Labeling Category

Representative labeling results. For illustrative purposes, we show the range of observations divided into visually good classification (generally precise), bad classification (rules were followed but the labeled images are not visually close to the truth), and ugly classification (inconsistent with the expected ground truth). All qualities of observations were observed using all input devices.

Characterizing and Optimizing Rater Performance for Internet-based Collaborative Labeling

Feb. 1, 2011—Joshua A. Stein, Andrew J. Asman, Bennett A. Landman. “Characterizing and Optimizing Rater Performance for Internet-based Collaborative Labeling”, In Proceedings of the SPIE Medical Imaging Conference. Lake Buena Vista, Florida, February 2011 (Oral Presentation) Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157950/ Abstract Labeling structures on medical images is crucial in determining clinically relevant correlations with morphometric and volumetric features....