For medical image registration of good robustness

high-accuracy and speed requirements

this paper proposes a DoG(difference of Gaussian) keypoints image registration algorithm based on Rényi entropy. This algorithm extracts DoG key points from images

then incorporates grey scale information of the key point into the joint Rényi entropy

and estimates joint Rényi entropy directly using minimum spanning tree. The new algorithm combines the robustness of DoG key points and the high speed of Rényi entropy estimated by the minimum spanning tree. Experimental results show that in the images with noise

non-uniform intensity and large scope of the initial misalignment case

the algorithm achieves better robustness and higher speed while maintaining good registration accuracy.