Papers and Public Datasets for Diabetic Retinopathy Detection

DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN models with GradCam score for interpretability,

Code for the paper "nnMobileNet: Rethinking CNN for Retinopathy Research"

A Django application developped for classification of a diabetes complication that affects eyes

Extended Retinopathy Detection Challenge with the Regression Activation Map for visual explaination

Detecting Diabetic Retinopathy using Deep learning algorithm - Convolution neural network (Resnet-152) using PyTorch + GUI + SMS notification

Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)

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

Identifying retina images with diabetic retinopathy using convolutional neural networks.

🥉 (Bronze medal - 163rd place - Top 6%) Repository for the "APTOS 2019 Blindness Detection" Kaggle competition.

Diabetic Retinopathy is a very common eye disease in people having diabetes. This disease can lead to blindness if not taken care of in early stages, This project is a part of the whole process of identifying Diabetic Retinopathy in its early stages. In this project, we'll extract basic features which can help us in identifying Diabetic Retinopa…

A Deep Convolutional Neural Network for Diabetic Retinopathy classification

Deep Learning Project on Diabetic Retinopathy Detection - TUM Team ID 47

O-MedAL: Online Active Deep Learning for Medical Image Analysis. This repo contains code for the paper.

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

New project, powerful model

Classification of Fundus Images into 5 stages of Diabetic Retinopathy, and segmentation of blood vessels in fundus images

Diabetic classification based on retinal images