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Reconstruction of simulated functional brain images using generalized matrix inverses and Algebraic Reconstruction Techniques

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dc.contributor.author Ventouras, Eric en
dc.contributor.author Uzunoglu, Nikos en
dc.contributor.author Papageorgiou, Charalambos en
dc.contributor.author Rabavilas, Andreas en
dc.contributor.author Stefanis, Costas en
dc.date.accessioned 2014-03-01T02:48:27Z
dc.date.available 2014-03-01T02:48:27Z
dc.date.issued 1996 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/33810
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-38449096328&partnerID=40&md5=535e230bfd7179e7a86af18c28b5ab57 en
dc.subject.other Algorithms en
dc.subject.other Bioelectric potentials en
dc.subject.other Brain en
dc.subject.other Image reconstruction en
dc.subject.other Least squares approximations en
dc.subject.other Matrix algebra en
dc.subject.other Voltage measurement en
dc.subject.other Abstract only en
dc.subject.other Algebraic reconstruction techniques en
dc.subject.other Event related potentials (ERP) en
dc.subject.other Generalized matrix inversion technique en
dc.subject.other Medical imaging en
dc.title Reconstruction of simulated functional brain images using generalized matrix inverses and Algebraic Reconstruction Techniques en
heal.type conferenceItem en
heal.publicationDate 1996 en
heal.abstract The feasibility of using the Generalized Matrix Inversion scheme and iterative algorithms known as Algebraic Reconstruction Techniques in the reconstruction of simulated functional brain images and Event-Related Potentials (ERP) measured at the scalp is evaluated. Various models are tested with respect to a number of ERP discrete sources and voltage measurement points. Results indicate that the ART4, when combined with underrelaxation, is the most reliable algorithm for reconstructing brain images in noisy environments. en
heal.publisher IEEE en
heal.journalName Trans Black Sea Region Symposium on Applied Electromagnetism en


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