The druse, an abnormal yellow/white deposit on retina, is a dominant characteristic of age-related macular degeneration (AMD) which is a retinal disorder associated with age. The early detection of drusen is useful for ophthalmologists to diagnose the patients that suffer from AMD. An automated method has been proposed in this work to detect and segment drusen using retinal fundus images by gradient based segmentation to find true edges of drusen, connected component labeling to remove suspicious pixels from drusen region and edge linking to connect all labeled pixels into a meaningful boundary. The proposed method outperforms other existing methods in detection of drusen with an accuracy/sensitivity/specificity of 96.17/89.81/99.00 on two publicly available retinal image databases. In order to grade the severity of AMD, the detected drusen by the proposed method are further quantified into small, intermediate and large with an accuracy of 88.46, 98.55, and 88.37%, respectively. 
Automated detection and segmentation of drusen in retinal fundus images