Comparison of deep learning models to detect crossbites on 2D intraoral photographs

Comparison of deep learning models to detect crossbites on 2D intraoral photographs

Abstract Background To support dentists with limited experience, this study trained and compared six convolutional neural networks to detect crossbites and classify non-crossbite, frontal, and lateral crossbites using 2D intraoral photographs. Methods Based on 676 photographs from 311 orthodontic pa...

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Bibliographic Details
Main Authors: Beatrice Noeldeke, Stratos Vassis, Mohammedreza Sefidroodi, Ruben Pauwels, Peter Stoustrup
Format: Article
Language:English
Published: BMC 2024-09-01
Series:Head & Face Medicine
Subjects:
Artificial intelligence
Orthodontic diagnosis
Deep learning
Neural networks
Crossbite
Online Access:https://doi.org/10.1186/s13005-024-00448-8

Internet

https://doi.org/10.1186/s13005-024-00448-8

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