Choroid characterization in EDI OCT retinal images based on texture analysis

Abstract

Optical Coherence Tomography (OCT) is a widely extended imaging technique in the opthalmic field for diagnostic purposes. Since layers composing retina can be identified in these images, several image processingbased methods have been presented to segment them automatically in these images, with the aim of developing medical-support applications. Recently, appearance of Enhanced Depth Imaging (EDI) OCT allows to tackle exploration of the choroid which provides high information of eye processes. Therefore, segmentation of choroid layer has become one of the more relevant problems tackled in this field, but it presents different features that rest of the layers. In this work, a novel texture-based study is proposed in order to show that textural information can be used to characterize this layer. A pattern recognition process is carried out by using different descriptors and a process of classification, considering marks performed by two experts for validation. Results show that characterization using texture features is effective with rates over 90% of success.