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Abstract #0560

Accelerating Dynamic MRI Via Spatially Varying Causal Windows

Uygar Smbl1, Juan Manuel Santos, John Mark Pauly1

1Electrical Engineering, Stanford University, Stanford, CA, USA

A causal, pixel-dependent exponential decay window is suggested to improve time series reconstruction. The study is motivated by the observation that many image pixels change slowly over time, while a few pixels experience rapid changes. The window interpretation is realized via a Kalman filter based algorithm. This fast statistical algorithm decreases the temporal blur of the sliding window reconstruction. Moreover, the algorithm handles arbitrary readout trajectories and multiple coils naturally.