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Publicação:
Stroke Lesion Detection Using Convolutional Neural Networks

dc.contributor.authorPereira, Danillo Roberto [UNESP]
dc.contributor.authorFilho, Pedro P. Rebouças
dc.contributor.authorDe Rosa, Gustavo Henrique [UNESP]
dc.contributor.authorPapa, João Paulo [UNESP]
dc.contributor.authorDe Albuquerque, Victor Hugo C.
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionCE
dc.contributor.institutionUniversity of Fortaleza
dc.date.accessioned2022-04-30T12:56:16Z
dc.date.available2022-04-30T12:56:16Z
dc.date.issued2018-10-10
dc.description.abstractStroke is an injury that affects the brain tissue, mainly caused by changes in the blood supply to a particular region of the brain. As consequence, some specific functions related to that affected region can be reduced, decreasing the quality of life of the patient. In this work, we deal with the problem of stroke detection in Computed Tomography (CT) images using Convolutional Neural Networks (CNN) optimized by Particle Swarm optimization (PSO). We considered two different kinds of strokes, ischemic and hemorrhagic, as well as making available a public dataset to foster the research related to stroke detection in the human brain. The dataset comprises three different types of images for each case, i.e., the original CT image, one with the segmented cranium and an additional one with the radiological density's map. The results evidenced that CNN's are suitable to deal with stroke detection, obtaining promising results.en
dc.description.affiliationDepartment of Computing São Paulo State University
dc.description.affiliationFederal Institute of Education Science and Technology of Ceará CE
dc.description.affiliationGraduate Program in Applied Informatics University of Fortaleza
dc.description.affiliationUnespDepartment of Computing São Paulo State University
dc.identifierhttp://dx.doi.org/10.1109/IJCNN.2018.8489199
dc.identifier.citationProceedings of the International Joint Conference on Neural Networks, v. 2018-July.
dc.identifier.doi10.1109/IJCNN.2018.8489199
dc.identifier.scopus2-s2.0-85056513830
dc.identifier.urihttp://hdl.handle.net/11449/232818
dc.language.isoeng
dc.relation.ispartofProceedings of the International Joint Conference on Neural Networks
dc.sourceScopus
dc.titleStroke Lesion Detection Using Convolutional Neural Networksen
dc.typeTrabalho apresentado em evento
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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