Abstract
Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities, different time points, and/or different subjects. A large number of methods for image registration are described in the literature. Unfortunately, there is no one method that works very well for all applications. Particle swarm optimization is a stochastic, population-based evolutionary computer algorithm. In this paper, we propose a new approach using improved Particle swarm optimization for medical image registration. The algorithm has been successfully used for medical image registration. The feasibility of the proposed method is demonstrated and compared with Standard PSO based image registration technique. The obtained results indicate that the proposed method yields better results in term of both algorithm stability and accuracy. Computational time is also relatively small in the proposed case compared to the other case.
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