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Abstract #1271

The Next Step in Self-Navigated Coronary MRI: A Hybrid Approach for Affine Motion Correction

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.