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Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape
BACKGROUND: The ability to quantify the geometry of plant organs at the cellular scale can provide novel insights into their structural organization. Hitherto manual methods of measurement provide only very low throughput and subjective solutions, and often quantitative measurements are neglected in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359173/ https://www.ncbi.nlm.nih.gov/pubmed/22385537 http://dx.doi.org/10.1186/1746-4811-8-7 |
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author | French, Andrew P Wilson, Michael H Kenobi, Kim Dietrich, Daniela Voß, Ute Ubeda-Tomás, Susana Pridmore, Tony P Wells, Darren M |
author_facet | French, Andrew P Wilson, Michael H Kenobi, Kim Dietrich, Daniela Voß, Ute Ubeda-Tomás, Susana Pridmore, Tony P Wells, Darren M |
author_sort | French, Andrew P |
collection | PubMed |
description | BACKGROUND: The ability to quantify the geometry of plant organs at the cellular scale can provide novel insights into their structural organization. Hitherto manual methods of measurement provide only very low throughput and subjective solutions, and often quantitative measurements are neglected in favour of a simple cell count. RESULTS: We present a tool to count and measure individual neighbouring cells along a defined file in confocal laser scanning microscope images. The tool allows the user to extract this generic information in a flexible and intuitive manner, and builds on the raw data to detect a significant change in cell length along the file. This facility can be used, for example, to provide an estimate of the position of transition into the elongation zone of an Arabidopsis root, traditionally a location sensitive to the subjectivity of the experimenter. CONCLUSIONS: Cell-o-tape is shown to locate cell walls with a high degree of accuracy and estimate the location of the transition feature point in good agreement with human experts. The tool is an open source ImageJ/Fiji macro and is available online. |
format | Online Article Text |
id | pubmed-3359173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33591732012-06-01 Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape French, Andrew P Wilson, Michael H Kenobi, Kim Dietrich, Daniela Voß, Ute Ubeda-Tomás, Susana Pridmore, Tony P Wells, Darren M Plant Methods Software BACKGROUND: The ability to quantify the geometry of plant organs at the cellular scale can provide novel insights into their structural organization. Hitherto manual methods of measurement provide only very low throughput and subjective solutions, and often quantitative measurements are neglected in favour of a simple cell count. RESULTS: We present a tool to count and measure individual neighbouring cells along a defined file in confocal laser scanning microscope images. The tool allows the user to extract this generic information in a flexible and intuitive manner, and builds on the raw data to detect a significant change in cell length along the file. This facility can be used, for example, to provide an estimate of the position of transition into the elongation zone of an Arabidopsis root, traditionally a location sensitive to the subjectivity of the experimenter. CONCLUSIONS: Cell-o-tape is shown to locate cell walls with a high degree of accuracy and estimate the location of the transition feature point in good agreement with human experts. The tool is an open source ImageJ/Fiji macro and is available online. BioMed Central 2012-03-02 /pmc/articles/PMC3359173/ /pubmed/22385537 http://dx.doi.org/10.1186/1746-4811-8-7 Text en Copyright ©2012 French et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software French, Andrew P Wilson, Michael H Kenobi, Kim Dietrich, Daniela Voß, Ute Ubeda-Tomás, Susana Pridmore, Tony P Wells, Darren M Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title | Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title_full | Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title_fullStr | Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title_full_unstemmed | Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title_short | Identifying biological landmarks using a novel cell measuring image analysis tool: Cell-o-Tape |
title_sort | identifying biological landmarks using a novel cell measuring image analysis tool: cell-o-tape |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359173/ https://www.ncbi.nlm.nih.gov/pubmed/22385537 http://dx.doi.org/10.1186/1746-4811-8-7 |
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