  Panoramic X-ray (PX) provides a 2D picture of the patient's mouth in a
panoramic view to help dentists observe the invisible disease inside the gum.
However, it provides limited 2D information compared with cone-beam computed
tomography (CBCT), another dental imaging method that generates a 3D picture of
the oral cavity but with more radiation dose and a higher price. Consequently,
it is of great interest to reconstruct the 3D structure from a 2D X-ray image,
which can greatly explore the application of X-ray imaging in dental surgeries.
In this paper, we propose a framework, named Oral-3D, to reconstruct the 3D
oral cavity from a single PX image and prior information of the dental arch.
Specifically, we first train a generative model to learn the cross-dimension
transformation from 2D to 3D. Then we restore the shape of the oral cavity with
a deformation module with the dental arch curve, which can be obtained simply
by taking a photo of the patient's mouth. To be noted, Oral-3D can restore both
the density of bony tissues and the curved mandible surface. Experimental
results show that Oral-3D can efficiently and effectively reconstruct the 3D
oral structure and show critical information in clinical applications, e.g.,
tooth pulling and dental implants. To the best of our knowledge, we are the
first to explore this domain transformation problem between these two imaging
methods.
