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ODSTRČILÍK, J. KOLÁŘ, R. HARABIŠ, V. TORNOW, R.
Original Title
Classification-Based Blood Vessel Segmentation in Retinal Images
Type
conference paper
Language
English
Original Abstract
Automatic and precise segmentation of retinal blood vessels can help in computer aided as-sessment of various retinal diseases, especially diseases related to cardiovascular system or glaucoma. Hence, an accurate detection of retinal vascular structures is one of the most addressed topic in the field of retinal im-age processing today. Most of the methods are designed directly for utilization with a special dataset only or have problems to segment blurry and noisy images. In this study, we showed that combination of three stand-ard approaches – matched filtering, Hessian-based approach, and morphological processing, together with support vector machine classification technique, can be satisfactorily used as a universal segmentation ap-proach in retinal images acquired using entirely different devices.
Keywords
segmentation, retinal vessels, blood vessels, classification, retinal images
Authors
ODSTRČILÍK, J.; KOLÁŘ, R.; HARABIŠ, V.; TORNOW, R.
RIV year
2015
Released
19. 10. 2015
Publisher
CRC Press Taylor and Francis Group
Location
London, UK
ISBN
978-1-138-02926-2
Book
Computational Vision and Medical Image Processing V
Pages from
95
Pages to
100
Pages count
6
BibTex
@inproceedings{BUT117935, author="Jan {Odstrčilík} and Radim {Kolář} and Vratislav {Harabiš} and Ralf-Peter {Tornow}", title="Classification-Based Blood Vessel Segmentation in Retinal Images", booktitle="Computational Vision and Medical Image Processing V", year="2015", pages="95--100", publisher="CRC Press Taylor and Francis Group", address="London, UK", isbn="978-1-138-02926-2" }