Volume 30, Issue 174, August 2026

Digital Transformation in Dental Radiology: How AI and Modern Technologies are Reshaping Diagnostics – A Literature Review

Jakub Papierz^1♦, Katarzyna Cybulska¹, Julia Banaszczyk¹, Erwin Górski¹, Stanisław Janczarski¹, Gabriela Królczyk⁴, Aleksandra Pietrzyk², Mikołaj Cezary Krajewski³

¹Institute of Dentistry of the Central Clinical Hospital of the Medical University of Łódź, Pomorska 251, 92-213 Łódź, Poland
²Centralna Wojskowa Przychodnia Lekarska CePeLek SPZOZ, 78 Koszykowa Street, 00-911 Warszawa, Poland
³Jessenius Faculty of Medicine, Comenius University Bratislava, Malá Hora 10701/4A, 036 01 Martin, Slovakia
⁴Zespół Przychodni Specjalistycznych Sp. z o.o., 1 Skłodowskiej-Curie Street, 33-100 Tarnów, Poland

^♦Corresponding author
Jakub Papierz, Institute of Dentistry of the Central Clinical Hospital of the Medical University of Łódź, Pomorska 251, 92-213 Łódź, Poland

ABSTRACT

The field of contemporary dentistry is experiencing fast development in its approach to diagnostics, which shifts from two-dimensional imaging to threedimensional imaging techniques, artificial intelligence, and non-ionizing diagnostics. These innovations improve the precision of diagnosis, minimize human factor influence, and decrease radiation dose. The objective of this literature review is to present the latest updates on the influence of artificial intelligence models such as ULDCBCT and GNN, as well as other imaging technologies such as OCT, MRI, and ultrasonography, on dental radiology. Analysis of relevant literature in different fields of medicine reveals the latest trends, the existing problems, and future perspectives. The latest research shows that CNN is as sensitive and specific in diagnosing dental caries, apical lesions, and marginal bone loss as experienced dentists. Furthermore, DL-based metal artifact reduction and automatic 3D tooth segmentation provide much better CBCT image analysis. Ultradose imaging allows volumetric examination with radiation doses close to traditional 2D exams. Nonionizing diagnostic methods can also be used for high-resolution visualization of soft tissue changes and early structural alterations without any risk of radiation exposure. Still, the issues of data bias, black box problems, and legal liability remain. Transformation of dental radiology through digital means provides accurate clinical significance with the use of certified software and practitioners' supervision. Artificial intelligence works well as a “second opinion,” but not as an independent decision maker.

Keywords: dental radiology; artificial intelligence; deep learning; cone-beam computed tomography; digital workflow; explainable AI

Medical Science, 2026, 30, e170ms3952

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Published: 27 August 2026