Journal of South China University of Technology (Natural Science Edition) ›› 2017, Vol. 45 ›› Issue (7): 98-106.doi: 10.3969/j.issn.1000-565X.2017.07.014

• Computer Science & Technology • Previous Articles     Next Articles

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

ZHANG Li LI Bin TIAN Lian-fang LI Xiang-Xia   

  1. School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2016-09-18 Revised:2016-12-16 Online:2017-07-25 Published:2017-06-01
  • Contact: 李彬( 1979-) ,男,副教授,主要从事医学图像处理与模式识别研究. E-mail:binlee@scut.edu.cn
  • About author: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
  • 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.

Key words: image registration, similarity measure, local structure tensor, mutual information