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Phase-Sensitive Region-of-Interest Computed Tomography

  • Lina Felsner
  • Martin Berger
  • Sebastian Kaeppler
  • Johannes Bopp
  • Veronika Ludwig
  • Thomas Weber
  • Georg Pelzer
  • Thilo Michel
  • Andreas Maier
  • Gisela Anton
  • Christian Riess
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11070)

Abstract

X-Ray Phase-Contrast Imaging (PCI) yields absorption, differential phase, and dark-field images. Computed Tomography (CT) of grating-based PCI can in principle provide high-resolution soft-tissue contrast. Recently, grating-based PCI took several hurdles towards clinical implementation by addressing, for example, acquisition speed, high X-ray energies, and system vibrations. However, a critical impediment in all grating-based systems lies in limits that constrain the grating diameter to few centimeters.

In this work, we propose a system and a reconstruction algorithm to circumvent this constraint in a clinically compatible way. We propose to perform a phase-sensitive Region-of-Interest (ROI) CT within a full-field absorption CT. The biggest advantage of this approach is that it allows to correct for phase truncation artifacts, and to obtain quantitative phase values. Our method is robust, and shows high-quality results on simulated data and on a biological mouse sample. This work is a proof of concept showing the potential to use PCI in CT on large specimen, such as humans, in clinical applications.

Notes

Acknowledgments

Lina Felsner is supported by the International Max Planck Research School - Physics of Light (IMPRS-PL).

Disclaimer. The concepts and information presented in this paper are based on research and are not commercially available.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Lina Felsner
    • 1
  • Martin Berger
    • 3
  • Sebastian Kaeppler
    • 1
  • Johannes Bopp
    • 1
  • Veronika Ludwig
    • 2
  • Thomas Weber
    • 2
  • Georg Pelzer
    • 2
  • Thilo Michel
    • 2
  • Andreas Maier
    • 1
  • Gisela Anton
    • 2
  • Christian Riess
    • 1
  1. 1.Pattern Recognition Lab, Computer ScienceUniversity of Erlangen-NürnbergErlangenGermany
  2. 2.Erlangen Centre for Astroparticle PhysicsUniversity of Erlangen-NürnbergErlangenGermany
  3. 3.Siemens Healthcare GmbHErlangenGermany

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