基于局部熵阈值Gabor滤波的糖尿病视网膜病变自动检测

S. K. Kuri
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引用次数: 9

摘要

糖尿病视网膜病变(DR)是糖尿病的一种并发症,也是导致视力丧失的主要原因。DR检测中,质量差的视网膜图像给眼科医生的分析增加了难度。视网膜血管的自动分割有助于眼科医生筛查更大的人群。本文提出了一种高精度的血管自动提取方法。该算法由Gabor滤波器和局部熵阈值构成,用于各种正常或异常条件下的血管提取。Gabor滤波器的频率和方向调整到与绿色通道图像中要增强的部分血管的频率和方向相匹配。该方法采用局部熵阈值技术对提取的血管像素点进行分类。利用MATLAB软件,结合DRIVE数据库对该算法的性能进行了分析。
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Automatic diabetic retinopathy detection using Gabor filter with local entropy thresholding
Diabetic retinopathy (DR) is a complication of diabetes and a leading cause of vision loss. DR detection, poor quality retinal image makes more difficult the analysis for ophthalmologist. Automatic segmentation of blood vessels in retina is helpful for ophthalmologists to screen larger populations. This literature presents a new automatic analysis to extract blood vessels with high accuracy. In this algorithm comprised of Gabor filter with local entropy thresholding for vessels extraction under various normal or abnormal conditions. The frequency and orientation of Gabor filter are tuned to match that of a part of blood vessels to be enhanced in a green channel image. Extraction of blood vessels pixels are classified by local entropy thresholding technique in this method. The performance of the proposed algorithm is analysed by MATLAB software with DRIVE database.
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