A view-based approach to registration: theory and application to vascular image registration

This paper presents an approach to registration centered on the notion of a view--a combination of an image resolution, a transformation model, an image region over which the model currently applies, and a set of image primitives from this region. The registration process is divided into three stages: initialization, automatic view generation, and estimation. For a given initial estimate, the latter two alternate until convergence; several initial estimates may be explored. The estimation process uses a novel generalization of the Iterative Closest Point (ICP) technique that simultaneously considers multiple correspondences for each point. View-based registration is applied successfully to alignment of vascular and neuronal images in 2-d and 3-d using similarity, affine, and quadratic transformations.