Autonomous reconstruction and segmentation of tomographic data

Markus Wollgarten; Michael Habeck

doi:10.1016/j.micron.2014.02.005

Autonomous reconstruction and segmentation of tomographic data

Micron. 2014 Aug:63:20-7. doi: 10.1016/j.micron.2014.02.005. Epub 2014 Feb 19.

Authors

Markus Wollgarten¹, Michael Habeck²

Affiliations

¹ Helmholtz Zentrum Berlin für Materialien und Energie, Hahn-Meitner-Platz 1, D-14109 Berlin, Germany. Electronic address: wollgarten@helmholtz-berlin.de.
² Institute for Mathematical Stochastics,Georg-August-University of Göttingen, Goldschmidtstrasse 7, D-37077 Göttingen, Germany.

PMID: 24613674
DOI: 10.1016/j.micron.2014.02.005

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.

Keywords: Segmentation; Tomographic reconstruction; Tomography.