NuSeT: A deep learning tool for reliably separating and analyzing crowded cells

Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learning-based models. We report a Nuclear Segmentation...

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Detalles Bibliográficos
Autores principales: Yang, Linfeng, Ghosh, Rajarshi P., Franklin, J. Matthew, Chen, Simon, You, Chenyu, Narayan, Raja R., Melcher, Marc L., Liphardt, Jan T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515182/
https://www.ncbi.nlm.nih.gov/pubmed/32925919
http://dx.doi.org/10.1371/journal.pcbi.1008193

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515182/
https://www.ncbi.nlm.nih.gov/pubmed/32925919
http://dx.doi.org/10.1371/journal.pcbi.1008193

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