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Non-rigid elastic registration of retinal images using local window mutual information

Legg, Philip Alexander, Rosin, Paul L. ORCID:, Marshall, Andrew David ORCID: and Morgan, James E. 2009. Non-rigid elastic registration of retinal images using local window mutual information. Presented at: Medical image understanding and analysis 2009, Kingston upon Thames, UK, 14-15 July 2009. Published in: Dehmeshki, J., Hoppe, A. and Greenhill, D. eds. Proceedings of the 13th Annual Conference on Medical Image Understanding and Analysis 2008, Kingston, UK, 14-15 July 2009. British Machine Vision Association, pp. 144-148.

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In this paper we consider the problem of non-rigid retinal image registration between colour fundus photographs and Scanning Laser Ophthalmoscope (SLO) images. Registration would allow for cross-comparison between modalities, giving both appearence and reflectivity information which would provide clearer visualisation for demarcation of the optic nerve head as part of early glaucoma detection. Due to the differences in acquisition technique, along with alterations in the eye between acquisitions, there can be subtle non-rigid deformations present in the images that become apparent when performing rigid registration. Whilst this is negligible towards the centre of the SLO, the effect becomes much more noticable towards the periphery of the image, where it can be seen that not all blood vessels are aligned correctly. We propose a two-stage registration consisting of finding an initial rigid registration using Feature Neighbourhood Mutual Information [1], and then to use Local Window Mutual Information to quickly determine deformation parameters for a non-rigid solution. We test our method on 135 image pairs, with results showing improved registration accuracy compared to rigid registration.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Optometry and Vision Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RE Ophthalmology
Publisher: British Machine Vision Association
ISBN: 9781901725391
Last Modified: 19 Oct 2022 09:53

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