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Semi-supervised Tooth Segmentation

First MICCAI Challenge, SemiToothSeg 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Conference proceedings
  • © 2025

Overview

Editors:
  1. Yaqi Wang

    1. Communication University of Zhejiang, Hangzhou, China

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  2. Xiaodiao Chen

    1. Hangzhou Dianzi University, Hangzhou, China

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  3. Dahong Qian

    1. Shanghai Jiao Tong University, Shanghai, China

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  4. Fan Ye

    1. Hangzhou Dianzi University, Hangzhou, China

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  5. Shuai Wang

    1. Sichuan University, Chengdu, China

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  6. Hongyuan Zhang

    1. Shenzhen University, Shenzhen, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14623)

Included in the following conference series:

Conference proceedings info: STS 2023.

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About this book

This book constitutes the proceedings of the First MICCAI 2023 Challenge on Semi-supervised
Tooth Segmentation, SemiToothSeg 2023, held in Conjunction with MICCAI 2023, in Vancouver, BC, Canada, on October 8, 2023.

The 16 full papers presented in this book were carefully reviewed and selected from 64 submissions. The papers were written by participants in the STS challenge to describe their solutions for automatic teeth segmentation using the offcial training dataset released for this purpose.

In general, this challenge aims to promote the development of the teeth segmentation in panoramic X-ray images and dental CBCT scans.

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Keywords

Table of contents (16 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Convolutional Neural Network-Based Multi-scale Semantic Segmentation for Two-Dimensional Panoramic X-Rays of Teeth

    • Qixuan Wang, Yangzheng Zhao, Zhuofan Zhang
    Pages 1-13

  3. TB-FPN: Enhancing Tooth Segmentation with Cascade Boundary-Aware FPN

    • Xinxu Cai, Yisong Zhang, Zeyuan Guan, Qi Sun, Zhenshen Qu
    Pages 14-24

  4. Perform Special Post-processing After Tooth Segmentation

    • Bing Wang, Chi Zhang, Weili Shi
    Pages 25-35

  5. A Multi-stage Framework for 3D Individual Tooth Segmentation in Dental CBCT

    • Chunshi Wang, Bin Zhao, Shuxue Ding
    Pages 36-45

  6. Preprocessing of Prior Knowledge Before Semi-supervised Tooth Segmentation

    • Bing Wang, Chi Zhang, Weili Shi
    Pages 46-57

  7. A Semi-supervised Tooth Segmentation Method Based on Entropy-Guided Mean Teacher and Weakly Mutual Consistency Network

    • Mingqian Li, Zhiqian Yan, Qinghang Lu, Qiongxiong Ma, Liang Guo, Qingmao Zhang
    Pages 58-71

  8. MsNet: Multi-stage Learning from Seldom Labeled Data for 3D Tooth Segmentation in Dental Cone Beam Computed Tomography

    • Xuewei Kang, Bingjiang Qiu, Lisha Yao, Zhihong Chen, Chu Han, Zaiyi Liu
    Pages 72-82

  9. Diffusion-Based Conv-Former Dual-Encode U-Net: DDPM for Level Set Evolution Mapping MICCAI STS 2023 Challenge

    • Junlin Li, Weixin Tian, Junliang Li, Yuan He, Wanglin Ke
    Pages 83-95

  10. Semi-supervised 3D Tooth Segmentation Using nn-UNet with Axial Attention and Positional Correction

    • Qiupu Chen, Yimou Wang, Jun Xu, Qiankun Li
    Pages 96-109

  11. Boundary Feature Fusion Network for Tooth Image Segmentation

    • Dongping Zhang, Zheng Li, Fangao Zeng, Yutong Wei
    Pages 110-123

  12. Self-training Based Semi-Supervised Learning and U-Net with Denoiser for Teeth Segmentation in X-Ray Image

    • Zhouhao Lin, Yibo Yang, Anrui Huang, Zeyang Shou, Qizhong Zhang
    Pages 124-132

  13. UX-CNet: Effective Edge Information Acquisition for Teeth Image Segmentation

    • Hao Leng, Lianghuang Huang
    Pages 133-144

  14. 2D Teeth Segmentation Base on Half-Image Approach and VCMix-Net+

    • Mengzhuo Shen, Haocheng Li, Qing Li, Shidong Zhang, Tairong Xing, Zhenzhen Wan
    Pages 145-155

  15. Automated Dental CBCT Segmentation Using Pseudo Labeling Method

    • Weiyan Feng
    Pages 156-168

  16. Prior-Aware Cross Pseudo Supervision for Semi-supervised Tooth Segmentation

    • Tingyi Lin, Pengju Lyu, Junchen Xiong, Xiaodong Wang, Kehan Song, Qiong Lou
    Pages 169-179

  17. High-Precision Semi-supervised 3D Dental Segmentation Based on nnUNet

    • Bingyan Zhang, Xuefei Zhu
    Pages 180-191

  18. Back Matter

    Pages 193-194
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Other volumes

  1. Semi-supervised Tooth Segmentation

Editors and Affiliations

  • Communication University of Zhejiang, Hangzhou, China

    Yaqi Wang

  • Hangzhou Dianzi University, Hangzhou, China

    Xiaodiao Chen, Fan Ye

  • Shanghai Jiao Tong University, Shanghai, China

    Dahong Qian

  • Sichuan University, Chengdu, China

    Shuai Wang

  • Shenzhen University, Shenzhen, China

    Hongyuan Zhang

Bibliographic Information

  • Book Title: Semi-supervised Tooth Segmentation

  • Book Subtitle: First MICCAI Challenge, SemiToothSeg 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Editors: Yaqi Wang, Xiaodiao Chen, Dahong Qian, Fan Ye, Shuai Wang, Hongyuan Zhang

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-72396-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2025

  • Softcover ISBN: 978-3-031-72395-7Published: 19 October 2024

  • eBook ISBN: 978-3-031-72396-4Published: 18 October 2024

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 194

  • Number of Illustrations: 16 b/w illustrations, 58 illustrations in colour

  • Topics: Computer Applications

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