Computer Science & Technology

Multi-Modal Image Registration on the Basis of Local Structure Tensor-Mutual Information

Expand
  • School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
张莉( 1987-) ,女,博士生,主要从事模式识别与医学图像处理研究. E-mail: 88zhangli0622@163. com

Received date: 2016-09-18

  Revised date: 2016-12-16

  Online published: 2017-06-01

Supported by

Supported by the National Natural Science Foundation of China( 61305038,61273249)

Abstract

Mutual information ( MI) measure considers the global characteristics of image gray statistics only,and ignores spatial structure information and local characteristics of image gray statistics.In order to overcome these drawbacks,a registration method on the basis of the new measure of local structure tensor-mutual information ( LST- MI) is proposed.The proposed LST-MI measure considers the structure information of image neighborhood fully,gives the pixel position with greater importance larger weighting factor.Thus,the distinguishing of global extremum strengthens,the risk of trapping at local extremum reduces,the success rate improves,and the robustness of regis- tration enhances.Moreover,some registration experiments are conducted on simulated brain images and clinical im- ages.The results show that,in comparison with the registration method on the basis of mutual information and local mutual information,the proposed method improves the success rate of registration by more than 50%,and enhances the registration robustness significantly.

Cite this article

ZHANG Li LI Bin TIAN Lian-fang LI Xiang-Xia . Multi-Modal Image Registration on the Basis of Local Structure Tensor-Mutual Information[J]. Journal of South China University of Technology(Natural Science), 2017 , 45(7) : 98 -106 . DOI: 10.3969/j.issn.1000-565X.2017.07.014

Outlines

/