Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device
Autor(a) principal: | |
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Data de Publicação: | 2020 |
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/10451/53518 |
Resumo: | Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging DeviceAxillary Lymph NodesBreast CancerDielectric PropertiesMRI SegmentationMicrowave ImagingMicrowave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices.The authors would like to acknowledge the study with ref. CES/44/2019/ME in Hospital da Luz Lisboa (19/09/2019).Repositório da Universidade de LisboaGodinho, Daniela M.Felicio, Joao M.Castela, TiagoSilva, Nuno A.Orvalho, M. LurdesFernandes, Carlos A.Conceicao, Raquel C.2022-06-28T10:09:40Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/53518eng10.23919/EuCAP48036.2020.9135980info: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:RCAAP2024-11-20T18:15:12Zoai:repositorio.ul.pt:10451/53518Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-20T18:15:12Repositório 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 |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
title |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
spellingShingle |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device Godinho, Daniela M. Axillary Lymph Nodes Breast Cancer Dielectric Properties MRI Segmentation Microwave Imaging |
title_short |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
title_full |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
title_fullStr |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
title_full_unstemmed |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
title_sort |
Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device |
author |
Godinho, Daniela M. |
author_facet |
Godinho, Daniela M. Felicio, Joao M. Castela, Tiago Silva, Nuno A. Orvalho, M. Lurdes Fernandes, Carlos A. Conceicao, Raquel C. |
author_role |
author |
author2 |
Felicio, Joao M. Castela, Tiago Silva, Nuno A. Orvalho, M. Lurdes Fernandes, Carlos A. Conceicao, Raquel C. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Godinho, Daniela M. Felicio, Joao M. Castela, Tiago Silva, Nuno A. Orvalho, M. Lurdes Fernandes, Carlos A. Conceicao, Raquel C. |
dc.subject.por.fl_str_mv |
Axillary Lymph Nodes Breast Cancer Dielectric Properties MRI Segmentation Microwave Imaging |
topic |
Axillary Lymph Nodes Breast Cancer Dielectric Properties MRI Segmentation Microwave Imaging |
description |
Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z 2022-06-28T10:09:40Z |
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/10451/53518 |
url |
http://hdl.handle.net/10451/53518 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.23919/EuCAP48036.2020.9135980 |
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.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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
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1817549193267380224 |