The steady increase in data volume is a significant problem in fMRI time series. Recently proposed signal processing architectures based on digital hardware enable data reduction in real-time before the data are stored. We demonstrate that a high degree of data savings can be achieved with few simple operations. Coil compression and field probe data processing help breaking the data bottleneck in fMRI time-series.
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