A deep learning approach for dental implant planning in cone-beam computed tomography images

BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. METHODS: Seventy-five CBCT images were included in this study. In these images, bone height and thickness...

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Detalles Bibliográficos
Autores principales: Bayrakdar, Sevda Kurt, Orhan, Kaan, Bayrakdar, Ibrahim Sevki, Bilgir, Elif, Ezhov, Matvey, Gusarev, Maxim, Shumilov, Eugene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132372/
https://www.ncbi.nlm.nih.gov/pubmed/34011314
http://dx.doi.org/10.1186/s12880-021-00618-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132372/
https://www.ncbi.nlm.nih.gov/pubmed/34011314
http://dx.doi.org/10.1186/s12880-021-00618-z

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