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A tissue classification approach for brain tumor segmentation using MRI

Seferlis Stavros, Zarifis Georgios, Giakos George C., Pezoulas Vasileios, Zervakis Michail, Pologiorgi Ifigeneia, Tsalikis, George

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URIhttp://purl.tuc.gr/dl/dias/9662CD77-E1D1-4407-B7D4-90B182FFDF1C-
Identifierhttps://doi.org/10.1109/IST.2017.8261542-
Identifierhttps://ieeexplore.ieee.org/abstract/document/8261542-
Languageen-
Extent7 pagesen
TitleA tissue classification approach for brain tumor segmentation using MRIen
CreatorSeferlis Stavrosen
CreatorZarifis Georgiosen
CreatorGiakos George C.en
CreatorPezoulas Vasileiosen
CreatorΠεζουλας Βασιλειοςel
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
CreatorPologiorgi Ifigeneiaen
CreatorΠολογιωργη Ιφιγενειαel
CreatorTsalikis, Georgeen
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryInnovative practices in the sector of medical imaging are nowadays applied in order to upgrade the medical services provided to individuals, giving answers to crucial medical issues, something impossible in the past. Brain tumor segmentation consists of separating the different tumor tissues (solid or active tumor, edema, and necrosis) from normal brain tissues such as white/white matter and cerebrospinal fluid. The present article attempts to provide an application of these practices on brain tumor segmentation using MRI data. More specifically, a new skull stripping method is proposed based on the Normalized-cut (N-cut) algorithm and then a histogram classification approach is applied on the skull-free images for a more accurate brain tumor segmentation alongside with an entropy filter for highlighting the necrotic tissue.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-10-03-
Date of Publication2018-
SubjectBrain tumor segmentationen
SubjectHistogram classificationen
SubjectMRIen
SubjectN-cuten
SubjectSkull-strippingen
Bibliographic CitationV.C. Pezoulas, M. Zervakis, I. Pologiorgi, S. Seferlis, G.M. Tsalikis, G. Zarifis and G.C. Giakos, "A tissue classification approach for brain tumor segmentation using MRI," in 2017 IEEE International Conference on Imaging Systems and Techniques, 2018, pp. 1-6. doi: 10.1109/IST.2017.8261542en

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