DocumentCode :
1994096
Title :
Adaptive particle swarm optimization for medical image registration
Author :
Zhou, Di ; Wang, Honghui ; Xu, Weizhong
Author_Institution :
Dept. of Comput. Sci., Sichuan Univ. of Arts & Sci., Dazhou, China
fYear :
2011
fDate :
16-18 Sept. 2011
Firstpage :
4713
Lastpage :
4716
Abstract :
In the practical applications, there are many medical images needing to be registered at some time and the requirement for the time of the registration is high. The current image registration methods register the images one by one independently, so the methods can be called static image registration methods. The kind of methods is time consuming since they need to initialize the relevant parameters before they start to deal with some image, so they can not meet the requirement of the practical applications for registration time. Through statistical research, we find the differences of the images are limited. We proposed one adaptive brain MR image registration algorithm combining inheritance idea and PSO. The experimental results show that this algorithm can obtain higher stability of image registration and lower time for image registration compared to corresponding static image registration methods. In many occasions, this algorithm can obtain high image registration precision too.
Keywords :
biomedical MRI; image registration; medical image processing; particle swarm optimisation; statistical analysis; adaptive brain MR image registration algorithm; adaptive particle swarm optimization; magnetic resonance imaging; medical image registration; static image registration methods; statistical research; Biomedical imaging; Computed tomography; Computer science; Educational institutions; Genetic algorithms; Image registration; Particle swarm optimization; PSO; adaptive; brain MR image; image registration; inheritance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
Type :
conf
DOI :
10.1109/ICECENG.2011.6058034
Filename :
6058034
Link To Document :
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