Interpolation of Tomographic Data Using a Self-Similar Approach

Asvestas, PA; Skevofilakas, M; Matsopoulos, GK; Nikita, KS

dc.contributor.author	Asvestas, PA	en
dc.contributor.author	Skevofilakas, M	en
dc.contributor.author	Matsopoulos, GK	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T02:42:16Z
dc.date.available	2014-03-01T02:42:16Z
dc.date.issued	2003	en
dc.identifier.issn	05891019	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30903
dc.subject	Interpolation	en
dc.subject	Self-similar model	en
dc.subject	Tomographic data	en
dc.subject.other	Self-similar models	en
dc.subject.other	Tomographic data	en
dc.subject.other	Approximation theory	en
dc.subject.other	Constraint theory	en
dc.subject.other	Data reduction	en
dc.subject.other	Information analysis	en
dc.subject.other	Interpolation	en
dc.subject.other	Mathematical models	en
dc.subject.other	Tomography	en
dc.title	Interpolation of Tomographic Data Using a Self-Similar Approach	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.2003.1279914	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.2003.1279914	en
heal.publicationDate	2003	en
heal.abstract	In this paper, a new method for slice interpolation of a tomographic dataset is presented. The method exploits the self-similarity that exists in the dataset, namely a part of the dataset is a scaled down copy of another larger part of the set. According to the proposed method, the interpolated slice is created using information from the four nearest available slices. Initially, correspondences between points, belonging to a properly chosen pair of the available slices, are established. These correspondences are used to guide a procedure for creating a slice that is an approximation of the interpolated slice. The same procedure is applied for the other pair of slices resulting in another approximation of the interpolated slice. A weighted sum of the two approximations is used in order to create the final version of the interpolated slice. Quantitative and qualitative results stress the superior performance of the proposed method against other widely used interpolation methods.	en
heal.journalName	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings	en
dc.identifier.doi	10.1109/IEMBS.2003.1279914	en
dc.identifier.volume	1	en
dc.identifier.spage	914	en
dc.identifier.epage	917	en