Camera-based respiratory motion sensing (VitalEye) was successfully used to compute a respiratory signal for motion-resolved 4D radial ultrashort echo time (UTE) lung MRI. k-space data were sorted with respect the respiratory signal and binned into 10 different motion states to resolve respiratory motion. The respiratory signals from VitalEye were comparable to self-navigators. The 4D lung MRI reconstructions from both VitalEye and self-navigators were able to resolve respiratory motion and the signal intensity profiles along with the lung-liver interface and pulmonary vessels demonstrated that they both provided sharper image contrast compared to the motion-averaged images.
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