Title
An efficient intelligent analysis system for confocal corneal endothelium images
Abstract
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. 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.
Year
DOI
Venue
2015
10.1016/j.cmpb.2015.09.003
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
Confocal microscope,Cornea,Endothelium layer, Snake, Particle swarm optimisation
Computer vision,Data set,Computer science,Corneal endothelium,Cornea,Microscope,Artificial intelligence,Patient care,Quality enhancement,Confocal
Journal
Volume
Issue
ISSN
122
3
0169-2607
Citations 
PageRank 
References 
3
0.41
6
Authors
6
Name
Order
Citations
PageRank
Mhd. Saeed Sharif1217.18
Rami Qahwaji212021.05
Ehsan Shahamatnia352.22
Rania Al-Zubaidi4121.06
Stanley S. Ipson56012.02
Arun Brahma641.44