HEAL DSpace

Interpolation of Tomographic Data Using a Self-Similar Approach

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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


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