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Four-Dimensional Cone-Beam Computed Tomography (4D-CBCT) imaging is important in upper abdomen tumor radiation treatment as it can obtain the tumor motion information immediately before treatment. However, the number of projections at a single phase for 4D-CBCT imaging is very small, and the CT images reconstructed by using conventional algorithms will be contaminated by view aliasing artifacts and noises. To address this problem, we propose a framework to jointly estimate and compensate the inter-phase motion for 4D-CBCT image reconstruction. Specifically, by introducing the intensity-based optical flow (OF) constraint into the reconstruction framework, the model can deal with the inter-frame displacements and improve the image quality simultaneously. The primal-dual algorithm method was used to optimize the cost function of the proposed model. Experiments on physical phantoms and patient data show that the proposed approach can effectively reduce the noise and artifacts in 4D&#x2013;CBCT images and achieve the inter-phase motion vector fields (MVFs).

Joint Motion Estimation and Compensation for Four-Dimensional Cone-Beam Computed Tomography Image Reconstruction