The research group CAMMA (Computational Analysis and Modeling of Medical Activities) led by Prof. Nicolas Padoy aims at developing new tools and methods based on computer vision, medical image analysis and machine learning to perceive, model, analyze and support clinician and staff activities in the operating room (OR) using the vast amount of digital data generated during surgeries. We are a joint group of the University of Strasbourg and the IHU MixSurg institute. We are also part of the wider research team AVR (Automatics, Vision and Robotics) in the ICube institute. We are located on the campus of Strasbourg’s University Hospital in the facilities of IHU Strasbourg and collaborate closely with the IRCAD institute and the Nouvel Hopital Civil.
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- multibypasstriplets2026_starter_kit Public
Codebase to get started with simple DINOV3 model for training and evaluation on the task of surgical action triplet recognition on the new MultiBypassT40 dataset.
CAMMA-public/multibypasstriplets2026_starter_kit’s past year of commit activity - Endoshare Public
CAMMA-public/Endoshare’s past year of commit activity - mbt40_challenge Public
CAMMA-public/mbt40_challenge’s past year of commit activity - OR_anonymization Public
CAMMA-public/OR_anonymization’s past year of commit activity - UltraSam Public
CAMMA-public/UltraSam’s past year of commit activity - camma-public.github.io Public
CAMMA-public/camma-public.github.io’s past year of commit activity - CliPPER Public
CAMMA-public/CliPPER’s past year of commit activity
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