An efficient intelligent analysis system for confocal corneal endothelium images. Issue 3 (December 2015)

• Record Type: Journal Article
• Authors: Sharif, M.S.; Qahwaji, R.; Shahamatnia, E.; Alzubaidi, R.; Ipson, S.; Brahma, A.
• Is Part Of: Computer methods and programs in biomedicine. Volume 122:Issue 3(2015)
• Page Start: 421
• Page End: 436
• Publication Date: 2015-12
• Subjects: Confocal microscope -- Cornea -- Endothelium layer, Snake, Particle swarm optimisation; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.09.003
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A new intelligent system to tackle the challenges of confocal corneal endothelium images is developed. This system underpins the expertise of ophthalmologists. It provides clinically useful factors, saves a useful amount of clinician time in the process. It is able to model endothelial cells for better evaluation and fast analysis. Useful system for busy clinic and patient care. 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.