A New Approach for Motion Correction in SPECT Imaging

  • Hanno Schumacher
  • Bernd Fischer
Part of the Informatik aktuell book series (INFORMAT)


Due to the long imaging times in SPECT, patient motion is inevitable and constitutes a serious problem for any reconstruction algorithm. The measured inconsistent projection data lead to reconstruction artifacts which can significantly affect the diagnostic accuracy of SPECT if not corrected. Among the most promising attempts for addressing this cause of artifacts is the so-called data-driven motion correction methodology. But even this algorithm is restricted to the correction of abrupt rigid patient motion and exclusive correction of gradual motion, which may lead to unsatisfactory results. In this note we present for the first time a motion correction approach which overcomes the mentioned restrictions. The new approach is based on the super-resolution methodology. To demonstrate the performance of the proposed scheme, corrections of abrupt and gradual motion are presented.


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  1. 1.
    Wheat JM, Currie GM. Incidence and characterization of patient motion in myocardial perfusion SPECT: Part 1. J Nucl Med Technol 2004;32(2):60–65.Google Scholar
  2. 2.
    Botvinick EH, Zhu YY, O’Connell WJ, Dae MW. A quantitative assessment of patient motion and its effect on myocardial perfusion SPECT images. J Nucl Med 1993;34(2):303–310.Google Scholar
  3. 3.
    Cooper JA, Neumann PH, McCandless BK. Effect of patient motion on tomographic myocardial perfusion imaging. J Nucl Med 1992;33(8):1566–1571.Google Scholar
  4. 4.
    Friedman J, van Train K, Maddahi J, Rozanski A, Prigent F, Bietendorf J, et al. “Upward creep” of the heart: A frequent source of false-positive reversible defects during thallium-201 stress-redistribution SPECT. J Nucl Med 1989;30(10):1718–1722.Google Scholar
  5. 5.
    Pellot-Barakat C, Ivanovic M, Weber DA, Herment A, Shelton DK. Motion detection in triple scan SPECT imaging. IEEE Trans Nucl Sci 1998;45(4):2238–2244.CrossRefGoogle Scholar
  6. 6.
    Passalaqua AM, Narayanaswamy R. Patient motion correction of SPECT images: dual scan approach. IEEE Proc NSSS’94, Norfolk, VA 1995;3:1270–1274.Google Scholar
  7. 7.
    Lee KJ, Barber DC. Use of forward projection to correct patient motion during SPECT imaging. Phys Med Biol 1998;43:171–187.CrossRefGoogle Scholar
  8. 8.
    Chen QS, Franken PR, Defrise M, Jonckheer MH, Deconinck F. Detection and correction of patient motion in SPECT imaging. J Nucl Med Technol 1993;21(4):198–205.Google Scholar
  9. 9.
    Fulton RR, Eberl S, Meikle SR, Hutton BF, Braun M. A practical 3D tomographic method for correcting patient head motion in clinical SPECT. IEEE Trans Nucl Sci 1999;46(3):667–672.CrossRefGoogle Scholar
  10. 10.
    Kyme AZ, Hutton BF, Hatton RL, Skerrett DW, Barnden LR. Practical aspects of a data-driven motion correction approach for brain SPECT. IEEE Trans Med Imag 2003;22(6):722–729.CrossRefGoogle Scholar
  11. 11.
    Vogel CR, Oman ME. Fast numerical methods for total variation minimization in image reconstruction. Procs SPIE 1995.Google Scholar
  12. 12.
    Hanke M, Nagy JG, Vogel C. Quasi-Newton approach to nonnegative image restoration. Linear Algebra and its Applications 2000;316:223–236.zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Nocedal J, Wright SJ. Numerical Optimization. Springer; 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hanno Schumacher
    • 1
  • Bernd Fischer
    • 1
  1. 1.Institute of MathematicsUniversity of LübeckLübeckGermany

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