Automatic Point Cloud Patching of Intraoral Three-Dimensional Scanning Based on Deep Learning
This method improves clinical efficiency, reduces chairside time, and enhances both patient comfort and treatment acceptance. In addition, it minimises human error and increases the precision of dental restorations. As digital dentistry continues to evolve, this approach holds great potential for improving the accuracy and efficiency of dental treatments, paving the way for broader artificial intelligence integration in clinical practice.
Authors
- Lixia Gao (ORCID: https://orcid.org/0000-0002-1884-0257)
- Weifang Zhang (ORCID: https://orcid.org/0000-0002-0769-3749)
- Mengqi Zhou
- Yongjia Wu (ORCID: https://orcid.org/0000-0001-6038-5801)
- Yimin Wang
- Jiahao Chen (ORCID: https://orcid.org/0009-0007-2621-5308)
- Xiaozhe Wang (ORCID: https://orcid.org/0000-0003-4824-4496)
- Qianhan Zheng
- Xuepeng Chen
- Ting Kang (ORCID: https://orcid.org/0000-0002-5046-2399)
Institutions
- Zhejiang Chinese Medical University (CN)
- Zhejiang Cancer Hospital (CN)
- Zhejiang University Medical College Affiliated Stomatological Hospital (CN)
- Stomatology Hospital (CN)
- Hangzhou Medical College (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- International Dental Journal
- Published
- 2025-07-19
- DOI
- https://doi.org/10.1016/j.identj.2025.100911
- Citations
- 2
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.60