Abstract #3190
Optimal Data Sampling for Noquist cin imaging
Moratal D, Brummer M, Dixon W
Universitat Politcnica de Valncia
Optimization of data selection for Noquist rFOV reconstruction using any size of the static and dynamic regions is investigated by exhaustive search in limited-size problems. Conclusions were extrapolated to Noquist acquisitions with realistic image dimensions that achieved optimal SNR for additive white noise. An upper bound of the attainable SNR as a function of the number of phases is also presented.