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Motion Correction in Conventional Nuclear Medicine Imaging

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Book cover Technologies for Medical Sciences

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 1))

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Abstract

In an imaging technique, it makes sense to address the issue of motion correction only if the relation between the frame rate of the image acquisition and the speed of the motion is such that there is an impact on the acquired image. When the acquisition frame rate is much higher than the speed of motion of the object, the harmful effects on the acquired images can usually be neglected. However, the opposite has dramatic consequences on the images, requiring specific procedures to correct for the motion effects.

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Notes

  1. 1.

    Septa are the walls that confine a hole of the collimator.

  2. 2.

    The photoelectric fration, \( \varepsilon \), is given by – \( \varepsilon = {{{{\sigma_F}}} \left/ {{\left( {{\sigma_F} + {\sigma_C}} \right)}} \right.} \)- which is the relation between the photoelectric scattering cross section, \( {\sigma_F} \) and the Compton scattering cross section \( {\sigma_C} \) [6].

  3. 3.

    In fact, other photons whose path is slightly tilted to perpendicular will also be detected which causes image blurring and loss of spatial resolution. (Fig. 5).

  4. 4.

    Quantitative Perfusion SPECT.

References

  1. Prata MI, Abrunhosa A (2008) Física em Medicina Nuclear: Temas e Aplicações. Imprensa da Universidade de Coimbra

    Google Scholar 

  2. Klein O, Nishina Y (1928) The scattering of light by free electrons according to dirac’s new relativistic dynamics. Nature 122:398–399

    Article  MATH  Google Scholar 

  3. http://physics.nist.gov/PhysRefData/Xcom/html/xcom1.html

  4. Anger HO (1964) Scintillation camera with multichannel collimators. J Nucl Med 5:515–531

    Google Scholar 

  5. Ricard M (2004) Imaging of gamma emitters using scintillation cameras. Nucl Instrum Methods Phys Res, Sect A 527(1–2):124–129

    Article  Google Scholar 

  6. Derenzo SE, Moses WW, Weber MJ, West AC (1994) Methods for a systematic, comprehensive search for fast, heavy scintillator materials. In: Materials research society symposium - proceedings, vol 348, Lawrence Berkeley Lab, Berkeley, pp 39–49

    Google Scholar 

  7. Moses W, Gayshan V, Gektin A (2006) The evolution of SPECT from anger to today and beyond. In: Radiation detectors for medical applications, pp. 37–80

    Google Scholar 

  8. Knoll GF (1979) Radiation detection and measurement. Wiley, New York

    Google Scholar 

  9. Links JM, Prince JL (2006) Medical imaging signals and systems. Pearson Prentice-Hall Bioengineering, New Jersey

    Google Scholar 

  10. Wernick MN, Aarsvold JN (eds) (2004) Emission tomography - the fundamentals of PET and SPECT. Elsevier Academic Press, San Diego, CA

    Google Scholar 

  11. Lee-Tzuu C (1978) A method for attenuation correction in radionuclide computed tomography. IEEE Trans Nucl Sci 25(1):638–643

    Article  Google Scholar 

  12. Novikov R (2002) An inversion formula for the attenuated x-ray transformation. Arkiv för Matematik 40(1):145–167

    Article  MATH  Google Scholar 

  13. Sidky EY, Pan X (2002) Variable sinograms and redundant information in single-photon emission computed tomography with non-uniform attenuation. Inverse Probl 18(6):1483–1497

    Article  MathSciNet  MATH  Google Scholar 

  14. Markoe A (1984) Fourier inversion of the attenuated x-ray transform. SIAM J Math Anal 15(4):718–722

    Article  MathSciNet  MATH  Google Scholar 

  15. Frey EC, Tsui BMW (2006) Quantitative analysis in nuclear medicine imaging. Springer, New York

    Google Scholar 

  16. http://www.dspguide.com/ch25/5.htm

  17. Bruyant PP (2002) Analytic and iterative reconstruction algorithms in spect. J Nucl Med 43(10):1343–1358

    Google Scholar 

  18. Gordon R, Bender R, Herman GT (1970) Algebraic reconstruction techniques (art) for three-dimensional electron microscopy and x-ray photography. J Theor Biol 29(3):471–481

    Article  Google Scholar 

  19. Herman GT, Meyer LB (1993) Algebraic reconstruction techniques can be made computationally efficient [positron emission tomography application]. IEEE Trans Med Imaging 12(3):600–609

    Article  Google Scholar 

  20. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the em algorithm. J R Stat Soc 39:1–38

