Reconstruction of intracranial evoked current distribution images using generalized matrix inverses and algebraic reconstruction techniques

Ventouras Errikos, M; Uzunoglu Nikos, K; Papageorgiou Charalambos, C; Rabavilas Andreas, D; Koutsouris Dimitrios, G; Stefanis Costas, N

dc.contributor.author	Ventouras Errikos, M	en
dc.contributor.author	Uzunoglu Nikos, K	en
dc.contributor.author	Papageorgiou Charalambos, C	en
dc.contributor.author	Rabavilas Andreas, D	en
dc.contributor.author	Koutsouris Dimitrios, G	en
dc.contributor.author	Stefanis Costas, N	en
dc.date.accessioned	2014-03-01T02:41:16Z
dc.date.available	2014-03-01T02:41:16Z
dc.date.issued	1996	en
dc.identifier.issn	05891019	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30437
dc.subject	Algebraic Reconstruction Technique	en
dc.subject	Current Distribution	en
dc.subject	Electroencephalography	en
dc.subject	event-related potential erp	en
dc.subject	Matrix Inversion	en
dc.subject	Noisy Data	en
dc.subject	Performance Evaluation	en
dc.subject	Direct Matrix Inversion	en
dc.subject.other	Algorithms	en
dc.subject.other	Approximation theory	en
dc.subject.other	Bioelectric potentials	en
dc.subject.other	Convergence of numerical methods	en
dc.subject.other	Electric current distribution	en
dc.subject.other	Electroencephalography	en
dc.subject.other	Image reconstruction	en
dc.subject.other	Mathematical models	en
dc.subject.other	Matrix algebra	en
dc.subject.other	Spurious signal noise	en
dc.subject.other	Algebraic reconstruction techniques (ART)	en
dc.subject.other	Generalized matrix inverse (GMI)	en
dc.subject.other	Medical imaging	en
dc.title	Reconstruction of intracranial evoked current distribution images using generalized matrix inverses and algebraic reconstruction techniques	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.1996.651994	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.1996.651994	en
heal.publicationDate	1996	en
heal.abstract	Inversion of Event-Related Potentials (ERPs) is studied using simulated potentials, through an analytic technique providing information about extended intracranial distributions, with separate source and sink positions. Comparative performance evaluation of the Generalized Matrix Inverse (GMI) technique and Algebraic Reconstruction Technique (ART) shows that for matrix dimensions used in inverse electroencephalography direct matrix inversion is faster than ART, in the noiseless case. Both methods present the same limitations concerning radial resolution due to their property of providing minimum norm solutions. When noise is present ART algorithms specifically designed for noisy data converge better to the original simulated current source distributions than GMI solutions, even if truncated approximations of pseudoinverses are used.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings	en
dc.identifier.doi	10.1109/IEMBS.1996.651994	en
dc.identifier.volume	2	en
dc.identifier.spage	825	en
dc.identifier.epage	826	en