DocumentCode :
2604685
Title :
Multi-modality Image Registration Using Mutual Information Based on Gradient Vector Flow
Author :
Yujun Guo ; Cheng-Chang Lu
Author_Institution :
Dept. of Comput. Sci., Kent State Univ., OH
Volume :
3
fYear :
2006
fDate :
20-24 Aug. 2006
Firstpage :
697
Lastpage :
700
Abstract :
Similarity measure plays a critical role in image registration. Mutual information (MI) has been proved to be a promising measure used widely in multi-modality image registration. However, mutual information only takes statistical information into consideration, while spatial information is not even considered. In this paper, a novel approach is proposed to incorporate spatial information into MI through gradient vector flow (GVF). Mutual information now is calculated from the GVF-intensity (GVFI) map of the original images instead of their intensity values. Multi-modality brain image registration was performed to test the accuracy and robustness of the proposed method. Experimental results showed that the success rate of our method is higher than that of traditional MI-based registration
Keywords :
gradient methods; image registration; gradient vector flow; multimodality image registration; mutual information; Biomedical imaging; Brain; Computer science; Fluid flow measurement; Image registration; Medical diagnostic imaging; Mutual information; Performance evaluation; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.826
Filename :
1699621
Link To Document :
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