A comprehensive artificial intelligence framework for dental diagnosis and charting

BACKGROUND: The aim of this study was to develop artificial intelligence (AI) guided framework to recognize tooth numbers in panoramic and intraoral radiographs (periapical and bitewing) without prior domain knowledge and arrange the intraoral radiographs into a full mouth series (FMS) arrangement t...

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Detalles Bibliográficos
Autores principales: Kabir, Tanjida, Lee, Chun-Teh, Chen, Luyao, Jiang, Xiaoqian, Shams, Shayan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9647924/
https://www.ncbi.nlm.nih.gov/pubmed/36352390
http://dx.doi.org/10.1186/s12903-022-02514-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9647924/
https://www.ncbi.nlm.nih.gov/pubmed/36352390
http://dx.doi.org/10.1186/s12903-022-02514-6

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