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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