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Tooth Anatomy

Tooth Anatomy

The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
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Caries Detection in Primary Molars with Bitewing Radiographs through Deep Learning Based-Object Detectors.

Zhi Qin Tan^1,2, Ilana Felix Pinho³, Ryan Banks²

¹Faculty of Dentistry, Oral and Craniofacial Sciences, King's College London, London, UK.

Caries Research

|December 18, 2025

Summary

Artificial intelligence, specifically DINO and YOLOv7 algorithms, shows promise for detecting and staging dental caries in children

Keywords:

Artificial intelligence Bitewing Caries detection Deep learning Primary teeth

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Area of Science:

Dentistry
Artificial Intelligence
Medical Imaging

Background:

Automated caries detection aids in prioritizing treatment for children.
AI algorithms can improve diagnostic accuracy for caries lesions.

Purpose of the Study:

Develop AI algorithms using object detection for caries detection and staging in primary molars.
Utilize bitewing radiographs for AI model training and evaluation.

Main Methods:

Trained five deep learning object detection algorithms on 1,023 primary molar bitewing radiographs.
Radiographs were annotated for four caries severity stages.
Evaluated models using sensitivity, specificity, accuracy, and weighted kappa scores across different lesion thresholds.

Main Results:

The DINO model achieved the highest concordance (kappa=0.513) for staging caries.
DINO demonstrated high sensitivity for detecting all caries (0.509) and dentine caries requiring treatment (0.659).
YOLOv7 showed excellent performance with specificity >0.98 and accuracy >0.91.

Conclusions:

DINO and YOLOv7 algorithms are effective for detecting caries in primary molars on bitewing radiographs.
These AI tools have potential clinical applications to assist dentists in daily practice.