    MathSciNet  MATH  Google Scholar 

  21. Shepp LA, Vardi Y (1982) Maximum likelihood reconstruction for emission tomography. IEEE Trans Med Imaging 1(2):113–122

    Article  Google Scholar 

  22. Hudson HM, Larkin RS (1994) Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging 13(4):601–609

    Article  Google Scholar 

  23. Zaidi H, Hutton BF, Nuyts J (2006) Quantitative analysis in nuclear medicine imaging. Springer, New York

    Book  Google Scholar 

  24. Murase K, Ishine M, Kataoka M, Itoh H, Mogami H, Iio A, Hamamoto K (1987) Simulation and experimental study of respiratory motion effect on image quality of single photon emission computed tomography (spect). Eur J Nucl Med 13(5):244–249

    Article  Google Scholar 

  25. Botvinick EH, Zhu YY, O’Connell WJ, Dae MW (1993) A quantitative assessment of patient motion and its effect on myocardial perfusion spect images. J Nucl Med 34(2):303–310

    Google Scholar 

  26. Cooper JA, Neumann PH, McCandless BK (1992) Effect of patient motion on tomographic myocardial perfusion imaging. J Nucl Med 33(8):1566–1571

    Google Scholar 

  27. Eisner R, Churchwell A, Noever T, Nowak D, Cloninger K, Dunn D, Carlson W, Oates J, Jones J, Morris D (1988) Quantitative analysis of the tomographic thallium-201 myocardial bullseye display: critical role of correcting for patient motion. J Nucl Med 29(1):91–97

    Google Scholar 

  28. Friedman J, Berman DS, Van Train K, Garcia EV, Bietendorf J, Prigent F, Rozanski A, Waxman A, Maddahi J (1988) Patient motion in thallium-201 myocardial spect imaging. an easily identified frequent source of artifactual defect. Clin Nucl Med 13(5):321–324

    Article  Google Scholar 

  29. Friedman J, Van Train K, Maddahi J, Rozanski A, Prigent F, Bietendorf J, Waxman A, Berman DS (1989) “upward creep” of the heart: a frequent source of false-positive reversible defects during thallium-201 stress-redistribution spect. J Nucl Med 30(10):1718–1722

    Google Scholar 

  30. Germano G, Kavanagh PB, Kiat H, Van Train K, Berman DS (1994) Temporal image fractionation: rejection of motion artifacts in myocardial spect. J Nucl Med 35(7):1193–1197

    Google Scholar 

  31. Ter-Pogossian MM, Bergmann SR, Sobel BE (1982) Influence of cardiac and respiratory motion on tomographic reconstructions of the heart: implications for quantitative nuclear cardiology. J Comput Assist Tomogr 6(6):1148–1155

    Article  Google Scholar 

  32. Tsui BMW, Segars WP, Lalush DS (2000) Effects of upward creep and respiratory motion in myocardial spect. IEEE Trans Nucl Sci 47(3):1192–1195

    Google Scholar 

  33. Wheat JM, Currie GM (2004) Impact of patient motion on myocardial perfusion spect diagnostic integrity: part 2. J Nucl Med Technol 32(3):158–163

    Google Scholar 

  34. Erdi YE, Nehmeh SA, Pan T, Pevsner A, Rosenzweig KE, Mageras G, Yorke ED, Schoder H, Hsiao W, Squire OD, Vernon P, Ashman JB, Mostafavi H, Larson SM, Humm JL (2004) The ct motion quantitation of lung lesions and its impact on pet-measured suvs. J Nucl Med 45(8):1287–1292

    Google Scholar 

  35. Goerres GW, Kamel E, Heidelberg T-NH, Schwitter MR, Burger C, von Schulthess GK (2002) Pet-ct image co-registration in the thorax: influence of respiration. Eur J Nucl Med Mol Imaging 29(3):351–360

    Article  Google Scholar 

  36. Visvikis D, Barret O, Fryer TD, Lamare F, Turzo A, Bizais Y, Le Rest C.C (2004) Evaluation of respiratory motion effects in comparison with other parameters affecting pet image quality. In: Nuclear science symposium conference record, 2004 IEEE, vol 6, pp 3668–3672

    Google Scholar 

  37. Boucher L, Rodrigue S, Lecomte R, Bénard F (2004) Respiratory gating for 3-dimensional pet of the thorax: feasibility and initial results. J Nucl Med 45(2):214–219

    Google Scholar 

  38. Nehmeh SA, Erdi YE, Ling CC, Rosenzweig KE, Squire OD, Braban LE, Ford E, Sidhu K, Mageras GS, Larson SM, Humm JL (2002) Effect of respiratory gating on reducing lung motion artifacts in pet imaging of lung cancer. Med Phys 29(3):366–371

