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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2014
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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. |
format | Online Article Text |
id | pubmed-4181643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
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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