Graph-based optimal multi-surface segmentation with a star-shaped prior: Application to the segmentation of the optic disc and cup

Abstract

A novel graph-based optimal segmentation method which can simultaneously segment multiple star-shaped surfaces is presented in this paper. Minimum and maximum surface distance constraints can be enforced between different surfaces. In addition, the segmented surfaces are ensured to be smooth by incorporating surface smoothness constraints which limit the variation between adjacent surface voxels. A consistent digital ray system is utilized to make sure the segmentation result is star-shaped and consistent, without interpolating image as required by other methods. To the best of our knowledge, the concept of consistent digital rays is for the first time introduced into the field of medical imaging. The problem is formulated as an MRF optimization problem which can be efficiently and exactly solved by computing a single min s-t cut in an appropriately constructed graph. The method is applied to the segmentation of the optic disc and cup on 70 registered fundus and SD-OCT images from glaucoma patients. The result shows improved accuracy by applying the proposed method (versus using a classification-based approach).