3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge
Achraf Ben-Hamadou
(1)
,
Oussama Smaoui
(2)
,
Ahmed Rekik
(1)
,
Sergi Pujades
(3)
,
Edmond Boyer
(3)
,
Hoyeon Lim
(4)
,
Minchang Kim
(4)
,
Minkyung Lee
(4)
,
Minyoung Chung
(5)
,
Yeong-Gil Shin
(4)
,
Mathieu Leclercq
(6)
,
Lucia Cevidanes
(7)
,
Juan Carlos Prieto
(6)
,
Shaojie Zhuang
(8)
,
Guangshun Wei
(8)
,
Zhiming Cui
(9)
,
Yuanfeng Zhou
(8)
,
Tudor Dascalu
(10)
,
Bulat Ibragimov
(10)
,
Tae-Hoon Yong
(11)
,
Hong-Gi Ahn
(11)
,
Wan Kim
(11)
,
Jae-Hwan Han
(11)
,
Byungsun Choi
(11)
,
Niels van Nistelrooij
(12)
,
Steven Kempers
(12)
,
Shankeeth Vinayahalingam
(12)
,
Julien Strippoli
(2)
,
Aurélien Thollot
(2)
,
Hugo Setbon
(2)
,
Cyril Trosset
(2)
,
Edouard Ladroit
(2)
1
CRNS -
Centre de Recherche en Numérique de Sfax
2 Udini [Aix-En-Provence]
3 MORPHEO - Capture and Analysis of Shapes in Motion
4 SNU - Seoul National University [Seoul]
5 Soongsil University, Seoul
6 UNC - University of North Carolina [Chapel Hill]
7 University of Michigan [Ann Arbor]
8 Shandong University
9 ShanghaiTech University [Shanghai]
10 ITU - IT University of Copenhagen
11 Osstem Implant [Seoul]
12 Radboud University Medical Center [Nijmegen]
2 Udini [Aix-En-Provence]
3 MORPHEO - Capture and Analysis of Shapes in Motion
4 SNU - Seoul National University [Seoul]
5 Soongsil University, Seoul
6 UNC - University of North Carolina [Chapel Hill]
7 University of Michigan [Ann Arbor]
8 Shandong University
9 ShanghaiTech University [Shanghai]
10 ITU - IT University of Copenhagen
11 Osstem Implant [Seoul]
12 Radboud University Medical Center [Nijmegen]
Sergi Pujades
- Fonction : Auteur
- PersonId : 738926
- IdHAL : sergi-pujades
- ORCID : 0000-0002-9604-7721
- IdRef : 191615536
Edmond Boyer
- Fonction : Auteur
- PersonId : 752316
- IdHAL : edmond-boyer
- ORCID : 0000-0002-1182-3729
- IdRef : 108147797
Résumé
Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health. However, developing automated algorithms for teeth analysis presents significant challenges due to variations in dental anatomy, imaging protocols, and limited availability of publicly accessible data. To address these challenges, the 3DTeethSeg'22 challenge was organized in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans. A dataset comprising a total of 1800 scans from 900 patients was prepared, and each tooth was individually annotated by a human-machine hybrid algorithm. A total of 6 algorithms were evaluated on this dataset. In this study, we present the evaluation results of the 3DTeethSeg'22 challenge. The 3DTeethSeg'22 challenge code can be accessed at: https://github.com/abenhamadou/3DTeethSeg22_challenge
