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.本数据集仓库包含复合式视网膜眼底图像与光学相干断层扫描（Optical Coherence Tomography, OCT）数据集，可用于视网膜层结构、视网膜病变的分析，以及正常与异常视网膜疾病的诊断，涵盖中心性累及糖尿病性黄斑水肿、急性中心性浆液性视网膜病变（CSR）、慢性CSR、地图样年龄相关性黄斑变性（AMD）、新生血管性AMD以及青光眼。 若您使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，《深度结构张量图搜索框架：面向视网膜SD-OCT扫描中视网膜层与液体病变的自动化提取与表征》，《计算机生物学与医学》，2018年12月。 2) T. Hassan、M. U. Akram、N. Werghi、N. Nazir，《RAG-FW：用于自动化提取视网膜病变及人类视网膜病变影响分级的混合卷积框架》，《IEEE生物医学与健康信息学杂志》，2020年3月。