Membre des anciens élèves

Activité

  • Étudiant au doctorat: nov. 2021 - 2025

Thèses de doctorat

  1. Towards Automatic Spinal Cord MRI Analysis for Improved Estimation of Imaging Biomarkers
    par , avec Julien Cohen-Adad et Sarath Chandar comme superviseurs.
    Polytechnique Montréal ⸺ mars 2026.
    [thesis]

Prépublications

  • Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?
    , Anne Kerbrat, Pierre Labauge, Tobias Granberg, Jason Talbott, Daniel S. Reich, Massimo Filippi, Rohit Bakshi, Virginie Callot, et Julien Cohen-Adad
    In ArXiv, 2022.
    [Medical Imaging meets NeurIPS, 2022]
    #DL, #Other
    [arXiv], [code]

Articles de conférence et de revue

2026

  1. Monitoring morphometric drift in lifelong learning segmentation of the spinal cord
    , Sandrine Bédard, Jan Valošek, Christoph S. Aigner, Elise Bannier, Josef Bednařík, Virginie Callot, Anna Combes, Armin Curt, Gergely David, Falk Eippert, Lynn Farner, Michael G Fehlings, Patrick Freund, Tobias Granberg, Cristina Granziera, RHSCIR Network Imaging Group, Ulrike Horn, Tomáš Horák, Suzanne Humphreys, Markus Hupp, Anne Kerbrat, Nawal Kinany, Shannon Kolind, Petr Kudlička, Anna Lebret, Lisa Eunyoung Lee, Caterina Mainero, Allan R. Martin, Megan McGrath, Govind Nair, Kristin P. O'Grady, Jiwon Oh, Russell Ouellette, Nikolai Pfender, Dario Pfyffer, Pierre-François Pradat, Alexandre Prat, Emanuele Pravatà, Daniel S. Reich, Ilaria Ricchi, Naama Rotem-Kohavi, Simon Schading-Sassenhausen, Maryam Seif, Andrew Smith, Seth A Smith, Grace Sweeney, Roger Tam, Anthony Traboulsee, Constantina Andrada Treaba, Charidimos Tsagkas, Zachary Vavasour, Dimitri Van De Ville, Kenneth Arnold Weber II, et Julien Cohen-Adad
    Imaging Neuroscience, 2026.
    #DL, #Other
    [mit], [arXiv]

2024

  1. Contrast-agnostic Spinal Cord Segmentation: A Comparative Study of ConvNets and Vision Transformers
    , Sandrine Bedard, Jan Valosek, et Julien Cohen-Adad
    Medical Imaging with Deep Learning (MIDL), 2024.
    #DL, #Other
    [openreview]

2023

  1. Label fusion and training methods for reliable representation of inter-rater uncertainty
    Andreanne Lemay, Charley Gros, et Julien Cohen-Adad
    The Journal of Machine Learning for Biomedical Imaging (MELBA), 2023.
    #DL, #Other
    [paper]