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2017 GTC San Jose

S7648 - Automating High-Content Screening Image Analysis with Deep Learning

Session Speakers
Session Description

Deep learning can automate the analysis of the hundreds of thousands of images produced by automated microscopy systems each day. High-content screening (HCS) systems that combine high-throughput biotechnology with automated microscopy are revolutionizing drug development and cell biology research. The images produced by these systems provide valuable insight into how cells respond to many chemical or genetic perturbations. Existing image analysis pipelines rely on hand-tuning the segmentation, feature extraction, and machine learning steps for each screen. For many research groups, tuning these pipelines remains a bottleneck in implementing HCS. We'll demonstrate how deep learning-based pipelines overcome this bottleneck and outperform existing methods. We'll show improved results on classifying sub-cellular protein localization in genome-wide screens of the GFP-tagged yeast collection.


Additional Session Information
Beginner
Talk
AI in Healthcare Summit Deep Learning and AI Healthcare and Life Sciences
Healthcare & Life Sciences Higher Education / Research
25 minutes
Session Schedule