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A Convolutional Neural Network for Automatic Tooth Numbering in Panoramic Images.

María Prados-Privado^1,2,3, Javier García Villalón¹, Antonio Blázquez Torres^1,4

¹Asisa Dental, Research Department, C/José Abascal, 32, 28003 Madrid, Spain.

Biomed Research International

|December 24, 2021

Summary

This study introduces an automated convolutional neural network (CNN) for precise tooth numbering in dental radiographs. The AI model achieved high accuracy, improving diagnostic efficiency in clinical practice.

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Area of Science:

Dentistry
Artificial Intelligence
Medical Imaging

Background:

Accurate tooth numbering is crucial for dental diagnosis and treatment planning.
Manual interpretation of tooth numbering in panoramic radiographs can be time-consuming and prone to errors.
Automating this process can enhance diagnostic efficiency and consistency.

Purpose of the Study:

To develop and evaluate a convolutional neural network (CNN) for automatic tooth numbering in panoramic dental radiographs.
To improve the accuracy and speed of tooth identification and numbering in clinical dental practice.

Main Methods:

A dataset of 8,000 panoramic radiographs was annotated by experienced dentists.
A two-layer neural network architecture was employed, integrating object detection (Matterport Mask RCNN) and classification (ResNet101).
Transfer learning techniques were utilized to optimize computing time and precision.

Main Results:

The proposed CNN model achieved an overall accuracy of 93.83% with a total loss of 6.17%.
The architecture demonstrated high performance with 99.24% accuracy in tooth detection.
The model accurately numbered teeth in various oral health conditions with 93.83% accuracy.

Conclusions:

The developed CNN offers a reliable and accurate automated solution for tooth numbering in panoramic radiographs.
This AI-driven approach has the potential to significantly streamline the diagnostic workflow in dentistry.
The model's high accuracy in detection and numbering supports its clinical applicability for improving dental diagnostics.