Publicação: Stroke Lesion Detection Using Convolutional Neural Networks
dc.contributor.author | Pereira, Danillo Roberto [UNESP] | |
dc.contributor.author | Filho, Pedro P. Rebouças | |
dc.contributor.author | De Rosa, Gustavo Henrique [UNESP] | |
dc.contributor.author | Papa, João Paulo [UNESP] | |
dc.contributor.author | De Albuquerque, Victor Hugo C. | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | CE | |
dc.contributor.institution | University of Fortaleza | |
dc.date.accessioned | 2022-04-30T12:56:16Z | |
dc.date.available | 2022-04-30T12:56:16Z | |
dc.date.issued | 2018-10-10 | |
dc.description.abstract | Stroke 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.affiliation | Department of Computing São Paulo State University | |
dc.description.affiliation | Federal Institute of Education Science and Technology of Ceará CE | |
dc.description.affiliation | Graduate Program in Applied Informatics University of Fortaleza | |
dc.description.affiliationUnesp | Department of Computing São Paulo State University | |
dc.identifier | http://dx.doi.org/10.1109/IJCNN.2018.8489199 | |
dc.identifier.citation | Proceedings of the International Joint Conference on Neural Networks, v. 2018-July. | |
dc.identifier.doi | 10.1109/IJCNN.2018.8489199 | |
dc.identifier.scopus | 2-s2.0-85056513830 | |
dc.identifier.uri | http://hdl.handle.net/11449/232818 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings of the International Joint Conference on Neural Networks | |
dc.source | Scopus | |
dc.title | Stroke Lesion Detection Using Convolutional Neural Networks | en |
dc.type | Trabalho apresentado em evento | |
dspace.entity.type | Publication | |
unesp.campus | Universidade Estadual Paulista (UNESP), Faculdade de Ciências, Bauru | pt |
unesp.department | Computação - FC | pt |