Quantius: Generic, high-fidelity human annotation of scientific images at 10 5 -clicks-per-hour
Alex J. Hughes, Joseph D. Mornin, Sujoy Kumar Biswas, David P. Bauer, Simone Bianco, Zev J. Gartner · bioRxiv (Cold Spring Harbor Laboratory) · 2017
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.