2 code implementations • 16 May 2018 • Charley Gros, Benjamin De Leener, Atef Badji, Josefina Maranzano, Dominique Eden, Sara M. Dupont, Jason Talbott, Ren Zhuoquiong, Yaou Liu, Tobias Granberg, Russell Ouellette, Yasuhiko Tachibana, Masaaki Hori, Kouhei Kamiya, Lydia Chougar, Leszek Stawiarz, Jan Hillert, Elise Bannier, Anne Kerbrat, Gilles Edan, Pierre Labauge, Virginie Callot, Jean Pelletier, Bertrand Audoin, Henitsoa Rasoanandrianina, Jean-Christophe Brisset, Paola Valsasina, Maria A. Rocca, Massimo Filippi, Rohit Bakshi, Shahamat Tauhid, Ferran Prados, Marios Yiannakas, Hugh Kearney, Olga Ciccarelli, Seth Smith, Constantina Andrada Treaba, Caterina Mainero, Jennifer Lefeuvre, Daniel S. Reich, Govind Nair, Vincent Auclair, Donald G. McLaren, Allan R. Martin, Michael G. Fehlings, Shahabeddin Vahdat, Ali Khatibi, Julien Doyon, Timothy Shepherd, Erik Charlson, Sridar Narayanan, Julien Cohen-Adad
The goal of this study was to develop a fully-automatic framework, robust to variability in both image parameters and clinical condition, for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data.
no code implementations • 20 Aug 2020 • Zachary M. C. Baum, Ester Bonmati, Lorenzo Cristoni, Andrew Walden, Ferran Prados, Baris Kanber, Dean C. Barratt, David J. Hawkes, Geoffrey J M Parker, Claudia A M Gandini Wheeler-Kingshott, Yipeng Hu
The diagnosis assistance module can then be trained with data that are deemed of sufficient quality, guaranteed by the closed-loop feedback mechanism from the quality assessment module.
1 code implementation • 22 Jan 2021 • Vien Ngoc Dang, Francesco Galati, Rosa Cortese, Giuseppe Di Giacomo, Viola Marconetto, Prateek Mathur, Karim Lekadir, Marco Lorenzi, Ferran Prados, Maria A. Zuluaga
First, deep learning techniques tend to show poor performances at the segmentation of relatively small objects compared to the size of the full image.
no code implementations • 12 Sep 2023 • Francesco Galati, Daniele Falcetta, Rosa Cortese, Barbara Casolla, Ferran Prados, Ninon Burgos, Maria A. Zuluaga
We present a semi-supervised domain adaptation framework for brain vessel segmentation from different image modalities.