Robust Image Registration Using Mutual Information and Structural Features of Images

摘要

Medical image registration methods which use mutual information as similarity measure have been improved in recent decades. Mutual Information is a basic concept of Information theory which indicates the dependency of two random variables (or two images). In the most of these intensity based methods, images are treated as 1D signal and each pixel is considered independent from its neighbors. Although the location of pixels in an image includes more information than the intensity of them, it is ignored in most of the intensity based methods and they use only the intensity of a pixel to compute the images' histogram. There are some other methods like Regional Mutual Information (RMI) which use both of intensity of pixels and the information of image structure for registration. In this paper using the intensity of neighbor pixels of a pixel in image, it is proposed to make a new feature matrix for any image and measure mutual information between these matrices to determine how much similar two images are. Because of the using structural information of images, this method is more robust against noise and intensity variation and it is more accurate in comparison with methods which use only intensity of pixels and also it is faster than methods like RMI. Experimental results of the rigid registration of clinical brain images (CT), show the superiority of the proposed scheme.