基于模糊C均值聚类的视盘定位

K. Padmanaban, R. Kannan
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引用次数: 13

摘要

本文采用模糊C均值聚类(FCM)数据挖掘技术对彩色眼底图像中的视盘进行定位。该方法考虑了RGB眼底图像中的绿色平面,因为它比其他红色和蓝色平面提供更好的对比度。由于视盘的强度比其他区域更亮,因此初始视盘由最亮的点识别,这些点称为感兴趣区域(ROI)。FCM是一种聚类方法,它允许一个数据块属于两个或多个聚类。在应用FCM技术对视盘进行聚类之前,首先使用中值滤波技术对初始感兴趣区域进行去噪处理。结果表明FCM对视盘的定位是诊断青光眼的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localization of optic disc using Fuzzy C Means clustering
In this paper, a data mining technique, Fuzzy C Means clustering (FCM) is used to locate the optic disc in colour fundus image. Green plane from the RGB fundus image is considered in the proposed approach because it provides better contrast than the other red and blue planes. As the intensity of the optic disc is brighter than other region, the initial optic disc is identified by the brightest points which are called Region of Interest (ROI). FCM is a method of clustering which allows one piece of data to belong to two or more clusters. Before applying the FCM technique to cluster the optic disc, the initial ROI is de-noised by using median filtering technique. Results show the efficiency of the FCM to localize the optic disc in order to diagnose glaucoma.
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