The multiscale bowler-hat transform for blood vessel enhancement in retinal images

Sazak, Ç., Nelson, C. J. and Obara, B. (2019) The multiscale bowler-hat transform for blood vessel enhancement in retinal images. Pattern Recognition, 88, pp. 739-750. (doi: 10.1016/j.patcog.2018.10.011)

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Enhancement, followed by segmentation, quantification and modelling of blood vessels in retinal images plays an essential role in computer-aided retinopathy diagnosis. In this paper, we introduce the bowler-hat transform method a new approach based on mathematical morphology for vessel enhancement. The proposed method combines different structuring elements to detect innate features of vessel-like structures. We evaluate the proposed method qualitatively and quantitatively and compare it with the state-of-the-art methods using both synthetic and real datasets. Our results establish that the proposed method achieves high-quality vessel-like structure enhancement in both synthetic examples and clinically relevant retinal images. The bowler-hat transform is shown to be able to detect fine vessels while still remaining robust at junctions.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Nelson, Dr Chas
Authors: Sazak, Ç., Nelson, C. J., and Obara, B.
College/School:College of Science and Engineering > School of Physics and Astronomy
Journal Name:Pattern Recognition
ISSN (Online):1873-5142
Published Online:10 October 2018
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Pattern Recognition 88: 739-750
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
738201EPSRC DTP 16/17 and 17/18Mary Beth KneafseyEngineering and Physical Sciences Research Council (EPSRC)EP/N509668/1R&I - RESEARCH STRATEGY & INNOVATION