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CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy
BACKGROUND: Super resolution (SR) microscopy enabled cell biologists to visualize subcellular details up to 20 nm in resolution. This breakthrough in spatial resolution made image analysis a challenging procedure. Direct and automated segmentation of SR images remains largely unsolved, especially wh...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4527132/ https://www.ncbi.nlm.nih.gov/pubmed/26251640 http://dx.doi.org/10.1186/s12575-015-0023-9 |
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author | Soliman, Kareem |
author_facet | Soliman, Kareem |
author_sort | Soliman, Kareem |
collection | PubMed |
description | BACKGROUND: Super resolution (SR) microscopy enabled cell biologists to visualize subcellular details up to 20 nm in resolution. This breakthrough in spatial resolution made image analysis a challenging procedure. Direct and automated segmentation of SR images remains largely unsolved, especially when it comes to providing meaningful biological interpretations. RESULTS: Here, we introduce a novel automated imaging analysis routine, based on Gaussian, followed by a segmentation procedure using CellProfiler software (www.cellprofiler.org). We tested this method and succeeded to segment individual nuclear pore complexes stained with gp210 and pan-FG proteins and captured by two-color STED microscopy. Test results confirmed accuracy and robustness of the method even in noisy STED images of gp210. CONCLUSIONS: Our pipeline and novel segmentation procedure may benefit end-users of SR microscopy to analyze their images and extract biologically significant quantitative data about them in user-friendly and fully-automated settings. |
format | Online Article Text |
id | pubmed-4527132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45271322015-08-07 CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy Soliman, Kareem Biol Proced Online Methodology BACKGROUND: Super resolution (SR) microscopy enabled cell biologists to visualize subcellular details up to 20 nm in resolution. This breakthrough in spatial resolution made image analysis a challenging procedure. Direct and automated segmentation of SR images remains largely unsolved, especially when it comes to providing meaningful biological interpretations. RESULTS: Here, we introduce a novel automated imaging analysis routine, based on Gaussian, followed by a segmentation procedure using CellProfiler software (www.cellprofiler.org). We tested this method and succeeded to segment individual nuclear pore complexes stained with gp210 and pan-FG proteins and captured by two-color STED microscopy. Test results confirmed accuracy and robustness of the method even in noisy STED images of gp210. CONCLUSIONS: Our pipeline and novel segmentation procedure may benefit end-users of SR microscopy to analyze their images and extract biologically significant quantitative data about them in user-friendly and fully-automated settings. BioMed Central 2015-08-07 /pmc/articles/PMC4527132/ /pubmed/26251640 http://dx.doi.org/10.1186/s12575-015-0023-9 Text en © Soliman. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Soliman, Kareem CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title | CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title_full | CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title_fullStr | CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title_full_unstemmed | CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title_short | CellProfiler: Novel Automated Image Segmentation Procedure for Super-Resolution Microscopy |
title_sort | cellprofiler: novel automated image segmentation procedure for super-resolution microscopy |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4527132/ https://www.ncbi.nlm.nih.gov/pubmed/26251640 http://dx.doi.org/10.1186/s12575-015-0023-9 |
work_keys_str_mv | AT solimankareem cellprofilernovelautomatedimagesegmentationprocedureforsuperresolutionmicroscopy |