title: An efficient intelligent analysis system for confocal corneal endothelium images.
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.
authors.affiliation: School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK.
authors.forename: M S
authors.initials: MS
authors.lastname: Sharif
authors.affiliation: School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK.
authors.forename: R
authors.initials: R
authors.lastname: Qahwaji
authors.affiliation: Universidade Nova de Lisboa/FCT-UNINOVA, Caparica 2829-516, Portugal.
authors.forename: E
authors.initials: E
authors.lastname: Shahamatnia
authors.affiliation: School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK.
authors.forename: R
authors.initials: R
authors.lastname: Alzubaidi
authors.affiliation: School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK.
authors.forename: S
authors.initials: S
authors.lastname: Ipson
authors.affiliation: Manchester Royal Eye Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK.
authors.forename: A
authors.initials: A
authors.lastname: Brahma
mesh_terms: D000465:Algorithms; D002452:Cell Count; D003315:Cornea / Q000033:anatomy & histology*; D004728:Endothelium, Corneal; D006801:Humans; D018613:Microscopy, Confocal / Q000379:methods*
keywords: Confocal microscope; Cornea; Endothelium layer, Snake, Particle swarm optimisation