Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase



Zhao, Yitian, Liu, Yonghui, Wu, Xiangqian, Harding, Simon ORCID: 0000-0003-4676-1158 and Zheng, Yalin ORCID: 0000-0002-7873-0922
(2015) Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase. PLOS One, 10 (4). e0122332-.

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Abstract

Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer.

Item Type: Article
Uncontrolled Keywords: imaging techniques, retinal vessels, retina, matched filters, angiography, eigenvalues, fluorescence imaging, blood vessels
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Depositing User: Symplectic Admin
Date Deposited: 23 Mar 2015 16:04
Last Modified: 15 Dec 2022 16:20
DOI: 10.1371/journal.pone.0122332
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/2008702