Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability

Detalhes bibliográficos
Autor(a) principal: Torres, Helena
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/11110/2419
Resumo: Shape analysis of infant’s heads is crucial to diagnose cranial deformities and evaluate head growth. Currently available 3D imaging systems can be used to create 3D head models, promoting the clinical practice for head evaluation. However, manual analysis of 3D shapes is difficult and operator-dependent, causing inaccuracies in the analysis. This study aims to validate an automatic landmark detection method for head shape analysis. The detection results were compared with manual analysis in three levels: (1) distance error of landmarks; (2) accuracy of standard cranial measurements, namely cephalic ratio (CR), cranial vault asymmetry index (CVAI), and overall symmetry ratio (OSR); and (3) accuracy of the final diagnosis of cranial deformities. For each level, the intra- and interobserver variability was also studied by comparing manual landmark settings. High landmark detection accuracy was achieved by the method in 166 head models. A very strong agreement with manual analysis for the cranial measurements was also obtained, with intraclass correlation coefficients of 0.997, 0.961, and 0.771 for the CR, CVAI, and OSR. 91% agreement with manual analysis was achieved in the diagnosis of cranial deformities. Considering its high accuracy and reliability in different evaluation levels, the method showed to be feasible for use in clinical practice for head shape analysis.
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spelling Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variabilityanthropometric measurementshead shape analysisShape analysis of infant’s heads is crucial to diagnose cranial deformities and evaluate head growth. Currently available 3D imaging systems can be used to create 3D head models, promoting the clinical practice for head evaluation. However, manual analysis of 3D shapes is difficult and operator-dependent, causing inaccuracies in the analysis. This study aims to validate an automatic landmark detection method for head shape analysis. The detection results were compared with manual analysis in three levels: (1) distance error of landmarks; (2) accuracy of standard cranial measurements, namely cephalic ratio (CR), cranial vault asymmetry index (CVAI), and overall symmetry ratio (OSR); and (3) accuracy of the final diagnosis of cranial deformities. For each level, the intra- and interobserver variability was also studied by comparing manual landmark settings. High landmark detection accuracy was achieved by the method in 166 head models. A very strong agreement with manual analysis for the cranial measurements was also obtained, with intraclass correlation coefficients of 0.997, 0.961, and 0.771 for the CR, CVAI, and OSR. 91% agreement with manual analysis was achieved in the diagnosis of cranial deformities. Considering its high accuracy and reliability in different evaluation levels, the method showed to be feasible for use in clinical practice for head shape analysis.Annals of Biomedical Engineering2022-07-04T13:23:06Z2022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/11110/2419oai:ciencipca.ipca.pt:11110/2419enghttp://hdl.handle.net/11110/2419metadata only accessinfo:eu-repo/semantics/openAccessTorres, Helenareponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2022-09-05T12:53:44Zoai:ciencipca.ipca.pt:11110/2419Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T10:04:03.934043Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
title Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
spellingShingle Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
Torres, Helena
anthropometric measurements
head shape analysis
title_short Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
title_full Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
title_fullStr Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
title_full_unstemmed Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
title_sort Anthropometric landmarking for diagnosis of cranial deformities: validation of an automatic approach and comparison with intra- and interobserver variability
author Torres, Helena
author_facet Torres, Helena
author_role author
dc.contributor.author.fl_str_mv Torres, Helena
dc.subject.por.fl_str_mv anthropometric measurements
head shape analysis
topic anthropometric measurements
head shape analysis
description Shape analysis of infant’s heads is crucial to diagnose cranial deformities and evaluate head growth. Currently available 3D imaging systems can be used to create 3D head models, promoting the clinical practice for head evaluation. However, manual analysis of 3D shapes is difficult and operator-dependent, causing inaccuracies in the analysis. This study aims to validate an automatic landmark detection method for head shape analysis. The detection results were compared with manual analysis in three levels: (1) distance error of landmarks; (2) accuracy of standard cranial measurements, namely cephalic ratio (CR), cranial vault asymmetry index (CVAI), and overall symmetry ratio (OSR); and (3) accuracy of the final diagnosis of cranial deformities. For each level, the intra- and interobserver variability was also studied by comparing manual landmark settings. High landmark detection accuracy was achieved by the method in 166 head models. A very strong agreement with manual analysis for the cranial measurements was also obtained, with intraclass correlation coefficients of 0.997, 0.961, and 0.771 for the CR, CVAI, and OSR. 91% agreement with manual analysis was achieved in the diagnosis of cranial deformities. Considering its high accuracy and reliability in different evaluation levels, the method showed to be feasible for use in clinical practice for head shape analysis.
publishDate 2022
dc.date.none.fl_str_mv 2022-07-04T13:23:06Z
2022-01-01T00:00:00Z
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dc.publisher.none.fl_str_mv Annals of Biomedical Engineering
publisher.none.fl_str_mv Annals of Biomedical Engineering
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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