Medical image registration by using salient phase congruency and regional mutual information

We have derived a new registration method for aligning medical images using salient phase congruency and regional mutual information. The proposed method firstly extracts the salient phase congruencies of the reference and floating image; secondly, it computes the regional mutual information with the salient phase congruency mappings; finally, the geometric transform is optimized by Particle Swarm Optimization. The proposed algorithm has three features: (1) Information of both intensity and space has been taken into consideration, because regional mutual information incorporates neighborhood pixels and the phase congruency can describe the structure of an image; (2) It is invariant to contrast; (3) It is not difficult to be implemented. Experiment results show that our method has acquired a high level of accuracy and robustness compared with some other algorithms.