Investigating the Impact of the Bit Depth of Fluorescence-Stained Images on the Performance of Deep Learning-Based Nuclei Instance Segmentation

Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. A...

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Detalles Bibliográficos
Autores principales: Mahbod, Amirreza, Schaefer, Gerald, Löw, Christine, Dorffner, Georg, Ecker, Rupert, Ellinger, Isabella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230326/
https://www.ncbi.nlm.nih.gov/pubmed/34072131
http://dx.doi.org/10.3390/diagnostics11060967

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230326/
https://www.ncbi.nlm.nih.gov/pubmed/34072131
http://dx.doi.org/10.3390/diagnostics11060967

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