Tomography reconstruction by entropy maximization with smoothing filtering

Abstract

The maximum entropy method (MEM) is a consistent way to treat the problem of tomography reconstruction where an image should be selected from a set of images that fit the measurement data. In this article, MEM is applied to image reconstruction from projections using an entropy formula modified by adding filter terms in order to eliminate the local noise. Numerical experiments were performed showing good results with local mean-square filter terms. The projection error can be used to estimate the weight of the filter term, providing a practical procedure to get improved solutions with limited sets of projections.