
Teeth3DS+: An Extended Benchmark for Intraoral 3D Scans Analysis
Achraf Ben-Hamadoua,b,∗
, Nour Neifara,b, Ahmed Rekika,b, Oussama Smaouic, Firas Bouzguendac,
Sergi Pujadesd, Edmond Boyerd, Edouard Ladroitc
aSMARTS Laboratory, Technopark of Sfax, Sakiet Ezzit 3021, Sfax, Tunisia
bDigital Research Center of Sfax, Technopark of Sfax, Sakiet Ezzit 3021, Sfax, Tunisia
cUdini, 37 BD Aristide Briand, 13100 Aix-En-Provence, France
dInria, Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, France
Abstract
Intraoral 3D scans analysis is a fundamental aspect of Computer-Aided Dentistry (CAD) systems,
playing a crucial role in various dental applications, including teeth segmentation, detection, labeling,
and dental landmark identification. Accurate analysis of 3D dental scans is essential for orthodon-
tic and prosthetic treatment planning, as it enables automated processing and reduces the need for
manual adjustments by dental professionals. However, developing robust automated tools for these
tasks remains a significant challenge due to the limited availability of high-quality public datasets and
benchmarks. This article introduces Teeth3DS+, the first comprehensive public benchmark designed
to advance the field of intraoral 3D scan analysis. Developed as part of the 3DTeethSeg 2022 and
3DTeethLand 2024 MICCAI challenges, Teeth3DS+ aims to drive research in teeth identification, seg-
mentation, labeling, 3D modeling, and dental landmarks identification. The dataset includes at least
1,800 intraoral scans (containing 23,999 annotated teeth) collected from 900 patients, covering both
upper and lower jaws separately. All data have been acquired and validated by experienced orthodon-
tists and dental surgeons with over five years of expertise. Detailed instructions for accessing the
dataset are available at https://crns-smartvision.github.io/teeth3ds
Keywords: Teeth3DS, Teeth3DS+, intraoral 3D scans, 3D point cloud, 3D segmentation, dentistry
1. Introduction
Computer-aided design (CAD) tools are becoming increasingly popular in modern dentistry for
highly accurate treatment planning. Advanced intra-oral scanners (IOSs) are particularly popular in or-
thodontic CAD software as they provide an accurate digital surface 3D representation of the dentition.
Such 3D representation can greatly assist dentists in simulating tooth extraction, realignment, and
smile design, making the treatment’s final results more predictable. As a result, digital teeth models
have the potential to relieve dentists from time-consuming and tedious tasks.
Although IOSs are becoming ubiquitous in clinical dental practice, there are only a few contri-
butions on teeth segmentation/labeling available in the literature, e.g., [1, 2, 3, 4, 5, 6], and, most
importantly, no publicly available benchmark. A fundamental challenge in IOS data analysis is the abil-
ity to accurately segment and identify teeth. Teeth segmentation and labeling are challenging due to
inter-class variations, such as inherent similarities between tooth shapes and ambiguous positions on
jaws, as well as intra-class variations such as damaged teeth or braces. This is in addition to the tight
∗Corresponding author
Email addresses: achraf.benhamadou@crns.rnrt.tn (Achraf Ben-Hamadou), (Nour Neifar), (Ahmed Rekik), (Oussama
Smaoui), (Firas Bouzguenda), (Sergi Pujades), (Edmond Boyer), (Edouard Ladroit)
Preprint submitted to Elsevier November 13, 2024
arXiv:2210.06094v2 [cs.CV] 11 Nov 2024