A Composite Retinal Fundus and OCT Dataset with Detailed Clinical Markings of Retinal Layers and Retinal Lesions to Grade Macular and Glaucomatous Disorders

Published: 22 September 2021| Version 4 | DOI: 10.17632/trghs22fpg.4
Taimur Hassan,


This repository contains composite retinal fundus and OCT dataset for analyzing retinal layers, retinal lesions, and to diagnose normal and abnormal retinal diseases like Centrally Involved Diabetic Macular Edema, Acute Central Serous Retinopathy (CSR), Chronic CSR, Geographic Age-related Macular Degeneration (AMD), Neovascular AMD, and Glaucoma. Please cite the following papers if you want to use any part of this dataset: 1) T. Hassan, M. U. Akram, M. F. Masood, U. Yasin, “Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans”, Computers in Biology and Medicine, December 2018. 2) T. Hassan, M. U. Akram, N. Werghi, and N. Nazir, “RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology,” IEEE Journal of Biomedical and Health Informatics, March 2020.



National University of Sciences and Technology, Khalifa University of Science and Technology


Ophthalmology, Retina, Glaucoma, Central Serous Chorioretinopathy, Cystoid Macular Edema, Age-Related Macular Degeneration, Optical Coherence Tomography, Fundus Imaging