Improvement of accuracy in deformable registration in radiation therapy

In this paper, we propose a segmentation assisted registration model. It partitions the domain of images into several regions such that the residue image in each region is identically distributed with zero mean and variance to be optimized. In this model, we minimize an energy that combines negative log-likelihood of the residue in each region, smoothness of the deformation field and length of the partition curve. It can be viewed as a generalization of the sum of squared difference model and global Gaussian model where the variance is a constant in the entire domain. By taking different variances in different regions, the registration becomes more efficient and accurate, which are demonstrated by the experiments on synthetic and clinical data.