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Abstract #3901

Automatic Extraction of Cardiac and Respiratory Motion via Self-Refocused Rosette Navigators and Independent Component Analysis

David Rigie1, Thomas Vahle2, Tiejun Zhao3, Klaus Schäfers4, Björn Czekalla 4, Lynn Frohwein4, and Fernando Boada1

1Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Medical Center, New York, NY, United States, 2Siemens Healthcare GmbH, Erlangen, Germany, 3Siemens Healthcare, New York, NY, 4European Institute for Molecular Imaging, University of Mϋnster, Mϋnster, Germany

Due to the recent availability of simultaneous PET-MR, there has been much interest in MR-based motion correction for PET imaging. A key component of any such scheme is a mechanism for tracking respiratory and cardiac motion phases throughout the entire exam. In this work, we present a robust, automated approach whereby respiratory and cardiac motion information is jointly encoded with rosette navigators and decoded via independent component analysis (ICA). This approach obviates the need for any external motion tracking devices (e.g. bellows or ECG) and requires just a contrast-neutral, self-refocused navigator echo (≈2ms) per repetition time and so may be easily incorporated into many clinical sequences.

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