  Teeth segmentation and labeling are critical components of Computer-Aided
Dentistry (CAD) systems. Indeed, before any orthodontic or prosthetic treatment
planning, a CAD system needs to first accurately segment and label each
instance of teeth visible in the 3D dental scan, this is to avoid
time-consuming manual adjustments by the dentist. Nevertheless, developing such
an automated and accurate dental segmentation and labeling tool is very
challenging, especially given the lack of publicly available datasets or
benchmarks. This article introduces the first public benchmark, named Teeth3DS,
which has been created in the frame of the 3DTeethSeg 2022 MICCAI challenge to
boost the research field and inspire the 3D vision research community to work
on intra-oral 3D scans analysis such as teeth identification, segmentation,
labeling, 3D modeling and 3D reconstruction. Teeth3DS is made of 1800
intra-oral scans (23999 annotated teeth) collected from 900 patients covering
the upper and lower jaws separately, acquired and validated by
orthodontists/dental surgeons with more than 5 years of professional
experience.
