title: Nonrigid image registration using an entropic similarity.
abstract: In this paper, we propose a nonrigid image registration technique by optimizing a generalized information-theoretic similarity measure using the quasi-Newton method as an optimization scheme and cubic B-splines for modeling the nonrigid deformation field between the fixed and moving 3-D image pairs. To achieve a compromise between the nonrigid registration accuracy and the associated computational cost, we implement a three-level hierarchical multiresolution approach such that the image resolution is increased in a coarse to fine fashion. Experimental results are provided to demonstrate the registration accuracy of our approach. The feasibility of the proposed method is demonstrated on a 3-D magnetic resonance data volume and also on clinically acquired 4-D CT image datasets.
authors.affiliation: Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada. ciise@linuxmail.org
authors.forename: Mohammed
authors.initials: M
authors.lastname: Khader
authors.forename: A
authors.initials: A
authors.lastname: Ben Hamza
mesh_terms: D019277:Entropy; D006801:Humans; D021621:Imaging, Three-Dimensional; D008962:Models, Theoretical; D015203:Reproducibility of Results