relation: https://khub.utp.edu.my/scholars/11974/
title: Unsupervised Method for Retinal Vessel Segmentation Based on Gabor Wavelet and Multiscale Line Detector
creator: Shah, S.A.A.
creator: Shahzad, A.
creator: Khan, M.A.
creator: Lu, C.-K.
creator: Tang, T.B.
description: 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.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2019
type: Article
type: PeerReviewed
identifier:   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     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077590989&doi=10.1109%2fACCESS.2019.2954314&partnerID=40&md5=f474122b3f4c37bf1aaaed0a074105b2
relation: 10.1109/ACCESS.2019.2954314
identifier: 10.1109/ACCESS.2019.2954314