@inproceedings{406933a42fb54be482cf28b183971f5a,
title = "High-performance medical image registration using improved particle swarm optimization",
abstract = "Optimization of a similarity metric is an essential component in intensity-based medical image registration. In this paper, an improved variable neighborhood selection based particle swarm optimization (VNS-PSO) is proposed. The PSO algorithm is co-operative, population-based global search swarm intelligence mataheuristics. The improved version of PSO algorithm possesses better ability to escape from the local minima to the global optimum, and more adapts for intensity-based medical image registration. The performances of VNS-PSO algorithm and downhill simplex method to medical image registration are compared. Experimental results demonstrate that the improved VNS-PSO method is robust, accurate, efficient and more suitable for medical image registration.",
keywords = "Image registration, Mutual information, Particle swarm optimization",
author = "Jing Jin and Qiang Wang and Yi Shen",
year = "2008",
doi = "10.1109/IMTC.2008.4547134",
language = "英语",
isbn = "1424415411",
series = "Conference Record - IEEE Instrumentation and Measurement Technology Conference",
pages = "736--740",
booktitle = "2008 IEEE International Instrumentation and Measurement Technology Conference Proceedings, I2MTC",
note = "2008 IEEE International Instrumentation and Measurement Technology Conference, I2MTC ; Conference date: 12-05-2008 Through 15-05-2008",
}