Artifacts reduction in mutual information-based image registration using prior information

Mutual information (MI) is currently the most popular match metric in handling the registration problem for multimodality images. However, interpolation artifacts impose deteriorating effects to the accuracy and robustness of MI-based methods. This paper analyzes the generation mechanism of the artifacts inherent in partial volume interpolation (PVI) and shows that the mutual information resulted from PVI is a convex function within each voxel grid. A new joint entropy estimation scheme using prior information is proposed to reduce the artifact effects and we demonstrate the improvements via experiments on misalignments between MR brain scans obtained using different image acquisition protocols.