AI-based automatic segmentation of craniomaxillofacial anatomy from CBCT scans for automatic detection of pharyngeal airway evaluations in OSA patients

This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The second aim is to validate the newly developed artificial intelligence system in comparison to commercially a...

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Detalles Bibliográficos
Autores principales: Orhan, Kaan, Shamshiev, Mamat, Ezhov, Matvey, Plaksin, Alexander, Kurbanova, Aida, Ünsal, Gürkan, Gusarev, Maxim, Golitsyna, Maria, Aksoy, Seçil, Mısırlı, Melis, Rasmussen, Finn, Shumilov, Eugene, Sanders, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279304/
https://www.ncbi.nlm.nih.gov/pubmed/35831451
http://dx.doi.org/10.1038/s41598-022-15920-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279304/
https://www.ncbi.nlm.nih.gov/pubmed/35831451
http://dx.doi.org/10.1038/s41598-022-15920-1

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