Multi-modal medical image registration based on phase congruency and quantitative-qualitative mutual information

摘要

A new approach of multi-modal medical image registration is proposed to overcome the drawbacks of mutual information as taking no consideration of the space information, taking all intensities without distinction, and being sensitive to noise. The proposed method firstly extracts the phase congruencies of the reference and floating image, secondly, it computes quantitative-qualitative mutual information with the phase congruency mappings, finally, the geometric transform is optimized by Particle Swarm Optimization. The quantitative-qualitative mutual information used in our algorithm select the pixels whose utility are larger than the threshold of 1. In addition, Mutual information incorporating phase congruency assimilates the information of both intensity and space. Experiment results show that our approach is more robust in suppressing noise and can achieve higher accuracy.