Improving dynamic tomography, through maximum a posteriori estimation

Abstract

Direct study of pore-scale fluid displacements, and other dynamic (i.e. time-dependent) processes is not feasible with conventional X-ray micro computed tomography (μCT). We have previously verified that a priori knowledge of the underlying physics can be used to conduct high-resolution, time-resolved imaging of continuous, complex processes, at existing X-ray μCT facilities. In this paper we present a maximum a posteriori (MAP) model of the dynamic tomography problem, which allows us to easily adapt and generalise our previous dynamic μCT approach to systems with more complex underlying physics. Show more