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dc.contributor.authorArtemyev, M. S.en
dc.contributor.authorSerazetdinov, A. R.en
dc.contributor.authorSmirnov, A. A.en
dc.date.accessioned2022-05-12T08:20:07Z-
dc.date.available2022-05-12T08:20:07Z-
dc.date.issued2020-
dc.identifier.citationArtemyev M. S. X-ray Image Segmentation with the Use of Machine Learning Algorithms / M. S. Artemyev, A. R. Serazetdinov, A. A. Smirnov // AIP Conference Proceedings. — 2020. — Vol. 2313. — 080006.en
dc.identifier.isbn9780735440531-
dc.identifier.issn0094-243X-
dc.identifier.otherAll Open Access, Green3
dc.identifier.urihttp://elar.urfu.ru/handle/10995/111654-
dc.description.abstractBrain tumor images segmentation plays a crucial role in the auxiliary diagnosis of disease, treatment planning and surgical navigation. In order to accurately segment brain tumor images, this paper proposes an automatic brain tumor Magnetic Resonance Imaging (MRI) image segmentation algorithm based on the U-net model. The neuron network based approached was closely analyzed in comparison with standard segmentation techniques (detection by threshold, K-means clustering, histogram-based approach and edge detection). The algorithm is validated and evaluated on the Jun Cheng dataset. The experimental results show that the proposed algorithm has strong competitiveness compared with the existing brain tumor MRI image segmentation algorithm. © 2020 American Institute of Physics Inc.. All rights reserved.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherAmerican Institute of Physics Inc.en1
dc.publisherAIP Publishingen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceAIP Conf. Proc.2
dc.sourceAIP Conference Proceedingsen
dc.titleX-ray Image Segmentation with the Use of Machine Learning Algorithmsen
dc.typeConference Paperen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.conference.name7th International Young Researchers'' Conference on Physics, Technology, Innovations, PTI 2020en
dc.conference.date18 May 2020 through 22 May 2020-
dc.identifier.doi10.1063/5.0032275-
dc.identifier.scopus85097996360-
local.contributor.employeeArtemyev, M.S., Ural Federal University, Yekaterinburg, Russian Federation; Serazetdinov, A.R., National Research Nuclear University MEPhI, Moscow, Russian Federation; Smirnov, A.A., Ural Federal University, Yekaterinburg, Russian Federationen
local.volume2313-
dc.identifier.wos000679348500069-
local.contributor.departmentUral Federal University, Yekaterinburg, Russian Federation; National Research Nuclear University MEPhI, Moscow, Russian Federationen
local.identifier.pure20414383-
local.description.order080006-
local.identifier.eid2-s2.0-85097996360-
local.identifier.wosWOS:000679348500069-
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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