STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation

Yaqi Wang ,

Yifan Zhang ,

Xiaodiao Chen ,

Shuai Wang ,

Dahong Qian ,

Fan Ye ,

Feng Xu ,

Hongyuan Zhang ,

Qianni Zhang ,

Chengyu Wu ,

Yunxiang Li ,

Weiwei Cui ,

Shan Luo ,

Chengkai Wang ,

Tianhao Li ,

Yi Liu ,

Xiang Feng ,

Huiyu Zhou ,

Dongyun Liu ,

Qixuan Wang ,

Zhouhao Lin ,

Wei Song ,

Yuanlin Li ,

Bing Wang ,

Chunshi Wang ,

Qiupu Chen ,

Mingqian Li

ML Semi-SL GSSSL CV MIAS LDCAD

2024年07月18日

计算机辅助设计（CAD）工具在现代牙科实践中越来越受欢迎，特别是用于治疗规划或全面预后评估。具体而言，2D全景X线图像可以有效地检测儿童的隐形龋齿、阻生牙和超数牙，而3D牙科锥形束计算机断层扫描（CBCT）由于其低辐射剂量而广泛用于正畸学和根管治疗。然而，目前没有针对儿童牙齿的开放式2D公共数据集，也没有开放的3D牙科CBCT数据集，这限制了自动算法用于分割牙齿和分析疾病的发展。半监督牙齿分割（STS）挑战赛是牙齿分割领域的先驱性活动，是阿里巴巴天池平台MICCAI 2023 ToothFairy研讨会的一部分。该挑战旨在研究有效的半监督牙齿分割算法，以推动牙科领域的发展。在这个挑战中，我们提供了包括2D全景X线图像和3D CBCT牙齿体积在内的两种模态。在任务1中，目标是分割成人和儿童牙齿的全景X线图像中的牙齿区域。任务2涉及使用CBCT体积分割牙齿部分。在这个挑战中，使用半监督算法进行训练的有限标记图像和大多数未标记图像。在初赛中，共有434支团队注册并提交结果，其中64支晋级到决赛。本文总结了STS MICCAI 2023挑战赛中排名前列的团队采用的多种方法。

Computer-aided design (CAD) tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation. In particular, the 2D panoramic X-ray image efficiently detects invisible caries, impacted teeth and supernumerary teeth in children, while the 3D dental cone beam computed tomography (CBCT) is widely used in orthodontics and endodontics due to its low radiation dose. However, there is no open-access 2D public dataset for children's teeth and no open 3D dental CBCT dataset, which limits the development of automatic algorithms for segmenting teeth and analyzing diseases. The Semi-supervised Teeth Segmentation (STS) Challenge, a pioneering event in tooth segmentation, was held as a part of the MICCAI 2023 ToothFairy Workshop on the Alibaba Tianchi platform. This challenge aims to investigate effective semi-supervised tooth segmentation algorithms to advance the field of dentistry. In this challenge, we provide two modalities including the 2D panoramic X-ray images and the 3D CBCT tooth volumes. In Task 1, the goal was to segment tooth regions in panoramic X-ray images of both adult and pediatric teeth. Task 2 involved segmenting tooth sections using CBCT volumes. Limited labelled images with mostly unlabelled ones were provided in this challenge prompt using semi-supervised algorithms for training. In the preliminary round, the challenge received registration and result submission by 434 teams, with 64 advancing to the final round. This paper summarizes the diverse methods employed by the top-ranking teams in the STS MICCAI 2023 Challenge.

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