Shah, S.A.A. and Shahzad, A. and Khan, M.A. and Lu, C.-K. and Tang, T.B. (2019) Unsupervised Method for Retinal Vessel Segmentation Based on Gabor Wavelet and Multiscale Line Detector. IEEE Access, 7. pp. 167221-167228. ISSN 21693536
Full text not available from this repository.Abstract
Eye and systemic diseases are known to manifest themselves in retinal vasculature. Segmentation of retinal vessel is one of the important steps in retinal image analysis. A simple unsupervised method based on Gabor wavelet and Multiscale Line Detector is proposed for retinal vessel segmentation. Vessels are enhanced by linear superposition of first scale Gabor wavelet image and complemented Green channel. Multiscale Line Detector is used to segment the blood vessels. Finally, a simple post processing scheme based on median filtering is deployed to remove false positives. The proposed scheme was evaluated with publicly available datasets called DRIVE, STARE and HRF, obtaining an accuracy of 0.9470, 0.9472, and 0.9559, and a sensitivity of 0.7421, 0.8004, and 0.7207, respectively. These results are comparable to the state-of-the-art methods, albeit with a simpler approach. © 2013 IEEE.
Item Type: | Article |
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Additional Information: | cited By 32 |
Uncontrolled Keywords: | Blood; Blood vessels; Eye protection; Image enhancement; Image processing; Median filters; Ophthalmology, Blood vessel segmentation; Color retinal images; Gabor wavelets; Image preprocessing; Line detectors; Unsupervised method, Image segmentation |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 10 Nov 2023 03:26 |
Last Modified: | 10 Nov 2023 03:26 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/11974 |