Non-rigid Image Registration Using Graph-cuts

Non-rigid image registration is an ill-posed yet challenging problem due to its supernormal high degree of freedoms and inherent requirement of smoothness. Graph-cuts method is a powerful combinatorial optimization tool which has been successfully applied into image segmentation and stereo matching. Under some specific constraints, graph-cuts method yields either a global minimum or a local minimum in a strong sense. Thus, it is interesting to see the effects of using graph-cuts in nonrigid image registration. In this paper, we formulate non-rigid image registration as a discrete labeling problem. Each pixel in the source image is assigned a displacement label (which is a vector) indicating which position in the floating image it is spatially corresponding to. A smoothness constraint based on first derivative is used to penalize sharp changes in displacement labels across pixels. The whole system can be optimized by using the graph-cuts method via alpha-expansions. We compare 2D and 3D...

• Type: Conference
• Year: 2007
• Where: MICCAI
• Authors: Tommy W. H. Tang, Albert C. S. Chung
• Keywords: Challenging Non-rigid Registration, Medical Imaging, MICCAI 2007, Non-rigid Image Registration, Nonrigid Image Registration