Optimisation of Artefact Removal Algorithm for Microwave Imaging of the Axillary Region Using Experimental Prototype Signals

Bibliographic Details
Main Author: Godinho, Daniela M.
Publication Date: 2021
Other Authors: Felicio, Joao M., Fernandes, Carlos A., Conceicao, Raquel C.
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10451/53513
Summary: 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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spelling 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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T14:46:42Zoai:repositorio.ulisboa.pt:10451/53513Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:24:19.418075Repositórios 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 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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str 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
repository.mail.fl_str_mv info@rcaap.pt
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