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Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research

机译：印度糖尿病视网膜病变图像数据集（IDRiD）：糖尿病视网膜病变筛查研究的数据库

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Diabetic Retinopathy is the most prevalent cause of avoidable vision impairment, mainly affecting the working-age population in the world. Recent research has given a better understanding of the requirement in clinical eye care practice to identify better and cheaper ways of identification, management, diagnosis and treatment of retinal disease. The importance of diabetic retinopathy screening programs and difficulty in achieving reliable early diagnosis of diabetic retinopathy at a reasonable cost needs attention to develop computer-aided diagnosis tool. Computer-aided disease diagnosis in retinal image analysis could ease mass screening of populations with diabetes mellitus and help clinicians in utilizing their time more efficiently. The recent technological advances in computing power, communication systems, and machine learning techniques provide opportunities to the biomedical engineers and computer scientists to meet the requirements of clinical practice. Diverse and representative retinal image sets are essential for developing and testing digital screening programs and the automated algorithms at their core. To the best of our knowledge, IDRiD (Indian Diabetic Retinopathy Image Dataset), is the first database representative of an Indian population. It constitutes typical diabetic retinopathy lesions and normal retinal structures annotated at a pixel level. The dataset provides information on the disease severity of diabetic retinopathy, and diabetic macular edema for each image. This makes it perfect for development and evaluation of image analysis algorithms for early detection of diabetic retinopathy.
机译：糖尿病性视网膜病是可避免的视力障碍的最普遍原因，主要影响世界上的适龄工作人群。最近的研究对临床眼保健实践的要求有了更好的理解，以识别出更好，更便宜的视网膜疾病识别，管理，诊断和治疗方法。糖尿病性视网膜病筛查程序的重要性以及以合理的成本难以实现可靠的糖尿病性视网膜病早期诊断的过程，需要注意开发计算机辅助诊断工具。视网膜图像分析中的计算机辅助疾病诊断可以简化对糖尿病人群的大规模筛查，并帮助临床医生更有效地利用他们的时间。计算能力，通信系统和机器学习技术方面的最新技术进步为生物医学工程师和计算机科学家提供了满足临床实践要求的机会。多样化和代表性的视网膜图像集对于开发和测试数字筛查程序及其自动化算法至关重要。据我们所知，IDRiD（印度糖尿病视网膜病变图像数据集）是印度人口的第一个数据库代表。它构成了典型的糖尿病性视网膜病变和正常的视网膜结构，在像素水平上有注释。该数据集为每个图像提供了有关糖尿病性视网膜病变的疾病严重程度和糖尿病性黄斑水肿的信息。这使其非常适合开发和评估用于早期检测糖尿病性视网膜病变的图像分析算法。

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