Rapid imaging protocols such as the Echo Planar (EPI) method minimise the data acquisition time required for each image in the sequence, but a time-efficient protocol must nevertheless minimise the number of images to be acquired. The Bayesian spectral analysis of Bretthorst (1988, 1991), although currently applied mainly to spectroscopic data containing several thousand data points, permits also the routine analysis, for period and attenuation parameters, of noisy, heavily truncated, non-uniformly and sparsely sampled data. Bayesian error intervals are also available.
We demonstrate (Xing et al., 1994) a non-uniform sampling strategy that requires only four images (four complex data points per pixel) to obtain velocity and diffusion images for laminar liquid flow in a cylindrical pipe. The Bayesian error intervals demonstrate the significance of small departures, arising from flow tube imperfections and other non-ideal flow conditions, from the ideal Poiseuille profile of flow velocity. Using both EPI and the Bayesian analysis of motion-encoding, total experimental time is reduced from several hours to a few seconds, the new data analysis being responsible for a factor of 4.5.
We also demonstrate these techniques on steady non-Newtonian flow (of a 1% solution of Xanthan gum) in a straight cylindrical pipe; and finally (Derbyshire et al. 1994) on a 3-dimensional flow of water in an object of complex geometry.
G.L. Bretthorst (1988) Bayesian Spectrum Analysis and Parameter Estimation,Lecture Notes in Statistics, 48, Springer-Verlag, New York.
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D. Xing, S.J. Gibbs, J.A. Derbyshire, E.J. Fordham, T.A. Carpenter & L.D. Hall (1994) J. Magn. Reson., in press.
J.A. Derbyshire, S.J. Gibbs, T.A. Carpenter & L.D. Hall (1994) A.I.Ch.E. Jnl., in press.