Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom

Detalhes bibliográficos
Autor(a) principal: Savazzi, M.
Data de Publicação: 2021
Outros Autores: Costa, J. R., Fernandes, C. A., Felício, J. M., Conceição, R. C.
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/25469
Resumo: We numerically assess the potential of microwave imaging (MWI) for the detection of axillary lymph nodes (ALNs). The proposed MWI system is radar-based, in which a broad-band signal (2-6 GHz) is transmitted by a single probing antenna to scan the axillary region. The full-wave simulations include a realistic phantom of the underarm region which was previously developed by the authors. The phantom includes the main tissues of the axillary region and the corresponding dielectric properties. We show that the proposed system can successfully detect an ALN embedded in a homogeneous fatty medium. Additionally, we show that despite the strong reflection of the muscle - caused by the high dielectric contrast between fat and muscle - we are able to distinguish an ALN from the background. To the best of our knowledge, this is the first study in literature which employs an anatomically realistic phantom to study ALN MWI.
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spelling Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantomAxillary lymph node imagingBroadband antennaMicrowave imagingNumerical assessmentRemote sensingWe numerically assess the potential of microwave imaging (MWI) for the detection of axillary lymph nodes (ALNs). The proposed MWI system is radar-based, in which a broad-band signal (2-6 GHz) is transmitted by a single probing antenna to scan the axillary region. The full-wave simulations include a realistic phantom of the underarm region which was previously developed by the authors. The phantom includes the main tissues of the axillary region and the corresponding dielectric properties. We show that the proposed system can successfully detect an ALN embedded in a homogeneous fatty medium. Additionally, we show that despite the strong reflection of the muscle - caused by the high dielectric contrast between fat and muscle - we are able to distinguish an ALN from the background. To the best of our knowledge, this is the first study in literature which employs an anatomically realistic phantom to study ALN MWI.IEEE2022-05-19T15:11:01Z2021-01-01T00:00:00Z20212022-05-19T16:09:53Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10071/25469eng978-88-31299-02-210.23919/EuCAP51087.2021.9410925Savazzi, M.Costa, J. R.Fernandes, C. A.Felício, J. M.Conceição, R. C.info: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:RCAAP2024-07-07T03:00:18Zoai:repositorio.iscte-iul.pt:10071/25469Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T03:00:18Repositório 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 Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
title Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
spellingShingle Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
Savazzi, M.
Axillary lymph node imaging
Broadband antenna
Microwave imaging
Numerical assessment
Remote sensing
title_short Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
title_full Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
title_fullStr Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
title_full_unstemmed Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
title_sort Numerical assessment of microwave imaging for axillary lymph nodes screening using anthropomorphic phantom
author Savazzi, M.
author_facet Savazzi, M.
Costa, J. R.
Fernandes, C. A.
Felício, J. M.
Conceição, R. C.
author_role author
author2 Costa, J. R.
Fernandes, C. A.
Felício, J. M.
Conceição, R. C.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Savazzi, M.
Costa, J. R.
Fernandes, C. A.
Felício, J. M.
Conceição, R. C.
dc.subject.por.fl_str_mv Axillary lymph node imaging
Broadband antenna
Microwave imaging
Numerical assessment
Remote sensing
topic Axillary lymph node imaging
Broadband antenna
Microwave imaging
Numerical assessment
Remote sensing
description We numerically assess the potential of microwave imaging (MWI) for the detection of axillary lymph nodes (ALNs). The proposed MWI system is radar-based, in which a broad-band signal (2-6 GHz) is transmitted by a single probing antenna to scan the axillary region. The full-wave simulations include a realistic phantom of the underarm region which was previously developed by the authors. The phantom includes the main tissues of the axillary region and the corresponding dielectric properties. We show that the proposed system can successfully detect an ALN embedded in a homogeneous fatty medium. Additionally, we show that despite the strong reflection of the muscle - caused by the high dielectric contrast between fat and muscle - we are able to distinguish an ALN from the background. To the best of our knowledge, this is the first study in literature which employs an anatomically realistic phantom to study ALN MWI.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01T00:00:00Z
2021
2022-05-19T15:11:01Z
2022-05-19T16:09:53Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/25469
url http://hdl.handle.net/10071/25469
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-88-31299-02-2
10.23919/EuCAP51087.2021.9410925
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 IEEE
publisher.none.fl_str_mv IEEE
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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