Autonomous reconstruction and segmentation of tomographic data

Abstract

A Bayesian approach to reconstruction and segmentation of tomographic data is outlined and further detailed for the case of absorption tomography. The algorithm allows the quantification of reconstruction errors and segmentation confidence. Calculation results for various experimental settings (number of projections, incident dose, different materials) are shown and discussed.We are pleased to dedicate this paper to the memory of David J. H. Cockayne. HighlightsSimultaneous tomographic reconstruction and segmentation algorithm Fully self-contained Probabilistic error metrics for both reconstructed densities and segmentation on a voxel basis Highlights (for review)Autonomous reconstruction and segmentation of tomographic data We are pleased to dedicate this paper to the memory of David J. H. Cockayne.