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Title: An Efficient Retinal Blood Vessel Segmentation using Morphological Operations
Authors: Özkaya, Umut
Öztürk, Şaban
Akdemir, B.
Seyfi, Leventl
Keywords: Biomedical Image Processing
Image Texture Analysis
Image Denoising
Image Edge Detection
Image Segmentation
Issue Date: 2018
Publisher: IEEE
Abstract: The structure of retinal vessel carries information about many diseases. It is difficult to analyze this complex structure by human eye. Additionally, it has time-consuming process. In this study, an extremely lower complex and more successful retinal blood vessel segmentation method is proposed via using morphological operators. Colorful retinal images are divided into red, green and blue channels. Green channel is preferred for segmentation on the account of including clear details about retinal vessels. Then, adaptive threshold with 5x5 Gaussian window is applied in order to obtain clean vessel geometry. In the next step, retinal image is sharpened and then, 3x3 wiener filter is applied to it. After wiener filter, some noise in the image decreases but retinal image pixels soften. Therefore, Otsu thresholding is applied to softened images. Finally, morphological operation is performed on gray level images. The proposed method is implemented on test images in DRIVE database. The process time of our method is 0.7-0.8 second and it is faster than other methods. 95,61% accuracy, 85.096% sensitivity and 96.33% specificity rates are obtained.
Description: 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) -- OCT 19-21, 2018 -- Kizilcahamam, TURKEY
ISBN: 978-1-5386-4184-2
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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