Comparison of three reconstruction methods based on deconvolution, iterative algorithm and neural network for X-ray fluorescence imaging with coded aperture optics-Reference-Cited by-同舟云学术

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Comparison of three reconstruction methods based on deconvolution, iterative algorithm and neural network for X-ray fluorescence imaging with coded aperture optics

Published:2020 Issue:7 Volume:35 Page:1423-1434
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Kulow Anico¹²³⁴⁵^ORCID,Guilherme Buzanich Ana¹²³^ORCID,Reinholz Uwe¹²³,Emmerling Franziska¹²³^ORCID,Hampel Sven⁶⁷⁸³^ORCID,Fittschen Ursula Elisabeth Adriane⁶⁷⁸³,Streli Christina⁴⁵⁹¹⁰,Radtke Martin¹²³

Affiliation:

1. Federal Institute for Materials Research and Testing (BAM)

2. 12489 Berlin

3. Germany

4. Vienna University of Technology

5. Atominstitut

6. Clausthal University of Technology

7. Institute of Inorganic and Analytical Chemistry

8. 38678 Clausthal-Zellerfeld

9. A-1020 Vienna

10. Austria

Abstract

Superimposed images acquired by XRF with coded aperture optics can be recovered successfully iteratively.

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/JA/D0JA00146E

Reference55 articles.

1. Recent advances in analysis of trace elements in environmental samples by X-ray based techniques (IUPAC Technical Report)

2. Hard X-Ray/Soft Gamma-Ray Experiments and Missions: Overview and Prospects

3. Synchrotron radiation micro X-ray fluorescence spectroscopy of thin structures in bone samples: comparison of confocal and color X-ray camera setups

4. Hard and soft X-ray microscopy and tomography in catalysis: bridging the different time and length scales

5. Formation of Optical Images by X-Rays

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