Research progress on deep learning algorithms to assist 3D tooth segmentation of digital dental models
10.12016/j.issn.2096-1456.2023.09.010
- Author:
ZHOU Yucong
1
,
2
,
3
;
TAN Yuwen
4
;
XIANG Xiang
4
;
XUE Chaoran
1
,
2
,
3
;
XU Hui
1
,
2
,
3
Author Information
1. State Key Laboratory of Oral Diseases &
2. National Clinical Research Center for Oral Diseases &
3. Department of Orthodontics, West China Hospital of Stomatology, Sichuan University
4. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Key Laboratory of Image Processing and Intelligent Control, Ministry of Education
- Publication Type:Review
- Keywords:
deep learning / artificial intelligence / orthodontics / digital diagnosis / dental model / tooth segmentation / appliance
- From:
Journal of Prevention and Treatment for Stomatological Diseases
2023;31(9):673-678
- CountryChina
- Language:Chinese
-
Abstract:
Three-dimensional tooth segmentation is the segmentation of single-tooth models from a digital dental model. It is an important foundation for diagnosis, planning, treatment and customized appliance manufacturing in digital orthodontics. With the deep integration of artificial intelligence technology and big data from stomatology, the use of deep learning algorithms to assist 3D tooth segmentation has gradually become mainstream. This review summarizes the current situation of deep learning algorithms that assist 3D tooth segmentation from the aspects of dataset establishment, algorithm architecture, algorithm performance, innovation and advantages, deficiencies of current research and prospects. The results of the literature review showed that deep learning tooth segmentation methods could obtain an accuracy of more than 95% and had good robustness. However, the segmentation of complex dental models, operation time and richness of the training database still need to be improved. Research and development of the "consumption reduction and strong core" algorithm, establishment of an authoritative data sample base with multiple centers, and expansion of data application depth and breadth will lead to further development in this field.
- Full text:深度学习算法辅助数字化牙模三维牙齿分割的研究进展.pdf
