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dc.contributor.authorBalocco, Simone-
dc.contributor.authorGonzález, Mauricio-
dc.contributor.authorÑancule, Ricardo-
dc.contributor.authorRadeva, Petia-
dc.contributor.authorThomas, Gabriel-
dc.coverage.spatial7004624en_US
dc.date.accessioned2021-07-14T13:47:49Z-
dc.date.available2021-07-14T13:47:49Z-
dc.date.issued2018-
dc.identifier.citationBalocco S., González M., Ñanculef R., Radeva P., Thomas G. (2018) Calcified Plaque Detection in IVUS Sequences: Preliminary Results Using Convolutional Nets. In: Hernández Heredia Y., Milián Núñez V., Ruiz Shulcloper J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2018. Lecture Notes in Computer Science, vol 11047. Springer, Cham. https://doi.org/10.1007/978-3-030-01132-1_4en_US
dc.identifier.urihttps://repositorio.uci.cu/jspui/handle/123456789/9484-
dc.description.abstractThe manual inspection of intravascular ultrasound (IVUS) images to detect clinically relevant patterns is a difficult and laborious task performed routinely by physicians. In this paper, we present a framework based on convolutional nets for the quick selection of IVUS frames containing arterial calcification, a pattern whose detection plays a vital role in the diagnosis of atherosclerosis. Preliminary experiments on a dataset acquired from eighty patients show that convolutional architectures improve detections of a shallow classifier in terms of F1-measure, precision and recall.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.subjectINTRAVASCULAR ULTRASOUND IMAGESen_US
dc.subjectCONVOLUTIONAL NETSen_US
dc.subjectDEEP LEARNINGen_US
dc.subjectMEDICAL IMAGE ANALYSISen_US
dc.titleCalcified Plaque Detection in IVUS Sequences: Preliminary Results Using Convolutional Netsen_US
dc.typeconferenceObjecten_US
dc.rights.holderUniversidad de las Ciencias Informáticasen_US
dc.identifier.doihttps://doi.org/10.1007/978-3-030-01132-1_4-
dc.source.initialpage34en_US
dc.source.endpage42en_US
dc.source.titleUCIENCIA 2018en_US
dc.source.conferencetitleUCIENCIAen_US
Aparece en las colecciones: UCIENCIA 2018

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