Accuracy and reliability of 3D cephalometric landmark detection with deep learning
This study shows that the AI-driven model delivers high-precision 3D localization of oral and maxillofacial landmarks, even in complex scenarios. The model demonstrates potential as a promising computer-aided tool to assist specialists in conducting accurate and efficient localization analyses; however, its robustness and generalizability require prospective clinical validation to ensure utility across varied experience levels.
Authors
- Wei Tang (ORCID: https://orcid.org/0000-0001-7568-2884)
- Yutao Xiong (ORCID: https://orcid.org/0000-0003-1257-4055)
- Boyan Liu (ORCID: https://orcid.org/0000-0002-7646-5299)
- Wei Zeng (ORCID: https://orcid.org/0000-0002-4486-8798)
- Jixiang Guo (ORCID: https://orcid.org/0000-0002-1678-8205)
- Chang Liu (ORCID: https://orcid.org/0000-0002-1232-8308)
- Wei Liu (ORCID: https://orcid.org/0000-0002-1470-3538)
- Jinglong Chen (ORCID: https://orcid.org/0000-0003-1640-7115)
- Hailin Zhu (ORCID: https://orcid.org/0000-0002-5649-2855)
Institutions
- Foshan University (CN)
- Sichuan University (CN)
- Foshan Second People's Hospital (CN)
Publication Details
- Journal
- European journal of medical research
- Published
- 2025-10-21
- DOI
- https://doi.org/10.1186/s40001-025-03198-8
- Citations
- 1
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- National Natural Science Foundation of China
- Sichuan University
- National Health Commission of the People's Republic of China
- West China Hospital, Sichuan University