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bioRxiv · 10.1101/505032

DeepCell 2.0: Automated cloud deployment of deep learning models for large-scale cellular image analysis

Bannon, D.·Moen, E.·Borba, E.·Ho, A.·Camplisson, I.·Chang, B.·Osterman, E.·Graf, W.·Van Valen, D.
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Abstract

Deep learning is transforming the analysis of biological images but applying these models to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native software that dynamically scales deep learning workflows to accommodate large imaging datasets. To demonstrate the scalability and affordability of this software, we identified cell nuclei in 106 1-megapixel images in ~5.5 h for ~$250, with a sub-$100 cost achievable depending on cluster configuration. The DeepCell Kiosk can be downloaded at https://github.com/vanvalenlab/kiosk-console; a persistent deployment is available at https://deepcell.org.

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Bannon, D., Moen, E., Borba, E., Ho, A., Camplisson, I., Chang, B., Osterman, E., Graf, W., Van Valen, D.. 2018-12-22. DeepCell 2.0: Automated cloud deployment of deep learning models for large-scale cellular image analysis. https://doi.org/10.1101/505032

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