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Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework
In a recent article, we described the edxia framework, a user‐friendly framework to analyse the microstructure of cementitious materials using SEM‐EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific questions. However, it is limited for batch anal...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311694/ https://www.ncbi.nlm.nih.gov/pubmed/35289927 http://dx.doi.org/10.1111/jmi.13099 |
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author | Georget, Fabien Wilson, William Scrivener, Karen L. |
author_facet | Georget, Fabien Wilson, William Scrivener, Karen L. |
author_sort | Georget, Fabien |
collection | PubMed |
description | In a recent article, we described the edxia framework, a user‐friendly framework to analyse the microstructure of cementitious materials using SEM‐EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific questions. However, it is limited for batch analysis and (semi‐)automated treatments. In this article, we show how the framework can be used to customise the analysis to the problem at hand. We first present some possible extensions, and then we provide a simple example of automatic clustering, using the flexible Python scientific libraries which will allow to define more custom workflows in the future. |
format | Online Article Text |
id | pubmed-9311694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93116942022-07-30 Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework Georget, Fabien Wilson, William Scrivener, Karen L. J Microsc Themed Issue Articles In a recent article, we described the edxia framework, a user‐friendly framework to analyse the microstructure of cementitious materials using SEM‐EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific questions. However, it is limited for batch analysis and (semi‐)automated treatments. In this article, we show how the framework can be used to customise the analysis to the problem at hand. We first present some possible extensions, and then we provide a simple example of automatic clustering, using the flexible Python scientific libraries which will allow to define more custom workflows in the future. John Wiley and Sons Inc. 2022-03-24 2022-05 /pmc/articles/PMC9311694/ /pubmed/35289927 http://dx.doi.org/10.1111/jmi.13099 Text en © 2022 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Themed Issue Articles Georget, Fabien Wilson, William Scrivener, Karen L. Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title | Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title_full | Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title_fullStr | Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title_full_unstemmed | Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title_short | Simple automation of SEM‐EDS spectral maps analysis with Python and the edxia framework |
title_sort | simple automation of sem‐eds spectral maps analysis with python and the edxia framework |
topic | Themed Issue Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311694/ https://www.ncbi.nlm.nih.gov/pubmed/35289927 http://dx.doi.org/10.1111/jmi.13099 |
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