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

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...

Full description

Bibliographic Details
Main Authors: Agnes Holtkamp, Karim Elhennawy, José E. Cejudo Grano de Oro, Joachim Krois, Sebastian Paris, Falk Schwendicke
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Journal of Clinical Medicine
Subjects:
artificial intelligence
caries
diagnostics
digital imaging/radiology
mathematical modeling
Online Access:https://www.mdpi.com/2077-0383/10/5/961

Internet

https://www.mdpi.com/2077-0383/10/5/961

Similar Items