Can artificial intelligence in orthopantomography advance dental diagnostics through automated image analysis?

Artificial Intelligence (AI) is rapidly transforming dental education and clinical practice, as deep learning-especially convolutional neural networks-brings unprecedented accuracy to interpreting orthopantomograms (OPGs). This review illuminates the cutting-edge frontiers of AI-driven dental imaging, tracing how recent breakthroughs are transforming the detection, classification, and segmentation of complex dental anatomy and pathology. Notably, state-of-the-art AI models have reached remarkably high accuracy in tooth identification, while commercial solutions demonstrate promising-though variable-performance in diagnosing complex conditions, such as the adequacy of endodontic procedures. Yet, bringing AI into routine dental care remains fraught with obstacles - demanding vast annotated datasets, coping with population variability, and confronting persistent medicolegal and trust concerns. Growing collaborations between regulators and professional bodies in the United States and European Union are now shaping ethical and legal frameworks to guide its safe use. This narrative review goes beyond summarizing technological progress in AI-driven dental radiology - it uniquely integrates diagnostic breakthroughs with the rapidly evolving regulatory and ethical landscape. By bridging innovation with implementation, it offers educators, practitioners, and learners a forward-looking roadmap that positions AI not as a distant promise, but as a transformative force already reshaping the future of dental diagnostics and training.

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Publication Details

Journal
Frontiers in Radiology
Published
2026-02-19
DOI
https://doi.org/10.3389/fradi.2026.1701356
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Can artificial intelligence in orthopantomography advance dental diagnostics through automated image analysis?

Claudiu Constantin Manole, Ana Maria Cristina Țâncu, Reinhard Chun Wang Chau, Szabolcs Felszeghy et al.
Frontiers in Radiology
Dental Radiography and Imaging
article

Can artificial intelligence in orthopantomography advance dental diagnostics through automated image analysis?

Claudiu Constantin Manole, Ana Maria Cristina Țâncu, Reinhard Chun Wang Chau, Szabolcs Felszeghy, Radu Ilinca, Dan Adrian Luțescu, Andreea Cristiana Didilescu
article en

Abstract

Artificial Intelligence (AI) is rapidly transforming dental education and clinical practice, as deep learning-especially convolutional neural networks-brings unprecedented accuracy to interpreting orthopantomograms (OPGs). This review illuminates the cutting-edge frontiers of AI-driven dental imaging, tracing how recent breakthroughs are transforming the detection, classification, and segmentation of complex dental anatomy and pathology. Notably, state-of-the-art AI models have reached remarkably high accuracy in tooth identification, while commercial solutions demonstrate promising-though variable-performance in diagnosing complex conditions, such as the adequacy of endodontic procedures. Yet, bringing AI into routine dental care remains fraught with obstacles - demanding vast annotated datasets, coping with population variability, and confronting persistent medicolegal and trust concerns. Growing collaborations between regulators and professional bodies in the United States and European Union are now shaping ethical and legal frameworks to guide its safe use. This narrative review goes beyond summarizing technological progress in AI-driven dental radiology - it uniquely integrates diagnostic breakthroughs with the rapidly evolving regulatory and ethical landscape. By bridging innovation with implementation, it offers educators, practitioners, and learners a forward-looking roadmap that positions AI not as a distant promise, but as a transformative force already reshaping the future of dental diagnostics and training.

Frontiers in RadiologyVol. 6
Carol Davila University of Medicine and Pharmacy (RO), University of Eastern Finland (FI), Avila University (US), Department of Embryology (US), University of Hong Kong (HK)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Dental Radiography and Imaging
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