Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks

Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks

Abstract Background Cell counting from cell cultures is required in multiple biological and biomedical research applications. Especially, accurate brightfield-based cell counting methods are needed for cell growth analysis. With deep learning, cells can be detected with high accuracy, but manually a...

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Bibliographic Details
Main Authors: Kaisa Liimatainen, Lauri Kananen, Leena Latonen, Pekka Ruusuvuori
Format: Article
Language:English
Published: BMC 2019-02-01
Series:BMC Bioinformatics
Subjects:
Cell detection
Brightfield
Deep learning
Semi-supervised learning
Unsupervised domain adaptation
Online Access:http://link.springer.com/article/10.1186/s12859-019-2605-z

Internet

http://link.springer.com/article/10.1186/s12859-019-2605-z

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