Local non-rigid image registration using mutual information
Clinton Fookes, Anthony John Maeder · QUT ePrints (Queensland University of Technology) · 2003
Recently there has emerged a need to compute multimodal non-rigid registrations in a lot of clinical applications. To date, the viscous fluid algorithm is perhaps the most adept method at recovering large local misregistrations that exist between two images. However, this model can only be used on images from the same modality as it assumes similar intensity values between images. This paper presents a solution to this problem by proposing a hybrid non-rigid registration using the viscous fluid algorithm and mutual information (MI). The MI is incorporated via the use of a block matching procedure to generate a sparse deformation field which drives the viscous fluid algorithm. This algorithmis compared to two other popular local registration approaches, namely Gaussian convolution and the thin-plate spline warp. Results showthat the thin-plate splinewarp and the MI-Fluid approach produce comparable results. However, Gaussian convolution is the superior choice, especially in controlled environments.