Hybrid spline-based multimodal registration using a local measure for mutual information

Abstract

We introduce a new hybrid approach for spline-based elastic registration of multimodal medical images. The approach uses point landmarks as well as intensity information based on local analytic measures for mutual information. The intensity similarity metrics are computationally efficient and can be optimized independently for each voxel. We have successfully applied our approach to synthetic images, brain phantom images, as well as real multimodal medical images.