Literature DB >> 11094367

Accuracy of computerized automatic identification of cephalometric landmarks.

J K Liu1, Y T Chen, K S Cheng.   

Abstract

Computerized cephalometric analysis can include both landmark identification and determination of linear or angular measurements. Although its use is time saving compared with a manual method, the accuracy of automatic landmark identification remains unclear. The purpose of this study was to evaluate the accuracy of a computerized automatic landmark identification system that used an edge-based technique. The technique divides the scanned cephalogram into 8 rectangular subimage regions. After the resolution of these subimages is reduced, the edges are detected and the landmarks are located automatically. Thirteen landmarks were selected for assessment on a set of 10 test cephalograms. The results showed that the errors between manual and computerized identification for landmarks were not significantly different (P > .05) for 5 of 13 landmarks: sella, nasion, porion, orbitale, and gnathion. These results suggest that the accuracy of computerized automatic identification is acceptable for certain landmarks only. Further studies to improve the accuracy of computerized automated landmark identification are needed.

Mesh:

Year:  2000        PMID: 11094367     DOI: 10.1067/mod.2000.110168

Source DB:  PubMed          Journal:  Am J Orthod Dentofacial Orthop        ISSN: 0889-5406            Impact factor:   2.650


  13 in total

1.  Influence of a programme of professional calibration in the variability of landmark identification using cone beam computed tomography-synthesized and conventional radiographic cephalograms.

Authors:  E L Delamare; G S Liedke; M B Vizzotto; H L D da Silveira; J L D Ribeiro; H E D Silveira
Journal:  Dentomaxillofac Radiol       Date:  2010-10       Impact factor: 2.419

2.  Reproducibility and speed of landmarking process in cephalometric analysis using two input devices: mouse-driven cursor versus pen.

Authors:  Alice Cutrera; Ersilia Barbato; Francesco Maiorana; Daniela Giordano; Rosalia Leonardi
Journal:  Ann Stomatol (Roma)       Date:  2015-07-28

3.  Accuracy and repeatability of computer aided cervical vertebra landmarking in cephalogram.

Authors:  Lili Chen; Zhicong Lan; Xiangyang Xu; Jiuxiang Lin; Huaifei Hu
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2012-01-27

4.  Artificial intelligence in orthodontics : Evaluation of a fully automated cephalometric analysis using a customized convolutional neural network.

Authors:  Felix Kunz; Angelika Stellzig-Eisenhauer; Florian Zeman; Julian Boldt
Journal:  J Orofac Orthop       Date:  2019-12-18       Impact factor: 1.938

5.  Accuracy of computerized automatic identification of cephalometric landmarks by a designed software.

Authors:  Sh Shahidi; S Shahidi; M Oshagh; F Gozin; P Salehi; S M Danaei
Journal:  Dentomaxillofac Radiol       Date:  2013       Impact factor: 2.419

6.  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

7.  Reliability Assessment of Orthodontic Apps for Cephalometrics.

Authors:  Sertaç Aksakallı; Hilal Yılancı; Erhan Görükmez; Sabri İlhan Ramoğlu
Journal:  Turk J Orthod       Date:  2016-12-01

8.  Reproducibility of measurements in tablet-assisted, PC-aided, and manual cephalometric analysis.

Authors:  Cecilia Goracci; Marco Ferrari
Journal:  Angle Orthod       Date:  2013-10-25       Impact factor: 2.079

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

Authors:  Ramadhan Hardani Putra; Chiaki Doi; Nobuhiro Yoda; Eha Renwi Astuti; Keiichi Sasaki
Journal:  Dentomaxillofac Radiol       Date:  2021-07-08       Impact factor: 2.419

10.  An evaluation of cellular neural networks for the automatic identification of cephalometric landmarks on digital images.

Authors:  Rosalia Leonardi; Daniela Giordano; Francesco Maiorana
Journal:  J Biomed Biotechnol       Date:  2009-09-10
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