New development of non-rigid registration

Authors

  • Guojun Gordon Liao University of Texas at Arlington
  • Hsi-Yue Hsiao University of Texas at Arlington
  • Chih-Yao Hsieh University of Texas at Arlington
  • Yongyi Gong Guangdong Foreign Language and International Business University
  • Xiaonan Luo Sun Yat-Sen University
  • Xi Chen University of Texas at Arlington

DOI:

https://doi.org/10.21914/anziamj.v55i0.5925

Keywords:

nonrigid registration, optimal control, brain images

Abstract

We propose a new nonrigid registration algorithm which is based on the optimal control approach. In our previously proposed methods, the Jacobian determinant and the curl vector were used as control functions. In this algorithm, we use a new set of control functions. A main advantage of using the new controls is that the positivity and normalization of the Jacobian determinant are satisfied automatically. Numerical results on large deformation brain images are provided to show the accuracy and efficiency of the algorithm. doi:10.1017/S1446181114000091

Author Biographies

Guojun Gordon Liao, University of Texas at Arlington

professor Mathematics Department

Hsi-Yue Hsiao, University of Texas at Arlington

Research Scientist Department of mathematics

Chih-Yao Hsieh, University of Texas at Arlington

research scientist Department of Mathematics

Yongyi Gong, Guangdong Foreign Language and International Business University

Associate Professor School of Information Technology

Xiaonan Luo, Sun Yat-Sen University

Professor Institute of Computer Application

Xi Chen, University of Texas at Arlington

Department of Mathematics

Published

2014-08-27

Issue

Section

Articles for Printed Issues