Data-driven AI platform for dens evaginatus detection on orthodontic intraoral photographs
Our BiStageNet was capable of recognizing premolars and detecting DE with high accuracy on intraoral photographs. On top of that, our self-developed DE detection platform was promising for clinical application and promotion.
Authors
- Shihao Li (ORCID: https://orcid.org/0000-0002-6418-7818)
- Xiaoyue Wu (ORCID: https://orcid.org/0000-0002-3840-281X)
- Xingchen Peng (ORCID: https://orcid.org/0000-0001-7042-718X)
- Zhihe Zhao (ORCID: https://orcid.org/0000-0003-2955-1706)
- Wen Liao (ORCID: https://orcid.org/0000-0002-6861-0054)
- Ruiyang Ren (ORCID: https://orcid.org/0000-0002-0562-9911)
- Jialing Liu (ORCID: https://orcid.org/0000-0001-5554-0870)
Institutions
- Sichuan University (CN)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1186/s12903-024-05231-4
- Citations
- 2
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 3.58
Funders
- Natural Science Foundation of Sichuan Province