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Title: Joint reconstruction of x-ray fluorescence and transmission tomography

Abstract

X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combined signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Furthermore, compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption.

Authors:
 [1]; ; ; ; ;
  1. Wendy
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); National Institutes of Health (NIH)
OSTI Identifier:
1364659
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Optics Express
Additional Journal Information:
Journal Volume: 25; Journal Issue: 12; Journal ID: ISSN 1094-4087
Publisher:
Optical Society of America (OSA)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; Image reconstruction techniques; Tomographic image processing; X-ray imaging; X-ray microscopy

Citation Formats

Di, Zichao, Chen, Si, Hong, Young Pyo, Jacobsen, Chris, Leyffer, Sven, and Wild, Stefan M. Joint reconstruction of x-ray fluorescence and transmission tomography. United States: N. p., 2017. Web. doi:10.1364/OE.25.013107.
Di, Zichao, Chen, Si, Hong, Young Pyo, Jacobsen, Chris, Leyffer, Sven, & Wild, Stefan M. Joint reconstruction of x-ray fluorescence and transmission tomography. United States. doi:10.1364/OE.25.013107.
Di, Zichao, Chen, Si, Hong, Young Pyo, Jacobsen, Chris, Leyffer, Sven, and Wild, Stefan M. Tue . "Joint reconstruction of x-ray fluorescence and transmission tomography". United States. doi:10.1364/OE.25.013107. https://www.osti.gov/servlets/purl/1364659.
@article{osti_1364659,
title = {Joint reconstruction of x-ray fluorescence and transmission tomography},
author = {Di, Zichao and Chen, Si and Hong, Young Pyo and Jacobsen, Chris and Leyffer, Sven and Wild, Stefan M.},
abstractNote = {X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combined signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Furthermore, compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption.},
doi = {10.1364/OE.25.013107},
journal = {Optics Express},
number = 12,
volume = 25,
place = {United States},
year = {2017},
month = {5}
}

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