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Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting

Cephalometric analysis is a standard tool for assessment and prediction of craniofacial growth, orthodontic diagnosis, and oral-maxillofacial treatment planning. The aim of this study is to develop a fully automatic system of cephalometric analysis, including cephalometric landmark detection and cep...

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Detalles Bibliográficos
Autores principales: Wang, Shumeng, Li, Huiqi, Li, Jiazhi, Zhang, Yanjun, Zou, Bingshuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276415/
https://www.ncbi.nlm.nih.gov/pubmed/30581546
http://dx.doi.org/10.1155/2018/1797502
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author Wang, Shumeng
Li, Huiqi
Li, Jiazhi
Zhang, Yanjun
Zou, Bingshuang
author_facet Wang, Shumeng
Li, Huiqi
Li, Jiazhi
Zhang, Yanjun
Zou, Bingshuang
author_sort Wang, Shumeng
collection PubMed
description Cephalometric analysis is a standard tool for assessment and prediction of craniofacial growth, orthodontic diagnosis, and oral-maxillofacial treatment planning. The aim of this study is to develop a fully automatic system of cephalometric analysis, including cephalometric landmark detection and cephalometric measurement in lateral cephalograms for malformation classification and assessment of dental growth and soft tissue profile. First, a novel method of multiscale decision tree regression voting using SIFT-based patch features is proposed for automatic landmark detection in lateral cephalometric radiographs. Then, some clinical measurements are calculated by using the detected landmark positions. Finally, two databases are tested in this study: one is the benchmark database of 300 lateral cephalograms from 2015 ISBI Challenge, and the other is our own database of 165 lateral cephalograms. Experimental results show that the performance of our proposed method is satisfactory for landmark detection and measurement analysis in lateral cephalograms.
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spelling pubmed-62764152018-12-23 Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting Wang, Shumeng Li, Huiqi Li, Jiazhi Zhang, Yanjun Zou, Bingshuang J Healthc Eng Research Article Cephalometric analysis is a standard tool for assessment and prediction of craniofacial growth, orthodontic diagnosis, and oral-maxillofacial treatment planning. The aim of this study is to develop a fully automatic system of cephalometric analysis, including cephalometric landmark detection and cephalometric measurement in lateral cephalograms for malformation classification and assessment of dental growth and soft tissue profile. First, a novel method of multiscale decision tree regression voting using SIFT-based patch features is proposed for automatic landmark detection in lateral cephalometric radiographs. Then, some clinical measurements are calculated by using the detected landmark positions. Finally, two databases are tested in this study: one is the benchmark database of 300 lateral cephalograms from 2015 ISBI Challenge, and the other is our own database of 165 lateral cephalograms. Experimental results show that the performance of our proposed method is satisfactory for landmark detection and measurement analysis in lateral cephalograms. Hindawi 2018-11-19 /pmc/articles/PMC6276415/ /pubmed/30581546 http://dx.doi.org/10.1155/2018/1797502 Text en Copyright © 2018 Shumeng Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Shumeng
Li, Huiqi
Li, Jiazhi
Zhang, Yanjun
Zou, Bingshuang
Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title_full Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title_fullStr Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title_full_unstemmed Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title_short Automatic Analysis of Lateral Cephalograms Based on Multiresolution Decision Tree Regression Voting
title_sort automatic analysis of lateral cephalograms based on multiresolution decision tree regression voting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276415/
https://www.ncbi.nlm.nih.gov/pubmed/30581546
http://dx.doi.org/10.1155/2018/1797502
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