Medical image registration based on maximization of mutual information and particle swarm optimization

In order to provide comprehensive information and improve the accuracy of clinical diagnoses and surgical therapies, medical image fusion is becoming a new hot topic. As the basic and key issue, medical image registration has very important meaning. This paper offers a solution to medical image registration based on maximization of mutual information (MI) and particle swarm optimization (PSO). First, the rigid transformation with translational and rotational parameters is applied to the floating image. As an increasingly popular matching criterion for image registration, MI is adopted in this method. Theoretically, the maximization of MI is obtained if the transformed image and the reference image are geometrically aligned. Then an improved PSO algorithm is used to search the registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.