NSF Award
1119830
The use of automated microscopy is increasing rapidly in academic biological research (as well as pharmaceutical and biotechnology industries). Image analysis software can extract information-rich cellular image data from microscopy images and eliminate tedious visual inspection. However, a significant challenge has been the lack of metrics and user-friendly software tools to explore the data and identify low-quality images that limit an experiment's value. This project will create tools to address these challenges and test them in the context of two biological experiments. This project will develop and characterize metrics of image quality and the final software will be distributed via the CellProfiler project as a validated, versatile, open-source toolbox of algorithms and metrics readily usable by biologists. <br/><br/>The research will improve data quality in a wide variety of biological experiments addressing important questions in basic science. Furthermore, the education and outreach efforts will increase the number of scientists trained in image analysis at the interface of biology and computer science, will increase the number of students interested in science, and will broaden the participation of people from under-represented minority groups in science, especially at the highest levels of achievement.
