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Workflow and Metrics for Image Quality Control in Large-Scale High-Content Screens.

Publication TypeJournal Article
AuthorsBray, MA, Fraser AN, Hasaka TP, and Carpenter AE
AbstractAutomated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments. They have implemented these as a versatile, open-source toolbox of algorithms and metrics readily usable by biologists to improve data quality in a wide variety of biological experiments.
Year of Publication2011
JournalJournal of biomolecular screening
Date Published (YYYY/MM/DD)2011/09/28
ISSN Number1087-0571
DOI10.1177/1087057111420292
PubMedhttp://www.ncbi.nlm.nih.gov/pubmed/21956170?dopt=Abstract