Multi-modal diffeomorphic demons registration based on mutual information

Diffeomorphic demons algorithm is an efficient and robust method in nonrigid image registration. It uses mean squared error as the similarity measure and set the gradient and gray level difference as the interior and exterior force respectively to make the points move. However it cannot deal with multiple modality images. In this paper, mutual information is used as the similarity measure instead of mean squared error and the gradient of mutual information respect to parameters is set as the force to make the points move. Then the diffeomorphic demons algorithm is extended to match multi-modal images. The experiment with magnetic resonance T1 image and magnetic resonance T2 image shows that this method is effective and performs better and more quickly compared with B-spline free-form deformation method.