Davide Piccini1, Arne Littmann2,
Hui Xue3, Jens Guehring3, Michael O. Zenge2
1Pattern Recognition Lab,
University of Erlangen-Nuremberg, Erlangen, Germany; 2MR
Applications & Workflow Development, Healthcare Sector, Siemens AG,
Erlangen, Germany; 3Imaging & Visualization, Siemens Corporate
Research, Princeton, NJ, United States
Conventional navigator-gated techniques for coronary MRI are limited both in scan-time efficiency and precision. Alternative approaches that derive the positional information of the heart directly from the readouts used for imaging achieve up to 100% efficiency, but are limited to 1D rigid respiratory motion correction. In contrast, image registration allows for a more realistic estimation of the underlying 3D motion, but is less efficient. In this work, a hybrid method that combines 1D self-navigation with registration-based affine motion compensation is presented. This method was implemented for 3D radial whole-heart coronary MRI and was compared with a navigator-gated approach in volunteers.