Evaluating popular non-linear image processing filters for their use in regularized iterative CT

Iterative CT algorithms are becoming increasingly popular in recent years, and have been found useful when the projections are limited in number, irregularly spaced, or noisy, which are imaging scenarios often encountered in low-dose imaging and compressed sensing. One way to cope with the associated streak and noise artifacts in these settings is either to incorporate or to interleave a regularization objective into the iterative reconstruction framework. In this paper we explore possible techniques for the latter. We investigate a number of non-linear filters popular in the image processing literature for their suitability in iterative CT application, here OS-SIRT.