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Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software

OBJECTIVE: The aim of this study was to compare the measurements performed with digital manual (DM) cephalometric analysis and automatic cephalometric analysis obtained from an online artificial intelligence (AI) platform, according to different sagittal skeletal malocclusions. METHODS: Cephalometri...

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Autores principales: ÇOBAN, Gökhan, ÖZTÜRK, Taner, HASHIMLI, Nizami, YAĞCI, Ahmet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dental Press International 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377318/
https://www.ncbi.nlm.nih.gov/pubmed/35976288
http://dx.doi.org/10.1590/2177-6709.27.4.e222112.oar
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author ÇOBAN, Gökhan
ÖZTÜRK, Taner
HASHIMLI, Nizami
YAĞCI, Ahmet
author_facet ÇOBAN, Gökhan
ÖZTÜRK, Taner
HASHIMLI, Nizami
YAĞCI, Ahmet
author_sort ÇOBAN, Gökhan
collection PubMed
description OBJECTIVE: The aim of this study was to compare the measurements performed with digital manual (DM) cephalometric analysis and automatic cephalometric analysis obtained from an online artificial intelligence (AI) platform, according to different sagittal skeletal malocclusions. METHODS: Cephalometric radiographs of 105 randomly selected individuals (mean age: 17.25 ± 1.87 years) were included in this study. Dolphin Imaging software was used for DM cephalometric analysis, and the WebCeph platform was used for AI-based cephalometric analysis. In total, 10 linear and 12 angular measurements were evaluated. The paired t-test, one-way ANOVA test, and intraclass correlation coefficient tests were used to evaluate the differences between the two methods. The level of statistical significance was set at p< 0.05. RESULTS: Except for SNB, NPog, U1.SN, U1.NA, L1-APog, I/I, and LLE parameters, all other parameters presented significant differences between the two methods (p< 0.05). While there was no difference (p> 0.05) in both SNA and SNB measurements between the two methods in the Class I malocclusion group, there was a difference between both methods in the Class II malocclusion group. Meanwhile, only the SNA in the Class III malocclusion group was different (p< 0.05). The ANB angle differed significantly in all three malocclusion groups. For both methods, all parameters except CoA and CoGn were found to have good correlation. CONCLUSION: Although significant differences were detected in some measurements between the two cephalometric analysis methods, not all differences were clinically significant. The AI-based cephalometric analysis method needs to be developed for more specific malocclusions.
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spelling pubmed-93773182022-08-18 Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software ÇOBAN, Gökhan ÖZTÜRK, Taner HASHIMLI, Nizami YAĞCI, Ahmet Dental Press J Orthod Original Article OBJECTIVE: The aim of this study was to compare the measurements performed with digital manual (DM) cephalometric analysis and automatic cephalometric analysis obtained from an online artificial intelligence (AI) platform, according to different sagittal skeletal malocclusions. METHODS: Cephalometric radiographs of 105 randomly selected individuals (mean age: 17.25 ± 1.87 years) were included in this study. Dolphin Imaging software was used for DM cephalometric analysis, and the WebCeph platform was used for AI-based cephalometric analysis. In total, 10 linear and 12 angular measurements were evaluated. The paired t-test, one-way ANOVA test, and intraclass correlation coefficient tests were used to evaluate the differences between the two methods. The level of statistical significance was set at p< 0.05. RESULTS: Except for SNB, NPog, U1.SN, U1.NA, L1-APog, I/I, and LLE parameters, all other parameters presented significant differences between the two methods (p< 0.05). While there was no difference (p> 0.05) in both SNA and SNB measurements between the two methods in the Class I malocclusion group, there was a difference between both methods in the Class II malocclusion group. Meanwhile, only the SNA in the Class III malocclusion group was different (p< 0.05). The ANB angle differed significantly in all three malocclusion groups. For both methods, all parameters except CoA and CoGn were found to have good correlation. CONCLUSION: Although significant differences were detected in some measurements between the two cephalometric analysis methods, not all differences were clinically significant. The AI-based cephalometric analysis method needs to be developed for more specific malocclusions. Dental Press International 2022-08-15 /pmc/articles/PMC9377318/ /pubmed/35976288 http://dx.doi.org/10.1590/2177-6709.27.4.e222112.oar Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License
spellingShingle Original Article
ÇOBAN, Gökhan
ÖZTÜRK, Taner
HASHIMLI, Nizami
YAĞCI, Ahmet
Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title_full Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title_fullStr Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title_full_unstemmed Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title_short Comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
title_sort comparison between cephalometric measurements using digital manual and web-based artificial intelligence cephalometric tracing software
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377318/
https://www.ncbi.nlm.nih.gov/pubmed/35976288
http://dx.doi.org/10.1590/2177-6709.27.4.e222112.oar
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