MAXIMUM-LIKELIHOOD X-RAY COMPUTED-TOMOGRAPHY FINITE-BEAMWIDTH CONSIDERATIONS

The underlying model and iterative image-reconstruction algorithm, bas ed on maximum-likelihood estimation, is extended to consider finite x- ray beam width. Simulations are presented by maximum-likelihood images compared with filtered-backprojection images. The main conclusion of this study is that it is feasible to obtain a marked improvement in im age clarity and reduction of artifacts: (1) There is an improvement in delineation of the boundaries of low-contrast soft-tissue substructur es. There is an improvement in the capability of identifying at least one of the low-contrast soft-tissue substructures. (2) The algorithm i s capable of reconstructing onto a discrete array of finer resolution, again with better delineation of substructures than the filtered-back projection algorithm. (3) Maximum-likelihood images at an atypically l ow photon flux level are, at the very least, comparable in image quali ty to filtered-backprojection images at a much higher and more typical photon flux level. These observations imply that the diagnostic capab ility of x-ray computed tomography may be improved to a broader range of otherwise adverse conditions. It may be capable of much better visu alization of soft-tissue regions that reside near dense regions (such as bone or metal prostheses), of visualizing finer spatial detail, and of use with much lower x-ray dosages.