Efficient semi-supervised semantic segmentation of electron microscopy cancer images with sparse annotations

Electron microscopy (EM) enables imaging at nanometer resolution and can shed light on how cancer evolves to develop resistance to therapy. Acquiring these images has become a routine task; however, analyzing them is now the bottleneck, as manual structure identification is very time-consuming and c...

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Detalles Bibliográficos
Autores principales: Pagano, Lucas, Thibault, Guillaume, Bousselham, Walid, Riesterer, Jessica L., Song, Xubo, Gray, Joe W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635003/
https://www.ncbi.nlm.nih.gov/pubmed/37961180
http://dx.doi.org/10.1101/2023.10.30.563998

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635003/
https://www.ncbi.nlm.nih.gov/pubmed/37961180
http://dx.doi.org/10.1101/2023.10.30.563998

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