There is an evolution in the demands of modern ophthalmology from descriptive findings to assessment of cellular level changes by using in vivo confocal microscopy. Confocal microscopy, by producing grey-scale images, enables a microstructural insight into the in vivo cornea in both health and disease, including epithelial changes, stromal degenerative or dystrophic diseases, endothelial pathologies, and corneal deposits and infections. Ophthalmologists use acquired confocal corneal images to identify health and disease states and then to diagnose which type of disease is affecting the cornea. This paper presents the main features of the healthy confocal corneal layers, and reviews the most common corneal diseases. It identifies the visual signature of each disease in the affected layer and extracts the main features of this disease in terms of intensity, certain regular shapes with both their size and diffusion, and some specific region of interest. These features will lead towards the development of a complete automatic corneal diagnostic system which predicts abnormalities in the confocal corneal data sets.

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. 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 (quality enhancement, noise reduction), detect the cells, measure the cell density and identify abnormalities in the analysed data sets. Three normal corneal data sets acquired using confocal microscope, and two abnormal endothelium images associated with diseases have been investigated in the proposed system. Promising results are achieved and the performance of this system are compared with the performance of two morphological based approaches. The developed system can be deployed as clinical tool to underpin the expertise of ophthalmologists in analysing confocal corneal images.

Abstract-A confocal microscope provides a sequence of images of the various 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. Preprocessing the confocal corneal images to make them suitable for analysis is very challenging due the nature of these images and the amount of the noise present in them. This paper presents an efficient preprocessing approach for confocal corneal images consisting of three main steps including enhancement, binarisation and refinement. Improved visualisation, cell counts and measurements of cell properties have been achieved through this system and an interactive graphical user interface has been developed.