Abstract #4524
Retrospective motion correction for carotid vessel wall imaging
Rui Li 1 , Shujing Cao 1 , Feng Huang 2 , and Chun Yuan 1,3
1
Center for Biomedical Imaging Research,
Tsinghua University, Beijing, Beijing, China,
2
Philips
Research China, Shanghai, China,
3
University
of Washington, Seattle, Washington, United States
Carotid vessel wall magnetic resonance imaging (MRI) has
been validated to discriminate different components in
plaques and evaluate their vulnerability. Patient motion
such as breathing and swallow is inevitable during
acquisition. Navigator echo or self-gating techniques
were explored by several previous works to monitor
swallowing. However all these techniques are prospective
methods and adopted accept/reject-reacquisition as their
data management strategy, which interrupted data
acquisition and prolonged scan duration. The target of
this work is to develop a retrospective motion
compensation method iteratively using a GRAPPA like
convolution and optimized coil element data combination
to preserve SNR during iteration.
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