Fully Automated Respiratory Motion Compensation in Myocardial Perfusion MRI Using Navigators

Henrik Pedersen¹, Steffen Ringgaard², Won Yong Kim²

Correction of respiratory motion represents a major practical problem in quantitative myocardial perfusion MRI. This study presents a retrospective method of respiratory motion correction that is fully automated, insensitive to image brightness changes, and suitable for correcting respiratory motion artifacts in accelerated MRI. The proposed method uses additionally acquired respiratory navigators to predict non-rigid motion over the entire field-of-view. The underlying motion model is learned from a set of training images. Among the navigator and training configurations evaluated in this study, the optimum setup achieved an average 4-5 fold in-plane motion reduction in 32 myocardial perfusion MRI data sets.