TY - JOUR
T1 - Current applications and development of artificial intelligence for digital dental radiography
AU - Putra, Ramadhan Hardani
AU - Doi, Chiaki
AU - Yoda, Nobuhiro
AU - Astuti, Eha Renwi
AU - Sasaki, Keiichi
N1 - Publisher Copyright:
© 2022 The Authors. Published by the British Institute of Radiology
PY - 2022
Y1 - 2022
N2 - In the last few years, artificial intelligence (AI) research has been rapidly developing and emerging in the field of dental and maxillofacial radiology. Dental radiography, which is commonly used in daily practices, provides an incredibly rich resource for AI development and attracted many researchers to develop its application for various purposes. This study reviewed the applicability of AI for dental radiography from the current studies. Online searches on PubMed and IEEE Xplore databases, up to December 2020, and subsequent manual searches were performed. Then, we categorized the application of AI according to similarity of the following purposes: diagnosis of dental caries, periapical pathologies, and periodontal bone loss; cyst and tumor classification; cephalometric analysis; screening of osteoporosis; tooth recognition and forensic odontology; dental implant system recognition; and image quality enhancement. Current development of AI methodology in each aforementioned application were subsequently discussed. Although most of the reviewed studies demonstrated a great potential of AI application for dental radiography, further development is still needed before implementation in clinical routine due to several challenges and limitations, such as lack of datasets size justification and unstandardized reporting format. Considering the current limitations and challenges, future AI research in dental radiography should follow standardized reporting formats in order to align the research designs and enhance the impact of AI development globally.
AB - In the last few years, artificial intelligence (AI) research has been rapidly developing and emerging in the field of dental and maxillofacial radiology. Dental radiography, which is commonly used in daily practices, provides an incredibly rich resource for AI development and attracted many researchers to develop its application for various purposes. This study reviewed the applicability of AI for dental radiography from the current studies. Online searches on PubMed and IEEE Xplore databases, up to December 2020, and subsequent manual searches were performed. Then, we categorized the application of AI according to similarity of the following purposes: diagnosis of dental caries, periapical pathologies, and periodontal bone loss; cyst and tumor classification; cephalometric analysis; screening of osteoporosis; tooth recognition and forensic odontology; dental implant system recognition; and image quality enhancement. Current development of AI methodology in each aforementioned application were subsequently discussed. Although most of the reviewed studies demonstrated a great potential of AI application for dental radiography, further development is still needed before implementation in clinical routine due to several challenges and limitations, such as lack of datasets size justification and unstandardized reporting format. Considering the current limitations and challenges, future AI research in dental radiography should follow standardized reporting formats in order to align the research designs and enhance the impact of AI development globally.
KW - Artificial intelligence
KW - Deep learning
KW - Machine learning
KW - Radiography
UR - http://www.scopus.com/inward/record.url?scp=85118555335&partnerID=8YFLogxK
U2 - 10.1259/DMFR.20210197
DO - 10.1259/DMFR.20210197
M3 - Review article
C2 - 34233515
AN - SCOPUS:85118555335
SN - 0250-832X
VL - 51
JO - Dentomaxillofacial Radiology
JF - Dentomaxillofacial Radiology
IS - 1
M1 - 20210197
ER -