1 code implementation • 27 Oct 2022 • Enamundram Naga Karthik, Anne Kerbrat, Pierre Labauge, Tobias Granberg, Jason Talbott, Daniel S. Reich, Massimo Filippi, Rohit Bakshi, Virginie Callot, Sarath Chandar, Julien Cohen-Adad
Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem.
no code implementations • 9 Aug 2021 • Haykel Snoussi, Julien Cohen-Adad, Benoit Combes, Elise Bannier, Slimane Tounekti, Anne Kerbrat, Christian Barillot, Emmanuel Caruyer
The diffusion-based metrics involved are extracted from the diffusion tensor imaging and Ball-and-Stick models and quantified for every cervical vertebral level using a collection of image processing methods and an atlas-based approach.
no code implementations • 9 Aug 2021 • Haykel Snoussi, Julien Cohen-Adad, Olivier Commowick, Benoit Combes, Elise Bannier, Soizic Leguy, Anne Kerbrat, Christian Barillot, Emmanuel Caruyer
Besides, subjective evaluation of the quality of the correction of healthy subjects images was performed by three expert raters.
no code implementations • 8 Aug 2021 • Haykel Snoussi, Emmanuel Caruyer, Benoit Combes, Olivier Commowick, Elise Bannier, Anne Kerbrat, Julien Cohen-Adad, Christian Barillot
In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain images, this is known as the clinical-radiological paradox (CRP).
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.