Clinical-oriented 3D visualization and quantitative analysis of gingival thickness using convolutional neural networks and CBCT
This system represents a methodological advancement from qualitative to spatial quantitative GT assessment. The intuitive 3D visualization serves as an innovative preoperative tool that identifies high-risk areas and guides personalized surgical planning, enhancing predictability for aesthetic and complex implant cases.
Authors
- Zhou Zhu (ORCID: https://orcid.org/0000-0002-0642-8919)
- Xiaoli Wang (ORCID: https://orcid.org/0000-0002-0640-9865)
- Jiang Chen (ORCID: https://orcid.org/0000-0002-7631-2591)
- Lan Yang
- Haoran Zheng (ORCID: https://orcid.org/0000-0001-7442-6299)
- Yongshan Li
- Jieying Huang
Institutions
- Fujian Medical University (CN)
- Guangzhou Panyu Polytechnic (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Stomatology Hospital (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Frontiers in Dental Medicine
- Published
- 2025-08-18
- DOI
- https://doi.org/10.3389/fdmed.2025.1635155
- Citations
- 1
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- Guangzhou Medical University
- Guangdong Medical Research Foundation
- Jinan University