Literature DB >> 34233515

Current applications and development of artificial intelligence for digital dental radiography.

Ramadhan Hardani Putra1,2, Chiaki Doi1, Nobuhiro Yoda1, Eha Renwi Astuti2, Keiichi Sasaki1.   

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.

Entities:  

Keywords:  Artificial intelligence; deep learning; machine learning; radiography

Mesh:

Year:  2021        PMID: 34233515      PMCID: PMC8693331          DOI: 10.1259/dmfr.20210197

Source DB:  PubMed          Journal:  Dentomaxillofac Radiol        ISSN: 0250-832X            Impact factor:   2.419


  124 in total

1.  Comparison of panoramic and intraoral radiography and pocket probing for the measurement of the marginal bone level.

Authors:  L Akesson; J Håkansson; M Rohlin
Journal:  J Clin Periodontol       Date:  1992-05       Impact factor: 8.728

2.  A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography.

Authors:  Teruhiko Hiraiwa; Yoshiko Ariji; Motoki Fukuda; Yoshitaka Kise; Kazuhiko Nakata; Akitoshi Katsumata; Hiroshi Fujita; Eiichiro Ariji
Journal:  Dentomaxillofac Radiol       Date:  2018-11-09       Impact factor: 2.419

3.  Personal Computer-Based Cephalometric Landmark Detection With Deep Learning, Using Cephalograms on the Internet.

Authors:  Soh Nishimoto; Yohei Sotsuka; Kenichiro Kawai; Hisako Ishise; Masao Kakibuchi
Journal:  J Craniofac Surg       Date:  2019-01       Impact factor: 1.046

4.  Automated measurement of mandibular cortical width on dental panoramic radiographs.

Authors:  Chisako Muramatsu; Takuya Matsumoto; Tatsuro Hayashi; Takeshi Hara; Akitoshi Katsumata; Xiangrong Zhou; Yukihiro Iida; Masato Matsuoka; Takashi Wakisaka; Hiroshi Fujita
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-11-23       Impact factor: 2.924

5.  Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.

Authors:  Jae-Hong Lee; Do-Hyung Kim; Seong-Nyum Jeong; Seong-Ho Choi
Journal:  J Dent       Date:  2018-07-26       Impact factor: 4.379

6.  A computer-aided diagnosis system to screen for osteoporosis using dental panoramic radiographs.

Authors:  T Nakamoto; A Taguchi; M Ohtsuka; Y Suei; M Fujita; M Tsuda; M Sanada; Y Kudo; A Asano; K Tanimoto
Journal:  Dentomaxillofac Radiol       Date:  2008-07       Impact factor: 2.419

7.  The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review.

Authors:  Kuofeng Hung; Carla Montalvao; Ray Tanaka; Taisuke Kawai; Michael M Bornstein
Journal:  Dentomaxillofac Radiol       Date:  2019-08-14       Impact factor: 2.419

8.  Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs.

Authors:  Michael G Endres; Florian Hillen; Marios Salloumis; Ahmad R Sedaghat; Stefan M Niehues; Olivia Quatela; Henning Hanken; Ralf Smeets; Benedicta Beck-Broichsitter; Carsten Rendenbach; Karim Lakhani; Max Heiland; Robert A Gaudin
Journal:  Diagnostics (Basel)       Date:  2020-06-24

9.  Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic Radiographs.

Authors:  Myrthel Vranckx; Adriaan Van Gerven; Holger Willems; Arne Vandemeulebroucke; André Ferreira Leite; Constantinus Politis; Reinhilde Jacobs
Journal:  Int J Environ Res Public Health       Date:  2020-05-25       Impact factor: 3.390

10.  Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm.

Authors:  Jae-Hong Lee; Do-Hyung Kim; Seong-Nyum Jeong; Seong-Ho Choi
Journal:  J Periodontal Implant Sci       Date:  2018-04-30       Impact factor: 2.614

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  5 in total

Review 1.  The Effectiveness of Semi-Automated and Fully Automatic Segmentation for Inferior Alveolar Canal Localization on CBCT Scans: A Systematic Review.

Authors:  Julien Issa; Raphael Olszewski; Marta Dyszkiewicz-Konwińska
Journal:  Int J Environ Res Public Health       Date:  2022-01-04       Impact factor: 3.390

Review 2.  Odontogenic Sinusitis: From Diagnosis to Treatment Possibilities-A Narrative Review of Recent Data.

Authors:  Cristian Martu; Maria-Alexandra Martu; George-Alexandru Maftei; Diana Antonela Diaconu-Popa; Luminita Radulescu
Journal:  Diagnostics (Basel)       Date:  2022-06-30

Review 3.  Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis.

Authors:  Andrej Thurzo; Wanda Urbanová; Bohuslav Novák; Ladislav Czako; Tomáš Siebert; Peter Stano; Simona Mareková; Georgia Fountoulaki; Helena Kosnáčová; Ivan Varga
Journal:  Healthcare (Basel)       Date:  2022-07-08

4.  Transfer learning in a deep convolutional neural network for implant fixture classification: A pilot study.

Authors:  Hak-Sun Kim; Eun-Gyu Ha; Young Hyun Kim; Kug Jin Jeon; Chena Lee; Sang-Sun Han
Journal:  Imaging Sci Dent       Date:  2022-03-15

5.  Comparing the effectiveness of two diagnostic approaches for the interpretation of oral radiographic lesions by dental students.

Authors:  Charmaine Ling Wei Kho; Dian Yi Chow; Jun Ming Wong; Jin Wei Loh; Yu Fan Sim; Mark Joo Seng Gan; Kelvin Weng Chiong Foong; Li Zhen Lim
Journal:  Adv Health Sci Educ Theory Pract       Date:  2022-07-29       Impact factor: 3.629

  5 in total

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