A computer implementation of a bayesian analysis of image reconstruction

We attack the problem of recovering an image (a function of two variables) from experimentally available integrals of its grayness over thin strips. This problem is of great importance in a large number of scientific areas. An important version of the problem in medicine is that of obtaining the exact density distribution within the human body from X-ray projections.This paper proposes an algorithm for finding an optimal Bayesian estimate of an unknown image from the projection data, shows that the algorithm is geometrically convergent, reports on its computer implementation, and demonstrates its performance on a medical problem