Predictive Filtering for Improved Robustness in Prospective Motion Correction

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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