Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/10451/53513 |
Resumo: | Microwave Imaging (MWI) has the potential to aid breast cancer staging through the detection of Axillary Lymph Nodes (ALNs). This type of system can present some challenges, mainly due to the irregular axillary surface. The optimisation of the artefact removal algorithm to successfully remove the surface reflections is of great importance. In this paper, we propose using Singular Value Decomposition (SVD) as an artefact removal algorithm and study the effect of choosing different subsets of antenna positions for artefact removal on imaging results using experimental signals. We show that different subsets of antenna positions affect the results and in some cases prevent the targets detection. Our analysis allowed us to find an optimal combination of parameters which results in Signal-to-Clutter Ratio higher than 2.77 dB and Location Error lower than 14.9 mm for three different experimental tests. These results are relevant for the development of dedicated algorithms for ALN-MWI application. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signalsartefact removal algorithmaxillary lymph nodesbreast cancermicrowave imagingMicrowave Imaging (MWI) has the potential to aid breast cancer staging through the detection of Axillary Lymph Nodes (ALNs). This type of system can present some challenges, mainly due to the irregular axillary surface. The optimisation of the artefact removal algorithm to successfully remove the surface reflections is of great importance. In this paper, we propose using Singular Value Decomposition (SVD) as an artefact removal algorithm and study the effect of choosing different subsets of antenna positions for artefact removal on imaging results using experimental signals. We show that different subsets of antenna positions affect the results and in some cases prevent the targets detection. Our analysis allowed us to find an optimal combination of parameters which results in Signal-to-Clutter Ratio higher than 2.77 dB and Location Error lower than 14.9 mm for three different experimental tests. These results are relevant for the development of dedicated algorithms for ALN-MWI application.Repositório da Universidade de LisboaGodinho, Daniela M.Felicio, Joao M.Fernandes, Carlos A.Conceicao, Raquel C.2022-06-27T22:23:43Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/53513eng10.23919/EuCAP51087.2021.9411134info: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:RCAAP2023-11-08T16:59:08Zoai:repositorio.ul.pt:10451/53513Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:04:20.688426Repositório 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 |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
title |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
spellingShingle |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals Godinho, Daniela M. artefact removal algorithm axillary lymph nodes breast cancer microwave imaging |
title_short |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
title_full |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
title_fullStr |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
title_full_unstemmed |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
title_sort |
Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals |
author |
Godinho, Daniela M. |
author_facet |
Godinho, Daniela M. Felicio, Joao M. Fernandes, Carlos A. Conceicao, Raquel C. |
author_role |
author |
author2 |
Felicio, Joao M. Fernandes, Carlos A. Conceicao, Raquel C. |
author2_role |
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. Fernandes, Carlos A. Conceicao, Raquel C. |
dc.subject.por.fl_str_mv |
artefact removal algorithm axillary lymph nodes breast cancer microwave imaging |
topic |
artefact removal algorithm axillary lymph nodes breast cancer microwave imaging |
description |
Microwave Imaging (MWI) has the potential to aid breast cancer staging through the detection of Axillary Lymph Nodes (ALNs). This type of system can present some challenges, mainly due to the irregular axillary surface. The optimisation of the artefact removal algorithm to successfully remove the surface reflections is of great importance. In this paper, we propose using Singular Value Decomposition (SVD) as an artefact removal algorithm and study the effect of choosing different subsets of antenna positions for artefact removal on imaging results using experimental signals. We show that different subsets of antenna positions affect the results and in some cases prevent the targets detection. Our analysis allowed us to find an optimal combination of parameters which results in Signal-to-Clutter Ratio higher than 2.77 dB and Location Error lower than 14.9 mm for three different experimental tests. These results are relevant for the development of dedicated algorithms for ALN-MWI application. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z 2022-06-27T22:23:43Z |
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/10451/53513 |
url |
http://hdl.handle.net/10451/53513 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.23919/EuCAP51087.2021.9411134 |
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 |
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1799134594116616192 |