Segmentation algorithms for ear image data towards biomechanical studies
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/13969 |
Resumo: | In recent years, the segmentation, i.e. the identification, of ear structures in video-otoscopy, computerised tomography (CT) and magnetic resonance (MR) image data, has gained significant importance in the medical imaging area, particularly those in CT and MR imaging. Segmentation is the fundamental step of any automated technique for supporting the medical diagnosis and, in particular, in biomechanics studies, for building realistic geometric models of ear structures. In this paper, a review of the algorithms used in ear segmentation is presented. The review includes an introduction to the usually biomechanical modelling approaches and also to the common imaging modalities. Afterwards, several segmentation algorithms for ear image data are described, and their specificities and difficulties as well as their advantages and disadvantages are identified and analysed using experimental examples. Finally, the conclusions are presented as well as a discussion about possible trends for future research concerning the ear segmentation. |
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Segmentation algorithms for ear image data towards biomechanical studiesBiomechanical PhenomenaEarFinite Element AnalysisHumansMagnetic Resonance ImagingTomography, X-Ray ComputedAlgorithmsModels, AnatomicIn recent years, the segmentation, i.e. the identification, of ear structures in video-otoscopy, computerised tomography (CT) and magnetic resonance (MR) image data, has gained significant importance in the medical imaging area, particularly those in CT and MR imaging. Segmentation is the fundamental step of any automated technique for supporting the medical diagnosis and, in particular, in biomechanics studies, for building realistic geometric models of ear structures. In this paper, a review of the algorithms used in ear segmentation is presented. The review includes an introduction to the usually biomechanical modelling approaches and also to the common imaging modalities. Afterwards, several segmentation algorithms for ear image data are described, and their specificities and difficulties as well as their advantages and disadvantages are identified and analysed using experimental examples. Finally, the conclusions are presented as well as a discussion about possible trends for future research concerning the ear segmentation.Taylor & FrancisRepositório Científico do Instituto Politécnico do PortoFerreira, AnaGentil, FernandaTavares, João Manuel R. S.2019-06-12T16:09:13Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/13969engFerreira, A., Gentil, F., & Tavares, J. M. R. S. (2014). Segmentation algorithms for ear image data towards biomechanical studies. Computer Methods in Biomechanics and Biomedical Engineering, 17(8), 888–904. https://doi.org/10.1080/10255842.2012.7237001025-584210.1080/10255842.2012.723700info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-20T01:53:23Zoai:recipp.ipp.pt:10400.22/13969Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:33:49.358051Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Segmentation algorithms for ear image data towards biomechanical studies |
title |
Segmentation algorithms for ear image data towards biomechanical studies |
spellingShingle |
Segmentation algorithms for ear image data towards biomechanical studies Ferreira, Ana Biomechanical Phenomena Ear Finite Element Analysis Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Algorithms Models, Anatomic |
title_short |
Segmentation algorithms for ear image data towards biomechanical studies |
title_full |
Segmentation algorithms for ear image data towards biomechanical studies |
title_fullStr |
Segmentation algorithms for ear image data towards biomechanical studies |
title_full_unstemmed |
Segmentation algorithms for ear image data towards biomechanical studies |
title_sort |
Segmentation algorithms for ear image data towards biomechanical studies |
author |
Ferreira, Ana |
author_facet |
Ferreira, Ana Gentil, Fernanda Tavares, João Manuel R. S. |
author_role |
author |
author2 |
Gentil, Fernanda Tavares, João Manuel R. S. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Ferreira, Ana Gentil, Fernanda Tavares, João Manuel R. S. |
dc.subject.por.fl_str_mv |
Biomechanical Phenomena Ear Finite Element Analysis Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Algorithms Models, Anatomic |
topic |
Biomechanical Phenomena Ear Finite Element Analysis Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Algorithms Models, Anatomic |
description |
In recent years, the segmentation, i.e. the identification, of ear structures in video-otoscopy, computerised tomography (CT) and magnetic resonance (MR) image data, has gained significant importance in the medical imaging area, particularly those in CT and MR imaging. Segmentation is the fundamental step of any automated technique for supporting the medical diagnosis and, in particular, in biomechanics studies, for building realistic geometric models of ear structures. In this paper, a review of the algorithms used in ear segmentation is presented. The review includes an introduction to the usually biomechanical modelling approaches and also to the common imaging modalities. Afterwards, several segmentation algorithms for ear image data are described, and their specificities and difficulties as well as their advantages and disadvantages are identified and analysed using experimental examples. Finally, the conclusions are presented as well as a discussion about possible trends for future research concerning the ear segmentation. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014 2014-01-01T00:00:00Z 2019-06-12T16:09:13Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/13969 |
url |
http://hdl.handle.net/10400.22/13969 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ferreira, A., Gentil, F., & Tavares, J. M. R. S. (2014). Segmentation algorithms for ear image data towards biomechanical studies. Computer Methods in Biomechanics and Biomedical Engineering, 17(8), 888–904. https://doi.org/10.1080/10255842.2012.723700 1025-5842 10.1080/10255842.2012.723700 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131430401343488 |