Generalizability of Deep Learning Models for Caries Detection in Near-Infrared Light Transillumination Images

Objectives: The present study aimed to train deep convolutional neural networks (CNNs) to detect caries lesions on Near-Infrared Light Transillumination (NILT) imagery obtained either in vitro or in vivo and to assess the models’ generalizability. Methods: In vitro, 226 extracted posterior permanent...

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Detalles Bibliográficos
Autores principales: Holtkamp, Agnes, Elhennawy, Karim, Cejudo Grano de Oro, José E., Krois, Joachim, Paris, Sebastian, Schwendicke, Falk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957685/
https://www.ncbi.nlm.nih.gov/pubmed/33804562
http://dx.doi.org/10.3390/jcm10050961

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957685/
https://www.ncbi.nlm.nih.gov/pubmed/33804562
http://dx.doi.org/10.3390/jcm10050961

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