Keywords: Data Processing, PET/MRNuclear Magnetic Resonance (NMR) has been a frequently-used analytical tool in many areas of modern biology, chemistry and medicine for decades. However, it is usually limited by a low Signal-to-Noise ratio (SNR). In practical applications, Signal Averaging (SA) with repeated samplings is required to improve the signal-to-noise ratio, which greatly increases the scanning time. In this paper, based on the characteristic that NMR time-domain signals can be decomposed exponentially, a model for denoising NMR spectroscopy based on exponential decomposition constraints is proposed. It can effectively improve the denoising ability and therefore save the scanning time.
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