Minimum Spanning Tree Fusing Uniform Sub-Sampling Points and High-Dimensional Features for Medical Image Registration

In this paper, we propose a novel registration algorithm based on minimal spanning tree. First, we extracted uniform sub-sampling points from image. Second, based on the feature points, in addition to using pixel intensity, we also added region based feature to include more spatial information. The proposed method is evaluated by performing registration experiments on BrainWeb database. The experimental results show that the proposed method achieves better robustness while maintaining good registration accuracy, compared to the conventional normalized mutual information (NMI) based registration method.