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An Automated System for the Grading of Diabetic Maculopathy in Fundus Images

机译:基底图像中糖尿病患者分级的自动化系统

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Computer aided diagnosis systems are very popular now days as they assist doctors in early detection of the disease. Diabetic maculopathy is one such disease which affects the retina of the diabetic patients. It affects the central vision of the person and causes blindness in severe cases. In this paper, an automated system for the grading of diabetic maculopathy has been developed, that will assist the ophthalmologists in early detection of the disease. Here, we propose a novel computerized method for the grading of diabetic maculopathy in fundus images. Our proposed system comprises of preprocessing of retinal image followed by macula and exudate regions detection. This is followed by feature extractor module for the formulation of feature set. SVM classifier is then used to grade the diabetic maculopathy. The publicly available fundus image database MESSIDOR has been used for the validation of our algorithm. The results of our proposed system have been compared with other methods in the literature in terms of sensitivity and specificity. Our system gives higher values of sensitivity and specificity as compared to others on the same database.
机译:计算机辅助诊断系统现在非常受欢迎,因为他们在早期检测疾病中协助医生。糖尿病菌癌是一种影响糖尿病患者视网膜的这种疾病。它影响了人的中心视觉,并在严重案件中引起失明。本文已经开发出一种用于糖尿病患者分级的自动化系统,其将有助于眼科医生早期发现该疾病。在这里,我们提出了一种新型计算机化方法,用于在眼底图像中进行糖尿病癌疗法评级。我们所提出的系统包括视网膜图像的预处理,然后是黄斑和渗出物区域检测。接下来是特征提取器模块,用于配制功能集。然后使用SVM分类剂来级糖尿病患者。公开可用的USFUS数据库Messidor已被用于验证我们的算法。在敏感性和特异性方面,我们提出的系统的结果与文献中的其他方法进行了比较。与同一数据库上的其他人相比,我们的系统提供了更高的灵敏度和特异性值。

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