Ravi Hassanaly

Aramis Lab. Paris Brain Institute. rhassana96@gmail.com

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I am a doctoral candidate at Aramis Lab in the Paris Brain Institute under the supervision of Ninon Burgos and Olivier Colliot. My main topic of research is the use of deep learning methods for medical imaging computing. More specifically I work with deep generative models for anomaly detection on neuroimages.

My research focus on methodological development of generative models and anomaly detection technics as well as their clinical applications. I am also strongly implicated in open source projects.

Graduated from Ecole Centrale de Lyon and Université de Lyon 1 in 2020, I have a computer science background. My expected PhD graduation time at Sorbonne University is Spring 2024.

I also love kicking balls (aka playing soccer) and riding bikes !

news

Feb 18, 2024 Hello from San Diego ! #SPIEMedicalImaging2024
Jan 1, 2024 Paper accepted in MELBA special issue for generative models !
Dec 1, 2023 Paper accepted for SPIE Medical Imaging 2024 in San Diego.
Oct 9, 2023 Hello from Vancouver ! #MICCAI2023
Oct 8, 2023 Presentation at DGM4MICCAI workshop

selected publications

  1. MELBA
    Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to Brain FDG PET
    Ravi Hassanaly, Camille Brianceau, Maëlys Solal, and 2 more authors
    Machine Learning for Biomedical Imaging, 2024
  2. DGM4MICCAI
    Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches
    Ravi Hassanaly, Camille Brianceau, Olivier Colliot, and 1 more author
    In Deep Generative Models workshop at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), 2023
  3. ClinicaDL: An open-source deep learning software for reproducible neuroimaging processing
    Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, and 4 more authors
    Computer Methods and Programs in Biomedicine, 2022