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al.Workflow and Metrics for Image Quality Control in HCS Workflow and Metrics for Image Quality Control in Large-Scale High-Content Screens Journal of Biomolecular Screening

By Mark-anthony Bray, Adam N. Fraser, Thomas P. Hasaka and Anne E. CarpenterMark-anthony Bray, Adam N. Fraser, Thomas P. Hasaka and Anne E. Carpenter

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. (Journal of Biomolecular Screening XXXX:000-000

Topics: high-content screening, image analysis, microscopy
Year: 1177
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.6427
Provided by: CiteSeerX
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