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TomoPy: a framework for the analysis of synchrotron tomographic data

Analysis of tomographic datasets at synchrotron light sources (including X-ray transmission tomography, X-ray fluorescence microscopy and X-ray diffraction tomography) is becoming progressively more challenging due to the increasing data acquisition rates that new technologies in X-ray sources and d...

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Autores principales: Gürsoy, Doǧa, De Carlo, Francesco, Xiao, Xianghui, Jacobsen, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181643/
https://www.ncbi.nlm.nih.gov/pubmed/25178011
http://dx.doi.org/10.1107/S1600577514013939
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author Gürsoy, Doǧa
De Carlo, Francesco
Xiao, Xianghui
Jacobsen, Chris
author_facet Gürsoy, Doǧa
De Carlo, Francesco
Xiao, Xianghui
Jacobsen, Chris
author_sort Gürsoy, Doǧa
collection PubMed
description Analysis of tomographic datasets at synchrotron light sources (including X-ray transmission tomography, X-ray fluorescence microscopy and X-ray diffraction tomography) is becoming progressively more challenging due to the increasing data acquisition rates that new technologies in X-ray sources and detectors enable. The next generation of synchrotron facilities that are currently under design or construction throughout the world will provide diffraction-limited X-ray sources and are expected to boost the current data rates by several orders of magnitude, stressing the need for the development and integration of efficient analysis tools. Here an attempt to provide a collaborative framework for the analysis of synchrotron tomographic data that has the potential to unify the effort of different facilities and beamlines performing similar tasks is described in detail. The proposed Python-based framework is open-source, platform- and data-format-independent, has multiprocessing capability and supports procedural programming that many researchers prefer. This collaborative platform could affect all major synchrotron facilities where new effort is now dedicated to developing new tools that can be deployed at the facility for real-time processing, as well as distributed to users for off-site data processing.
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spelling pubmed-41816432014-10-07 TomoPy: a framework for the analysis of synchrotron tomographic data Gürsoy, Doǧa De Carlo, Francesco Xiao, Xianghui Jacobsen, Chris J Synchrotron Radiat Research Papers Analysis of tomographic datasets at synchrotron light sources (including X-ray transmission tomography, X-ray fluorescence microscopy and X-ray diffraction tomography) is becoming progressively more challenging due to the increasing data acquisition rates that new technologies in X-ray sources and detectors enable. The next generation of synchrotron facilities that are currently under design or construction throughout the world will provide diffraction-limited X-ray sources and are expected to boost the current data rates by several orders of magnitude, stressing the need for the development and integration of efficient analysis tools. Here an attempt to provide a collaborative framework for the analysis of synchrotron tomographic data that has the potential to unify the effort of different facilities and beamlines performing similar tasks is described in detail. The proposed Python-based framework is open-source, platform- and data-format-independent, has multiprocessing capability and supports procedural programming that many researchers prefer. This collaborative platform could affect all major synchrotron facilities where new effort is now dedicated to developing new tools that can be deployed at the facility for real-time processing, as well as distributed to users for off-site data processing. International Union of Crystallography 2014-08-01 /pmc/articles/PMC4181643/ /pubmed/25178011 http://dx.doi.org/10.1107/S1600577514013939 Text en © Doǧa Gürsoy et al. 2014 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Gürsoy, Doǧa
De Carlo, Francesco
Xiao, Xianghui
Jacobsen, Chris
TomoPy: a framework for the analysis of synchrotron tomographic data
title TomoPy: a framework for the analysis of synchrotron tomographic data
title_full TomoPy: a framework for the analysis of synchrotron tomographic data
title_fullStr TomoPy: a framework for the analysis of synchrotron tomographic data
title_full_unstemmed TomoPy: a framework for the analysis of synchrotron tomographic data
title_short TomoPy: a framework for the analysis of synchrotron tomographic data
title_sort tomopy: a framework for the analysis of synchrotron tomographic data
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181643/
https://www.ncbi.nlm.nih.gov/pubmed/25178011
http://dx.doi.org/10.1107/S1600577514013939
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