Medical Image Registration Algorithm Based on Bounded Generalized Gaussian Mixture Model - Wang, Jingkun; Xiang, Kun; Chen, Kuo; Liu, Rui; Ni, Ruifeng; Zhu, Hao; Xiong, Yan (Frontiers in Neuroscience, 2022)
In this paper, a registration method based on the bounded generalized Gaussian mixture model is proposed for medical images. We apply a bounded generalized Gaussian mixture model to approximate the joint intensity of source medical images. The mixture model problem is formulated in a maximum likelihood framework, solved by an expectation-maximization algorithm. Extensive computer simulations verify the registration performance of the proposed approach on different medical images. Empirical findings confirm that the versions of the proposed approach are significantly better than those of other conventional approaches.