orobix/retina-unet

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1354 stars · 464 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python implementation of a U-Net convolutional neural network for segmenting blood vessels in retina fundus images. It performs binary pixel-wise classification and achieves state-of-the-art AUC results on the DRIVE and STARE datasets.

Use cases

• segment blood vessels in retina fundus images
• train a U-Net model for medical image segmentation
• reproduce state-of-the-art results on the DRIVE dataset
• apply deep learning to retinal vessel detection
• learn how to implement pixel-wise binary classification with CNNs

When to choose

• you need a proven U-Net baseline for retinal vessel segmentation
• you want to benchmark against DRIVE/STARE dataset results
• you are studying medical image segmentation with CNNs

When to avoid

• you need a maintained, production-ready medical imaging pipeline
• you require a permissive or clearly defined license
• you need segmentation of other anatomical structures without modification

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision deep-learning computer-vision image-processing healthcare python u-net medical-imaging semantic-segmentation retina fundus-images keras drive-dataset gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="orobix/retina-unet")