NDLI: Unsupervised Segmentation of Retinal Blood Vessels Using a Single Parameter Vesselness Measure

Content Provider	IEEE Xplore Digital Library
Author	Salem, N.M. Nandi, A.K.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng. & Electron., Univ. of Liverpool, Liverpool (Salem, N.M.; Nandi, A.K.)
Abstract	In this paper, a novel vesselness measure based on analysis of the Hessian matrix is presented. The larger eigenvalue of the Hessian matrix is used for vessel centerlines detection, while vessel orientations are estimated from the eigenvectors corresponding to the smaller eigenvalue. The vesselness measure combines information from vessel centerlines and orientations over scales to segment retinal blood vessels from colour fundus images. A publicly available dataset is used to evaluate the performance of our proposed method which has the advantage of being unsupervised and of using only one parameter.
Starting Page	528
Ending Page	534
File Size	4547277
Page Count	7
File Format	PDF
ISBN	9780769534763
DOI	10.1109/ICVGIP.2008.34
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-16
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Retinal images Retinopathy Scale space Vessel extraction Blood vessels Retina Image segmentation Matched filters Image analysis Hessian matrix Eigenvalues and eigenfunctions Diabetes Biomedical image processing Pixel Biomedical imaging
Content Type	Text
Resource Type	Article

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Unsupervised Segmentation of Retinal Blood Vessels Using a Single Parameter Vesselness Measure