Retinal Macular Edema Detection Using Optical Coherence Tomography Images

Abstract

Macular Edema affects around 20 million people of the world each year.Optical Coherence Tomography (OCT), a non-invasive eye-imaging modality, is capable of detecting Macular Edema both in its early and advanced stages.In this paper, an algorithm which detects Macular Edema from OCT images has been presented.Initially the images are filtered to de-noise them.Then, the retinal layers -Inner Limiting Membrane (ILM) and Retinal Pigment Epithelium (RPE) are segmented using Graph Theory method.Region splitting is performed on the OCT scan and the thickness between the two layers in the different regions are determined.Area enclosed between the two layers is also estimated.Support Vector Machine, a binary classifier is used to draw a classification between normal and abnormal OCT scans.Region-wise thickness, a few Haralick's features, area between ILM and RPE and a few wavelet features are used to train the classifier.The classifier yielded an accuracy of 95% and a sensitivity of 100%.Thus, this algorithm can be used by ophthalmologists in early detection of Macular Edema.