Department of Research and Development, Chandigarh Group of Colleges (CGC), Mohali, India.
Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, India.
Proc Inst Mech Eng H. 2020 Sep;234(9):1036-1048. doi: 10.1177/0954411920938569. Epub 2020 Jul 1.
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.
糖尿病性视网膜病变是糖尿病的一种无症状医学病症，是全球视力损害的主要原因之一。早期发现和诊断可以减少急性视力丧失的发生，并提高治疗效率。眼底成像作为一种非侵入性的诊断技术，是分析与糖尿病性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，并作为评估治疗对视网膜异常反应的有效手段。然而，为了评估计算机辅助系统，需要一个临床视网膜眼底图像的基准数据库。因此，本文开发并呈现了一个包含 2942 张临床视网膜眼底图像的代表性数据库。这个临床数据库具有不同的属性，如位置、尺寸、形状和颜色，旨在评估计算机辅助系统用于糖尿病性视网膜病变诊断的泛化能力。本文还提出了一个开发基准视网膜眼底图像数据库的框架。所开发的数据库包含来自专家眼科医生的每个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性视网膜病变的阶段。此外，该数据库具有实质性的性能比较能力，可以帮助分析不同方法的候选性，并随后将其用于医疗实践中的实时应用。
