U-CatcHCC: An Accurate HCC Detector in Hepatic DCE-MRI Sequences Based on an U-Net Framework

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Autor(es): dc.contributorLodz Univ Technol-
Autor(es): dc.contributorUniv Clermont Auvergne-
Autor(es): dc.contributorCtr Hosp Univ-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorFabijanska, Anna-
Autor(es): dc.creatorVacavant, Antoine-
Autor(es): dc.creatorLebre, Marie-Ange-
Autor(es): dc.creatorPavan, Ana L. M. [UNESP]-
Autor(es): dc.creatorPina, Diana R. de [UNESP]-
Autor(es): dc.creatorAbergel, Armand-
Autor(es): dc.creatorChabrot, Pascal-
Autor(es): dc.creatorMagnin, Benoit-
Autor(es): dc.creatorChmielewski, L. J.-
Autor(es): dc.creatorKozera, R.-
Autor(es): dc.creatorOrlowski, A.-
Autor(es): dc.creatorWojciechowski, K.-
Autor(es): dc.creatorBruckstein, A. M.-
Autor(es): dc.creatorPetkov, N.-
Data de aceite: dc.date.accessioned2022-02-22T00:58:14Z-
Data de disponibilização: dc.date.available2022-02-22T00:58:14Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2018-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-030-00692-1_28-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/210000-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/210000-
Descrição: dc.descriptionThis paper presents a novel framework devoted to the detection of HCC (Hepato-Cellular Carcinoma) within hepatic DCE-MRI (Dynamic Contrast-Enhanced MRI) sequences, by a deep learning approach. In clinical routine, radiologists usually consider different phases during contrast injection (before injection; arterial phase; portal phase for instance) for HCC diagnosis. By employing a U-Net architecture, we are able to identify such tumors with a very high accuracy (98.5% of classification rate at best) for a small cohort of patients, which should be confirmed in future works by considering larger groups. We also show in this paper the influence of patch size for this machine learning process, and the positive impact of employing all phases available in DCE-MRI sequences, compared to use only one.-
Descrição: dc.descriptionLodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering-
Descrição: dc.descriptionLodz Univ Technol, Inst Appl Comp Sci, 18-22 Stefanowskiego St, PL-90924 Lodz, Poland-
Descrição: dc.descriptionUniv Clermont Auvergne, SIGMA Clermont, CNRS, Inst Pascal, F-63000 Clermont Ferrand, France-
Descrição: dc.descriptionCtr Hosp Univ, Clermont Ferrand, France-
Descrição: dc.descriptionSao Paulo State Univ, Dept Phys & Biophys, Botucatu, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Phys & Biophys, Botucatu, SP, Brazil-
Descrição: dc.descriptionLodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering: 501/12-24-1-5428-
Formato: dc.format319-328-
Idioma: dc.languageen-
Publicador: dc.publisherSpringer-
Relação: dc.relationComputer Vision And Graphics ( Iccvg 2018)-
???dc.source???: dc.sourceWeb of Science-
Título: dc.titleU-CatcHCC: An Accurate HCC Detector in Hepatic DCE-MRI Sequences Based on an U-Net Framework-
Aparece nas coleções:Repositório Institucional - Unesp

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