A Projection Match Based Motion Compensated Algorithm in 4DCBCT

Motion blurring artifacts in CBCT can be alleviated by providing a sequence of phase-depended images through 4D-CBCT technique. However, it introduces streaking artifacts due to the under-sampled projection problem for each phase. One possible solution is to use deformable registration algorithms to estimate the deformation vector fields (DVF) between different phase-depended images, which is essentially an optimization problem. Usually, we use an intensity-based similarity metric in the optimization problem by minimizing the squared sum of intensity differences (SSD) of the reference image and the target image. However, this metric is not suitable for the 4D-CBCT registration case, because both the reference image and the target image are not with high image quality. As a result, the registration accuracy of the conventional SSD metric still has room to improve. In our method, we develop a novel similarity metric in the registration framework by considering the characteristic of the phase-depended images. 1) A prior image reconstructed by the whole projection set is regarded as the reference image; 2) Instead of an intensity-based similarity metric, a CT projection domain metric is adopted by minimizing the forward projection of the prior image and the corresponding acquired projection data of the target image. To validate the performance of the proposed method, we used a set of simulation data and compared with the Demons algorithm. To be specific, the image quality was improved to a large extent, especially in regions of interest of moving tissues. Quantitative evaluations were shown in terms of the rooted mean square error (RMSE) by our method when compared with existing Demons method.