awesome-ophthalmology
github.com/chrisnielsen/awesome-ophthalmology ↗A curated list of awesome AI developments for ophthalmology
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me generative models resources from awesome-ophthalmology"
Installation instructions →What's inside
Papers
- (paper)Generative Models
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models (Mangaokar et al.)
- (paper)Generative Models
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network (Kamran et al.)
- (paper)Generative Models
VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers (Kamran et al.)
- (paper)Generative Models
Analysis of Macula on Color Fundus Images Using Heightmap Reconstruction Through Deep Learning (Tahghighi et al.)
- (paper)Generative Models
Attention2AngioGAN: Synthesizing Fluorescein Angiography from Retinal Fundus Images using Generative Adversarial Networks (Kamran et al.)
- (paper)Generative Models
Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography (Hassan et al.)
Showing a sample of 630 resources. View the full list on GitHub →