title: 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.
authors.affiliation: Helmholtz Zentrum Berlin für Materialien und Energie, Hahn-Meitner-Platz 1, D-14109 Berlin, Germany. Electronic address: wollgarten@helmholtz-berlin.de.
authors.forename: Markus
authors.initials: M
authors.lastname: Wollgarten
authors.affiliation: Institute for Mathematical Stochastics,Georg-August-University of Göttingen, Goldschmidtstrasse 7, D-37077 Göttingen, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Habeck
keywords: Segmentation; Tomographic reconstruction; Tomography