Assessing microscope image focus quality with deep learning

BACKGROUND: Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unb...

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Detalles Bibliográficos
Autores principales: Yang, Samuel J., Berndl, Marc, Michael Ando, D., Barch, Mariya, Narayanaswamy, Arunachalam, Christiansen, Eric, Hoyer, Stephan, Roat, Chris, Hung, Jane, Rueden, Curtis T., Shankar, Asim, Finkbeiner, Steven, Nelson, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5853029/
https://www.ncbi.nlm.nih.gov/pubmed/29540156
http://dx.doi.org/10.1186/s12859-018-2087-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5853029/
https://www.ncbi.nlm.nih.gov/pubmed/29540156
http://dx.doi.org/10.1186/s12859-018-2087-4

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