DocumentCode
2193000
Title
Multi-modal Medical Image Registration Based on Gradient of Mutual Information and Hybrid Genetic Algorithm
Author
Huang, Xiaosheng ; Zhang, Fang
Author_Institution
Sch. of Inf. Eng., East China Jiaotong Univ., Nanchang, China
fYear
2010
fDate
2-4 April 2010
Firstpage
125
Lastpage
128
Abstract
Genetic algorithm is easy to fall into premature and Powell algorithm depends on the initial value, according to the characteristics of these two algorithms, in this paper, we combined the two optimization algorithms, the optimal parameter solution which is obtained by genetic algorithm is used as the initial value in Powell algorithm, and then Powell algorithm is used to obtain global optimization parameter solution. In the process of optimizing, the maximum gradient of mutual information is used for measuring the similarity between the two registered images. The experiment shows that the registration algorithm proposed in this paper can do more effectively and more accurately work than the optimizing algorithm based on mutual information and genetic algorithm. And the registration accuracy could achieve sub-pixel.
Keywords
genetic algorithms; gradient methods; image registration; medical image processing; Powell algorithm; global optimization parameter solution; hybrid genetic algorithm; multimodal medical image registration; mutual information gradient; Biomedical engineering; Biomedical imaging; Clinical diagnosis; Genetic algorithms; Genetic engineering; Image registration; Layout; Medical diagnostic imaging; Mutual information; Simulated annealing; Powell algorithm; genetic algorithm; gradient of mutual information; image registration;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on
Conference_Location
Jinggangshan
Print_ISBN
978-1-4244-6730-3
Electronic_ISBN
978-1-4244-6743-3
Type
conf
DOI
10.1109/IITSI.2010.112
Filename
5453635
Link To Document