Evaluation of Two Iterative Techniques for Reducing Metal Artifacts in Computed Tomography

Published Online:https://doi.org/10.1148/radiol.11101782

Multidetector CT facilitates reduced metal artifacts in images from simulated and clinical scans and has the potential to improve diagnostic accuracy.


To evaluate two methods for reducing metal artifacts in computed tomography (CT)—the metal deletion technique (MDT) and the selective algebraic reconstruction technique (SART)—and compare these methods with filtered back projection (FBP) and linear interpolation (LI).

Materials and Methods

The institutional review board approved this retrospective HIPAA-compliant study; informed patient consent was waived. Simulated projection data were calculated for a phantom that contained water, soft tissue, bone, and iron. Clinical projection data were obtained retrospectively from 11 consecutively identified CT scans with metal streak artifacts, with a total of 178 sections containing metal. Each scan was reconstructed using FBP, LI, SART, and MDT. The simulated scans were evaluated quantitatively by calculating the average error in Hounsfield units for each pixel compared with the original phantom. Two radiologists who were blinded to the reconstruction algorithms used qualitatively evaluated the clinical scans, ranking the overall severity of artifacts for each algorithm. P values for comparisons of the image quality ranks were calculated from the binomial distribution.


The simulations showed that MDT reduces artifacts due to photon starvation, beam hardening, and motion and does not introduce new streaks between metal and bone. MDT had the lowest average error (76% less than FBP, 42% less than LI, 17% less than SART). Blinded comparison of the clinical scans revealed that MDT had the best image quality 100% of the time (95% confidence interval: 72%, 100%). LI had the second best image quality, and SART and FBP had the worst image quality. On images from two CT scans, as compared with images generated by the scanner, MDT revealed information of potential clinical importance.


For a wide range of scans, MDT yields reduced metal streak artifacts and better-quality images than does FBP, LI, or SART.

© RSNA, 2011

Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101782/-/DC1


  • 1 Kak AC, Slaney M. Principles of computerized tomographic imaging New York, NY: IEEE Press, 1988. Google Scholar
  • 2 De Man B, Nuyts J, Dupont P, Marchal G, Suetens P. Metal streak artifacts in x-ray computed tomography: a simulation study. IEEE Trans Nucl Sci 1999;46(3):691–696. CrossrefGoogle Scholar
  • 3 Joseph PM, Spital RD. The effects of scatter in x-ray computed tomography. Med Phys 1982;9(4):464–472. Crossref, MedlineGoogle Scholar
  • 4 Joseph PM, Spital RD. The exponential edge-gradient effect in x-ray computed tomography. Phys Med Biol 1981;26(3):473–487. Crossref, MedlineGoogle Scholar
  • 5 Hsieh J, Molthen RC, Dawson CA, Johnson RH. An iterative approach to the beam hardening correction in cone beam CT. Med Phys 2000;27(1):23–29. Crossref, MedlineGoogle Scholar
  • 6 De Man B, Nuyts J, Dupont P, Marchal G, Suetens P. Reduction of metal streak artifacts in x-ray computed tomography using a transmission maximum a posteriori algorithm. IEEE Trans Nucl Sci 2000;47(3):977–981. CrossrefGoogle Scholar
  • 7 Vandenberghe S, D’Asseler Y, Van de Walle Ret al.. Iterative reconstruction algorithms in nuclear medicine. Comput Med Imaging Graph 2001;25(2):105–111. Crossref, MedlineGoogle Scholar
  • 8 Verhoeven D. Limited-data computed tomography algorithms for the physical sciences. Appl Opt 1993;32(20):3736–3754. Crossref, MedlineGoogle Scholar
  • 9 De Man B, Nuyts J, Dupont P, Marchal G, Suetens P. An iterative maximum-likelihood polychromatic algorithm for CT. IEEE Trans Med Imaging 2001;20(10):999–1008. Crossref, MedlineGoogle Scholar
  • 10 Hsieh J. Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise. Med Phys 1998;25(11):2139–2147. Crossref, MedlineGoogle Scholar
  • 11 Glover GH, Pelc NJ. An algorithm for the reduction of metal clip artifacts in CT reconstructions. Med Phys 1981;8(6):799–807. Crossref, MedlineGoogle Scholar
  • 12 Mahnken AH, Raupach R, Wildberger JEet al.. A new algorithm for metal artifact reduction in computed tomography: in vitro and in vivo evaluation after total hip replacement. Invest Radiol 2003;38(12):769–775. Crossref, MedlineGoogle Scholar
  • 13 Kalender WA, Hebel R, Ebersberger J. Reduction of CT artifacts caused by metallic implants. Radiology 1987;164(2):576–577. LinkGoogle Scholar
  • 14 Rinkel J, Dillon WP, Funk T, Gould R, Prevrhal S. Computed tomographic metal artifact reduction for the detection and quantitation of small features near large metallic implants: a comparison of published methods. J Comput Assist Tomogr 2008;32(4):621–629. Crossref, MedlineGoogle Scholar
  • 15 Prell D, Kyriakou Y, Beister M, Kalender WA. A novel forward projection-based metal artifact reduction method for flat-detector computed tomography. Phys Med Biol 2009;54(21):6575–6591. Crossref, MedlineGoogle Scholar
  • 16 Hubbell J, Seltzer S. Tables of x-ray mass attenuation coefficients and mass energy-absorption coefficients. National Institute of Standards and Technology Web site. http://physics.nist.gov/PhysRefData/XrayMassCoef/cover.html. Accessed February 21, 2010. Google Scholar
  • 17 Flohr TG, Stierstorfer K, Ulzheimer S, Bruder H, Primak AN, McCollough CH. Image reconstruction and image quality evaluation for a 64-slice CT scanner with z-flying focal spot. Med Phys 2005;32(8):2536–2547. Crossref, MedlineGoogle Scholar
  • 18 Schaller S, Stierstorfer K, Bruder H, Kachelrieß M, Flohr T. Novel approximate approach for high-quality image reconstruction in helical cone beam CT at arbitrary pitch. Proc SPIE 2001;4322:113–127. CrossrefGoogle Scholar
  • 19 Devore JL. Probability and statistics for engineering and the sciences Pacific Grove, Calif: Brooks/Cole, 1991. CrossrefGoogle Scholar
  • 20 Clopper CJ, Pearson ES. The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 1934;26(4):404–413. CrossrefGoogle Scholar
  • 21 Prell D, Kyriakou Y, Kachelrie M, Kalender WA. Reducing metal artifacts in computed tomography caused by hip endoprostheses using a physics-based approach. Invest Radiol 2010;45(11):747–754. Crossref, MedlineGoogle Scholar
  • 22 Robertson DD, Yuan J, Wang G, Vannier MW. Total hip prosthesis metal-artifact suppression using iterative deblurring reconstruction. J Comput Assist Tomogr 1997;21(2):293–298. Crossref, MedlineGoogle Scholar

Article History

Received September 20, 2010; revision requested November 10; revision received November 24; accepted December 10; final version accepted December 20.
Published online: June 2011
Published in print: June 2011