Abstract #1599
Predictive Filtering for Improved Robustness in Prospective Motion Correction
Brian Keating 1 , Aditya Singh 1 , Benjamin Zahneisen 1 , Linda Chang 1 , and Thomas Ernst 1
1
Department of Medicine, University of
Hawaii, Honolulu, HI, United States
System latencies can reduce the efficacy of prospective
motion correction (PMC) with external optical tracking,
especially during fast movements (50mm/s or 50/s
range). We integrated a Kalman filter into a
prospectively corrected gradient echo (GRE) sequence in
order to estimate the velocity and acceleration of the
head from lagged optical tracking data. The latency was
accounted for by extrapolating forward in time before
each prospective update. In addition, conjugate
gradient-based retrospective motion correction was
performed in Matlab to correct for residual tracking
errors. GRE images show reduced motion artifacts when
predictive filtering is used as compared to standard
PMC.
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