Blood vessel segmentation in color fundus images based on regional and Hessian features

Blood vessel segmentation in color fundus images based on regional and Hessian features Graefes Arch Clin Exp Ophthalmol (2017) 255:1525–1533 DOI 10.1007/s00417-017-3677-y RETINAL DISORDERS Blood vessel segmentation in color fundus images based on regional and Hessian features 1 1 1 2 Syed Ayaz Ali Shah & Tong Boon Tang & Ibrahima Faye & Augustinus Laude Received: 6 December 2016 /Revised: 23 March 2017 /Accepted: 18 April 2017 /Published online: 4 May 2017 Springer-Verlag Berlin Heidelberg 2017 Abstract Introduction Purpose To propose a new algorithm of blood vessel segmen- tation based on regional and Hessian features for image anal- The complication of diabetes mellitus results in diabetic reti- ysis in retinal abnormality diagnosis. nopathy (DR), which is eye-sight-threatening. Timely detection Methods Firstly, color fundus images from the publicly avail- of DR may save patients from sight loss. But, it is very difficult, able database DRIVE were converted from RGB to grayscale. if not impossible, to screen every patient in large population To enhance the contrast of the dark objects (blood vessels) studies. A more economical option is to use a computer-aided/ against the background, the dot product of the grayscale image automated telemedicine or diagnostic system [1]. Retinal vessel with itself was generated. To rectify the variation in contrast, segmentation is an important http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Graefe's Archive for Clinical and Experimental Ophthalmology Springer Journals

Blood vessel segmentation in color fundus images based on regional and Hessian features

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag Berlin Heidelberg
Subject
Medicine & Public Health; Ophthalmology
ISSN
0721-832X
eISSN
1435-702X
D.O.I.
10.1007/s00417-017-3677-y
Publisher site
See Article on Publisher Site

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