Detecting red-lesions from retinal fundus images using unique morphological features
Abstract
One of the most important retinal diseases is Diabetic Retinopathy (DR) which can lead to serious
damage to vision if remains untreated. Red-lesions are from important demonstrations of DR helping
its identification in early stages. The detection and verification of them is helpful in the evaluation of
disease severity and progression. In this paper, a novel image processing method is proposed for
extracting red-lesions from fundus images. The method works based on finding and extracting the
unique morphological features of red-lesions. After quality improvement of images, a pixel-based
verification is performed in the proposed method to find the ones which provide a significant
intensity change in a curve-like neighborhood. In order to do so, a curve is considered around each
pixel and the intensity changes around the curve boundary are considered. The pixels for which it is
possible to find such curves in at least two directions are considered as parts of red-lesions. The
simplicity of computations, the high accuracy of results, and no need to post-processing operations
are the important characteristics of the proposed method endorsing its good performance.