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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...

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Detalles Bibliográficos
Autores principales: Heller, Davide, Hoppe, Andreas, Restrepo, Simon, Gatti, Lorenzo, Tournier, Alexander L., Tapon, Nicolas, Basler, Konrad, Mao, Yanlan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cell Press 2016
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.
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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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