Blood vessel extraction of diabetic retinopathy using optimized enhanced images and matched filter

被引：11

作者：

Subudhi A. ^{[1
]}

Pattnaik S. ^{[1
]}

Sabut S. ^{[2
]}

机构：

[1] SOA University, Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Bhubaneswar, Odisha

[2] SOA University, Department of Electronics and Instrumentation Engineering, Institute of Technical Education and Research, Bhubaneswar, Odisha

来源：

Journal of Medical Imaging | 2016年 / 3卷 / 04期

关键词：

accuracy; blood vessels; diabetic retinopathy; matched filter; particle swarm optimization; retinal image;

D O I：

10.1117/1.JMI.3.4.044003

中图分类号：

学科分类号：

摘要：

Accurate extraction of structural changes in the blood vessels of the retina is an essential task in diagnosis of retinopathy. Matched filter (MF) technique is the effective way to extract blood vessels, but the effectiveness is reduced due to noisy images. The concept of MF and MF with first-order derivative of Gaussian (MF-FDOG) has been implemented for retina images of the DRIVE database. The optimized particle swarm optimization (PSO) algorithm is used for enhancing the images by edgels to improve the performance of filters. The vessels were detected by the response of thresholding to the MF, whereas the threshold is adjusted in response to the FDOG. The PSO-based enhanced MF response significantly improved the performances of filters to extract fine blood vessels structures. Experimental results show that the proposed method based on enhanced images improved the accuracy to 91.1%, which is higher than that of MF and MF-FDOG, respectively. The peak signal-to-noise ratio was also found to be higher with low mean square error values in enhanced MF response. The accuracy, sensitivity, and specificity values are significantly improved among MF, MF-FDOG, and PSO-enhanced images (P<0.05). © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE).

引用

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