Deep learning-based prediction of buccal, middle and palatal orientations of impacted maxillary canines using panoramic radiographs: a pilot study
This pilot study presented certain challenges in accurately classifying the spatial orientation of impacted maxillary canines due to methodological limitations (e.g., small sample size, preliminary nature). While satisfactory performance was achieved for palatal orientations, reduced classification accuracy and frequent misclassifications were observed for buccal and middle orientations. Given the inherent limitations of panoramic imaging, future studies incorporating larger datasets and 3D imaging techniques would be warranted to improve classification accuracy and clinical applicability.
Authors
- Muhammet Üsame Özıç (ORCID: https://orcid.org/0000-0002-3037-2687)
- Serpil Çokakoğlu (ORCID: https://orcid.org/0000-0002-1240-6951)
- Samet Tosun (ORCID: https://orcid.org/0000-0003-3277-197X)
Institutions
- Pamukkale University (TR)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1186/s12903-025-07395-z
- Primary Topic
- dental development and anomalies
- Type
- article
- Field-Weighted Citation Impact
- 0.00