Automated Drusen Detection Technique for Age-Related Macular Degeneration
Age-related macular degeneration is one of the leading cause of vision loss and blindness among people of age 50 and higher. Macular degeneration is usually characterized by drusen. Drusens are accumulation of lipids, fatty proteins that appears as abnormal white-yellow deposits on the retina. Detection of these lesions using conventional image analysis methods is quite complicated and time taking mainly due to non-uniform illumination and the variability of the pigmentation of the background tissues. This paper presents an automated technique for segmentation and quantitative analysis of drusen in publicly available retinal images i.e. Structured Analysis of retina (STARE) and Automated Retinal Image Analysis (ARIA), acquired with the aid of a digital fundus camera. The present methodology emphasizes on quantitative analysis of drusen based on: First, region-based statistical analysis which corrects the non-uniform illumination of background, enhances local intensity, minimizes image noise, segment image through Otsu’s threshold in addition with morphological operation and hence compute area and edge of the detected drusen. Second, pixel-wise feature extraction which extracts the feature of overlapped components through weighted centroid and standard deviation, makes counting of number of drusen easy. Hence, this system can provide vital information about the quantity of drusen and can aid clinicians in their diagnosis to evaluate the stage of age-related macular degeneration.
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