An iterative projection-based motion estimation and compensation scheme for head x-ray CT




Although current computed tomography (CT) systems can scan the head in a very short time, patient motion sometimes still induces artifacts. If motion occurs, one has to repeat the scan; to avoid motion, sedation or anesthesia is sometimes applied.


The authors propose a method to iteratively estimate and compensate this motion during the reconstruction. In every iteration, the rigid motion was estimated view-by-view and then used to update the system matrix. A multiresolution scheme was used to speed up the convergence of this joint estimation of the image and the motion of the subject. A final iterative reconstruction was performed with the last motion estimate.


The method was evaluated on simulations, patient scans, and a phantom study. The quality of the reconstructed images was improved substantially after the compensation. In simulation and phantom studies, root-mean-square error was reduced and mean structural similarity was increased. In the patient studies, most of the motion blurring in the reconstructed images disappeared after the compensation.


The proposed method effectively eliminated motion-induced artifacts in head CT scans. Since only measured raw data are needed for the motion estimation and compensation, the proposed method can be applied retrospectively to clinical helical CT scans affected by motion.