Automatic Cephalometric Landmark Identification System Based on the Multi-Stage Convolutional Neural Networks with CBCT Combination Images

This study was designed to develop and verify a fully automated cephalometry landmark identification system, based on multi-stage convolutional neural networks (CNNs) architecture, using a combination dataset. In this research, we trained and tested multi-stage CNNs with 430 lateral and 430 MIP late...

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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: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828192/
https://www.ncbi.nlm.nih.gov/pubmed/33445758
http://dx.doi.org/10.3390/s21020505

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828192/
https://www.ncbi.nlm.nih.gov/pubmed/33445758
http://dx.doi.org/10.3390/s21020505

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