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

机译:糖尿病眼底图像中黄斑病变自动分级系统

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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:如今,计算机辅助诊断系统非常受欢迎,因为它们可以帮助医生及早发现疾病。糖尿病性黄斑病是一种影响糖尿病患者视网膜的疾病。它会影响人的中心视力,并在严重的情况下导致失明。在本文中,已经开发了用于糖尿病性黄斑病变分级的自动化系统,该系统将有助于眼科医生对疾病进行早期检测。在这里,我们提出了一种用于眼底图像中的糖尿病性黄斑病变分级的新型计算机化方法。我们提出的系统包括对视网膜图像进行预处理,然后进行黄斑和渗出液区域检测。接下来是用于特征集制定的特征提取器模块。然后,将SVM分类器用于对糖尿病性黄斑病进行分级。公开的眼底图像数据库MESSIDOR已用于验证我们的算法。就敏感性和特异性而言,我们提出的系统的结果已与文献中的其他方法进行了比较。与同一数据库中的其他系统相比,我们的系统提供了更高的灵敏度和特异性值。

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