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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- camma_dataset_overlaps Public
CAMMA-public/camma_dataset_overlaps’s past year of commit activity - MultiBypass140 Public
CAMMA-public/MultiBypass140’s past year of commit activity - attention-tripnet Public
CAMMA-public/attention-tripnet’s past year of commit activity - tripnet Public
CAMMA-public/tripnet’s past year of commit activity - cholect50 Public
A repository for surgical action triplet dataset. Data are videos of laparoscopic cholecystectomy that have been annotated with <instrument, verb, target> labels for every surgical fine-grained activity.
CAMMA-public/cholect50’s past year of commit activity - rendezvous Public
A transformer-inspired neural network for surgical action triplet recognition from laparoscopic videos.
CAMMA-public/rendezvous’s past year of commit activity
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