Keywords: Heart, Motion CorrectionMagnetic resonance imaging (MRI) is susceptible to respiratory motion-induced artifacts due to the relatively slow data acquisition. These artifacts remain an impediment to clinical application and are further amplified in cardiovascular MRI. Respiratory motion model is an effectively method to reduce motion artifacts. In this study, we proposed a novel patient-specific respiratory motion correction method with more reliable training data and capability to perform spoke-wise correction. Combined with compressed sensing, parallel imaging, image registration and model fitting, this method greatly reduces respiratory motion artifacts.
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