Helper framework for Medical Image Analysis

An implementation of "Fundus Image Transformation Revisited: Towards Determining More Accurate Registrations" in MATLAB.

Api to host Retfound

Optic disk is detected using image processing

[ACL 2024] Evaluation of the Fundus News Scraper

Official repository of the paper "RRWNet: Recursive Refinement Network for Effective Retinal Artery/Vein Segmentation and Classification", accepted for publication at Expert Systems with Applications (2024).

Standardized Multi-Channel Dataset for Glaucoma (SMDG-19) is a collection and standardization of 19 public full-fundus glaucoma images and associated metadata.

The Hamilton Eye Institute Macular Edema Dataset (HEI-MED) (formerly DMED) is a collection of 169 fundus images to train and test image processing algorithms for the detection of exudates and diabetic macular edema. The images have been collected as part of a telemedicine network for the diagnosis of diabetic retinopathy

A python package to read, analyse and visualize OCT and fundus data from various sources.

Actively maintained and comprehensive public glaucoma dataset catalog

PyTorch implementation for our paper on TMI2022: Retinal Vessel Segmentation with Skeletal Prior and Contrastive Loss

exudates detection using hybrid approach (Image Morphology & Machine Learning)

Patho-GAN: interpretation + medical data augmentation. Code for paper work "Explainable Diabetic Retinopathy Detection and Retinal Image Generation"

[MICCAI'21] [Tensorflow] Retinal Vessel Segmentation using a Novel Multi-scale Generative Adversarial Network

Project for segmentation of blood vessels, microaneurysm and hardexudates in fundus images.

Tools for extracting the raw optical coherence tomography (OCT) and fundus data from proprietary file formats.