An efficient intelligent analysis system for confocal corneal endothelium images
Article
Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436. https://doi.org/10.1016/j.cmpb.2015.09.003
Authors | Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. |
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Abstract | A confocal microscope provides a sequence of images of the corneal layers and structures at different depths from which medical clinicians can extract clinical information on the state of health of the patient's cornea. A hybrid model based on snake and particle swarm optimisation (S-PSO) is proposed in this paper to analyse the confocal endothelium images. The proposed system is able to pre-process images (including quality enhancement and noise reduction), detect cells, measure cell densities and identify abnormalities in the analysed data sets. Three normal corneal data sets acquired using a confocal microscope, and three abnormal confocal endothelium images associated with diseases have been investigated in the proposed system. Promising results are presented and the performance of this system is compared with manual and two morphological based approaches. The average differences between the manual and the automatic cell densities calculated using S-PSO and two other morphological based approaches is 5%, 7% and 13% respectively. The developed system will be deployable as a clinical tool to underpin the expertise of ophthalmologists in analysing confocal corneal images. |
Keywords | Confocal microscope; Cornea; Endothelium layer; Snake; Particle swarm optimisation |
Journal | Computer Methods and Programs in Biomedicine |
Journal citation | 122 (3), pp. 421-436 |
ISSN | 0169-2607 |
1872-7565 | |
Year | 2015 |
Publisher | Elsevier |
Accepted author manuscript | License CC BY-NC-ND |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2015.09.003 |
Web address (URL) | https://doi.org/10.1016/j.cmpb.2015.09.003 |
Publication dates | |
07 Sep 2015 | |
Publication process dates | |
Deposited | 06 Mar 2017 |
Accepted | 01 Sep 2015 |
Funder | NHS National Innovation Centre |
University of Bradford | |
NHS National Innovation Centre | |
University of Bradford | |
Copyright information | © 2015 Elsevier |
https://repository.uel.ac.uk/item/854wz
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