A 3-D Projection Model for X-ray Dark-field Imaging.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
25 Jun 2019
Historique:
received: 04 03 2019
accepted: 11 06 2019
entrez: 27 6 2019
pubmed: 27 6 2019
medline: 27 6 2019
Statut: epublish

Résumé

The X-ray dark-field signal can be measured with a grating-based Talbot-Lau interferometer. It measures small angle scattering of micrometer-sized oriented structures. Interestingly, the signal is a function not only of the material, but also of the relative orientation of the sample, the X-ray beam direction, and the direction of the interferometer sensitivity. This property is very interesting for potential tomographically reconstructing structures below the imaging resolution. However, tomographic reconstruction itself is a substantial challenge. A key step of the reconstruction algorithm is the inversion of a forward projection model. In this work, we propose a very general 3-D projection model. We derive the projection model under the assumption that the observed scatter distribution has a Gaussian shape. We theoretically show the consistency of our model with existing, more constrained 2-D models. Furthermore, we experimentally show the compatibility of our model with simulations and real dark-field measurements. We believe that this 3-D projection model is an important step towards more flexible trajectories and, by extension, dark-field imaging protocols that are much better applicable in practice.

Identifiants

pubmed: 31239499
doi: 10.1038/s41598-019-45708-9
pii: 10.1038/s41598-019-45708-9
pmc: PMC6592954
doi:

Types de publication

Journal Article

Langues

eng

Pagination

9216

Subventions

Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : AN 257/21-1 | MA 4898/6-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : AN 257/21-1 | MA 4898/6-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : AN 257/21-1 | MA 4898/6-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : AN 257/21-1 | MA 4898/6-1

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Auteurs

Lina Felsner (L)

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany. lina.felsner@fau.de.
International Max Planck Research School, Erlangen, Germany. lina.felsner@fau.de.

Shiyang Hu (S)

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany. shiyang.hu@fau.de.
Erlangen Graduate School in Advanced Optical Technologies, Erlangen, Germany. shiyang.hu@fau.de.

Andreas Maier (A)

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.
International Max Planck Research School, Erlangen, Germany.
Erlangen Graduate School in Advanced Optical Technologies, Erlangen, Germany.

Johannes Bopp (J)

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Veronika Ludwig (V)

International Max Planck Research School, Erlangen, Germany.
Erlangen Centre for Astroparticle Physics (ECAP), Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Gisela Anton (G)

International Max Planck Research School, Erlangen, Germany.
Erlangen Centre for Astroparticle Physics (ECAP), Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Christian Riess (C)

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Classifications MeSH