Maximum-likelihood x-ray computed-tomography finite-beamwidth considerations

The underlying model and iterative image-reconstruction algorithm, based 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 image clarity and reduction of artifacts: (1) There is an improvement in delineation of the boundaries of low-contrast soft-tissue substructures. There is an improvement in the capability of identifying at least one of the low-contrast soft-tissue substructures. (2) The algorithm is capable of reconstructing onto a discrete array of finer resolution, again with better delineation of substructures than the filtered-backprojection algorithm. (3) Maximum-likelihood images at an atypically low photon flux level are, at the very least, comparable in image quality to filtered-backprojection images at a much higher and more typical photon flux level. These observations imply that the diagnostic capability of x-ray computed tomography may be improved to a broader range of otherwise adverse conditions. It may be capable of much better visualization 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.