Integration Of Boundary Finding And Regionbased Segmentation Using Game Theory

Abstract

. Robust segmentation of structures from an image is essential for a variety of applications in biomedical image analysis. Here we propose a method that integrates region based segmentation and gradient based boundary finding using game theory in an effort to form a unified approach that is robust to noise and poor initialization. The novelty of the method is that this is a bi-directional framework whereby the two seperate modules improve their results through mutual information sharing. Keywords: game theory, boundary finding, region based segmentation, Maximum A posteriori probability 1. Introduction Precise segmentation of underlying objects in an image is very important especially for biomedical image analysis where it constitutes an important pre-processing step to such tasks as the registration of images obtained from two modalities, quantitative analysis of anatomical structures, the derivation of priors for image reconstruction in another modality and cardiac motion tracking..