Title :
Medical Images Registration Based on Gradient Mutual Information and Improved Genetic Algorithm
Author :
Yang, Feng ; Fu, Kuang
Author_Institution :
Sch. of Comput. Sci. Technol., Heilongjiang Univ., Harbin, China
Abstract :
This paper suggests one method to process images registration to promote time and precise combined gradient mutation information with improved genetic algorithm. Adaptive probabilities of the crossover and the mutation are adopted to prevent the process from falling into a local maximum. Combination of the mutual information strategy with adaptive probabilities of GA accelerates convergence of the iterative process.
Keywords :
genetic algorithms; gradient methods; image registration; iterative methods; medical image processing; probability; adaptive probabilities; genetic algorithm; gradient mutual information; iterative process; medical images registration; Accuracy; Biological cells; Genetic algorithms; Image registration; Medical diagnostic imaging; Mutual information; adaptive crossover and mutation probabilities; genetic algorithm (GA); gradient mutual information (GMI); medical image registration;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2012 International Conference on
Conference_Location :
Rajkot
Print_ISBN :
978-1-4673-1538-8
DOI :
10.1109/CSNT.2012.62