Online dynamic magnetic resonance imaging based on an improved motion prediction scheme

Motion prediction algorithms are often used in dynamic magnetic resonance imaging to improve the compressed sensing based reconstruction. Previously, the difference calculation (DC) between the current frame (to be reconstructed) and the estimated frame was used as sparse residual signals. In order to obtain sparser signal, an improved Motion Estimation (ME) and Motion Compensation (MC) method was proposed to predict the current frame from previous reconstructed frames with an extrapolation procedure. An overlapped block motion compensation algorithm was used to suppress the block artifacts. The sparse residual signal was used to reconstruct the current frame using an iterative soft thresholding algorithm. The experiment results show that, the ME/MC prediction can improve the quality of reconstructed frames at slight additional computational cost. For the case that ME/MC combined with previous DC method, a high quality image reconstruction can be achieved with relatively small time consumption.