Optimized clinical segmentation of retinal blood vessels by using combination of adaptive filtering,fuzzy entropy and skeletonization |
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| Affiliation: | 1. Biomedical Group, Department of Electrical and Computer Engineering, Hakim Sabzeari University, Sabzevar, Iran;2. Medical Science Department, Faculty of Medical Science University of Sabzevar, Sabzevar, Iran;3. Electrical and Electronics Engineering Department, Shiraz University of Technology, Shiraz, Iran;1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China;2. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;3. Guilin University of Electronic Technology, Guilin, China;4. School of Engineering, University of Glasgow, Glasgow, UK;1. Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia;2. Department of Computer Engineering, Hashtgerd Branch, Islamic Azad University, Alborz, Iran;1. School of Aerospace, Transport Systems and Manufacturing, Cranfield University, College Road, Bedfordshire MK43 0AL, UK;2. College of Engineering, Mathematics and Physical Systems, University of Exeter, EX4 4SB, UK |
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| Abstract: | The analysis of retina blood vessels in clinics indices is one of the most efficient methods employed for diagnosing diseases such as diabetes, hypertension and arthrosclerosis. In this paper, an efficient algorithm is proposed that introduces a higher ability of segmentation by employing Skeletonization and a threshold selection based on Fuzzy Entropy. In the first step, the blurring noises caused by hand shakings during ophthalmoscopy and color photography imageries are removed by a designed Wiener’s filter. Then, in the second step, a basic extraction of the blood vessels from the retina based on an adaptive filtering is obtained. At the last step of the proposed method, an optimal threshold for discriminating main vessels of the retina from other parts of the tissue is achieved by employing fuzzy entropy. Finally, an assessment procedure based on four different measurement techniques in the terms of retinal fundus colors is established and applied to DRIVE and STARE database images. Due to the evaluation comparative results, the proposed extraction of retina blood vessels enables specialists to determine the progression stage of potential diseases, more accurate and in real-time mode. |
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| Keywords: | Retinas vessels Image processing Wiener filter Adaptive filter Fuzzy entropy and skeleton method |
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