A performance comparison study of optimization methods for registration of medical images
Nie Fang-yan · Journal of Hunan University of Arts and Science · 2011
Medical image registration,in essence,is the process that the similarity metric is referred to as the objective function,and the multi-parameter optimization method as the tool for obtaining the optimal transform parameters.In this paper,by use of the mutual information as the similarity metric,two optimization methods including the Powell method and the particle swarm optimization method(PSO) are exerted to explore the optimal transform parameters respectively,and their optimizing performances are evaluated and compared.The experimental results reveal that the Powell and PSO methods can cater to both the mono-modality and the multi-modality medical image registrations.Unfortunately,however,the running time of PSO is relatively longer and needs to be substantially reduced.So in order to improve the optimization efficiency,it is very necessary for PSO to counterbalance the registration accuracy and the running time.