Age-related macular degeneration identification based on HRC layers analyses in OCT images

Age-related macular degeneration (AMD) is a very dangerous disease which usually affects the eyes of people with age above 50 years. AMD is characterised by extra-cellular deposition that accumulate between the retinal pigment epithelium (RPE) and the inner collagenous layer of Bruch's membrane, causing the death of RPE cells and subsequent loss of photoreceptor cells. Optical coherence tomography (OCT) imaging technique is the powerful tool that can detect at early stage the different macular abnormalities, in view of its high-resolution cross-sectional images. The purpose of this work is to separate the healthy images from AMD OCT images by analysing and quantifying the extracted hyper reflective complex (HRC) layer using the image processing technique. The extracted layer is divided in to ten quadrants. In each sample, the number of white pixels is counted, and the mean value of these pixels is then calculated. For both the healthy and the AMD affected images, the average mean value is calculated. Based on this value, a decision rule is fixed to classify the images of interest. The proposed method showed an accuracy of 87.5%.