Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3607
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dc.contributor.authorCandemir C.-
dc.contributor.authorOguz K.-
dc.contributor.authorKorukoglu S.-
dc.contributor.authorGonul A.S.-
dc.date.accessioned2023-06-16T15:00:55Z-
dc.date.available2023-06-16T15:00:55Z-
dc.date.issued2018-
dc.identifier.isbn9.78154E+12-
dc.identifier.urihttps://doi.org/10.1109/SIU.2018.8404273-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/3607-
dc.descriptionAselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netasen_US
dc.description26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780en_US
dc.description.abstractChange point analysis is an efficient method for understanding the unexpected behavior of the data used in many different disciplines including medical imaging. It is important to find the instances the activations occur as much as finding the activation areas in the analysis of functional magnetic resonance imaging (fMRI). Change point detection algorithms can be used to find the activation instances. In this study, a regression based point detection method is proposed to find the activation instances in fMRI experiments. The proposed method is applied to a fMRI experiment which includes a motor task. A linear based evaluation method is also proposed. The analyses show that the activations are in accordance with the established methods in the literature. © 2018 IEEE.en_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof26th IEEE Signal Processing and Communications Applications Conference, SIU 2018en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectActivation detectionen_US
dc.subjectActivation timeen_US
dc.subjectChange point problemen_US
dc.subjectFunctional MRIen_US
dc.subjectChemical activationen_US
dc.subjectMagnetic resonance imagingen_US
dc.subjectMedical imagingen_US
dc.subjectSignal processingen_US
dc.subjectActivation detectionen_US
dc.subjectActivation timeen_US
dc.subjectChange point detectionen_US
dc.subjectChange-point analysisen_US
dc.subjectChange-point problemen_US
dc.subjectFunctional magnetic resonance imagingen_US
dc.subjectFunctional MRIen_US
dc.subjectPoint detectionen_US
dc.subjectActivation analysisen_US
dc.titleDetection and evaluation of activation instances as change points in functional MR imagesen_US
dc.title.alternativeFonksiyonel MR Görüntülerinde Aktivasyon Anlarinin De?isim Noktalari ile Belirlenmesi ve De?erlendirilmesien_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/SIU.2018.8404273-
dc.identifier.scopus2-s2.0-85050791144en_US
dc.authorscopusid55807447100-
dc.authorscopusid6506204656-
dc.authorscopusid55942313100-
dc.identifier.startpage1en_US
dc.identifier.endpage4en_US
dc.identifier.wosWOS:000511448500126en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.grantfulltextreserved-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeConference Object-
item.fulltextWith Fulltext-
item.languageiso639-1tr-
crisitem.author.dept05.05. Computer Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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