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Teeth segmentation and labeling are critical components of Computer-AidedDentistry (CAD) systems. Indeed, before any orthodontic or prosthetic treatmentplanning, a CAD system needs to first accurately segment and label eachinstance of teeth visible in the 3D dental scan, this is to avoidtime-consuming manual adjustments by the dentist. Nevertheless, developing suchan automated and accurate dental segmentation and labeling tool is verychallenging, especially given the lack of publicly available datasets orbenchmarks. This article introduces the first public benchmark, named Teeth3DS,which has been created in the frame of the 3DTeethSeg 2022 MICCAI challenge toboost the research field and inspire the 3D vision research community to workon intra-oral 3D scans analysis such as teeth identification, segmentation,labeling, 3D modeling and 3D reconstruction. Teeth3DS is made of 1800intra-oral scans (23999 annotated teeth) collected from 900 patients coveringthe upper and lower jaws separately, acquired and validated byorthodontists/dental surgeons with more than 5 years of professionalexperience.

Teeth3DS: a benchmark for teeth segmentation and labeling from intra-oral 3D scans