Segmentation of the bone structure from MRI Knee Joint - A use case

Bibliographic Details
Main Author: Silva, Vasco
Publication Date: 2024
Other Authors: Vilaça, Adélio, Veloso, Rita, Coelho, Luís, Magalhães, Renato
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.22/30050
Summary: Manual and automatic segmentation techniques can be applied to DICOM medical images from magnetic resonance imaging (MRI) to extract certain structures, such as soft tissues, but the precise extraction of bone structures may be limited. This study studies these types of knee bone tissue segmentation on MRI, to avoid the need to resort to computed tomography (CT) for obtaining the desired bone structures. Manual segmentation was done using ITK-Snap and automatic segmentation algorithms were applied in Python and the ITK library. As a result of this study, it was found that although manual segmentation allowed for precise and consistent identification of the femur, tibia, fibula, and patella, the automatic segmentation needed to achieve the same level of accuracy.
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spelling Segmentation of the bone structure from MRI Knee Joint - A use caseMagnetic resonance imaging (MRI)DICOMManual and automatic segmentation techniques can be applied to DICOM medical images from magnetic resonance imaging (MRI) to extract certain structures, such as soft tissues, but the precise extraction of bone structures may be limited. This study studies these types of knee bone tissue segmentation on MRI, to avoid the need to resort to computed tomography (CT) for obtaining the desired bone structures. Manual segmentation was done using ITK-Snap and automatic segmentation algorithms were applied in Python and the ITK library. As a result of this study, it was found that although manual segmentation allowed for precise and consistent identification of the femur, tibia, fibula, and patella, the automatic segmentation needed to achieve the same level of accuracy.Universidade da CoruñaREPOSITÓRIO P.PORTOSilva, VascoVilaça, AdélioVeloso, RitaCoelho, LuísMagalhães, RenatoMagalhães, Renato2025-05-08T16:45:09Z2024-102024-10-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.22/30050eng10.17979/spudc.9788497498913.12info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-05-14T01:47:58Zoai:recipp.ipp.pt:10400.22/30050Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T07:14:52.961388Repositórios 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 Segmentation of the bone structure from MRI Knee Joint - A use case
title Segmentation of the bone structure from MRI Knee Joint - A use case
spellingShingle Segmentation of the bone structure from MRI Knee Joint - A use case
Silva, Vasco
Magnetic resonance imaging (MRI)
DICOM
title_short Segmentation of the bone structure from MRI Knee Joint - A use case
title_full Segmentation of the bone structure from MRI Knee Joint - A use case
title_fullStr Segmentation of the bone structure from MRI Knee Joint - A use case
title_full_unstemmed Segmentation of the bone structure from MRI Knee Joint - A use case
title_sort Segmentation of the bone structure from MRI Knee Joint - A use case
author Silva, Vasco
author_facet Silva, Vasco
Vilaça, Adélio
Veloso, Rita
Coelho, Luís
Magalhães, Renato
author_role author
author2 Vilaça, Adélio
Veloso, Rita
Coelho, Luís
Magalhães, Renato
author2_role author
author
author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Silva, Vasco
Vilaça, Adélio
Veloso, Rita
Coelho, Luís
Magalhães, Renato
Magalhães, Renato
dc.subject.por.fl_str_mv Magnetic resonance imaging (MRI)
DICOM
topic Magnetic resonance imaging (MRI)
DICOM
description Manual and automatic segmentation techniques can be applied to DICOM medical images from magnetic resonance imaging (MRI) to extract certain structures, such as soft tissues, but the precise extraction of bone structures may be limited. This study studies these types of knee bone tissue segmentation on MRI, to avoid the need to resort to computed tomography (CT) for obtaining the desired bone structures. Manual segmentation was done using ITK-Snap and automatic segmentation algorithms were applied in Python and the ITK library. As a result of this study, it was found that although manual segmentation allowed for precise and consistent identification of the femur, tibia, fibula, and patella, the automatic segmentation needed to achieve the same level of accuracy.
publishDate 2024
dc.date.none.fl_str_mv 2024-10
2024-10-01T00:00:00Z
2025-05-08T16:45:09Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/30050
url http://hdl.handle.net/10400.22/30050
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.17979/spudc.9788497498913.12
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade da Coruña
publisher.none.fl_str_mv Universidade da Coruña
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instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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