Methods and systems for automatically identifying the schwalbe's line

Abstract

Various methods for automatically identifying the Schwalbe's line location in an optical coherence tomography (OCT) image of the anterior chamber of an eye are described. In one example method, the posterior corneal surface in the ROI is segmented by using one or more segmentation approaches to produce a segmented output. A curvature is computed at each segmented point to identify a set of local curvature maxima locations. Features at each local curvature maxima location are evaluated. The Schwalbe's line location is identified using the evaluated features at each maxima location. Other methods for identifying the Schwalbe's line location discussed in the present application are based on identification of a location of maximum curvature in the curvature function and identification of a maximum distance to the convex-hull of a model fit.