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EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics
Epithelia grow and undergo extensive rearrangements to achieve their final size and shape. Imaging the dynamics of tissue growth and morphogenesis is now possible with advances in time-lapse microscopy, but a true understanding of their complexities is limited by automated image analysis tools to ex...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cell Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4712040/ https://www.ncbi.nlm.nih.gov/pubmed/26766446 http://dx.doi.org/10.1016/j.devcel.2015.12.012 |
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author | Heller, Davide Hoppe, Andreas Restrepo, Simon Gatti, Lorenzo Tournier, Alexander L. Tapon, Nicolas Basler, Konrad Mao, Yanlan |
author_facet | Heller, Davide Hoppe, Andreas Restrepo, Simon Gatti, Lorenzo Tournier, Alexander L. Tapon, Nicolas Basler, Konrad Mao, Yanlan |
author_sort | Heller, Davide |
collection | PubMed |
description | Epithelia grow and undergo extensive rearrangements to achieve their final size and shape. Imaging the dynamics of tissue growth and morphogenesis is now possible with advances in time-lapse microscopy, but a true understanding of their complexities is limited by automated image analysis tools to extract quantitative data. To overcome such limitations, we have designed a new open-source image analysis toolkit called EpiTools. It provides user-friendly graphical user interfaces for accurately segmenting and tracking the contours of cell membrane signals obtained from 4D confocal imaging. It is designed for a broad audience, especially biologists with no computer-science background. Quantitative data extraction is integrated into a larger bioimaging platform, Icy, to increase the visibility and usability of our tools. We demonstrate the usefulness of EpiTools by analyzing Drosophila wing imaginal disc growth, revealing previously overlooked properties of this dynamic tissue, such as the patterns of cellular rearrangements. |
format | Online Article Text |
id | pubmed-4712040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Cell Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47120402016-02-11 EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics Heller, Davide Hoppe, Andreas Restrepo, Simon Gatti, Lorenzo Tournier, Alexander L. Tapon, Nicolas Basler, Konrad Mao, Yanlan Dev Cell Technology Epithelia grow and undergo extensive rearrangements to achieve their final size and shape. Imaging the dynamics of tissue growth and morphogenesis is now possible with advances in time-lapse microscopy, but a true understanding of their complexities is limited by automated image analysis tools to extract quantitative data. To overcome such limitations, we have designed a new open-source image analysis toolkit called EpiTools. It provides user-friendly graphical user interfaces for accurately segmenting and tracking the contours of cell membrane signals obtained from 4D confocal imaging. It is designed for a broad audience, especially biologists with no computer-science background. Quantitative data extraction is integrated into a larger bioimaging platform, Icy, to increase the visibility and usability of our tools. We demonstrate the usefulness of EpiTools by analyzing Drosophila wing imaginal disc growth, revealing previously overlooked properties of this dynamic tissue, such as the patterns of cellular rearrangements. Cell Press 2016-01-11 /pmc/articles/PMC4712040/ /pubmed/26766446 http://dx.doi.org/10.1016/j.devcel.2015.12.012 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technology Heller, Davide Hoppe, Andreas Restrepo, Simon Gatti, Lorenzo Tournier, Alexander L. Tapon, Nicolas Basler, Konrad Mao, Yanlan EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title | EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title_full | EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title_fullStr | EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title_full_unstemmed | EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title_short | EpiTools: An Open-Source Image Analysis Toolkit for Quantifying Epithelial Growth Dynamics |
title_sort | epitools: an open-source image analysis toolkit for quantifying epithelial growth dynamics |
topic | Technology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4712040/ https://www.ncbi.nlm.nih.gov/pubmed/26766446 http://dx.doi.org/10.1016/j.devcel.2015.12.012 |
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