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

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.

本存储库包含用于分析视网膜层、视网膜病变以及诊断正常及异常视网膜疾病（如中心性糖尿病黄斑水肿、急性中央性浆液性视网膜病变（CSR）、慢性CSR、地域性年龄相关性黄斑变性（AMD）、新生血管AMD和青光眼）的复合视网膜眼底和OCT数据集。若需引用本数据集的任何部分，请引用以下论文：1) T. Hassan, M. U. Akram, M. F. Masood, U. Yasin, “基于深度结构张量图搜索框架的自动提取和表征视网膜层及视网膜扫描OCT中的液体病理学”，发表于《生物医学计算机杂志》，2018年12月。2) T. Hassan, M. U. Akram, N. Werghi, 和 N. Nazir, “RAG-FW：一种用于自动提取视网膜病变及评估人类视网膜病理学影响的混合卷积框架”，发表于《IEEE生物医学与健康信息学杂志》，2020年3月。