  Finding summaries from an orthopantomogram, or a dental panoramic radiograph,
has significant potential to improve patient communication and to speed up
clinical judgments. While orthopantomogram is a first-line tool for dental
examinations, no existing work has explored the summarization of findings from
it. A finding summary has to not only find teeth in the imaging study but also
label the teeth with several types of treatments. To tackle the problem, we
develop DeepOPG that breaks the summarization process into functional
segmentation and teeth localization, the latter of which is further refined by
a novel dental coherence module. We also leverage weak supervision labels to
improve detection results in a reinforcement learning scenario. Experiments
show high efficacy of DeepOPG on finding summarization, achieving an overall
AUC of 88.2% in detecting six types of findings. The proposed dental coherence
and weak supervision both are shown to improve DeepOPG by adding 5.9% and 0.4%
to AP@IoU=0.5 respectively.
