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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...

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Autores principales: French, Andrew P, Wilson, Michael H, Kenobi, Kim, Dietrich, Daniela, Voß, Ute, Ubeda-Tomás, Susana, Pridmore, Tony P, Wells, Darren M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
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.
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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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