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Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model

Lee, Sangyeol and Reinhardt, Joseph M. and Cattin, Philippe C. and Abràmoff, Michael D.. (2010) Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model. Medical image analysis, Vol. 14, H. 4. pp. 539-549.

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Official URL: http://edoc.unibas.ch/dok/A6005729

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Abstract

Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal images by modeling the geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present a validation process that can be used for any retinal image registration method by tracing through the distortion path and assessing the geometric misalignment in the coordinate system of the reference standard. The proposed method can be used to perform an accuracy evaluation over the whole image, so that distortion in the non-overlapping regions of the montage components can be easily assessed. We demonstrate the technique by generating test image sets with a variety of overlap conditions and compare the accuracy of several retinal image registration models.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Cattin, Philippe Claude
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Elsevier
ISSN:1361-8415
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:07 Dec 2012 13:03
Deposited On:07 Dec 2012 13:00

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