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BioengineeringbioRxiv

Fast, versatile, and quantitative annotation of complex images

K. Bates, S. Jiang, R. Bates, S. Chaudhary, E. Jackson-Holmes, M. Jue, E. McCaskey, D. Goldman, H. Lu

Abstract

We report a generic smartphone app for quantitative annotation of complex images. The app is simple enough to be used by children, and annotation tasks are distributed across app users, contributing to efficient annotation. We demonstrate its flexibility and speed by annotating >30,000 images, including features of rice root growth and structure, stem cell aggregate morphology, and complex worm (C. elegans) postures, for which we show that the speed of annotation is >130-fold faster than state-of-the-art techniques with similar accuracy.

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02 /Specification & Classification

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