OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods

Optical coherence tomography (OCT) is a non-invasive imaging technique that has extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases. OCT uses the principle of light wave interference to create detailed images of the retinal microstructures, making it a valuable tool for diagnosing ocular conditions. Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods (OCTDL) dataset comprising over 2000 high-resolution OCT images labeled according to disease group and retinal pathology.The dataset consists of the following categories and images:Age-Related Macular Degeneration - 1231 images;Diabetic Macular Edema - 147 images;Epiretinal Membrane- 155 images;Normal - 332 images;Retinal Artery Occlusion - 22 images;Retinal Vein Occlusion - 101 images;Vitreomacular Interface Disease - 76 images.This dataset is published to provide researchers and developers with access to a large set of labeled images, which contributes to the development and improvement of algorithms for the automatic processing and analysis of OCT images for early diagnosis and monitoring of eye diseases. CSV file consists of file_name, disease, subcategory, condition, patient_id, eye, sex, year, image_width, and image_height. The dataset will be updated periodically.

光学相干断层扫描（Optical Coherence Tomography，简称OCT）是一种无创成像技术，在眼科领域具有广泛的应用前景。OCT技术能够清晰地呈现视网膜各层结构，对于视网膜疾病的早期诊断与监测发挥着至关重要的作用。该技术基于光波干涉原理，生成视网膜微观结构的详细图像，因而成为眼科疾病诊断的重要工具。光学相干断层扫描图像深度学习方法数据集（Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods，简称OCTDL）包含超过2000张高分辨率OCT图像，这些图像按照疾病类别和视网膜病理学进行标注。数据集包含以下类别和图像：年龄相关性黄斑变性 - 1231张图像；糖尿病性黄斑水肿 - 147张图像；视网膜色素上皮层 - 155张图像；正常 - 332张图像；视网膜动脉阻塞 - 22张图像；视网膜静脉阻塞 - 101张图像；玻璃体视网膜界面疾病 - 76张图像。本数据集的发布旨在为研究人员和开发者提供大量标注图像的访问权限，有助于推动自动处理和分析OCT图像算法的发展与优化，以实现眼科疾病的早期诊断和监测。CSV文件包括文件名、疾病、子类别、状况、患者ID、眼睛、性别、年份、图像宽度和图像高度等信息。数据集将定期更新。