Nonrigid image registration using an entropic similarity

IEEE Trans Inf Technol Biomed. 2011 Sep;15(5):681-90. doi: 10.1109/TITB.2011.2159806. Epub 2011 Jun 16.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Entropy*
  • Humans
  • Imaging, Three-Dimensional
  • Models, Theoretical*
  • Reproducibility of Results