CAMMA-public/SelfSupSurg
Official repository for "Dissecting Self-Supervised Learning Methods for Surgical Computer Vision"
This project provides pre-trained models and scripts for analyzing surgical videos to understand what's happening during an operation. It takes raw surgical video frames as input and can identify surgical phases (like 'dissection' or 'clipping'), detect the presence of specific tools, or recognize action triplets (e.g., 'grasper grasping tissue'). This is useful for surgeons, researchers, and medical educators who want to develop better automated systems for surgical training, assistance, or quality control.
No commits in the last 6 months.
Use this if you are a medical researcher or developer working with surgical video data and need to accurately identify surgical phases, detect tools, or recognize actions without extensive manual video annotation.
Not ideal if you are looking for a ready-to-use, deployable application for real-time surgical assistance, as this project focuses on research and development of underlying models.
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Language
Python
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Last pushed
May 23, 2025
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