MICCAI 2023 STS Challenge: A retrospective study of semi-supervised approaches for teeth segmentation
Computer-aided diagnosis greatly enhances personalized treatment planning and diagnostic efficiency by providing accurate dental anatomy through teeth segmentation. However, it still constrained by the scarcity of high-quality annotated dental datasets. To address this issue, this paper presents a dataset combining both 2D panoramic X-rays with over 6,500 images and 3D CBCT with over 580 volumes (88,500+ slices) to support the Semi-supervised Teeth Segmentation (STS) Challenge, which includes partially meticulous annotations and covers all age groups. Moreover, multi-phase semi-supervised teeth segmentation algorithms and high-confidence pseudo-labels refinement strategies were proposed by competitors during this challenge. Algorithms were verified on this proposed dataset and good segmentation performance were achieved, over 93+ and 80+ Dice score were obtained for top three 2D and 3D participants, demonstrating the high quality of this proposed dataset. This paper also summarizes the diverse methods employed by the top-ranking teams in the MICCAI 2023 STS Challenge. Our dataset is publicly accessible through Zenodo ( https://zenodo.org/records/10597292 ), and the participants’ code is hosted on GitHub ( https://github.com/ricoleehduu/STS-Challenge ).
Authors
- Ruilong Dan
- Qiupu Chen (ORCID: https://orcid.org/0000-0003-1036-6762)
- Chunshi Wang (ORCID: https://orcid.org/0009-0001-5994-2639)
- Feng Xu (ORCID: https://orcid.org/0000-0002-0953-1057)
- Yuanlin Li (ORCID: https://orcid.org/0009-0003-1028-9354)
- Zhenghai Ma (ORCID: https://orcid.org/0000-0002-0930-7696)
- Dongyun Liu (ORCID: https://orcid.org/0000-0001-9712-5106)
- Shuai Wang (ORCID: https://orcid.org/0000-0003-3730-6401)
- Xiao‐Diao Chen (ORCID: https://orcid.org/0000-0002-7523-7657)
- Yifan Zhang (ORCID: https://orcid.org/0000-0002-9182-6267)
- Zhi Li (ORCID: https://orcid.org/0000-0002-8789-0151)
- Qun Jin (ORCID: https://orcid.org/0000-0002-1325-4275)
- Huiyu Zhou (ORCID: https://orcid.org/0000-0003-1634-9840)
- Qianni Zhang (ORCID: https://orcid.org/0000-0001-7685-2187)
- Chengkai Wang (ORCID: https://orcid.org/0009-0000-2690-9608)
- Wei Song (ORCID: https://orcid.org/0000-0002-3182-8906)
- Xingru Huang (ORCID: https://orcid.org/0000-0003-3971-8434)
- Yaqi Wang (ORCID: https://orcid.org/0000-0002-4627-3392)
- Jun Liu (ORCID: https://orcid.org/0000-0001-8859-5405)
- Bing Wang (ORCID: https://orcid.org/0000-0003-4621-9115)
- Yifei Chen (ORCID: https://orcid.org/0009-0001-9475-0480)
- Hongyuan Zhang (ORCID: https://orcid.org/0000-0001-5292-5732)
- Weiwei Cui (ORCID: https://orcid.org/0000-0003-0870-7628)
- Yunxiang Li (ORCID: https://orcid.org/0000-0003-3244-2228)
- Yi Liu (ORCID: https://orcid.org/0000-0002-2683-1262)
- Tianhao Li (ORCID: https://orcid.org/0000-0002-3099-7855)
- Shan Luo (ORCID: https://orcid.org/0009-0004-9378-7291)
- Qixuan Wang (ORCID: https://orcid.org/0009-0003-4006-851X)
- Fan Ye (ORCID: https://orcid.org/0009-0001-4637-4345)
- Zhao Huang
- Chengyu Wu (ORCID: https://orcid.org/0009-0009-0450-8649)
- Dahong Qian
- Junfeng Ni (ORCID: https://orcid.org/0009-0004-0581-0974)
- Xiang Feng (ORCID: https://orcid.org/0009-0006-5961-1182)
- Meimingwei Li (ORCID: https://orcid.org/0009-0003-1400-562X)
- Zhiwen Zheng (ORCID: https://orcid.org/0009-0009-1423-8160)
- Zhouhao Lin
Institutions
- Shandong University (CN)
- Queen Mary University of London (GB)
- Shenzhen University (CN)
- Shanghai Jiao Tong University (CN)
- Sichuan University (CN)
- Suzhou Research Institute (CN)
- Stomatology Hospital (CN)
- State Key Laboratory of Oral Diseases
- Hangzhou Dianzi University (CN)
Publication Details
- Journal
- Pattern Recognition
- Published
- 2025-07-05
- DOI
- https://doi.org/10.1016/j.patcog.2025.112049
- Citations
- 1
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.79