Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45874
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dc.contributor.authorTostes, Paulo-
dc.contributor.authorBalinisteanu, Anca E.-
dc.contributor.authorMOURA FERREIRA, Sara-
dc.contributor.authorWilliams, Helena-
dc.contributor.authorVoigt, Jens-Uwe-
dc.contributor.authorD'hooge, Jan-
dc.date.accessioned2025-04-17T11:13:11Z-
dc.date.available2025-04-17T11:13:11Z-
dc.date.issued2024-
dc.date.submitted2025-04-11T12:51:57Z-
dc.identifier.citation2024 IEEE Ultrasonic, ferroelectrics, and frequency control joint symposium, UFFC-JS 2024, IEEE, (Art N° 8318)-
dc.identifier.isbn979-8-3503-7191-8; 979-8-3503-7190-1-
dc.identifier.issn1099-4734-
dc.identifier.urihttp://hdl.handle.net/1942/45874-
dc.description.abstractUltrasound is the most practical, cost-effective and patient-friendly clinical imaging modality. However, Computed Tomography and Magnetic Resonance Imaging outperform echography when texture or tissue characterization is clinically required. As AI-methodologies could help resolve this, a Deep Learning algorithm was applied to classify localized infarcted tissue from static ultrasound recordings.-
dc.description.sponsorshipThis work was in the context of the International Training Network project called MArie Curie Intelligent UltraSound (MARCIUS). The MARCIUS project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860745.-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesIEEE International Symposium on Applications of Ferroelectrics-
dc.rightsIEEE-
dc.subject.otherConvolutional Neural Networks-
dc.subject.otherDeep Learning-
dc.subject.otherInfarct Classification-
dc.subject.otherRadio Frequency-
dc.subject.otherUltrasound Texture-
dc.titleComparison of Radio Frequency vs beamformed ultrasound data for infarct classification with CNNs-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate2024, September 22-26-
local.bibliographicCitation.conferencename2024 IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint-
local.bibliographicCitation.conferencenameSymposium-
local.bibliographicCitation.conferenceplaceTaipei, TAIWAN-
local.format.pages4-
local.bibliographicCitation.jcatC1-
dc.description.notesTostes, P (corresponding author), Katholieke Univ Leuven, Dept Cardiovasc Sci, Leuven, Belgium.-
dc.description.notespaulo.tostes@kuleuven.be; anca.balinisteanu@ymail.com;-
dc.description.notessara.mouraferreira@gmail.com; helena.williams@kuleuven.be;-
dc.description.notesjens-uwe.voigt@uzleuven.be; jan.dhooge@kuleuven.be-
local.publisher.place345 E 47TH ST, NEW YORK, NY 10017 USA-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.bibliographicCitation.artnr8318-
local.type.programmeH2020-
local.relation.h2020860745-
dc.identifier.doi10.1109/UFFC-JS60046.2024.10794162-
dc.identifier.isi001428150100622-
local.provider.typewosris-
local.bibliographicCitation.btitle2024 IEEE Ultrasonic, ferroelectrics, and frequency control joint symposium, UFFC-JS 2024-
local.description.affiliation[Tostes, Paulo; Balinisteanu, Anca E.; Voigt, Jens-Uwe; D'hooge, Jan] Katholieke Univ Leuven, Dept Cardiovasc Sci, Leuven, Belgium.-
local.description.affiliation[Balinisteanu, Anca E.] Univ Med & Pharm, Biomed Res Inst, Bucharest, Romania.-
local.description.affiliation[Ferreira, Sara Moura] Hasselt Univ, Fac Med & Life Sci, Hasselt, Belgium.-
local.description.affiliation[Williams, Helena] Katholieke Univ Leuven, Dept Dev & Regenerat, Leuven, Belgium.-
local.uhasselt.internationalyes-
item.contributorTostes, Paulo-
item.contributorBalinisteanu, Anca E.-
item.contributorMOURA FERREIRA, Sara-
item.contributorWilliams, Helena-
item.contributorVoigt, Jens-Uwe-
item.contributorD'hooge, Jan-
item.accessRightsRestricted Access-
item.fullcitationTostes, Paulo; Balinisteanu, Anca E.; MOURA FERREIRA, Sara; Williams, Helena; Voigt, Jens-Uwe & D'hooge, Jan (2024) Comparison of Radio Frequency vs beamformed ultrasound data for infarct classification with CNNs. In: 2024 IEEE Ultrasonic, ferroelectrics, and frequency control joint symposium, UFFC-JS 2024, IEEE, (Art N° 8318).-
item.fulltextWith Fulltext-
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