Self-supervised machine learning for live cell imagery segmentation

Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall under supervised learning (SL) which requires vast...

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Detalles Bibliográficos
Autores principales: Robitaille, Michael C., Byers, Jeff M., Christodoulides, Joseph A., Raphael, Marc P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630527/
https://www.ncbi.nlm.nih.gov/pubmed/36323790
http://dx.doi.org/10.1038/s42003-022-04117-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630527/
https://www.ncbi.nlm.nih.gov/pubmed/36323790
http://dx.doi.org/10.1038/s42003-022-04117-x

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