Advertisement

3D X-ray Tomography - Basics and Latest Developments

  • Theobald O. J. Fuchs
  • Randolf Hanke
Living reference work entry

Abstract

In the following, the basic principles of X-ray physics are discussed which includes generation and detection of X-rays and the acquisition of X-ray projection images. Further on, the process of computer-assisted sectional image calculation is briefly introduced and the latest developments in the field are mentioned. Additionally, particular issues of micro- and nano-scale X-ray Computed Tomography are described. Finally, we attempt to look forward into the upcoming future of industrial X-ray imaging systems which most probably will evolve to cognitive sensor networks by applying advanced machine-learning technologies.

References

  1. Buzug TM (2008) Computed tomography: from photon statistics to modern cone-beam CT. Springer, Berlin. ISBN-13: 978-3540394075Google Scholar
  2. De Man B, Fessler JA (2009) Statistical iterative reconstruction for X-ray computed tomography. In: Censor Y, Jiang M, Wang G (eds) Biomedical mathematics: promising directions in imaging, therapy planning, and inverse problems. Medical Physics Publishing, MadisonGoogle Scholar
  3. Dittmann J (2009) Tomographic reconstruction from few projections based on the theory of compressed sensing. Master thesis, Chair for X-ray microscopy, Julius-Maximilians-University, WürzburgGoogle Scholar
  4. Feldkamp LA, Davis LC, Kress JW (1984) Practical cone-beam algorithm. J Opt Soc Am 6:612CrossRefGoogle Scholar
  5. Fuchs T, Hanke R (2008) Task-driven design of X-ray systems for industrial inspection. In: IEEE nuclear science symposium conference record.  https://doi.org/10.1109/NSSMIC.2008.4775230
  6. Fuchs T, Kalender W (2003) On the correlation of pixel noise, spatial resolution and dose in computed tomography: theoretical prediction and verification by simulation and measurement. Phys Med XIX(2):153–164Google Scholar
  7. Gordon R, Bender R, Herman GT (1970) Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography. J Theor Biol 29:471–481CrossRefGoogle Scholar
  8. Hemberg O, Otendal M, Hertz HM (2003) Liquid-metal-jet anode electron-impact X-ray source. Appl Phys Lett 83:1483–1485CrossRefGoogle Scholar
  9. Herman GT (2009) Fundamentals of computerized tomography: image reconstruction from projections, 2nd edn. Springer, Dordrecht. ISBN 978-1-85233-617-2CrossRefGoogle Scholar
  10. Hounsfield GN (1973) Computerized transverse axial scanning (tomography): part 1. Description of system. Br J Radiol 46:1016–1022CrossRefGoogle Scholar
  11. Hubbell JH (1982) Photon mass attenuation coefficients and energy-absorption coefficients from 1 keV to 20 MeV. Int J Appl Radiat Isot 33:1260–1290CrossRefGoogle Scholar
  12. Hubbell JH, Seltzer SM (1989) Tables of X-Ray mass attenuation coefficients and mass energy-absorption coefficients. [Online] National Institute of Standards and Technology. http://www.nist.gov/pml/data/xraycoef/
  13. Katsevich A (2004) Improved exact filtered back-projection algorithm for spiral CT. Adv Appl Math 32:681–697MathSciNetCrossRefGoogle Scholar
  14. Mayo SC (2002) Quantitative X-ray projection microscopy: phase-contrast and multi-spectral imaging. J Microsc 207:79–96MathSciNetCrossRefGoogle Scholar
  15. Natterer F (1986) The mathematics of computerized tomography. B.G. Teubner, Stuttgart. ISBN 0-471-90959-9MATHGoogle Scholar
  16. Otendal M (2006) A compact high-brightness liquid-metal-jet X-ray source. Doctoral thesis, Department of Applied Physics, Royal Institute of Technology, StockholmGoogle Scholar
  17. Salamon M, Hanke R, Krüger P, Sukowski F, Uhlmann N, Voland V (2008a) Comparison of different methods for determining the size of a focal spot of microfocus X-ray tubes. Nucl Inst Methods Phys Res A 591:54–58CrossRefGoogle Scholar
  18. Salamon M, Hanke R, Krüger P, Uhlmann N, Voland V (2008b) Realization of a computed tomography setup to achieve resolutions below 1 μm. Nucl Inst Methods Phys Res A 591:50–53CrossRefGoogle Scholar
  19. Salamon M, Burtzlaff S, Voland V, Sukowski F, Uhlmann N (2009) Upcoming challenges in high resolution CT below 1 micron. Nucl Instrum Methods Phys Res A 607:176–178CrossRefGoogle Scholar
  20. Scholz O, Schmitt P, Kube M, Behrendt R, Uhlmann N (2009) Improvements in detector design for X-ray inspection of cast parts. SAE Int J Mater Manufac 2:134–139CrossRefGoogle Scholar
  21. Sidky EY, Pan X (2008) Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. Phys Med Biol 53:4777–4807CrossRefGoogle Scholar
  22. Stahlhut P, Ebensperger T, Zabler S, Hanke R (2013) Laboratory X-ray microscopy using a reflection target system and geometric magnification. J Phys Conf Ser 46:1–4Google Scholar
  23. Stahlhut P, Ebensperger T, Zabler S, Hanke R (2014) A laboratory X-ray microscopy setup using a field emission electron source and micro-structured reflection targets. Nucl Instrum Methods Phys Res, Sect B 324:4–10CrossRefGoogle Scholar
  24. Sukowski F, Yaneu JF, Salamon M, Ebert S, Uhlmann N (2009) Virtual detector characterization with Monte-Carlo-simulations. Nucl Instrum Methods Phys Res, Sect A 607:253–255CrossRefGoogle Scholar
  25. Zabler S, Fella C, Dietrich A (2012) High-resolution and high-speed CT in industry and research. In: SPIE conference: developments in X-ray tomography VIII, vol 8506Google Scholar
  26. Zou Y, Pan X (2004) Exact image reconstruction on PI-lines from minimum data in helical cone-beam CT. Phys Med Biol 49:941–959CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Fraunhofer IZFPSaarbruckenGermany
  2. 2.Fraunhofer EZRTFürthGermany

Section editors and affiliations

  • Ida Nathan
    • 1
  • Norbert Meyendorf
    • 2
  1. 1.Department of Electrical and Computer EngineeringUniversity of AkronAkronUSA
  2. 2.Center for Nondestructive EvaluationIowa State UniversityAmesUSA

Personalised recommendations