AI-driven gingival segmentation on CBCT: Validation using delineation by intraoral scanning and CBCT-based cotton roll separation
Automated 3D gingival models may assist efficient diagnosis, treatment planning, and outcome visualization in esthetic dentistry, orthodontic treatment planning, and periodontal assessment. This approach has strong potential to transform digital dentistry workflows.
Authors
- Fernanda Bulhões Fagundes (ORCID: https://orcid.org/0000-0002-9777-4197)
- Dhanaporn Papasratorn (ORCID: https://orcid.org/0000-0001-9952-6704)
- Bahaaeldeen M. Elgarba (ORCID: https://orcid.org/0000-0003-4936-6567)
- Rocharles Cavalcante Fontenele
- Frederico Sampaio Neves
- Reinhilde Jacobs
Institutions
- Universidade Federal da Bahia (BR)
- Universidade de São Paulo (BR)
- KU Leuven (BE)
Publication Details
- Journal
- Journal of Dentistry
- Published
- 2026-01-05
- DOI
- https://doi.org/10.1016/j.jdent.2026.106331
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Mahidol University