Ontology highlight
ABSTRACT:
SUBMITTER: Blasi T
PROVIDER: S-EPMC4729834 | biostudies-other | 2016 Jan
REPOSITORIES: biostudies-other
Nature communications 20160107
Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding ...[more]