Improved emission tomography via multiscale sinogram analysis

In this paper, we extend a multiscale Bayesian approach to modeling and estimation of general Poisson processes previously developed in [1] by the first two authors, and apply it to the emission computed tomography (ECT) image reconstruction problem. We develop a practical prior model for the sinogram image, which we use to estimate the underlying sinogram intensity from the raw projection data prior reconstruction. This sinogram estimate is then used in conjunction with the standard filtered-backprojection algorithm to produce an improved image reconstruction. The impact of the new filtering approach on ECT imaging is illustrated with simulated and clinical data.