Morphological and Neural Network Based Approach for Detection of Exudates in Fundus Images

S. Bharkad
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引用次数: 3

Abstract

This paper presents a technique for detection of hard exudates in fundus images. Hard exudates is one of the anomaly formed in retina due to diabetic retinopathy. Early detection of hard exudates may prevent the vision loss of diabetic retinopathy patient. In this work, optic disc (OD) is extracted with the help of morphological operators. OD is masked in green component image to avoid the misclassification between OD region and hard exudates region. Then features of green component image are computed and applied to neural network for detection of hard exudates. Experimental results show the better competency of algorithm on DIARETDB0 and DIARETDB1 databases.
基于形态学和神经网络的眼底图像渗出物检测方法
本文提出了一种眼底图像中硬渗出物的检测方法。硬渗出物是糖尿病视网膜病变引起的视网膜异常之一。早期发现硬渗出物可预防糖尿病视网膜病变患者视力丧失。在这项工作中,视盘(OD)在形态学算子的帮助下被提取。为了避免OD区与硬渗出区之间的误分类,将OD区遮挡在绿色分量图像中。然后计算绿色分量图像的特征,并将其应用到神经网络中进行硬渗出物的检测。实验结果表明,该算法在DIARETDB0和DIARETDB1数据库上具有较好的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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