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Photorealistic Learned Landscapes for Augmented Reality
Published on: June 27, 2025
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Deep learning for preliminary profiling of panoramic images.
Kiyomi Kohinata1, Tomoya Kitano2, Wataru Nishiyama2
1Department of Oral Radiology, Asahi University School of Dentistry, Mizuho, Gifu, Japan. kohinata@dent.asahi-u.ac.jp.
Oral Radiology
|June 27, 2022
Summary
Deep learning effectively profiles panoramic radiographs for dental characteristics like dentition and prosthetic status. This AI approach aids preliminary image interpretation and preprocessing for further analysis.
Area of Science:
- Dentistry
- Artificial Intelligence
- Medical Imaging
Background:
- Panoramic radiographs are crucial for dental diagnostics.
- Automated analysis of radiographic features can improve efficiency.
- Deep learning offers potential for image profiling.
Purpose of the Study:
- To assess the feasibility of deep learning for profiling panoramic radiographs.
- To classify patients based on various dental and physical characteristics using AI.
Main Methods:
- Utilized deep learning systems, including VGG-Net, for image classification.
- Analyzed 1000 panoramic radiographs from patients categorized by age, gender, dentition, tooth count, impaction, implant, and prosthetic status.
Main Results:
- High classification accuracies achieved for dentition (93.5%) and prosthetic status (90.5%).
- Accurate classification for tooth number (89.5%) and implant status (89.5%).
- Moderate accuracy for impacted wisdom tooth status (69.0%), age (56.0%), and gender (75.5%).
Conclusions:
- Deep learning demonstrates feasibility for preliminary panoramic radiograph profiling.
- The method can assist in initial image interpretation and AI preprocessing.
- Potential applications in enhancing diagnostic workflows and AI-driven dental analysis.
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