Fisheye transformation enhances deep-learning-based single-cell phenotyping by including cellular microenvironment

Incorporating information about the surroundings can have a significant impact on successfully determining the class of an object. This is of particular interest when determining the phenotypes of cells, for example, in the context of high-throughput screens. We hypothesized that an ideal approach w...

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Detalles Bibliográficos
Autores principales: Toth, Timea, Bauer, David, Sukosd, Farkas, Horvath, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795324/
https://www.ncbi.nlm.nih.gov/pubmed/36590690
http://dx.doi.org/10.1016/j.crmeth.2022.100339

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795324/
https://www.ncbi.nlm.nih.gov/pubmed/36590690
http://dx.doi.org/10.1016/j.crmeth.2022.100339

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