An automated image analysis system to measure and count organisms in laboratory microcosms.

1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the a...

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Autores principales:	François Mallard, Vincent Le Bourlot, Thomas Tully
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3052d8482a0744379d17f53f598162c1
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spelling	oai:doaj.org-article:3052d8482a0744379d17f53f598162c12021-11-18T07:43:57ZAn automated image analysis system to measure and count organisms in laboratory microcosms.1932-620310.1371/journal.pone.0064387https://doaj.org/article/3052d8482a0744379d17f53f598162c12013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23734199/pdf/?tool=EBIhttps://doaj.org/toc/1932-62031. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia) to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.François MallardVincent Le BourlotThomas TullyPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 5, p e64387 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q François Mallard Vincent Le Bourlot Thomas Tully An automated image analysis system to measure and count organisms in laboratory microcosms.
description	1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia) to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.
format	article
author	François Mallard Vincent Le Bourlot Thomas Tully
author_facet	François Mallard Vincent Le Bourlot Thomas Tully
author_sort	François Mallard
title	An automated image analysis system to measure and count organisms in laboratory microcosms.
title_short	An automated image analysis system to measure and count organisms in laboratory microcosms.
title_full	An automated image analysis system to measure and count organisms in laboratory microcosms.
title_fullStr	An automated image analysis system to measure and count organisms in laboratory microcosms.
title_full_unstemmed	An automated image analysis system to measure and count organisms in laboratory microcosms.
title_sort	automated image analysis system to measure and count organisms in laboratory microcosms.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/3052d8482a0744379d17f53f598162c1
work_keys_str_mv	AT francoismallard anautomatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms AT vincentlebourlot anautomatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms AT thomastully anautomatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms AT francoismallard automatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms AT vincentlebourlot automatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms AT thomastully automatedimageanalysissystemtomeasureandcountorganismsinlaboratorymicrocosms
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An automated image analysis system to measure and count organisms in laboratory microcosms.

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