Current applications and development of artificial intelligence for digital dental radiography

被引:68
|
作者
Putra, Ramadhan Hardani [1 ,2 ]
Doi, Chiaki [1 ]
Yoda, Nobuhiro [1 ]
Astuti, Eha Renwi [2 ]
Sasaki, Keiichi [1 ]
机构
[1] Tohoku Univ, Grad Sch Dent, Div Adv Prosthet Dent, 4-1 Seiryo Machi, Sendai, Miyagi, Japan
[2] Univ Airlangga, Fac Dent Med, Dept Dentomaxillofacial Radiol, Jl Mayjen Prof Dr Moestopo 47, Surabaya, Indonesia
关键词
Artificial intelligence; machine learning; deep learning; radiography; CONVOLUTIONAL NEURAL-NETWORK; NONINVASIVE DIFFERENTIAL-DIAGNOSIS; COMPUTER-AIDED DIAGNOSIS; METAL ARTIFACT REDUCTION; ACTIVE SHAPE MODELS; X-RAY IMAGES; AUTOMATIC DETECTION; PANORAMIC RADIOGRAPHS; MAXILLOFACIAL CYSTS; PERIAPICAL LESIONS;
D O I
10.1259/dmfr.20210197
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
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.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review
    Hung, Kuofeng
    Montalvao, Carla
    Tanaka, Ray
    Kawai, Taisuke
    Bornstein, Michael M.
    DENTOMAXILLOFACIAL RADIOLOGY, 2020, 49 (01)
  • [2] A brief introduction to concepts and applications of artificial intelligence in dental imaging
    Pauwels, Ruben
    ORAL RADIOLOGY, 2021, 37 (01) : 153 - 160
  • [3] Evaluation of a Novel Veterinary Dental Radiography Artificial Intelligence Software Program
    Nyquist, Markay L.
    Fink, Lisa A.
    Mauldin, Glenna E.
    Coffman, Curt R.
    JOURNAL OF VETERINARY DENTISTRY, 2025, 42 (02) : 118 - 127
  • [4] Current Applications of Artificial Intelligence in Sarcoidosis
    Dana Lew
    Eyal Klang
    Shelly Soffer
    Adam S. Morgenthau
    Lung, 2023, 201 : 445 - 454
  • [5] Current Applications of Artificial Intelligence in Sarcoidosis
    Lew, Dana
    Klang, Eyal
    Soffer, Shelly
    Morgenthau, Adam S.
    LUNG, 2023, 201 (05) : 445 - 454
  • [6] Current and emerging artificial intelligence applications for pediatric abdominal imaging
    Dillman, Jonathan R.
    Somasundaram, Elan
    Brady, Samuel L.
    He, Lili
    PEDIATRIC RADIOLOGY, 2022, 52 (11) : 2139 - 2148
  • [7] Artificial intelligence: A review of current applications in hepatocellular carcinoma imaging
    Pellat, Anna
    Barat, Maxime
    Coriat, Romain
    Soyer, Philippe
    Dohan, Anthony
    DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2023, 104 (01) : 24 - 36
  • [8] Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers
    Wong, Alex Ngai Nick
    He, Zebang
    Leung, Ka Long
    To, Curtis Chun Kit
    Wong, Chun Yin
    Wong, Sze Chuen Cesar
    Yoo, Jung Sun
    Chan, Cheong Kin Ronald
    Chan, Angela Zaneta
    Lacambra, Maribel D.
    Yeung, Martin Ho Yin
    CANCERS, 2022, 14 (15)
  • [9] Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions
    Taylor, Clayton R.
    Monga, Natasha
    Johnson, Candise
    Hawley, Jeffrey R.
    Patel, Mitva
    DIAGNOSTICS, 2023, 13 (12)
  • [10] Artificial intelligence in digital breast pathology: Techniques and applications
    Ibrahim, Asmaa
    Gamble, Paul
    Jaroensri, Ronnachai
    Abdelsamea, Mohammed M.
    Mermel, Craig H.
    Chen, Po-Hsuan Cameron
    Rakha, Emad A.
    BREAST, 2020, 49 : 267 - 273