关键词: 医学图像配准, 全局寻优, 粒子群算法, 动态调整惯性权重

Abstract: Particle Swarm Optimization （PSO） is a global evolutionary approach，which can effectively avoid the local extremum in biomedical image registration.A new particle swarm optimization with dynamically changing inertia weight is applied in image registration based on mutual information.The initial location is assigned uniformly to avoid local extremum caused by evolution in some little area initiated randomly.A parameter is added to control the ceasing of iteration，improving the speed.Experimental results indicate that the new algorithm can find the global optimization and converged fast.

Key words: image registration, Particle Swarm Optimization（PSO）, dynamically changing inertia weight