Optimising sampling patterns for bi-exponentially decaying signals.

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Reci, A 
Ainte, MI 
Sederman, AJ 
Mantle, MD 
Gladden, LF 

A recently reported method, based on the Cramér-Rao Lower Bound theory, for optimising sampling patterns for a wide range of nuclear magnetic resonance (NMR) experiments is applied to the problem of optimising sampling patterns for bi-exponentially decaying signals. Sampling patterns are optimised by minimizing the percentage error in estimating the most difficult to estimate parameter of the bi-exponential model, termed the objective function. The predictions of the method are demonstrated in application to pulsed field gradient NMR data recorded for the two-component diffusion of a binary mixture of methane/ethane in a zeolite. It is shown that the proposed method identifies an optimal sampling pattern with the predicted objective function being within 10% of that calculated from the experiment dataset. The method is used to advise on the number of sampled points and the noise level needed to resolve two-component systems characterised by a range of ratios of populations and diffusion coefficients. It is subsequently illustrated how the method can be used to reduce the experiment acquisition time while still being able to resolve a given two-component system.

Bi-exponential model, Cramér-Rao Lower Bound theory, PFG NMR diffusion, Sampling pattern, Diffusion, Ethane, Image Processing, Computer-Assisted, Magnetic Resonance Spectroscopy, Methane
Journal Title
Magn Reson Imaging
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Elsevier BV