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Enhanced spatial resolution using iterative focal desmearing in computed tomography

  • Computed tomography reconstructions of projected data usually assume an ideal point-like focal spot. However, in practice, the actual finite focus size leads to blurred projections, unavoidably. The elements (voxels) of the reconstruction array are smeared differently as a function of their individual position relative to source and detector. Neglecting the focal smearing generates considerably blurred reconstructions. Previous attempts were based on directly deconvolving blurred projections from a constant kernel, which yields better results but still exhibits artefacts. Iterative algorithms can be adopted to take into account focal smearing as a function of position. However, this requires detailed prior knowledge of quantitative smear functions. The DIRECTT (Direct Iterative Reconstruction of Computed Tomography Trajectories) algorithm is a promising candidate to meet these requirements. It has been demonstrated elsewhere that DIRECTT copes with limited data sets such as limitedComputed tomography reconstructions of projected data usually assume an ideal point-like focal spot. However, in practice, the actual finite focus size leads to blurred projections, unavoidably. The elements (voxels) of the reconstruction array are smeared differently as a function of their individual position relative to source and detector. Neglecting the focal smearing generates considerably blurred reconstructions. Previous attempts were based on directly deconvolving blurred projections from a constant kernel, which yields better results but still exhibits artefacts. Iterative algorithms can be adopted to take into account focal smearing as a function of position. However, this requires detailed prior knowledge of quantitative smear functions. The DIRECTT (Direct Iterative Reconstruction of Computed Tomography Trajectories) algorithm is a promising candidate to meet these requirements. It has been demonstrated elsewhere that DIRECTT copes with limited data sets such as limited view and region-of- interest data by tracing single sinusoidal-like trajectories in Radon space, which are selected from the set of all possible trajectories by appropriate criteria. Currently, position-dependent smearing is used in the projection part of iterations. At the example of model reconstructions we demonstrate the gain of spatial resolution by iterative variable desmearing according to the DIRECTT algorithm in comparison to the standard filtered back-projection.zeige mehrzeige weniger

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Metadaten
Autor*innen:Axel Lange, Manfred P. Hentschel, Andreas KupschORCiD
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):10th European conference on non-destructive testing (Proceedings)
Jahr der Erstveröffentlichung:2010
Ausgabe/Heft:Paper 4.02.18
Erste Seite:1
Letzte Seite:9(?)
Freie Schlagwörter:Computed tomography; Focal smearing; Reconstruction algorithm; Spatial reslution
Veranstaltung:10th European conference on non-destructive testing
Veranstaltungsort:Moscow, Russia
Beginndatum der Veranstaltung:2010-06-07
Enddatum der Veranstaltung:2010-06-11
URL:http://www.ndt.net/article/ecndt2010/reports/1_09_18.pdf
Verfügbarkeit des Dokuments:Physisches Exemplar in der Bibliothek der BAM vorhanden ("Hardcopy Access")
Bibliotheksstandort:Sonderstandort: Publica-Schrank
Datum der Freischaltung:19.02.2016
Referierte Publikation:Nein
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