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

Kim, Min-Jung; Liu, Yi; Oh, Song Hee; Ahn, Hyo-Won; Kim, Seong-Hun; Nelson, Gerald

Kim, Min-Jung; Liu, Yi; Oh, Song Hee; Ahn, Hyo-Won; Kim, Seong-Hun; Nelson, Gerald.

Afiliação

Kim MJ; Department of Orthodontics, Graduate School, Kyung Hee University, Seoul, Korea.
Liu Y; Department of Orthodontics, Peking University School of Stomatology, Beijing, China.
Oh SH; Department of Oral and Maxillofacial Radiology, Graduate School, Kyung Hee University, Seoul, Korea.
Ahn HW; Department of Orthodontics, Graduate School, Kyung Hee University, Seoul, Korea.
Kim SH; Department of Orthodontics, Graduate School, Kyung Hee University, Seoul, Korea.
Nelson G; Division of Orthodontics, Department of Orofacial Science, University of California San Francisco, CA, USA.

Korean J Orthod ; 51(2): 77-85, 2021 Mar 25.

Article em En | MEDLINE | ID: mdl-33678623

Palavras-chave

Artificial intelligence; Cone-beam computed tomography; Convolutional neural networks; Posteroanterior cephalometrics

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: Korean J Orthod Ano de publicação: 2021 Tipo de documento: Article

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