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

|View full text |Cite

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

Philippe Pognonec¹,

Michel Barlaud

Wattellier Benoit³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Quantitative phase microscopy for non-invasive live cell population monitoring

Aknoun¹,

Yonnet²,

Djabari

et al. 2021

Sci Rep

View full text Add to dashboard Cite

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.

show abstract

Quantitative phase microscopy for non-invasive live cell population monitoring

Aknoun¹,

Yonnet²,

Djabari

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

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.

View full text Add to dashboard Cite

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.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

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

Contact Info

Product

Resources

About