Abstract
ABSTRACT We address in this study the construction of a public data set of dental panoramic radiographs. Our objects of interest are the teeth, which are segmented and numbered. We benefited from the human-in-the-loop concept to expedite the labelling procedure, using predictions from deep neural networks as provisional labels, later verified by human annotators. Our results demonstrated a 51% labelling time reduction using HITL, saving us more than 390 continuous working hours. In a novel online platform, called OdontoAI, created to work as task central for this novel data set, we released 4,000 images, from which 2,000 have their labels publicly available for model fitting. The labels of the other 2,000 images are private and used for model evaluation on different tasks. To the best of our knowledge, this is the largest-scale publicly available data set for panoramic radiographs, and the OdontoAI is the first platform of its kind in dentistry.
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