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Preliminary development of anatomically realistic breast tumor models for microwave imaging

2022Artigo científico Acesso aberto
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dc.contributor.authorPelicano, Ana Catarina
dc.contributor.authorAraujo, Nuno A. M.
dc.contributor.authorConceicao, Raquel C.
dc.date.accessioned2024-12-20T18:34:05Z
dc.date.available2024-12-20T18:34:05Z
dc.date.issued2022
dc.description.abstractIn this work, we present a preliminary study of three classifiers – Linear Discriminant Analysis (LDA), Support Vector Machines (SVMs) and k-Nearest Neighbors (kNN) – to differentiate between malignant and benign tumors extracted from Magnetic Resonance (MR) images, based on their morphological features. The dataset in this study comprises 24 tumors: 12 malignant and 12 benign. Twelve morphological features were initially considered for tumor classification. The Mann-Whitney test was employed for feature selection, and the performance of the classifiers was evaluated with accuracy, sensitivity, specificity, F1-score and Matthew’s Correlation Coefficient (MCC) metrics. kNN (with k=6 and Chebyshev distance) outperformed the other classifiers with an accuracy, sensitivity, and specificity of 87.5%, 83.3% and 91.7%, respectively.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.23919/EuCAP53622.2022.9769591pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/96650
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT): UI/BD/150762/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT): UIDB/00645/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia (FCT): PTDC/FISMAC/28146/2017 (LISBOA-01-0145-FEDER-028146)pt_PT
dc.relationFundação para a Ciência e Tecnologia: UIDB/00618/2020pt_PT
dc.relationFundação para a Ciência e Tecnologia: UIDP/00618/2020pt_PT
dc.subjectbreast cancerpt_PT
dc.subjecttumor classificationpt_PT
dc.subjectmorphological featurespt_PT
dc.titlePreliminary development of anatomically realistic breast tumor models for microwave imagingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceMadrid, Espanhapt_PT
oaire.citation.endPage4pt_PT
oaire.citation.startPage1pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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