Correction of respiratory motion with 100% acquisition efficiency is of great significance for clinical abdominal imaging. In this study, we propose a novel self-navigation liver respiratory motion correction method for 3D radial sampling. This new approach is based on the fact that radial acquisition enables oversampled k-space center to extract motion-state signal and neural network can be used for data dimensionality reduction. Both regular and irregular hepatic breathing experiments were conducted and the proposed method has shown similar reconstruction image quality with bellow.
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