Diabetic retinopathy, a symptomless medical condition of diabetes, is one of the significant reasons of vision impairment all over the world. The prior detection and diagnosis can decrease the occurrence of acute vision loss and enhance efficiency of treatment. Fundus imaging, a non-invasive diagnostic technique, is the most frequently used mode for analyzing retinal abnormalities related to diabetic retinopathy. Computer-aided methods based on retinal fundus images support quick diagnosis, impart an additional perspective during decision-making, and behave as an efficient means to assess response of treatment on retinal abnormalities. However, in order to evaluate computer-aided systems, a benchmark database of clinical retinal fundus images is required. Therefore, a representative database comprising of 2942 clinical retinal fundus images is developed and presented in this work. This clinical database, having varying attributes such as position, dimensions, shapes, and color, is formed to evaluate the generalization capability of computer-aided systems for diabetic retinopathy diagnosis. A framework for the development of benchmark retinal fundus images database is also proposed. The developed database comprises of medical image annotations for each image from expert ophthalmologists corresponding to anatomical structures, retinal lesions and stage of diabetic retinopathy. In addition, the substantial performance comparison capability of the proposed database aids in analyzing candidature of different methods, and subsequently its usage in medical practice for real-time applications.

糖尿病视网膜病变是一种无症状的糖尿病疾病，是全世界视力受损的重要原因之一。事先检测和诊断可以减少急性视力丧失的发生，提高治疗效率。眼底成像是一种非侵入性诊断技术，是分析与糖尿病视网膜病变相关的视网膜异常的最常用模式。基于视网膜眼底图像的计算机辅助方法支持快速诊断，在决策过程中提供额外的视角，并作为评估视网膜异常治疗反应的有效手段。然而，为了评估计算机辅助系统，需要临床视网膜眼底图像的基准数据库。因此，在这项工作中开发并展示了一个由 2942 个临床视网膜眼底图像组成的代表性数据库。该临床数据库具有位置、尺寸、形状和颜色等不同属性，用于评估计算机辅助系统对糖尿病视网膜病变诊断的泛化能力。还提出了用于开发基准视网膜眼底图像数据库的框架。开发的数据库包括来自专家眼科医生的每幅图像的医学图像注释，对应于解剖结构、视网膜病变和糖尿病视网膜病变阶段。此外，所提出的数据库的实质性性能比较能力有助于分析不同方法的候选资格，并随后在实时应用的医疗实践中使用。