In this paper a maximization of mutual information based multi-modality medical image registration method is described. The method presented in this paper applies mutual information to measure the information redundancy between the intensities of corresponding voxels in both images

which is assumed to be maximal if the images are geometrically aligned. MI is used as a measure of similarity of two images. There exist many important technical issues to be solved about the method such as how to compute MI more accurately and how to obtain the maximization of MI

which are seldom mentioned in published papers. In this paper we provide some implementation issues

for example

subsampling

PV interpolation

outlier strategy. Powell searching algorithm is used which does not compute gradients. The combination of these computation techniques and searching strategy leads to a fast and accurate multi-modality image registration. The registration results of 3D human brain volume data of 41 CT-MR and 35 PET-MR from seven patients are validated to be subvoxel. The registration method is promising in clinical use.