Identification of individual cells from z-stacks of bright-field microscopy images

Obtaining single cell data from time-lapse microscopy images is critical for quantitative biology, but bottlenecks in cell identification and segmentation must be overcome. We propose a novel, versatile method that uses machine learning classifiers to identify cell morphologies from z-stack bright-f...

Descripción completa

Detalles Bibliográficos
Autores principales: Lugagne, Jean-Baptiste, Jain, Srajan, Ivanovitch, Pierre, Ben Meriem, Zacchary, Vulin, Clément, Fracassi, Chiara, Batt, Gregory, Hersen, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065389/
https://www.ncbi.nlm.nih.gov/pubmed/30061662
http://dx.doi.org/10.1038/s41598-018-29647-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065389/
https://www.ncbi.nlm.nih.gov/pubmed/30061662
http://dx.doi.org/10.1038/s41598-018-29647-5

Ejemplares similares