TY - JOUR
T1 - Surveying the landscape of diagnostic imaging in dentistry's future
T2 - Four emerging technologies with promise
AU - Tyndall, Donald A.
AU - Price, Jeffery B.
AU - Gaalaas, Laurence
AU - Spin-Neto, Rubens
N1 - Publisher Copyright:
© 2024 American Dental Association
PY - 2024
Y1 - 2024
N2 - Background: Advances in digital radiography for both intraoral and panoramic imaging and cone-beam computed tomography have led the way to an increase in diagnostic capabilities for the dental care profession. In this article, the authors provide information on 4 emerging technologies with promise. Types of Studies Reviewed: The authors feature the following: artificial intelligence in the form of deep learning using convolutional neural networks, dental magnetic resonance imaging, stationary intraoral tomosynthesis, and second-generation cone-beam computed tomography sources based on carbon nanotube technology and multispectral imaging. The authors review and summarize articles featuring these technologies. Results: The history and background of these emerging technologies are previewed along with their development and potential impact on the practice of dental diagnostic imaging. The authors conclude that these emerging technologies have the potential to have a substantial influence on the practice of dentistry as these systems mature. The degree of influence most likely will vary, with artificial intelligence being the most influential of the 4. Conclusions and Practical Implications: The readers are informed about these emerging technologies and the potential effects on their practice going forward, giving them information on which to base decisions on adopting 1 or more of these technologies. The 4 technologies reviewed in this article have the potential to improve imaging diagnostics in dentistry thereby leading to better patient care and heightened professional satisfaction.
AB - Background: Advances in digital radiography for both intraoral and panoramic imaging and cone-beam computed tomography have led the way to an increase in diagnostic capabilities for the dental care profession. In this article, the authors provide information on 4 emerging technologies with promise. Types of Studies Reviewed: The authors feature the following: artificial intelligence in the form of deep learning using convolutional neural networks, dental magnetic resonance imaging, stationary intraoral tomosynthesis, and second-generation cone-beam computed tomography sources based on carbon nanotube technology and multispectral imaging. The authors review and summarize articles featuring these technologies. Results: The history and background of these emerging technologies are previewed along with their development and potential impact on the practice of dental diagnostic imaging. The authors conclude that these emerging technologies have the potential to have a substantial influence on the practice of dentistry as these systems mature. The degree of influence most likely will vary, with artificial intelligence being the most influential of the 4. Conclusions and Practical Implications: The readers are informed about these emerging technologies and the potential effects on their practice going forward, giving them information on which to base decisions on adopting 1 or more of these technologies. The 4 technologies reviewed in this article have the potential to improve imaging diagnostics in dentistry thereby leading to better patient care and heightened professional satisfaction.
KW - artificial intelligence
KW - Cone-beam CT improvements
KW - dental MRI
KW - stationary intraoral tomosynthesis
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U2 - 10.1016/j.adaj.2024.01.005
DO - 10.1016/j.adaj.2024.01.005
M3 - Review article
C2 - 38520421
AN - SCOPUS:85188692597
SN - 0002-8177
JO - Journal of the American Dental Association
JF - Journal of the American Dental Association
ER -