    Article  Google Scholar 

  39. Balter JM, Ten Haken RK, Lawrence TS, Lam KL, Robertson JM (1996) Uncertainties in ct-based radiation therapy treatment planning associated with patient breathing. Int J Radiat Oncol Biol Phys 36(1):167–174

    Article  Google Scholar 

  40. Hugo GD, Agazaryan N, Solberg TD (2003) The effects of tumor motion on planning and delivery of respiratory-gated imrt. Med Phys 30(6):1052–1066

    Article  Google Scholar 

  41. Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, van Herk M, Lebesque JV, Miyasaka K (2002) Precise and real-time measurement of 3d tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 53(4):822–834

    Article  Google Scholar 

  42. Shimizu S, Shirato H, Kagei K, Nishioka T, Bo X, Dosaka-Akita H, Hashimoto S, Aoyama H, Tsuchiya K, Miyasaka K (2000) Impact of respiratory movement on the computed tomographic images of small lung tumors in three-dimensional (3d) radiotherapy. Int J Radiat Oncol Biol Phys 46(5):1127–1133

    Article  Google Scholar 

  43. Baimel NH, Bronskill MJ (1978) Optimization of analog-circuit motion correction for liver scintigraphy. J Nucl Med 19(9):1059–1066

    Google Scholar 

  44. Elings VB, Martin CB, Pollock IG, McClintock JT (1974) Electronic device corrects for motion in gamma camera images. J Nucl Med 15(1):36–37

    Google Scholar 

  45. Oppenheim BE (1971) A method using a digital computer for reducing respiratory artifact on liver scans made with a camera. J Nucl Med 12(9):625–628

    Google Scholar 

  46. Fleming JS (1984) A technique for motion correction in dynamic scintigraphy. Eur J Nucl Med 9(9):397–402

    Article  Google Scholar 

  47. Britten AJ, Jamali F, Gane JN, Joseph AE (1998) Motion detection and correction using multi-rotation 180 degrees single-photon emission tomography for thallium myocardial imaging. Eur J Nucl Med 25(11):1524–1530

    Article  Google Scholar 

  48. Eisner RL, Noever T, Nowak D, Carlson W, Dunn D, Oates J, Cloninger K, Liberman HA, Patterson RE (1987) Use of cross-correlation function to detect patient motion during spect imaging. J Nucl Med 28(1):97–101

    Google Scholar 

  49. Pellot-Barakat C, Ivanovic M, Weber DA, Herment A, Shelton DK (1998) Motion detection in triple scan spect imaging. IEEE Trans Nucl Sci 45(4):2238–2244

    Article  Google Scholar 

  50. Geckle WJ, Frank TL, Links JM, Becker LC (1988) Correction for patient and organ movement in spect: application to exercise thallium-201 cardiac imaging. J Nucl Med 29(4):441–450

    Google Scholar 

  51. Cooper JA, Neumann PH, McCandless BK (1993) Detection of patient motion during tomographic myocardial perfusion imaging. J Nucl Med 34(8):1341–1348

    Google Scholar 

  52. Germano G, Chua T, Kavanagh PB, Kiat H, Berman DS (1993) Detection and correction of patient motion in dynamic and static myocardial spect using a multi-detector camera. J Nucl Med 34(8):1349–1355

    Google Scholar 

  53. Noumeir R, Mailloux GE, Lemieux R (1996) Detection of motion during tomographic acquisition by an optical flow algorithm. Comput Biomed Res 29(1):1–15

    Article  Google Scholar 

  54. Leslie WD, Dupont JO, McDonald D, Peterdy AE (1997) Comparison of motion correction algorithms for cardiac spect. J Nucl Med 38(5):785–790

    Google Scholar 

  55. O’Connor MK, Kanal KM, Gebhard MW, Rossman PJ (1998) Comparison of four motion correction techniques in spect imaging of the heart: a cardiac phantom study. J Nucl Med 39(12):2027–2034

    Google Scholar 

  56. Bloomfield PM, Spinks TJ, Reed J, Schnorr L, Westrip AM, Livieratos L, Fulton R, Jones T (2003) The design and implementation of a motion correction scheme for neurological pet. Phys Med Biol 48(8):959–978

    Article  Google Scholar 

  57. Bruyant PP, Nadella S, Gennert MA, King MA (2005) Quality control of the stereo calibration of a visual tracking system (vts) for patient motion detection in spect. In: IEEE nuclear science symposium conference record, vol 5, pp 2599–2602

