Branches filtering approach to extract retinal blood vessels in fundus image

I. Purnama, K. Y. E. Aryanto
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引用次数: 6

Abstract

Retinal blood vessels can give information about an abnormality or disease by examining its pathological changes. One of the abnormalities is diabetic retinopathy that is signed by a disorder of retinal blood vessels resulting from diabetes mellitus. Currently, diabetic retinopathy is one of major cause of human vision abnormalities or even blindness. Hence, early detection of such an abnormality can provide early and proper treatment, and segmentation of the abnormality provides a map of retinal vessels that can ease the assessment of the characteristics of the vessels. We propose a new method to segment blood vessels in a retinal image. In the method, Max-Tree is used to represent the image based on its gray level. Afterwards, the filtering process is done using branches filtering approach in which the tree branches is selected based on the elongation attribute of the nodes. The selection is started from the leaf nodes. This experiment was done to 40 retinal images, and utilized its manual segmentation by experts to validate the results. We obtain the accuracy of 93.95% and 94.21%, respectively to 40 images and 20 images.
分支滤波法提取眼底图像中的视网膜血管
视网膜血管可以通过检查其病理变化来提供异常或疾病的信息。其中一种异常是糖尿病视网膜病变,其特征是由糖尿病引起的视网膜血管紊乱。目前,糖尿病视网膜病变是导致人类视力异常甚至失明的主要原因之一。因此,早期发现这种异常可以提供早期和适当的治疗,并且异常的分割提供了视网膜血管的地图,可以简化血管特征的评估。提出了一种新的视网膜图像血管分割方法。在该方法中,利用Max-Tree根据图像的灰度值来表示图像。然后,采用分支过滤的方法,根据节点的伸长属性选择树的分支。选择从叶节点开始。本实验对40幅视网膜图像进行了实验,并利用专家手工分割的方法对实验结果进行了验证。我们对40张和20张图像分别获得了93.95%和94.21%的准确率。
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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