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Bioimage Analysis and Cell Motility

Abstract : 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.
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https://hal-pasteur.archives-ouvertes.fr/pasteur-03152918
Contributor : Aleix Boquet-Pujadas <>
Submitted on : Thursday, February 25, 2021 - 9:51:13 PM
Last modification on : Wednesday, March 3, 2021 - 6:26:13 PM
Long-term archiving on: : Wednesday, May 26, 2021 - 7:27:48 PM

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Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

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Aleix Boquet-Pujadas, Jean-Christophe Olivo-Marin, Nancy Guillén. Bioimage Analysis and Cell Motility. Patterns, Cell Press Elsevier, 2021, 2 (1), pp.100170. ⟨10.1016/j.patter.2020.100170⟩. ⟨pasteur-03152918⟩

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