Current applications and development of artificial intelligence for digital dental radiography

Ramadhan Hardani Putra, Chiaki Doi, Nobuhiro Yoda, Eha Renwi Astuti, Keiichi Sasaki

Research output: Contribution to journalReview articlepeer-review

11 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number20210197
JournalDentomaxillofacial Radiology
Volume51
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Artificial intelligence
  • Deep learning
  • Machine learning
  • Radiography

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