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dc.contributor.authorAymerich Martínez, Francisco Javier
dc.contributor.authorSobrevilla Frisón, Pilar
dc.contributor.authorMontseny Masip, Eduard
dc.contributor.authorRovira, Alex
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2017-02-27T17:08:13Z
dc.date.available2017-02-27T17:08:13Z
dc.date.issued2016
dc.identifier.citationAymerich, F.X., Sobrevilla, P., Montseny, E., Rovira, A. Application of a Mamdani-type fuzzy rule-based system to segment periventricular cerebral veins in susceptibility-weighted images. A: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. "16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016: proceedings book". Eindhoven: Springer, 2016, p. 612-623.
dc.identifier.isbn9783319405957
dc.identifier.urihttp://hdl.handle.net/2117/101654
dc.description.abstractThis paper presents an algorithm designed to segment veins in the periventricular region of the brain in susceptibility-weighted magnetic resonance images. The proposed algorithm is based on a Mamdani-type fuzzy rule-based system that enables enhancement of veins within periventricular regions of interest as the first step. Segmentation is achieved after determining the cut-off value providing the best trade-off between sensitivity and specificity to establish the suitability of each pixel to belong to a cerebral vein. Performance of the algorithm in susceptibility-weighted images acquired in healthy volunteers showed very good segmentation, with a small number of false positives. The results were not affected by small changes in the size and location of the regions of interest. The algorithm also enabled detection of differences in the visibility of periventricular veins between healthy subjects and multiple sclerosis patients. © Springer International Publishing Switzerland 2016.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherSpringer
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells de radiologia mèdica
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics
dc.subject.lcshPatient monitoring
dc.subject.lcshMagnetic resonance imaging
dc.subject.lcshBrain--Magnetic resonance imaging
dc.subject.otherAlgorithms
dc.subject.otherBrain
dc.subject.otherEconomic and social effects
dc.subject.otherFuzzy inference
dc.subject.otherFuzzy rules
dc.subject.otherImage segmentation
dc.subject.otherInformation management
dc.subject.otherInformation science
dc.subject.otherMagnetic resonance imaging
dc.subject.otherCerebral veins
dc.subject.otherCut-off value
dc.subject.otherFalse positive
dc.subject.otherHealthy subjects
dc.subject.otherHealthy volunteers
dc.subject.otherMultiple sclerosis
dc.subject.otherRegions of interest
dc.subject.otherSensitivity and specificity
dc.titleApplication of a Mamdani-type fuzzy rule-based system to segment periventricular cerebral veins in susceptibility-weighted images
dc.typeConference report
dc.subject.lemacMonitoratge de pacients
dc.subject.lemacImatges per ressonància magnètica
dc.subject.lemacCervell -- Imatges per ressonància magnètica
dc.identifier.doi10.1007/978-3-319-40596-4_51
dc.relation.publisherversionhttp://link.springer.com/chapter/10.1007%2F978-3-319-40596-4_51
dc.rights.accessOpen Access
drac.iddocument18785079
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorAymerich, F.X., Sobrevilla, P., Montseny, E., Rovira, A.
upcommons.citation.contributorInternational Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
upcommons.citation.pubplaceEindhoven
upcommons.citation.publishedtrue
upcommons.citation.publicationName16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016: proceedings book
upcommons.citation.startingPage612
upcommons.citation.endingPage623


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