Non Invasive Live Cell Cycle Monitoring using Quantitative Phase Imaging and Proximal Machine Learning Methods

Pognonec, Philippe; Barlaud, Michel; Benoit, Wattellier; Pourcher, Thierry; Zhou, Yanmin; Aknoun, Shérazade; Yonnet, Manuel; Antonini, Marc

doi:10.1109/cbms.2019.00099

2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) 2019

DOI: 10.1109/cbms.2019.00099

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Non Invasive Live Cell Cycle Monitoring using Quantitative Phase Imaging and Proximal Machine Learning Methods

Philippe Pognonec¹,

Michel Barlaud

Wattellier Benoit³

et al.

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2021

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Cited by 2 publications

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Quantitative phase microscopy for non-invasive live cell population monitoring

Aknoun¹,

Yonnet²,

Djabari

et al. 2021

Sci Rep

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We present here a label-free development based on preexisting Quantitative Phase Imaging (QPI) that allows non-invasive live monitoring of both individual cells and cell populations. Growth, death, effect of toxic compounds are quantified under visible light with a standard inverted microscope. We show that considering the global biomass of a cell population is a more robust and accurate method to assess its growth parameters in comparison to compiling individually segmented cells. This is especially true for confluent conditions. This method expands the use of light microscopy in answering biological questions concerning live cell populations even at high density. In contrast to labeling or lysis of cells this method does not alter the cells and could be useful in high-throughput screening and toxicity studies.

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Quantitative phase microscopy for non-invasive live cell population monitoring

Aknoun¹,

Yonnet²,

Djabari

et al. 2021

Sci Rep

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Mitotic Index Determination on Live Cells From Label-Free Acquired Quantitative Phase Images Using a Supervised Autoencoder

Pognonec¹,

Gustovic²,

Djabari³

et al. 2021

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Non Invasive Live Cell Cycle Monitoring using Quantitative Phase Imaging and Proximal Machine Learning Methods

Cited by 2 publications

References 21 publications

Quantitative phase microscopy for non-invasive live cell population monitoring

Quantitative phase microscopy for non-invasive live cell population monitoring

Mitotic Index Determination on Live Cells From Label-Free Acquired Quantitative Phase Images Using a Supervised Autoencoder

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