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Abstract #4360

A Robust and Automatic Cardiac and Respiratory Motion Detection Framework for Self-Navigated Radial MRI

Li Feng 1 , Daniel K Sodickson 1 , and Ricardo Otazo 1

1 Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University, School of Medicine, New York, New York, United States

Self-navigation provides an alternative to ECG triggering/gating in cardiac MRI and has been used in radial imaging where inherent navigator signal is obtained from the centers of k-space. However, this signal, which is an average of image over entire FOV, includes unwanted signals outside the region of interest and reduces the capability of accurate motion detection, particularly for patients with arrhythmias or irregular breathing. This study proposes a novel approach to automatic detect both respiratory and cardiac signal for free-breathing cardiac imaging by restricting the radial spokes to include signal from only region of interest based on the Fourier-slice theorem.

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