Post-detection analysis for grating-based ultra-small angle X-ray scattering.

Détails

ID Serval
serval:BIB_82F9746922E2
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Post-detection analysis for grating-based ultra-small angle X-ray scattering.
Périodique
Physica Medica
Auteur⸱e⸱s
Scattarella F., Tangaro S., Modregger P., Stampanoni M., De Caro L., Bellotti R.
ISSN
1724-191X (Electronic)
ISSN-L
1120-1797
Statut éditorial
Publié
Date de publication
2013
Peer-reviewed
Oui
Volume
29
Numéro
5
Pages
478-486
Langue
anglais
Notes
Publication types: Journal Article Publication Status: ppublish
Résumé
Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.
Pubmed
Web of science
Création de la notice
21/02/2014 18:23
Dernière modification de la notice
20/08/2019 14:42
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