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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- ivtmetrics Public template
A Python evaluation metrics package for surgical action triplet recognition
CAMMA-public/ivtmetrics’s past year of commit activity - peskavlp.github.io Public
CAMMA-public/peskavlp.github.io’s past year of commit activity - SelfPose3d Public
Official code for "SelfPose3d: Self-Supervised Multi-Person Multi-View 3d Pose Estimation"
CAMMA-public/SelfPose3d’s past year of commit activity - SurgLatentGraph Public
This repository contains the code associated with our 2023 TMI paper "Latent Graph Representations for Critical View of Safety Assessment" and our MICCAI 2023 paper "Encoding Surgical Videos as Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning".
CAMMA-public/SurgLatentGraph’s past year of commit activity - surgical-imagen Public
CAMMA-public/surgical-imagen’s past year of commit activity