Morphological technique for detection of microaneurysms from RGB fundus images

Abstract

One of the most vital components of diabetes mellitus that cause visual blindness is Diabetic Retinopathy (DR). The primary sign of DR in the retina is the presence of the microaneurysms (MAs) that cause because of injury in the retina as a long-term abnormality effect leads to diabetes mellitus. Early identification of the MAs helps us to reduce and prevent DR at the early stage. In this process, ophthalmologists continuously observe the previous and current fundus images obtained using the fundus camera manually which consumes more time and energy. In the proposed work, we describe a procedure for automatic detection of MAs by applying thresholding and mathematical morphology techniques, which alternates the tedious and timeconsuming manual method. The set of techniques is used for detecting MAs from the RGB fundus image. Preprocess techniques are used to resize the input image. The exudates are eliminated using the thresholding technique. The optic disc (OD) and blood vessels are removed by implementing morphological methods, and the feature extraction is implemented, based on their size. The experiment was carried out on freely accessible dataset DIARETDB1. The performance of the presented method detects MAs from the RGB fundus image and the results obtained show us the positive sign of the proposed technique. This technique not only helps ophthalmologist in automatic detection of MAs, it also helps in keeping track of the current and previous results of a patient for diagnosis. © 2017 IEEE.