Until today, several software-based approaches to increase the temporal resolution in cardiac computed tomography by estimating motion vector fields (MVFs) have been developed. Thereunder, the majority are motion compensation algorithms, which estimate the MVFs employing a three-dimensional registration routine working on reconstructions of multiple cardiac phases.2, 6, 7, 12 We present an algorithm that requires nothing more than the data needed for a short scan reconstruction for motion estimation and motion-compensated reconstruction, which both are based on the reconstruction of volumes from a limited angular range.2, 3, 7, 8 Those partial angle reconstructions are centered at different time points during the short scan and have a temporal resolution of about 10ms each. The MVFs are estimated by a constrained cost function optimization routine employing a motion artifact measuring cost function. During optimization, the MVFs are applied directly by warping the partial angle reconstructions, and the motion compensation is established by simply adding the shifted images. In order to enforce smooth vector fields and keep the number of parameters low, the motion is modeled by a low degree polynomial. Furthermore, to find a good estimation of the MVFs even in phases with rapid cardiac motion, the constrained optimization is re-initialized multiple times. The algorithm is validated with the help of a simulation study and applied to patient data, where motion- compensated reconstructions are performed in various cardiac phases. We show that the image quality can be improved, also in more rapid cardiac phases due to re-initialization of the optimization routine.