Automatic identification of posteroanterior cephalometric landmarks using a novel deep learning algorithm: a comparative study with human experts

This study aimed to propose a fully automatic posteroanterior (PA) cephalometric landmark identification model using deep learning algorithms and compare its accuracy and reliability with those of expert human examiners. In total, 1032 PA cephalometric images were used for model training and validat...

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Detalles Bibliográficos
Autores principales: Lee, Hwangyu, Cho, Jung Min, Ryu, Susie, Ryu, Seungmin, Chang, Euijune, Jung, Young-Soo, Kim, Jun-Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509166/
https://www.ncbi.nlm.nih.gov/pubmed/37726392
http://dx.doi.org/10.1038/s41598-023-42870-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509166/
https://www.ncbi.nlm.nih.gov/pubmed/37726392
http://dx.doi.org/10.1038/s41598-023-42870-z

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