MJAHMADEE/Cataract-LMM
Advanced computer vision framework for surgical video analysis, featuring multi-task learning for cataract surgery procedure understanding, instrument segmentation, and skill assessment.
This project helps medical professionals like surgeons and educators automatically analyze cataract surgery videos. It takes raw surgical video footage as input and provides detailed outputs such as identified surgical instruments, recognized procedural phases (like 'lens removal'), and objective assessments of surgical skill. It's designed for those who need a comprehensive understanding of surgical performance and procedures for training, quality control, or research.
Use this if you need an automated system to break down cataract surgery videos into understandable components, identify instruments, track procedural phases, and evaluate surgical skill.
Not ideal if you are looking for analysis of non-cataract surgeries or require a simple, manual review process rather than a comprehensive AI framework.
Stars
10
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 21, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/MJAHMADEE/Cataract-LMM"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dipy/dipy
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for...
Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
Project-MONAI/MONAILabel
MONAI Label is an intelligent open source image labeling and learning tool.
neuronets/nobrainer
A framework for developing neural network models for 3D image processing.
Project-MONAI/monai-deploy-app-sdk
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify...