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NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts

Most super-resolution microscopy techniques depend on steps that can contribute to the formation of image artefacts, leading to misinterpretation of biological information. We present NanoJ-SQUIRREL, an ImageJ-based analytical approach that provides quantitative assessment of super-resolution image...

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Detalles Bibliográficos
Autores principales: Culley, Siân, Albrecht, David, Jacobs, Caron, Pereira, Pedro Matos, Leterrier, Christophe, Mercer, Jason, Henriques, Ricardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884429/
https://www.ncbi.nlm.nih.gov/pubmed/29457791
http://dx.doi.org/10.1038/nmeth.4605
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author Culley, Siân
Albrecht, David
Jacobs, Caron
Pereira, Pedro Matos
Leterrier, Christophe
Mercer, Jason
Henriques, Ricardo
author_facet Culley, Siân
Albrecht, David
Jacobs, Caron
Pereira, Pedro Matos
Leterrier, Christophe
Mercer, Jason
Henriques, Ricardo
author_sort Culley, Siân
collection PubMed
description Most super-resolution microscopy techniques depend on steps that can contribute to the formation of image artefacts, leading to misinterpretation of biological information. We present NanoJ-SQUIRREL, an ImageJ-based analytical approach that provides quantitative assessment of super-resolution image quality, capable of guiding researchers in optimising imaging parameters. By comparing diffraction-limited images and super-resolution equivalents of the same acquisition volume, this approach generates a quality score and quantitative map of super-resolution defects.
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spelling pubmed-58844292018-08-19 NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts Culley, Siân Albrecht, David Jacobs, Caron Pereira, Pedro Matos Leterrier, Christophe Mercer, Jason Henriques, Ricardo Nat Methods Article Most super-resolution microscopy techniques depend on steps that can contribute to the formation of image artefacts, leading to misinterpretation of biological information. We present NanoJ-SQUIRREL, an ImageJ-based analytical approach that provides quantitative assessment of super-resolution image quality, capable of guiding researchers in optimising imaging parameters. By comparing diffraction-limited images and super-resolution equivalents of the same acquisition volume, this approach generates a quality score and quantitative map of super-resolution defects. 2018-02-19 2018-04 /pmc/articles/PMC5884429/ /pubmed/29457791 http://dx.doi.org/10.1038/nmeth.4605 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Culley, Siân
Albrecht, David
Jacobs, Caron
Pereira, Pedro Matos
Leterrier, Christophe
Mercer, Jason
Henriques, Ricardo
NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title_full NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title_fullStr NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title_full_unstemmed NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title_short NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts
title_sort nanoj-squirrel: quantitative mapping and minimisation of super-resolution optical imaging artefacts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884429/
https://www.ncbi.nlm.nih.gov/pubmed/29457791
http://dx.doi.org/10.1038/nmeth.4605
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