Authors
Olivier Commowick, Audrey Istace, Michael Kain, Baptiste Laurent, Florent Leray, Mathieu Simon, Sorina Camarasu Pop, Pascal Girard, Roxana Ameli, Jean-Christophe Ferré, Anne Kerbrat, Thomas Tourdias, Frédéric Cervenansky, Tristan Glatard, Jeremy Beaumont, Senan Doyle, Florence Forbes, Jesse Knight, April Khademi, Amirreza Mahbod, Chunliang Wang, Richard Mckinley, Franca Wagner, John Muschelli, Elizabeth Sweeney, Eloy Roura, Xavier Lladó, Michel M Santos, Wellington P Santos, Abel G Silva-Filho, Xavier Tomas-Fernandez, Hélène Urien, Isabelle Bloch, Sergi Valverde, Mariano Cabezas, Francisco Javier Vera-Olmos, Norberto Malpica, Charles Guttmann, Sandra Vukusic, Gilles Edan, Michel Dojat, Martin Styner, Simon K Warfield, François Cotton, Christian Barillot
Publication date
2018/9/12
Journal
Scientific reports
Volume
8
Issue
1
Pages
13650
Publisher
Nature Publishing Group UK
Description
We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and …
Scholar articles
O Commowick, A Istace, M Kain, B Laurent, F Leray… - Scientific reports, 2018