Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/337167
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampCosta, Eduardo Tavares-
dc.typeArtigopt_BR
dc.titleJoint adaptive beamforming to enhance noise suppression for medical ultrasound imagingpt_BR
dc.contributor.authorZimbico, Acacio J.-
dc.contributor.authorGranado, Diogo W.-
dc.contributor.authorSchneider, Fabio K.-
dc.contributor.authorMaia, Joaquim M.-
dc.contributor.authorAssef, Amauri A.-
dc.contributor.authorS. Junior, Nivaldo-
dc.contributor.authorCosta, Eduardo T.-
dc.subjectUltrassompt_BR
dc.subject.otherlanguageUltrasonicspt_BR
dc.description.abstractIn this work we suggest a combination of two beamformers (BFs) to improve the array noise-suppression abilities using the moments of the eigenvalues (EV) of the data covariance matrix (CM). The eigenspace minimum variance (EMV) BF suffers from the input signal with low SNR, while with high SNR, the dominant mode rejection (DMR) BF degrades. Thus, the random matrix theory (RMT) is used based on the principle that the EV of CM allow predicting the actual moments of the EV so that the SNR level of the proper input data is estimated based on a specified threshold. Compared to the threshold, the higher values of the EV function are associated with the input signal with higher SNR level, so that the EMV BF is adopted, otherwise, the DMR BF. The raw data of the multipurpose phantom (84-317) were acquired using the Verasonics ultrasound system with linear array transducer L11-4v. The performance of the proposed BF (EMV + DMR) was evaluated in terms of lateral resolution using the full width at half maximum (FWHM), peak sidelobe level (PSL) and contrast (CR). Furthermore, the resolution and contrast were improved, indicating that the proposed approach can improve the image qualitypt_BR
dc.relation.ispartofIFMBE proceedingspt_BR
dc.publisher.countrySingapurapt_BR
dc.publisherSpringer Naturept_BR
dc.date.issued2019-
dc.language.isoengpt_BR
dc.description.volume68pt_BR
dc.description.issuenumber1pt_BR
dc.description.firstpage 233pt_BR
dc.description.lastpage237pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn1680-0737pt_BR
dc.identifier.doi10.1007/978-981-10-9035-6_42pt_BR
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-981-10-9035-6_42pt_BR
dc.date.available2020-03-23T15:47:48Z-
dc.date.accessioned2020-03-23T15:47:48Z-
dc.description.provenanceSubmitted by Susilene Barbosa da Silva (susilene@unicamp.br) on 2020-03-23T15:47:48Z No. of bitstreams: 0en
dc.description.provenanceMade available in DSpace on 2020-03-23T15:47:48Z (GMT). No. of bitstreams: 0 Previous issue date: 2019en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/337167-
dc.description.conferencenomeWorld congress on medical physics and biomedical engineeringpt_BR
dc.description.conferencedate2018-
dc.description.conferencelocationPraga, República Checapt_BR
dc.contributor.departmentDepartamento de Engenharia Biomédicapt_BR
dc.contributor.unidadeFaculdade de Engenharia Elétrica e da Computaçãopt_BR
dc.subject.keywordAdaptive beamformerpt_BR
dc.subject.keywordNoise suppressionpt_BR
dc.subject.keywordImage qualitypt_BR
dc.identifier.source000450908300042pt_BR
dc.creator.orcidSem informaçãopt_BR
dc.type.formArtigo de Eventopt_BR
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