Abstract #2552
Real-Time Dynamic Prediction of Motion during Prospective Motion Correction Helps Reduce Errors Caused by Fast Motions and Delayed Motion Measurements
Burak Erem 1,2 , Onur Afacan 1,2 , Ali Gholipour 1,2 , and Simon K Warfield 1,2
1
Department of Radiology, Boston Children's
Hospital, Boston, MA, United States,
2
Harvard
Medical School, Boston, MA, United States
Prospective motion correction of MRI steers the imaging
field of view (FOV) to image as if the subject was not
moving. All existing prospective motion correction
techniques to date will perform the action of steering
the FOV using motion measurements made in the past,
because all motion measurements are available after some
delay. Moreover, all of these existing techniques assume
that this delay is infinitesimal. However, recent work
demonstrates that this assumption is wrong and leads to
poor motion compensation, especially when motions are
rapid. Prediction of motion parameters shortly into the
future has been proposed to reduce errors due to
measurement delays and improve motion compensation. Here
we assess how dynamic prediction compares to PROMO and
static motion estimation.
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