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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

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Published on: February 23, 2024

Diagnostic charting of panoramic radiography using deep-learning artificial intelligence system.

Melike Başaran¹, Özer Çelik^2,3, Ibrahim Sevki Bayrakdar^4,5

¹Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Kütahya Health Science University, Kütahya, Turkey.

|October 6, 2021

Summary

A new artificial intelligence (AI) model shows promise for detecting dental conditions in panoramic radiographs, with high accuracy for crowns and implants. Further development is needed for detecting caries and dental calculus.

Keywords:

Artificial intelligence Deep-learning Dentistry Panoramic radiography

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Area of Science:

Dental Radiology
Artificial Intelligence
Deep Learning

Background:

Panoramic radiography is a crucial tool in dental diagnostics.
Accurate diagnostic charting is essential for treatment planning.
Deep learning (DL) and artificial intelligence (AI) offer potential for improving diagnostic accuracy.

Purpose of the Study:

To develop and evaluate a novel DL-AI model for diagnostic charting in panoramic radiography.
To assess the model's performance in identifying various dental conditions.

Main Methods:

A deep convolutional neural network (CNN) model, Faster R-CNN Inception v2, was developed using TensorFlow.
1084 dental panoramic radiographs were annotated by dento-maxillofacial radiologists for ten conditions.
Model performance was evaluated using sensitivity, precision, and F1 scores.

Main Results:

The AI model achieved high sensitivity for crowns (0.9674), implants (0.9615), and impacted teeth (0.9658).
High precision was observed for pontics (0.8783), implants (0.9259), and implant-supported crowns (0.8947).
The highest F1 scores were for implants (0.9433), crowns (0.9122), and implant-supported crowns (0.8947).
Lower performance was noted for caries (sensitivity 0.3026, precision 0.5096) and dental calculus (sensitivity 0.0934, precision 0.1923).

Conclusions:

The developed AI model demonstrates promising diagnostic capabilities for several dental conditions in panoramic radiographs.
The model's performance for detecting caries and dental calculus requires improvement.
AI in dental radiology is predicted to aid diagnosis, treatment planning, and digital education.