Medical image registration using mutual information

Abstract

Analysis of multispectral or multitemporal images requires proper geometric alignment of the images to compare corresponding regions in each image volume. Retrospective three-dimensional alignment or registration of multimodal medical images based on features intrinsic to the image data itself is complicated by their different photometric properties, by the complexity of the anatomical objects in the scene and by the large variety of clinical applications in which registration is involved. While the accuracy of registration approaches based on matching of anatomical landmarks or object surfaces suffers from segmentation errors, voxel-based approaches consider all voxels in the image without the need for segmentation. The recent introduction of the criterion of maximization of mutual information, a basic concept from information theory, has proven to be a breakthrough in the field. While solutions for intrapatient affine registration based on this concept are already commercially available, current research in the field focuses on interpatient nonrigid matching.

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