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Abstract Retinal fundus image registration is a key step in clinical eye disease diagnosis and treatment. Targeting the difficulties in dealing with pair of images with large field of view differences or with great structural noises caused by over-segmentation, this paper presents an improved graph-based algorithm to match retinal vessel networks by utilizing higher-order relations constructed from the vessel structural graphs whose nodes represent vascular bifurcations with the edges describing relations between feature points. The method performs in a fully automatic fashion, with a multi-scale Gabor filter first employed for detection and extraction of retinal vessels and with the correspondences then recovered between two pathwise hyper-edge graphs using an efficient pairwise spectral matching scheme. Experimental evaluation shows that the developed method is effective and accurate in terms of the feature recall rate and the vascular CEM distance.
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| Keywords
graph matching
hyper-edge
spectral matching
vessel detection
retinal image registration
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Issue Date: 15 May 2014
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2014,
Vol. 54
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