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

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

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

[TMI'22] "AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentation".

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

Deep learning applied to Kaggle's Diabetic retinopathy dataset.

Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models

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…

Joint Vessel Segmentation and Deformable Registration on Multi-Modal Retinal Images based on Style Transfer

Deep learning based retinal vessel segmentation for fluorescein angiography retinal images, IEEE Trans. Image Processing, 2020

Deep learning based retinal vessel segmentation for wide-field fundus photography retinal images, IEEE Trans. Medical Imaging, 2020

ICML Workshop 18 - Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model

Retinal image processing with python and opencv

Diabetic classification based on retinal images

Code for the paper "OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing"

ACCV'18 workshop - Synthesizing New Retinal Symptom Images by Multiple Generative Models

Predicting heart disease 🦠 with Retinal Vessel 🚢 Segmentation using Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) and Attention R2U-Net (Zahangir et al.) -> Ongoing Research..

[ICIP'20] [Tensorflow] Improving robustness using Joint Supervised-Unsupervised Network for OCT images