Automatic Segmentation of outer edges of retinal layers in OCT scan images using Eikonal Equation

Abstract

Optical coherence tomography (OCT) is a non-invasive diagnostic method specially used in retinal as it the most sensitive organs among human parts. It uses low coherence light waves to render the cross-section view of the retina in micrometer resolution. In the analysis of a retinal anomaly, the sectional visualization proves to be an immensely powerful mechanism. For prior detection of retinal diseases, slicing of the required portion from the dataset images into definite layers is a necessary step. It helps to map and measure their thickness. These measurements help with the diagnosis and provide proper guidance for the treatment of diseases of the retina.In this work, we are taking an account of calculating the precise geodesic distance approach for the OCT segmentation of images in two-dimensional spaces. The technique we are using takes into account horizontal and vertical intensity variation and get onto a weighted geodesic distance. By applying the fast marching approach on the Eikonal equation, this work is calculating the shortest path. Although the proposed Geodesic distance method using the Eikonal equation is a bit complex method it outperforms graph as well as other techniques in portraying precisely the retinal layers.