Preparation of 2D sequences of corneal images for 3D model building
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2014-04Keyword
Artificial neural networksConfocal microscopy
Classification
Registration
Segmentation
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(c) 2014 Elsevier Ireland Ltd. Full-text reproduced in accordance with the publisher's self-archiving policy.Peer-Reviewed
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openAccess
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Show full item recordAbstract
A confocal microscope provides a sequence of images, at incremental depths, of the various corneal layers and structures. From these, medical practioners can extract clinical information on the state of health of the patient's cornea. In this work we are addressing problems associated with capturing and processing these images including blurring, non-uniform illumination and noise, as well as the displacement of images laterally and in the anterior posterior direction caused by subject movement. The latter may cause some of the captured images to be out of sequence in terms of depth. In this paper we introduce automated algorithms for classification, reordering, registration and segmentation to solve these problems. The successful implementation of these algorithms could open the door for another interesting development, which is the 3D modelling of these sequences.Version
Accepted manuscriptCitation
Elbita A, Qahwaji RSR, Ipson SS, Sharif MS and Ghanchi F (2014) Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine.Link to Version of Record
https://doi.org/10.1016/j.cmpb.2014.01.009Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1016/j.cmpb.2014.01.009