A novel method for automatic Hard Exudates detection in color retinal images

Xiang Chen, Wei Bu, Xiangqian Wu, Baisheng Dai, Y. Teng
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引用次数: 25

Abstract

Diabetic Retinopathy (DR) is one of the major causes of blindness, and Hard Exudates (HEs) which are common and early clinical signs of DR. This paper presented a novel method to automatically detect HEs in color retinal images. We first extract HEs candidate regions by combining histogram segmentation with morphological reconstruction. Next, we define 44 significant features for each candidate region. A supervised support vector machine (SVM) is finally trained based on these features to classify the candidate regions for HEs. We evaluate the proposed method on the public DIARETDB1 database and achieve an sensitivity of 94.7% and an positive predictive value of 90.0%. Experimental results show that our method can produce reliable detection of HEs.
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彩色视网膜图像硬渗出物自动检测的新方法
糖尿病视网膜病变(DR)是导致失明的主要原因之一,而硬渗出物(HEs)是糖尿病视网膜病变常见的早期临床症状,本文提出了一种彩色视网膜图像中硬渗出物的自动检测方法。首先采用直方图分割和形态学重构相结合的方法提取HEs候选区域。接下来,我们为每个候选区域定义44个重要特征。最后,基于这些特征训练有监督支持向量机(SVM)对候选区域进行分类。我们在公共DIARETDB1数据库上对该方法进行了评估,获得了94.7%的灵敏度和90.0%的阳性预测值。实验结果表明,该方法可以实现可靠的he检测。
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