基于差异进化算法的医学图像配准方法

Medical Image Registration Based on Differential Evolution

基于互信息的医学图像配准是一种目标函数的优化问题,但传统优化方法往往由于目标函数收敛到局部极值而导致错误的结果.该文将差异进化算法引入到医学图像配准中,利用其收敛特性避免互信息测度优化陷入局部极值,实现了多模态医学图像的配准.实验数据表明,以互信息测度为目标函数的医学图像仿射配准中,差异进化算法优于Powell算法和模拟退火算法.

Medical image registration using mutual information can be viewed as an optimization problem. In optimization problems, the objective function is often trapped into a local minimum. In this paper, differential evolution is proposed for medical image registration, and applied to registration of muhi-modality medical images. The proposed method can avoid local minimum due to its converging characteristics. Experimental results show that, using mutual information and affine transformation as objective functions, the differential evolution algorithm outperforms the Powell algorithm and the simulated annealing for medical image registration.