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

作者：Zhang, Li; Li, Bin^*; Tian, Lian-Fang; Li, Xiang-Xia

来源：Journal of South China University of Technology(Natural Science Edition), 2017, 45(7): 98-106.

DOI：10.3969/j.issn.1000-565X.2017.07.014

• Local characteristics
• Local structure tensors
• Multimodal image registration
• Mutual informations
• Registration methods
• Similarity measure
• Spatial structure information
• Structure information

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 registration enhances. Moreover, some registration experiments are conducted on simulated brain images and clinical images. 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.

• 出版日期2017-7-1
• 单位华南理工大学