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Abstract #3161

Feasibility Study: 2-D Self-Navigation using Compressed Sensing Reconstruction for Respiratory Gating in Free-breathing 3-D CINE Imaging

Ivo Prochaska1, Jens Wetzl1,2, Christoph Forman3, Armin Nagel4, and Andreas Maier1,2

1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 2Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 3Siemens Healthcare GmbH, Magnetic Resonance, Erlangen, Germany, 4Universitätsklinikum Erlangen, Erlangen, Germany

We investigate the feasibility of using 2-D self-navigation for respiratory gating for free-breathing whole-heart 3-D CINE imaging, where respiration-induced cardiac motion may be more easily detected than in commonly used 1-D self-navigation methods. We compare self-navigation images, derived gating signals and resulting 3-D CINE images of the 1-D and 2-D methods and find that respiratory motion can be well visualized with the 2-D method; both methods show a good overlap of gating signals and little difference in resulting image quality. 2-D self-gating may thus be considered a promising alternative to 1-D self-navigation as it allows easier detection of respiratory motion.

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