Evaluation of a multi-stage convolutional neural network-based fully automated landmark identification system using cone-beam computed tomography-synthesized posteroanterior cephalometric images

OBJECTIVE: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. METHODS: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesize...

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Detalles Bibliográficos
Autores principales: Kim, Min-Jung, Liu, Yi, Oh, Song Hee, Ahn, Hyo-Won, Kim, Seong-Hun, Nelson, Gerald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Association of Orthodontists 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940808/
https://www.ncbi.nlm.nih.gov/pubmed/33678623
http://dx.doi.org/10.4041/kjod.2021.51.2.77

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940808/
https://www.ncbi.nlm.nih.gov/pubmed/33678623
http://dx.doi.org/10.4041/kjod.2021.51.2.77

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