Accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning

This study evaluates the accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning. We developed a dynamic graph convolutional neural network (DGCNN)-based algorithm for automatic tooth segmentation and classification using 516 digital dental models. We seg...

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Detalles Bibliográficos
Autores principales: Im, Joon, Kim, Ju-Yeong, Yu, Hyung-Seog, Lee, Kee-Joon, Choi, Sung-Hwan, Kim, Ji-Hoi, Ahn, Hee-Kap, Cha, Jung-Yul
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/PMC9178028/
https://www.ncbi.nlm.nih.gov/pubmed/35676524
http://dx.doi.org/10.1038/s41598-022-13595-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178028/
https://www.ncbi.nlm.nih.gov/pubmed/35676524
http://dx.doi.org/10.1038/s41598-022-13595-2

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