Consistent feature-aligned 4D image registration for respiratory motion modeling

This paper presents a consistent feature-aligned 4D image registration algorithm and its medical application. The matching across a temporal sequence of volumetric images is based on a 4D (3D spatial + 1D temporal) free-form B-spline deformation model, which ensures interpolated motions with both spatial and temporal smoothness. We first develop the forward and inverse matching models with feature alignment constraints, then iteratively refine the registration results by incorporating extra inverse consistency. Experimental results show that our method achieves better registration accuracy than previous 3D registration and 4D registration methods. This algorithm can be used to parameterize temporal CT lung volume images for motion analysis and tracking.