MRI Artifact Cancellation due to Unknown Respiratory Motion

In this study, an improved post-processing technique for canceling MRI artifact due to unknown respiratory motion in the imaging plane is presented. Respiratory motion is modeled by a two dimensional linear expanding-shrinking movement. Assuming that the body tissues are incompressible fluid like materials, the proton density per unit volume of the imaging object is kept constant. According to the applied model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MR data. When the motion parameters are known or can be estimated, a reconstruction algorithm based on bilinear superposition method was used to cancel the MRI artifact. In the case of motion parameters are unknown, first, the spectrum shift method is applied to find the respiratory fluctuation function, x directional expansion coefficient and x directional expansion center. Next, y directional expansion coefficient and y directional expansion center are estimated by using the minimum energy method. Finally, the validity of this proposed method is shown to be effective by using the simulated motion images.