基于互信息的功能磁共振图像配准

互信息作为衡量两幅图像配准的相似性测度函数，当两幅图像配准时，互信息达到最大值。该文提出了基于互信息脑功能磁共振图像配准新方法，采用了无需计算梯度的Powell直接搜索算法，并通过多分辨的方式加快了图像配准速度。磁共振的配准实验证明，互信息法能准确地实现多模态医学图像的配准，并且能达到亚像素的精度。
关 键 词 功能磁共振; 图像配准; 互信息; 亚像素

Abstract The functional magnetic resonance imaging (fMRI) image registration is a key technology in the study of the human brain function. In this article, we present a new fMRI image registration algorithm based on the mutual information. The mutual information is specified as scaling the similarity of two images registration. The mutual information of two images reaches to maximization when the two images are registered. Powell direct searching and multi-scale algorithm are introduced to accelerate the image registration speed without calculating gradient algorithm. Simulative experiments of fMRI image registration demonstrate that this method can precisely achieve the multimodal medical image registration, and can reach sub-pixel precision
Key words functional magnetic resonance imaging (fMRI); image registration; mutual information; sub- pixel