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Bioimage Analysis and Cell Motility
Bioimage analysis (BIA) has historically helped study how and why cells move; biological experiments evolved in intimate feedback with the most classical image processing techniques because they contribute objectivity and reproducibility to an eminently qualitative science. Cell segmentation, tracki...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815951/ https://www.ncbi.nlm.nih.gov/pubmed/33511365 http://dx.doi.org/10.1016/j.patter.2020.100170 |
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author | Boquet-Pujadas, Aleix Olivo-Marin, Jean-Christophe Guillén, Nancy |
author_facet | Boquet-Pujadas, Aleix Olivo-Marin, Jean-Christophe Guillén, Nancy |
author_sort | Boquet-Pujadas, Aleix |
collection | PubMed |
description | Bioimage analysis (BIA) has historically helped study how and why cells move; biological experiments evolved in intimate feedback with the most classical image processing techniques because they contribute objectivity and reproducibility to an eminently qualitative science. Cell segmentation, tracking, and morphology descriptors are all discussed here. Using ameboid motility as a case study, these methods help us illustrate how proper quantification can augment biological data, for example, by choosing mathematical representations that amplify initially subtle differences, by statistically uncovering general laws or by integrating physical insight. More recently, the non-invasive nature of quantitative imaging is fertilizing two blooming fields: mechanobiology, where many biophysical measurements remain inaccessible, and microenvironments, where the quest for physiological relevance has exploded data size. From relief to remedy, this trend indicates that BIA is to become a main vector of biological discovery as human visual analysis struggles against ever more complex data. |
format | Online Article Text |
id | pubmed-7815951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-78159512021-01-27 Bioimage Analysis and Cell Motility Boquet-Pujadas, Aleix Olivo-Marin, Jean-Christophe Guillén, Nancy Patterns (N Y) Review Bioimage analysis (BIA) has historically helped study how and why cells move; biological experiments evolved in intimate feedback with the most classical image processing techniques because they contribute objectivity and reproducibility to an eminently qualitative science. Cell segmentation, tracking, and morphology descriptors are all discussed here. Using ameboid motility as a case study, these methods help us illustrate how proper quantification can augment biological data, for example, by choosing mathematical representations that amplify initially subtle differences, by statistically uncovering general laws or by integrating physical insight. More recently, the non-invasive nature of quantitative imaging is fertilizing two blooming fields: mechanobiology, where many biophysical measurements remain inaccessible, and microenvironments, where the quest for physiological relevance has exploded data size. From relief to remedy, this trend indicates that BIA is to become a main vector of biological discovery as human visual analysis struggles against ever more complex data. Elsevier 2021-01-08 /pmc/articles/PMC7815951/ /pubmed/33511365 http://dx.doi.org/10.1016/j.patter.2020.100170 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Boquet-Pujadas, Aleix Olivo-Marin, Jean-Christophe Guillén, Nancy Bioimage Analysis and Cell Motility |
title | Bioimage Analysis and Cell Motility |
title_full | Bioimage Analysis and Cell Motility |
title_fullStr | Bioimage Analysis and Cell Motility |
title_full_unstemmed | Bioimage Analysis and Cell Motility |
title_short | Bioimage Analysis and Cell Motility |
title_sort | bioimage analysis and cell motility |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815951/ https://www.ncbi.nlm.nih.gov/pubmed/33511365 http://dx.doi.org/10.1016/j.patter.2020.100170 |
work_keys_str_mv | AT boquetpujadasaleix bioimageanalysisandcellmotility AT olivomarinjeanchristophe bioimageanalysisandcellmotility AT guillennancy bioimageanalysisandcellmotility |