Longitudinal multiple sclerosis lesion segmentation: Resource and challenge

Aaron Carass 1, 2, * Snehashis Roy 3 Amod Jog 1 Jennifer L. Cuzzocreo 4 Elizabeth Magrath 3 Adrian Gherman 2 Julia Button 4 James Nguyen 4 Ferran Prados 5, 6 Carole Sudre 6 Manuel Jorge Cardoso 7, 6 Niamh Cawley 5 Olga Ciccarelli 5 Claudia Wheeler-Kingshott 5 Sébastien Ourselin 6, 7 Laurence Catanese 8 Hrishikesh Deshpande 9 Pierre Maurel 9 Olivier Commowick 9 Christian Barillot 9 Xavier Tomas-Fernandez 10 Simon Warfield 10 Suthirth Vaidya 11 Abhijith Chunduru 11 Ramanathan Muthuganapathy 11 Ganapathy Krishnamurthi 11 Andrew Jesson 12 Tal Arbel 12 Oskar Maier 13 Heinz Handels 13 Leonardo Iheme 14 Devrim Unay 14 Saurabh Jain 15 Diana Sima 15 Dirk Smeets 15 Mohsen Ghafoorian 16 Bram Platel 17 Ariel Birenbaum 18 Hayit Greenspan 19 Pierre-Louis Bazin 20 Peter Calabresi 4 Ciprian Crainiceanu 21 Lotta Ellingsen 2, 22 Daniel Reich 4, 23 Jerry Prince 2 Dzung Pham 8
Abstract : In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters.
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NeuroImage, Elsevier, 2017, 148, pp.77 - 102. 〈10.1016/j.neuroimage.2016.12.064〉
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Aaron Carass, Snehashis Roy, Amod Jog, Jennifer L. Cuzzocreo, Elizabeth Magrath, et al.. Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage, Elsevier, 2017, 148, pp.77 - 102. 〈10.1016/j.neuroimage.2016.12.064〉. 〈inserm-01480156〉

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