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Conventional and Newer Reconstruction Techniques in CT

  • Homer Pien
  • Synho Do
  • Sarabjeet Singh
  • Mannudeep K. Kalra
Part of the Medical Radiology book series (MEDRAD)

Abstract

Heightened concerns over increasing radiation dose from CT scanning have highlighted limitations of real-time image reconstruction methods using conventional filtered back-projection techniques. Significant advances in computational power have enabled commercial availability of several iterative approaches for CT image reconstruction and processing. These techniques enable radiation dose reduction, as well as opportunity to improve scanner resolution, while reducing some image artifacts. In this chapter, we review the technical basis of conventional and newer reconstruction techniques for CT.

Keywords

Reconstruction Algorithm Iterative Reconstruction Iterative Reconstruction Algorithm Image Reconstruction Algorithm Iterative Reconstruction Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Buzug TM (2008) Computed tomography: from photon statistics to modern cone-beam CT. Springer, BerlinGoogle Scholar
  2. Do S, Karl WC, Kalra MK, Brady TJ, Pien H (2010) A variational approach for reconstructing low dose images in clinical helical CT. IEEE Int’l Symp Biomed ImagingGoogle Scholar
  3. Do S, Karl WC, Liang Z, Kalra M, Brady TJ, Pien H (2011) A decomposition-based CT reconstruction algorithm for reducing blooming artifacts. Phys Med Biol 56:7109–7125PubMedCrossRefGoogle Scholar
  4. Feldkamp LA, David LC, Kress JW (1984) Practical cone-beam algorithm. J Opt Soc Am A1:612–619CrossRefGoogle Scholar
  5. Gervaise A, Osemont B, Lecocq S, Noel A, Micard E et al (2011) CT image quality improvement using adaptive iterative dose reduction with wide-volume acquisition. Eur Radiol [epub ahead of print]Google Scholar
  6. Gonzalez RC, Woods RE (2002) Digital image processing 2nd edn. Prentice-Hall, Upper Saddle RiverGoogle 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 29:471–481PubMedCrossRefGoogle Scholar
  8. Gordon R, Herman GT (1971) Reconstruction of pictures from their projections. Commun Assoc Comput Mach 14:759–768Google Scholar
  9. Kak AC, Slaney M (1988) Principles of computerized tomographic imaging. IEEE Press, New YorkGoogle Scholar
  10. Kalra MK, Niels W, Woisetschläger M, Singh S, Lindblom M, Choy G et al Radiation dose reduction with Sinogram Affirmed Iterative Reconstruction Technique for abdominal CT. Radiology (to appear)Google Scholar
  11. Katsevich A (2002) Theoretically exact FBP-type inversion algorithm for spiral CT. SIAM J Appl Math 62:2012–2026CrossRefGoogle Scholar
  12. Katsevich A (2004) An improved exact filtered backprojection algorithm for spiral computed tomography. Adv Appl Math 32:681–697CrossRefGoogle Scholar
  13. Kohler T, Proksa R, Bontus C, Grass M (2002) Artifact analysis of approximate helical cone-beam CT reconstruction algorithms. Med Phys 29:51–64 PubMedCrossRefGoogle Scholar
  14. Leipsic J, Heilbron BG, Hague C (2011) Iterative reconstruction for coronary CT angiography: finding its way. Int J Cardiovasc Imag [epub ahead of print]Google Scholar
  15. Nelson RC, Feuerlein S, Boll DT (2011) New iterative reconstruction techniques for cardiovascular computed tomography: how do they work, and what are their advantages and disadvantages? J Cardiovasc Comput Tomogr 5:286–292PubMedCrossRefGoogle Scholar
  16. Prakash P, Kalra MK, Kambadakone AK, Pien H, Hsieh J, Blake MA et al (2010a) Reducing abdominal CT radiation dose with adaptive statistical iterative reconstruction technique. Invest Radiol 45:202–210PubMedCrossRefGoogle Scholar
  17. Prakash P, Kalra MK, Ackman JB, Digumarthy SR, Hsieh J, Do S et al (2010b) Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology 256:261–269PubMedCrossRefGoogle Scholar
  18. Prakash P, Kalra MK, Digumarthy SR, Hsieh J, Pien H, Singh S et al (2010c) Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience. J Comput Assist Tomogr 34:40–45PubMedCrossRefGoogle Scholar
  19. Shepp LA, Vardi Y (1982) Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imag MI-1:113–122CrossRefGoogle Scholar
  20. Singh S, Kalra MK, Gilman MD, Hsieh J, Pien HH, Digumarthy SR et al (2011) Adaptive statistical iterative reconstruction technique for radiation dose reduction in chest CT: a pilot study. Radiology 2011(259):565–573CrossRefGoogle Scholar
  21. Singh S, Kalra MK, Hsieh J, Licato PE, Do S, Pien HH (2010) Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology 257:373–383PubMedCrossRefGoogle Scholar
  22. Singh S, Kalra MK, Bhangle AS, Saini A, Gervais DA, Westra SJ et al Pediatric CT protocols: Radiation dose reduction with hybrid iterative reconstruction. Radiology (in press)Google Scholar
  23. Singh S, Kalra MK, Do S, Thibault JB, Pien H, Connor OJ et al Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: dose reduction potential in the abdomen. J Comput Assist Tomogr (in press)Google Scholar
  24. Swindell W, Webb S (1988) X-ray transmission computed tomography. In: Webb S (ed) The physics of medical imaging. IOP Publishing, PhiladelphiaGoogle Scholar
  25. Thibault JB, Sauer KD, Bouman CA, Hsieh J (2007) A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 34:4526–4544PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Homer Pien
    • 1
  • Synho Do
    • 1
  • Sarabjeet Singh
    • 1
  • Mannudeep K. Kalra
    • 1
  1. 1.Department of RadiologyMassachusetts General HospitalBostonUSA 

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