Automated Identification of Accessory Mental Foramen Using Cone-Beam Computed Tomography and Convolutional Neural Networks
Deep learning-based detection of AMFs on CBCT can enhance diagnostic accuracy and reduce the risk of surgical complications by providing consistent, observer-independent evaluations.
Authors
- Zuhal Ovuz (ORCID: https://orcid.org/0000-0002-2419-9793)
- Taha Etem
- Eda Gursu Sahin
Institutions
- Çankırı Karatekin University (TR)
Publication Details
- Journal
- International Dental Journal
- Published
- 2026-02-24
- DOI
- https://doi.org/10.1016/j.identj.2026.109428
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00