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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.

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