• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Compressed sensing as a tool for scanning very large objects with high energy X-ray computed tomography
 
  • Details
  • Full
Options
2014
Conference Paper
Title

Compressed sensing as a tool for scanning very large objects with high energy X-ray computed tomography

Abstract
We propose a novel high-energy X-ray Computed Tomography system for inspecting very large objects like automobiles and sea freight containers. In this context we discuss appropriate strategies for efficient scanning and reconstruction methods. Due to scattering adiation the system uses a line detector which leads to longer acquisition times compared to planar detectors. In order to reach adequate scanning times the number of projections is reduced and compressed Sensing techniques are used for the reconstruction. The image quality is discussed with respect to its suitability for applications in the field of industrial non-destructive testing as well as security. We present an experimental evaluation with real data of a sea freight container scanned at the high-energy testing facility of the Fraunhofer Development Center for X-ray Technology. The image quality is quantitatively assessed by a separate test specimen. We can show that Computed Tomography of very large, complex objects is technologically feasible.
Author(s)
Schön, Tobias  
Firsching, Markus  
Reims, Nils  
Sukowski, Frank  
Dittmann, Jonas
University Würzburg
Mainwork
Third International Conference on Image Formation in X-Ray Computed Tomography 2014. Proceedings  
Conference
International Conference on Image Formation in X-Ray Computed Tomography 2014  
Language
English
Fraunhofer-Institut für Integrierte Schaltungen IIS  
Keyword(s)
  • Rekonstruktion

  • Algorithmik

  • industrielle CT

  • CT-Systeme

  • Computer-Tomografie (CT)

  • compressed sensing

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024