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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Bibliographische Detailangaben
Veröffentlicht in:Journal of synchrotron radiation. - 1994. - 21(2014), Pt 5 vom: 22. Sept., Seite 1188-93
1. Verfasser: Gürsoy, Dogˇa (VerfasserIn)
Weitere Verfasser: De Carlo, Francesco, Xiao, Xianghui, Jacobsen, Chris
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:Journal of synchrotron radiation
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S. X-ray imaging phase retrieval tomography
Beschreibung
Zusammenfassung: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
Beschreibung:Date Completed 30.03.2015
Date Revised 21.10.2021
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1600-5775
DOI:10.1107/S1600577514013939