    Google Scholar 

  58. Gennert MA, Bruyant PP, Narayanan MV, King MA (2002) Assessing a system to detect patient motion in spect imaging using stereo optical cameras. In: IEEE nuclear science symposium conference record, vol 3, pp 1567–1570

    Google Scholar 

  59. Goddard JS, Gleason SS, Paulus MJ, Majewski S, Popov V, Smith M, Weisenberger A, Welch B, Wojcik R (2002) Real-time landmark-based unrestrained animal tracking system for motion-corrected pet/spect imaging. In: IEEE nuclear science symposium conference record, vol 3, pp 1534–1537

    Google Scholar 

  60. Weisenberger AG, Gleason SS, Goddard J, Kross B, Majewski S, Meikle SR, Paulus MJ, Pomper M, Popov V, Smith MF, Welch BL, Wojcik R (2005) A restraint-free small animal spect imaging system with motion tracking. IEEE Trans Nucl Sci 52(3):638–644

    Google Scholar 

  61. Weisenberger AG, Kross B, Gleason SS, Goddard J, Majewski S, Meikle SR, Paulus MJ, Pomper M, Popov V, Smith MF, Welch BL, Wojcik R (2003) Development and testing of a restraint free small animal spect imaging system with infrared based motion tracking. In: IEEE nuclear science symposium conference record, vol 3, pp 2090–2094

    Google Scholar 

  62. Nehmeh SA, Erdi YE (2008) Respiratory motion in positron emission tomography/computed tomography: a review. Semin Nucl Med 38(3):167–176

    Article  Google Scholar 

  63. Fitzgerald J, Danias PG (2001) Effect of motion on cardiac spect imaging: recognition and motion correction. J Nucl Cardiol 8(6):701–706

    Article  Google Scholar 

  64. De Agostini A, Moretti R, Belletti S, Maira G, Magri GC, Bestagno M (1992) A motion correction algorithm for an image realignment programme useful for sequential radionuclide renography. Eur J Nucl Med 19(7):476–483

    Article  Google Scholar 

  65. Fulton RR, Hutton BF, Braun M, Ardekani B, Larkin R (1994) Use of 3d reconstruction to correct for patient motion in spect. Phys Med Biol 39(3):563–574

    Article  Google Scholar 

  66. Fulton RR, Eberl S, Meikle SR, Hutton BF, Braun M (1999) A practical 3d tomographic method for correcting patient head motion in clinical spect. IEEE Tran Nucl Sci 46(3):667–672

    Article  Google Scholar 

  67. Ma L, Gu S, Nadella S, Bruyant PP, King MA, Gennert MA (2005) A practical rebinning-based method for patient motion compensation in spect imaging. In: Proceedings of international conference on computer graphics, imaging and vision: new trends, pp 209–214

    Google Scholar 

  68. Songxiang Gu, McNamara JE, Mitra J, Gifford HC, Johnson K, Gennert MA, King M.A (2007) Body deformation correction for spect imaging. In: IEEE nuclear science symposium conference record NSS’07, vol 4, pp 2708–2714

    Google Scholar 

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Authors and Affiliations

  1. Institute of Biomedical Research on Light and Image – IBILI, Faculty of Medicine, University of Coimbra, Coimbra, Portugal

    Francisco J. Caramelo & Nuno C. Ferreira

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  1. Francisco J. Caramelo
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  2. Nuno C. Ferreira
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Correspondence to Francisco J. Caramelo .

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Editors and Affiliations

  1. Porto, 4200-465, Portugal

    Renato M. Natal Jorge

  2. Fac. Engenharia, Lab. Engenharia de Processos,, Universidade do Porto, Rua Dr. Roberto Frias, Porto, 4200-465, Portugal

    João Manuel R. S. Tavares

  3. UFMG, Laboratorio de Bioengenharia, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte, 31270-901, Minas Gerais, Brazil

    Marcos Pinotti Barbosa

  4. University of Dundee, College of Art, Science and Engineering, Medical Engineering Research Institute, Dundee, DD1 4 HN, United Kingdom

    A.P. Slade

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Caramelo, F.J., Ferreira, N.C. (2012). Motion Correction in Conventional Nuclear Medicine Imaging. In: Natal Jorge, R., Tavares, J., Pinotti Barbosa, M., Slade, A. (eds) Technologies for Medical Sciences. Lecture Notes in Computational Vision and Biomechanics, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4068-6_6

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  • DOI: https://doi.org/10.1007/978-94-007-4068-6_6

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