Sundaresan Vaanathi, Ram Keerthi, Joshi Niranjan, Sivaprakasam Mohanasankar, Gandhi Rashmin
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:4330-3. doi: 10.1109/EMBC.2015.7319353.
Diabetic macular edema (DME) is one of the vision-impairing manifestations of Diabetic Retinopathy (DR). Early detection and treatment of DME can prevent permanent vision loss in people suffering from DR. However, the clinical detection through biomicroscopy is time-consuming. In this paper, a computer-assisted grading method has been proposed to determine the DME severity based on the spatial distribution of exudative lesions around macula. The region around macula is classified into zonal levels and severity of the DME is graded based on the presence of exudative lesions in each zone. The proposed method has been evaluated on diverse public and local databases, and produced the sensitivity of 89.54% for 9.1 false positive per image (FPPI) for exudate detection and 98.8% accuracy for DME grading.
糖尿病性黄斑水肿（DME）是糖尿病视网膜病变（DR）导致视力受损的表现之一。早期检测和治疗DME可预防DR患者永久性视力丧失。然而，通过生物显微镜进行临床检测耗时较长。本文提出了一种计算机辅助分级方法，基于黄斑周围渗出性病变的空间分布来确定DME的严重程度。黄斑周围区域被划分为不同的区域等级，并根据每个区域中渗出性病变的存在情况对DME的严重程度进行分级。该方法已在各种公共和本地数据库上进行评估，对于渗出物检测，每幅图像的误报率为9.1时，灵敏度为89.54%，对于DME分级，准确率为98.8%。
