Image processing for detection of Cataract, Retinopathy of Prematurity and Glaucoma

The field of ophthalmology is in need of more support as it is unable to meet the need of the growing population. This thesis considers procedures which may be used as part of an assistive telemedical tool for aiding ophthalmologists in diagnosing wide range of ophthalmological disorders including Cataract, Retinopathy of Prematurity and Glaucoma, which affect more than 60% of the population worldwide. Many different image processing techniques have been analysed and in the process some of the most favourable and advanced systems have been selected for identifying some of the key features of the eye which are commonly used by ophthalmologists for disease detection. To address this aim and create a more suitable telemedical solution, different stages of image processing is reconsidered and enhances in the study. The stages include, image pre-processing, feature localisation and feature extraction. The aim is to create simple, fast but universal algorithms and procedures which could be implemented on any captured data with any specifications. After image acquisition, the first image processing stage is the image pre-processing. The general processes such as the colour conversion to the gray scale and green band selection, masking the region of interest and preliminary filtering for sharpening the images are initially implemented. However, to improve the results in further stages, new procedures such as a trimming circle to reduce fringe noise and image colour enhancements are also implemented. The final results show significant improvements and more accurate findings in these cases. The next stage is the feature localisation stage. Previous studies have shown the main areas of interest in retinal images are vessels, Optic Disk and the Macula. The features are extracted using the new proposed algorithms. The results are promising and the localisation is compatible with previously conducted studies. Moreover, in this stage, another approach is suggested resulting in the Iris and Pupil localisation. The method may be used both for biometric purposes as well as inter-operatively in surgeries such as those of cataract. In the feature extraction stage, different methodologies are suggested for detecting the centre of the Iris, Pupil, Optic Disk and Macula. The radius and the area of these features are also calculated and compared. For vessels an approach is suggested for detecting its end points. The use of the information may result in detection of different diseases such as Cataract, ROP and Glaucoma. To further assist the ophthalmologists and medical practitioners an approach is proposed which results in mapping of the retina, which may then be used as an aiding tool for disease diagnosis, progression and treatment. Lastly, to reduce the error associated with each result, the light refraction within the eye is considered and the error calculated. The error can then be taken under consideration while analysing each result. The outcomes of the following study suggests a reliable yet cost-effective, simple and fast approaches in which captured eye images may be analysed as part of an automatic assistive telemedical tool.