AI-Driven Dental Disease Detection: A Web-Based Application Utilizing an AI Engine for Panoramic Image Analysis

Teeth are integral to human health, and the prevention and treatment of dental diseases are closely linked to advanced imaging techniques. Panoramic imaging effectively captures the crowns and roots of all teeth, as well as the associated facial and jawbone structures, making precise reporting critical for effective screening and diagnosis. Traditionally, this process relies heavily on the expertise of radiologists, resulting in a workflow that is both timeconsuming and labor-intensive. This paper introduces a webbased application that utilizes a customized artificial intelligence engine based on the YOLOv11 architecture, which has been trained for the first time on the publicly available DENTEX dataset to diagnose dental diseases from panoramic images. Comparative analysis with similar studies demonstrates significant enhancements in evaluation metrics, with the customized YOLOv11 model surpassing the performance of the YOLOv8 model in both accuracy and localization tasks. Notably, an average precision improvement of over 21% has been achieved compared to previous research, thereby facilitating the interpretation of dental images and extending essential services to regions with limited access to medical professionals.

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Publication Details

Published
2025-04-16
DOI
https://doi.org/10.1109/icwr65219.2025.11006210
Primary Topic
Dental Radiography and Imaging
Type
article
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article

AI-Driven Dental Disease Detection: A Web-Based Application Utilizing an AI Engine for Panoramic Image Analysis

Mahdieh Dehghani, Reza A. Zoroofi
Dental Radiography and Imaging
article

AI-Driven Dental Disease Detection: A Web-Based Application Utilizing an AI Engine for Panoramic Image Analysis

Mahdieh Dehghani, Reza A. Zoroofi
article en

Abstract

Teeth are integral to human health, and the prevention and treatment of dental diseases are closely linked to advanced imaging techniques. Panoramic imaging effectively captures the crowns and roots of all teeth, as well as the associated facial and jawbone structures, making precise reporting critical for effective screening and diagnosis. Traditionally, this process relies heavily on the expertise of radiologists, resulting in a workflow that is both timeconsuming and labor-intensive. This paper introduces a webbased application that utilizes a customized artificial intelligence engine based on the YOLOv11 architecture, which has been trained for the first time on the publicly available DENTEX dataset to diagnose dental diseases from panoramic images. Comparative analysis with similar studies demonstrates significant enhancements in evaluation metrics, with the customized YOLOv11 model surpassing the performance of the YOLOv8 model in both accuracy and localization tasks. Notably, an average precision improvement of over 21% has been achieved compared to previous research, thereby facilitating the interpretation of dental images and extending essential services to regions with limited access to medical professionals.

University of Tehran (IR)
Openalex Percentile: Top 85%
Dental Radiography and Imaging
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