Retinal blood vessel segmentation based on fractal dimension in spatial-frequency domain

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Author list: Paripurana S., Chiracharit W., Chamnongthai K., Higuchi K.

Publisher: Hindawi

Publication year: 2010

Start page: 1185

End page: 1190

Number of pages: 6

ISBN: 9781424470105

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651251955&doi=10.1109%2fISCIT.2010.5665170&partnerID=40&md5=76e1dc3cd47d02b9cf25f202b2e37800

Languages: English-Great Britain (EN-GB)

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Abstract

Vessel segmentation is very important in an automatic screening system for fundus images. Vessels are often segmented and removed from retinal images before the other residual lesions are detected. Incomplete vessel removal usually causes a false positive in lesion detection, especially for Microaneurysms detection. Segmenting vessels in spatial image domain makes miss detection due to non illumination and noises in retinal images. Non-illumination problem can be disregarded by segmenting the vessels in spatial-frequency domain, which invariant subbands can be ignored. This paper presents a new retinal blood vessel segmentation method based on fractal dimension in spatial-frequency domain of retinal images. The fractal dimension value of each pixel is computed in order to extract the vessels from their retinal background. The performance of the proposed method is evaluated and compared with the experts' diagnosis in the STARE database. ฉ2010 IEEE.

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