3D Reconstruction from Sparse Radiographic Data

  • James SachsJr.
  • Ken Sauer
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)

Abstract

Nondestructive evaluation of materials through X-ray and -y-ray radiography has long been achieved by inferring three-dimensional structure from exposed films. Multiple views with varying positions of radioactive sources and the film have the potential for direct three-dimensional tomographic reconstruction for more detailed diagnosis of material flaws. The data are sufficiently sparse, however, to leave the reconstruction badly under-specified, requiring regularization and/ or constraints to achieve meaningful results. In this chapter we discuss and illustrate the application of Bayesian binary 3D tomographic reconstruction to radiographs, including the several non-idealities frequently encountered in the field.

Keywords

Attenuation Radioactive Isotope Expense Convolution Radon 

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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • James SachsJr.
    • 1
  • Ken Sauer
    • 2
  1. 1.Ford Motor Corporation, Product Development CenterPDC MD-331DearbornUSA
  2. 2.Department of Electrical EngineeringUniversity of Notre DameNotre DameUSA

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