Cargando…

Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms

Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to the classificat...

Descripción completa

Detalles Bibliográficos
Autores principales: Lindner, Claudia, Wang, Ching-Wei, Huang, Cheng-Ta, Li, Chung-Hsing, Chang, Sheng-Wei, Cootes, Tim F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5028843/
https://www.ncbi.nlm.nih.gov/pubmed/27645567
http://dx.doi.org/10.1038/srep33581
_version_ 1782454409990504448
author Lindner, Claudia
Wang, Ching-Wei
Huang, Cheng-Ta
Li, Chung-Hsing
Chang, Sheng-Wei
Cootes, Tim F.
author_facet Lindner, Claudia
Wang, Ching-Wei
Huang, Cheng-Ta
Li, Chung-Hsing
Chang, Sheng-Wei
Cootes, Tim F.
author_sort Lindner, Claudia
collection PubMed
description Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to the classification of skeletal malformations. Digital cephalograms of 400 subjects (age range: 7–76 years) were available. All cephalograms had been manually traced by two experienced orthodontists with 19 cephalometric landmarks, and eight clinical parameters had been calculated for each subject. A FALA system to locate the 19 landmarks in lateral cephalograms was developed. The system was evaluated via comparison to the manual tracings, and the automatically located landmarks were used for classification of the clinical parameters. The system achieved an average point-to-point error of 1.2 mm, and 84.7% of landmarks were located within the clinically accepted precision range of 2.0 mm. The automatic landmark localisation performance was within the inter-observer variability between two clinical experts. The automatic classification achieved an average classification accuracy of 83.4% which was comparable to an experienced orthodontist. The FALA system rapidly and accurately locates and analyses cephalometric landmarks in lateral cephalograms, and has the potential to significantly improve the clinical work flow in orthodontic treatment.
format Online
Article
Text
id pubmed-5028843
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-50288432016-09-26 Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms Lindner, Claudia Wang, Ching-Wei Huang, Cheng-Ta Li, Chung-Hsing Chang, Sheng-Wei Cootes, Tim F. Sci Rep Article Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to the classification of skeletal malformations. Digital cephalograms of 400 subjects (age range: 7–76 years) were available. All cephalograms had been manually traced by two experienced orthodontists with 19 cephalometric landmarks, and eight clinical parameters had been calculated for each subject. A FALA system to locate the 19 landmarks in lateral cephalograms was developed. The system was evaluated via comparison to the manual tracings, and the automatically located landmarks were used for classification of the clinical parameters. The system achieved an average point-to-point error of 1.2 mm, and 84.7% of landmarks were located within the clinically accepted precision range of 2.0 mm. The automatic landmark localisation performance was within the inter-observer variability between two clinical experts. The automatic classification achieved an average classification accuracy of 83.4% which was comparable to an experienced orthodontist. The FALA system rapidly and accurately locates and analyses cephalometric landmarks in lateral cephalograms, and has the potential to significantly improve the clinical work flow in orthodontic treatment. Nature Publishing Group 2016-09-20 /pmc/articles/PMC5028843/ /pubmed/27645567 http://dx.doi.org/10.1038/srep33581 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Lindner, Claudia
Wang, Ching-Wei
Huang, Cheng-Ta
Li, Chung-Hsing
Chang, Sheng-Wei
Cootes, Tim F.
Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title_full Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title_fullStr Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title_full_unstemmed Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title_short Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
title_sort fully automatic system for accurate localisation and analysis of cephalometric landmarks in lateral cephalograms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5028843/
https://www.ncbi.nlm.nih.gov/pubmed/27645567
http://dx.doi.org/10.1038/srep33581
work_keys_str_mv AT lindnerclaudia fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms
AT wangchingwei fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms
AT huangchengta fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms
AT lichunghsing fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms
AT changshengwei fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms
AT cootestimf fullyautomaticsystemforaccuratelocalisationandanalysisofcephalometriclandmarksinlateralcephalograms