DSpace Repository

Classification of fMRI Data by Using Clustering

Show simple item record

dc.contributor.author Moğultay, Hazal
dc.contributor.author Alkan, Sarper
dc.contributor.author Yarman Vural, Fatoş T.
dc.date.accessioned 2020-04-19T23:53:43Z
dc.date.available 2020-04-19T23:53:43Z
dc.date.issued 2015
dc.identifier.issn 2165-0608
dc.identifier.uri http://hdl.handle.net/20.500.12416/3381
dc.description.abstract Recognition of the the cognitive states by using functional Magnetic Rezonans Imaging (fMRI) data is a challenging problem that has been a focus of scientific research for a long time. In this study the effectiveness of clustering and the ensemble learning techniques on fMRI dataset is investigated and different paramaters are compared. Moreover, the performance of these techniques are tested on both raw voxel intensity values and meshes formed by multiple voxels. Clusters are compared to the functional brain regions, however higher performances are obtained when the number of clusters is higher than the number of functional brain regions. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject fMRI tr_TR
dc.subject Clustering tr_TR
dc.subject Multi Voxel Pattern Analysis (MVPA) tr_TR
dc.title Classification of fMRI Data by Using Clustering tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 23nd Signal Processing and Communications Applications Conference (SIU) tr_TR
dc.identifier.startpage 2381 tr_TR
dc.identifier.endpage 2383 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Mekatronik Mühendisliği Bölümü tr_TR


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record