Graphical Shape Templates for Deformable Model Registration with Applications toMRI Brain Scans

摘要

A new method of template matching is proposed using graphical templates. A graphof landmarks is chosen in the template image. All possible candidates for these landmarks are found in the data image using robust relational local operators. A dynamic programming algorithm on decomposable subgraphs of the template graph finds the optimal match to a subset of the candidate points in polynomial time. This combination of local operators to describe points of interest/landmarks and a graph to describe their geometric orientation in the plane, yields fast and precise matches of the model to the data, with no initialization required. In addition it provides a generic toolbox for modeling shape in a variety of applications. This methodology is applied in the context of T2 weighted MR images of the brain.