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Data fusion in X-ray computed tomography using a superiorization approach.

Michael J Schrapp1, Gabor T Herman2

  • 1Siemens AG, CT Munich, Germany and Physics Department E21, Technical University of Munich, Munich, Germany.

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|June 2, 2014
PubMed
Summary
This summary is machine-generated.

Industrial non-destructive testing using X-ray computed tomography (CT) struggles with large objects. A new superiorization method integrates complementary data to enhance CT image quality and precisely localize edges not visible with CT alone.

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Area of Science:

  • Industrial non-destructive testing
  • Image reconstruction
  • Optimization methods

Background:

  • X-ray computed tomography (CT) is crucial for industrial inspection but produces artifacts with large or dense objects.
  • Limited penetration and view angles in CT can obscure critical specimen details.
  • Complementary imaging modalities like optical scanning and ultrasonic testing offer data (e.g., edge maps) not available from CT alone.

Purpose of the Study:

  • To develop a superiorization approach for integrating complementary data into CT reconstruction.
  • To improve the precise localization of edges that are not resolvable by CT data alone.
  • To enhance the overall quality of CT reconstructed images for industrial applications.

Main Methods:

  • A superiorization method based on constrained optimization was employed.
  • This approach modifies the simultaneous algebraic reconstruction technique (SART) to incorporate complementary data.
  • The modified SART is resilient to perturbations, allowing it to remain consistent with CT measurements while improving consistency with complementary data.

Main Results:

  • The superiorized SART method successfully incorporated complementary data into the CT reconstruction process.
  • Precise localization of edges, previously unresolvable by CT alone, was achieved.
  • Application to a turbine blade demonstrated a clear improvement in the reconstructed image quality.

Conclusions:

  • Superiorization offers a powerful method for enhancing CT image reconstruction by integrating complementary data.
  • This technique addresses limitations of traditional CT for large and heavily absorbing industrial objects.
  • The superiorized SART method significantly improves the diagnostic value of CT in non-destructive testing.