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NEW DEVELOPMENT OF NONRIGID REGISTRATION

Published online by Cambridge University Press:  05 June 2014

HSI-YUE HSIAO
Affiliation:
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA email hsiyue@gmail.com, josephsieh@gmail.com, chen.xi@mavs.uta.edu
CHIH-YAO HSIEH
Affiliation:
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA email hsiyue@gmail.com, josephsieh@gmail.com, chen.xi@mavs.uta.edu
XI CHEN
Affiliation:
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA email hsiyue@gmail.com, josephsieh@gmail.com, chen.xi@mavs.uta.edu
YONGYI GONG
Affiliation:
School of Information Technology, Guangdong Foreign Language and International Business University, Guangzhou, China
XIAONAN LUO
Affiliation:
National Engineering Research Center of Digital Life, School of Information Science & Technology, Sun Yat-sen University, Guangzhou, China
GUOJUN LIAO*
Affiliation:
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA email hsiyue@gmail.com, josephsieh@gmail.com, chen.xi@mavs.uta.eduNational Engineering Research Center of Digital Life, School of Information Science & Technology, Sun Yat-sen University, Guangzhou, China
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Abstract

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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.

Information

Type
Research Article
Copyright
Copyright © 2014 Australian Mathematical Society