说明：  摘 要：针对人脑的二维图像设计了一种遗传算法和最大互信息相结合的医学图像配准算法，采用互信息配准模型，以图像的灰度统计信息为配准依据，用改进的遗传算法搜索图像间的最优变换参数，并用最大互信息作为目标函数指导最优变换参数的搜索。通过实验验证了算法的可行性和稳定性。
(Abstract: The paper designs a registration algorithm which links improved genetic algorithm and the maximal mutual information method for two 2D brain images. It takes mutual information model and bases on the intensities of the images, and uses improved genetic algorithm to search the best transformation parameters. It also uses the maximal mutual information as the aim function to guide searching the best transformation parameters, and the effectiveness of the algorithm is proved.)