Graphical Shape Templates for Automatic AnatomyDetection with Applications to MRI Brain

|A new method of model registration is proposed using graphical templates. A decomposable graph of 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 the template graph nds the optimal match to a subset of the candidate points in polynomial time. This combination of local operators to describe points of inter-est/landmarks and a graph to describe their geometric arrangement in the plane, yields fast and precise matches of the model to the data, with no initialization required. In addition it provides a generic tool box for modeling shape in a variety of applications. This methodology is applied in the context of T2 weighted MR axial and sagittal images of the brain to identify speciic anatomies.