Compressive Sensing for Dynamic XRF Scanning
(2020) In Scientific Reports 10(1).- Abstract
X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it, some of them, such as wide scale brain imaging, are prohibitively difficult due to time constraints. However, typically the overall XRF imaging performance is improving through technological progress on XRF detectors and X-ray sources. This paper suggests an additional approach where XRF scanning is performed in a sparse way by skipping specific points or by varying dynamically... (More)
X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it, some of them, such as wide scale brain imaging, are prohibitively difficult due to time constraints. However, typically the overall XRF imaging performance is improving through technological progress on XRF detectors and X-ray sources. This paper suggests an additional approach where XRF scanning is performed in a sparse way by skipping specific points or by varying dynamically acquisition time or other scan settings in a conditional manner. This paves the way for Compressive Sensing in XRF scans where data are acquired in a reduced manner allowing for challenging experiments, currently not feasible with the traditional scanning strategies. A series of different compressive sensing strategies for dynamic scans are presented here. A proof of principle experiment was performed at the TwinMic beamline of Elettra synchrotron. The outcome demonstrates the potential of Compressive Sensing for dynamic scans, suggesting its use in challenging scientific experiments while proposing a technical solution for beamline acquisition software.
(Less)
- author
- Kourousias, George ; Billè, Fulvio ; Borghes, Roberto ; Alborini, Antonio ; Sala, Simone LU ; Alberti, Roberto and Gianoncelli, Alessandra
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Reports
- volume
- 10
- issue
- 1
- article number
- 9990
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85086657872
- pmid:32561797
- ISSN
- 2045-2322
- DOI
- 10.1038/s41598-020-66435-6
- language
- English
- LU publication?
- yes
- id
- a1549d3a-bf1b-4852-a8a6-545f91d0e848
- date added to LUP
- 2021-01-15 12:02:03
- date last changed
- 2024-04-18 00:21:55
@article{a1549d3a-bf1b-4852-a8a6-545f91d0e848,
abstract = {{<p>X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it, some of them, such as wide scale brain imaging, are prohibitively difficult due to time constraints. However, typically the overall XRF imaging performance is improving through technological progress on XRF detectors and X-ray sources. This paper suggests an additional approach where XRF scanning is performed in a sparse way by skipping specific points or by varying dynamically acquisition time or other scan settings in a conditional manner. This paves the way for Compressive Sensing in XRF scans where data are acquired in a reduced manner allowing for challenging experiments, currently not feasible with the traditional scanning strategies. A series of different compressive sensing strategies for dynamic scans are presented here. A proof of principle experiment was performed at the TwinMic beamline of Elettra synchrotron. The outcome demonstrates the potential of Compressive Sensing for dynamic scans, suggesting its use in challenging scientific experiments while proposing a technical solution for beamline acquisition software.</p>}},
author = {{Kourousias, George and Billè, Fulvio and Borghes, Roberto and Alborini, Antonio and Sala, Simone and Alberti, Roberto and Gianoncelli, Alessandra}},
issn = {{2045-2322}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Scientific Reports}},
title = {{Compressive Sensing for Dynamic XRF Scanning}},
url = {{http://dx.doi.org/10.1038/s41598-020-66435-6}},
doi = {{10.1038/s41598-020-66435-6}},
volume = {{10}},
year = {{2020}},
}