  Clinical finding summaries from an orthopantomogram, or a dental panoramic
radiograph, have significant potential to improve patient communication and
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 find teeth in the imaging study and
label the teeth with several types of past treatments. To tackle the problem,
we developDeepOPG that breaks the summarization process into functional
segmentation and tooth 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%
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