Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

Gros, Charley; Leener, Benjamin De; Badji, Atef; Maranzano, Josefina; Eden, Dominique; Talbott, Jason F.; Zhuoquiong, Ren; Granberg, Tobias; Ouellette, Russell; Tachibana, Yasuhiko; Hori, Masaaki; Kamiya, Kazutaka; Chougar, Lydia; Stawiarz, Leszek; Hillert, Jan; Bannier, Élise; Kerbrat, Anne; Edan, Gilles; Labauge, Pierre; Callot, Virginie; Pelletier, Jean; Audoin, Bertrand; Rasoanandrianina, Henitsoa; Brisset, Jean-Christophe; Valsasina, Paola; Rocca, Maria A.; Filippi, Massimo; Bakshi, Rohit; Tauhid, Shahamat; Prados, Ferrán; Yiannakas, Marios C.; Kearney, Hugh; Ciccarelli, Olga; Smith, Seth A.; Treabă, Constantina Andrada; Mainero, Caterina; Lefeuvre, Jennifer; Reich, Daniel S.; Nair, Govind; Auclair, Vincent; McLaren, Donald G.; Martín, Allan; Fehlings, Michael G.; Vahdat, Shahabeddin; Khatibi, Ali; Doyon, Julien; Shepherd, Timothy M.; Charlson, Erik; Narayanan, Sridar; Cohen‐Adad, Julien

doi:10.48550/arxiv.1805.06349

2018

DOI: 10.48550/arxiv.1805.06349

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Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

Charley Gros¹,

Benjamin De Leener²,

Atef Badji³

et al.

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