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bioRxiv · 10.1101/164087

Quantius: Generic, high-fidelity human annotation of scientific images at 105-clicks-per-hour

Hughes, A.·Mornin, J. D.·Biswas, S. K.·Bauer, D. P.·Bianco, S.·Gartner, Z. J.
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Abstract

We describe Quantius, a crowd-based image annotation platform that provides an accurate alternative to task-specific computational algorithms for difficult image analysis problems. We use Quantius to quantify a variety of computationally challenging medium-throughput tasks with ~50x and 30x savings in analysis time and cost respectively, relative to a single expert annotator. We show equivalent deep learning performance for Quantius- and expert-derived annotations, bridging towards scalable integration with tailored machine-learning algorithms.

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Hughes, A., Mornin, J. D., Biswas, S. K., Bauer, D. P., Bianco, S., Gartner, Z. J.. 2017-07-15. Quantius: Generic, high-fidelity human annotation of scientific images at 105-clicks-per-hour. https://doi.org/10.1101/164087

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