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Segmentation algorithms for ear image data towards biomechanical studies

2014Journal article Open access
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dc.contributor.authorFerreira, Ana
dc.contributor.authorGentil, Fernanda
dc.contributor.authorTavares, João Manuel R. S.
dc.date.accessioned2019-06-12T16:09:13Z
dc.date.available2019-06-12T16:09:13Z
dc.date.issued2014
dc.description.abstractIn 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFerreira, 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
dc.identifier.doi10.1080/10255842.2012.723700pt_PT
dc.identifier.issn1025-5842
dc.identifier.urihttp://hdl.handle.net/10400.22/13969
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relationBio-computational study of tinnitus
dc.relation.publisherversionhttps://www.tandfonline.com/doi/full/10.1080/10255842.2012.723700pt_PT
dc.subjectBiomechanical Phenomenapt_PT
dc.subjectEarpt_PT
dc.subjectFinite Element Analysispt_PT
dc.subjectHumanspt_PT
dc.subjectMagnetic Resonance Imagingpt_PT
dc.subjectTomography, X-Ray Computedpt_PT
dc.subjectAlgorithmspt_PT
dc.subjectModels, Anatomicpt_PT
dc.titleSegmentation algorithms for ear image data towards biomechanical studiespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleBio-computational study of tinnitus
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/PTDC%2FEEA-CRO%2F103320%2F2008/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FSAU-BEB%2F104992%2F2008/PT
oaire.citation.endPage904pt_PT
oaire.citation.issue8pt_PT
oaire.citation.startPage888pt_PT
oaire.citation.titleComputer Methods in Biomechanics and Biomedical Engineeringpt_PT
oaire.citation.volume17pt_PT
oaire.fundingStream5876-PPCDTI
oaire.fundingStream3599-PPCDT
person.familyNameGentil Costa
person.givenNameMaria Fernanda
person.identifier.ciencia-id8A1B-AB35-07A4
person.identifier.orcid0000-0002-6521-3475
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationa322f388-4cfc-4430-ae6f-ba10bf53758f
relation.isAuthorOfPublication.latestForDiscoverya322f388-4cfc-4430-ae6f-ba10bf53758f
relation.isProjectOfPublication575e3b2e-a933-4033-bf42-d3578968a558
relation.isProjectOfPublicationb54f89f7-c594-4a29-8c2d-7c49ed71e1e1
relation.isProjectOfPublication.latestForDiscoveryb54f89f7-c594-4a29-8c2d-7c49ed71e1e1

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