Red blood cell phenotyping from 3D confocal images using artificial neural networks

The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fine shape details from confocal microscopy recording...

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Detalles Bibliográficos
Autores principales: Simionato, Greta, Hinkelmann, Konrad, Chachanidze, Revaz, Bianchi, Paola, Fermo, Elisa, van Wijk, Richard, Leonetti, Marc, Wagner, Christian, Kaestner, Lars, Quint, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118337/
https://www.ncbi.nlm.nih.gov/pubmed/33983926
http://dx.doi.org/10.1371/journal.pcbi.1008934

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118337/
https://www.ncbi.nlm.nih.gov/pubmed/33983926
http://dx.doi.org/10.1371/journal.pcbi.1008934

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