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Guided-deconvolution for correlative light and electron microscopy
Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. The EM images only contain contrast information. Therefore, some of the detailed structures cannot...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997956/ https://www.ncbi.nlm.nih.gov/pubmed/36893111 http://dx.doi.org/10.1371/journal.pone.0282803 |
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author | Ma, Fengjiao Kaufmann, Rainer Sedzicki, Jaroslaw Cseresnyés, Zoltán Dehio, Christoph Hoeppener, Stephanie Figge, Marc Thilo Heintzmann, Rainer |
author_facet | Ma, Fengjiao Kaufmann, Rainer Sedzicki, Jaroslaw Cseresnyés, Zoltán Dehio, Christoph Hoeppener, Stephanie Figge, Marc Thilo Heintzmann, Rainer |
author_sort | Ma, Fengjiao |
collection | PubMed |
description | Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. The EM images only contain contrast information. Therefore, some of the detailed structures cannot be specified from these images alone, especially when different cell organelle are contacted. However, the classical approach of overlaying LM onto EM images to assign functional to structural information is hampered by the large discrepancy in structural detail visible in the LM images. This paper aims at investigating an optimized approach which we call EM-guided deconvolution. This applies to living cells structures before fixation as well as previously fixed sample. It attempts to automatically assign fluorescence-labeled structures to structural details visible in the EM image to bridge the gaps in both resolution and specificity between the two imaging modes. We tested our approach on simulations, correlative data of multi-color beads and previously published data of biological samples. |
format | Online Article Text |
id | pubmed-9997956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99979562023-03-10 Guided-deconvolution for correlative light and electron microscopy Ma, Fengjiao Kaufmann, Rainer Sedzicki, Jaroslaw Cseresnyés, Zoltán Dehio, Christoph Hoeppener, Stephanie Figge, Marc Thilo Heintzmann, Rainer PLoS One Research Article Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. The EM images only contain contrast information. Therefore, some of the detailed structures cannot be specified from these images alone, especially when different cell organelle are contacted. However, the classical approach of overlaying LM onto EM images to assign functional to structural information is hampered by the large discrepancy in structural detail visible in the LM images. This paper aims at investigating an optimized approach which we call EM-guided deconvolution. This applies to living cells structures before fixation as well as previously fixed sample. It attempts to automatically assign fluorescence-labeled structures to structural details visible in the EM image to bridge the gaps in both resolution and specificity between the two imaging modes. We tested our approach on simulations, correlative data of multi-color beads and previously published data of biological samples. Public Library of Science 2023-03-09 /pmc/articles/PMC9997956/ /pubmed/36893111 http://dx.doi.org/10.1371/journal.pone.0282803 Text en © 2023 Ma et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ma, Fengjiao Kaufmann, Rainer Sedzicki, Jaroslaw Cseresnyés, Zoltán Dehio, Christoph Hoeppener, Stephanie Figge, Marc Thilo Heintzmann, Rainer Guided-deconvolution for correlative light and electron microscopy |
title | Guided-deconvolution for correlative light and electron microscopy |
title_full | Guided-deconvolution for correlative light and electron microscopy |
title_fullStr | Guided-deconvolution for correlative light and electron microscopy |
title_full_unstemmed | Guided-deconvolution for correlative light and electron microscopy |
title_short | Guided-deconvolution for correlative light and electron microscopy |
title_sort | guided-deconvolution for correlative light and electron microscopy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997956/ https://www.ncbi.nlm.nih.gov/pubmed/36893111 http://dx.doi.org/10.1371/journal.pone.0282803 |
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