Implementation and assessment of the black body bias correction in quantitative neutron imaging

• Published in: PloS one Vol. 14; no. 1; p. e0210300
• Main Authors: Carminati, Chiara, Boillat, Pierre, Schmid, Florian, Vontobel, Peter, Hovind, Jan, Morgano, Manuel, Raventos, Marc, Siegwart, Muriel, Mannes, David, Gruenzweig, Christian, Trtik, Pavel, Lehmann, Eberhard, Strobl, Markus, Kaestner, Anders
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.01.2019; Public Library of Science (PLoS)
• Subjects: Algorithms; Bias; Biology and Life Sciences; Blackbody; Computational biology; Computed tomography; Computer and Information Sciences; Computer Simulation; Copper - chemistry; Crystallography; Cultural heritage; Dark current; Databases, Factual; Image enhancement; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - statistics & numerical data; Image reconstruction; Innovations; Laboratories; Lead - chemistry; Management; Medical care quality; Medical imaging; Medicine and Health Sciences; Methods; Neuroimaging; Neutron Diffraction - methods; Neutron Diffraction - statistics & numerical data; Neutrons; Phantoms, Imaging; Physical Sciences; Physics; Quantitative analysis; Reproducibility; Research and Analysis Methods; Scattering; Sensors; Software; Tomography; Tomography, X-Ray Computed - statistics & numerical data; Water - chemistry; Switzerland
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0210300

We describe in this paper the experimental procedure, the data treatment and the quantification of the black body correction: an experimental approach to compensate for scattering and systematic biases in quantitative neutron imaging based on experimental data. The correction algorithm is based on two steps; estimation of the scattering component and correction using an enhanced normalization formula. The method incorporates correction terms into the image normalization procedure, which usually only includes open beam and dark current images (open beam correction). Our aim is to show its efficiency and reproducibility: we detail the data treatment procedures and quantitatively investigate the effect of the correction. Its implementation is included within the open source CT reconstruction software MuhRec. The performance of the proposed algorithm is demonstrated using simulated and experimental CT datasets acquired at the ICON and NEUTRA beamlines at the Paul Scherrer Institut.