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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...
Autores principales: | Yang, Linfeng, Ghosh, Rajarshi P., Franklin, J. Matthew, Chen, Simon, You, Chenyu, Narayan, Raja R., Melcher, Marc L., Liphardt, Jan T. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
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 |
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