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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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