Abstract
Image registration aims at establishing pointwise correspondences between given images. However, in many practical applications, no correspondences can be established in certain parts of the images. A typical example is the tumor resection area in pre- and post-operative medical images. In this paper, we introduce a novel variational framework that combines registration with an automatic detection of non-correspondence regions. The formulation of the proposed approach is simple but efficient, and compatible with a large class of image registration similarity measures and regularizers. The resulting minimization problem is solved numerically with a non-alternating gradient flow scheme. Furthermore, the method is validated on synthetic data as well as axial slices of pre-, post- and intra-operative MR T1 head scans.