Penalized-likelihood sinogram restoration for CT artifact correction

In CT sinogram preprocessing, the best possible estimate of the line integrals needed for image reconstruction from the set of noisy, degraded detector measurements is reported. A general imaging model relating the degraded measurements to the ideal sinogram and the estimation of the ideal line integrals by iteratively maximizing an appropriate penalized statistical likelihood function are discussed. Image reconstruction is then performed by the use of existing non-iterative approaches.