Artifacts reduction in mutual information-based CT-MR image registration

Mutual information (MI) is currently the most popular match metric in handling the registration problem for multi modality 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 linear partial volume interpolation (PVI) and shows that the mutual information resulted from PVI is a convex function within each voxel grid. We conclude that the generation of the artifacts is due to two facts: 1) linear interpolation causes the histogram bin values to change at a synchronized pace; 2) entropy computation function Sigma xlgx is convex. As a remedy we propose to use non-uniform interpolation functions as the interpolation kernels in estimating the joint histogram. Cubic B-splin and Gaussian interpolators are compared and we demonstrate the improvements via experiments on misalignments between CT/MR brain scans.