Abstract #4523
Prediction of the Benefit of Motion-Compensated Reconstruction for Whole-Heart Coronary MRI
Jens Wetzl 1,2 , Christoph Forman 3 , Andreas Maier 1,2 , Joachim Hornegger 1,2 , and Michael O. Zenge 3
1
Pattern Recognition Lab, Department of
Computer Science, Friedrich-Alexander-Universitt
Erlangen-Nrnberg, Erlangen, Germany,
2
Erlangen
Graduate School in Advanced Optical Technologies (SAOT),
Friedrich-Alexander-Universitt Erlangen-Nrnberg,
Erlangen, Germany,
3
Siemens
AG, Healthcare, Imaging & Therapy Systems, Magnetic
Resonance, Erlangen, Germany
Respiratory motion represents a challenge in
free-breathing whole-heart coronary MR angiograpy. For
respiratory motion compensation, weighted iterative
reconstruction aims to reconstruct a consistent sub-set
of the acquired data. However, this may lead to
increased sub-sampling artifacts. Motion-compensated
(MoCo) reconstruction promises to overcome this by
incorporating all acquired data using a motion model.
Unfortunately, computation times are longer, and the
resulting signal-to-noise ratio (SNR) improvement may
not always justify this effort. This work proposes a
method to predict the benefit of MoCo over weighted
reconstruction directly after data acquisition. This
prediction method was evaluated with in-vivo experiments
in 15 volunteers.
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