Landmark-Based Non-rigid Registration Via Graph Cuts

This paper presents an approach based on graph cuts initially used for motion segmentation that is being applied to the nonrigid registration problem. The main contribution of our method is the formulation of landmarks in the graph cut minimization framework. In the graph cut method, we add a penalty cost based on landmarks to the data energy. In the presence of a landmark, we adjust the T-link weights to cut strategic links. Our formulation also allows the spread of a landmark influence to its neighborhood. We first show with synthetic images that minimization with graph cuts can indeed be used for non-rigid registration and show how landmarks can guide the minimization process towards a customized solution. We later use this method with real images and show how landmarks can successfully guide the registration of a coronary angiogram.