TissueImageAnalytics/cerberus
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification
This tool helps pathologists and medical researchers automatically analyze detailed features in histology images. It takes raw whole-slide images or image tiles as input and precisely identifies and classifies structures like glands, nuclei, and lumens. This enables users to quickly get quantified data on tissue composition for research or diagnostic purposes.
100 stars. No commits in the last 6 months.
Use this if you need to simultaneously segment and classify multiple features in histology images to understand tissue architecture and cellular characteristics.
Not ideal if you are looking for a tool to train new models or if your images are not histology slides.
Stars
100
Forks
15
Language
Python
License
GPL-3.0
Category
Last pushed
Nov 27, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TissueImageAnalytics/cerberus"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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