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Workflow and Metrics for Image Quality Control in Large-Scale High-Content Screens.
|Publication Type||Journal Article|
|Authors||Bray, MA, Fraser AN, Hasaka TP, and Carpenter AE|
|Abstract||Automated 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 Publication||2011|
|Journal||Journal of biomolecular screening|
|Date Published (YYYY/MM/DD)||2011/09/28|