DengPingFan/PraNet
PraNet: Parallel Reverse Attention Network for Polyp Segmentation, MICCAI 2020 (Oral). Code using Jittor Framework is available.
This project helps medical professionals accurately identify and segment polyps in colonoscopy images. It takes an input image from a colonoscopy and outputs a precise mask highlighting the polyp's exact location and boundaries. End-users are medical doctors, gastroenterologists, or researchers working on automated diagnostic tools.
532 stars.
Use this if you need a highly accurate tool for segmenting polyps within medical imaging for diagnostic assistance or research.
Not ideal if you are looking for a general-purpose image segmentation tool outside of medical imaging, or specifically outside of polyp detection.
Stars
532
Forks
130
Language
Python
License
—
Category
Last pushed
Dec 11, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/DengPingFan/PraNet"
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...