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Recovering refraction and attenuation information in an unknown sample using x-ray propagation-based phase-contrast tomography.

Authors :
Alloo, S. J.
Croton, L. C. P.
Kitchen, M. J.
Paganin, D. M.
Morgan, K. S.
Nesterets, Ya. I.
Mohammadi, S.
Lockie, D.
Menk, R. H.
Arfelli, F.
Zanconati, F.
Dullin, C.
Tromba, G.
Pavlov, K. M.
Source :
AIP Conference Proceedings. 9/2/2023, Vol. 2990 Issue 1, p1-10. 10p.
Publication Year :
2023

Abstract

Phase-contrast X-ray imaging (PCXI) techniques employ both X-ray refraction and attenuation to generate image contrast, and are therefore capable of forming high-quality images of weakly attenuating samples, for example, soft-tissues in mammography. Propagation-based phase-contrast X-ray imaging (PB-PCXI) is an especially simple PCXI technique as it requires no additional precision optics in the experimental set-up, and hence can be easily implemented in numerous disciplines. We recently published a PB-PCXI algorithm capable of extracting the real, δ, and imaginary, β, refractive index components of composite materials within an unknown sample [1]. This was previously applied to PB-PCXI data collected using a synchrotron facility where the X-ray wavefield was monochromatic, highly coherent, and paraxial. Within this work, we have validated, and further extended, this approach by applying it to PB-PCXI data collected using a conventional laboratory X-ray source that produces a polychromatic, relatively temporally incoherent and divergent wavefield. We demonstrate that our previously published phase and attenuation extraction algorithm can be applied to biological tissue sample data collected using such a laboratory X-ray source, thereby broadening the applicability of this algorithm. A link to a repository is provided, where a Python3 script implementing this approach can be downloaded. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2990
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
172420827
Full Text :
https://doi.org/10.1063/5.0168155