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DC poleHodnotaJazyk
dc.contributor.authorKuo, M. H.
dc.contributor.authorChen, M. C.
dc.contributor.editorSkala, Václav
dc.date.accessioned2015-09-22T12:20:01Z
dc.date.available2015-09-22T12:20:01Z
dc.date.issued1998
dc.identifier.citationJournal of WSCG. 1998, vol. 6, no. 1-3, p. 208-214.en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (online)
dc.identifier.urihttp://hdl.handle.net/11025/15858
dc.identifier.urihttp://wscg.zcu.cz/wscg1998/wscg98.htm
dc.format7 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectpočítačová tomografiecs
dc.subjectinterpolacecs
dc.subject3D biomedicínský modelcs
dc.titleBiomedical data interpolation for 3D visual modelsen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedComputed Tomography (CT) is an X-ray technique that produces 2D biomedical slice image data. In such images, the slice spacing is much greater than the spacing of individual samples on a slice. Thus, a robust interpolation method to generate quality intermediate images for the reconstruction of 3D biomedical model is necessary. The subject of this paper is to compare three different interpolation techniques: linear, cubic spline, and Fourier interpolation for generating intermediate slices. Linear interpolation is shown to be the best of the three interpolation techniques. This research also shows that without the image segmentation or the matching process poor intermediate images will be generated.en
dc.subject.translatedcomputed tomographyen
dc.subject.translatedinterpolationen
dc.subject.translated3D biomedical modelen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 6, number 1-3 (1998)

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