Commowick - Frédéric Cervenansky - Roxana Ameli -

Fuente: https://hal.archives-ouvertes.fr/



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