Search Results for author: Virginie Callot

Found 3 papers, 3 papers with code

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

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.

Continual Learning Lesion Segmentation +1

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2D Multi-Class Model for Gray and White Matter Segmentation of the Cervical Spinal Cord at 7T

1 code implementation • 13 Oct 2021 • Nilser J. Laines Medina, Charley Gros, Julien Cohen-Adad, Virginie Callot, Arnaud Le Troter

The spinal cord (SC), which conveys information between the brain and the peripheral nervous system, plays a key role in various neurological disorders such as multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS), in which both gray matter (GM) and white matter (WM) may be impaired.

Data Augmentation Segmentation

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

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.

Lesion Segmentation Segmentation

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Code

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