Skip to main content
SpringerLink
Log in

Multimodality image registration with software: state-of-the-art

  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Introduction

Multimodality image integration of functional and anatomical data can be performed by means of dedicated hybrid imaging systems or by software image co-registration techniques. Hybrid positron emission tomography (PET)/computed tomography (CT) systems have found wide acceptance in oncological imaging, while software registration techniques have a significant role in patient-specific, cost-effective, and radiation dose-effective application of integrated imaging.

Objectives

Software techniques allow accurate (2–3 mm) rigid image registration of brain PET with CT and MRI. Nonlinear techniques are used in whole-body image registration, and recent developments allow for significantly accelerated computing times. Nonlinear software registration of PET with CT or MRI is required for multimodality radiation planning. Difficulties remain in the validation of nonlinear registration of soft tissue organs. The utilization of software-based multimodality image integration in a clinical environment is sometimes hindered by the lack of appropriate picture archiving and communication systems (PACS) infrastructure needed to efficiently and automatically integrate all available images into one common database.

Discussion

In cardiology applications, multimodality PET/single photon emission computed tomography and coronary CT angiography imaging is typically not required unless the results of one of the tests are equivocal. Software image registration is likely to be used in a complementary fashion with hybrid PET/CT or PET/magnetic resonance imaging systems. Software registration of stand-alone scans “paved the way” for the clinical application of hybrid scanners, demonstrating practical benefits of image integration before the hybrid dual-modality devices were available.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Townsend DW. A combined PET/CT scanner: the choices. J Nucl Med 2001;42(3):533–4.

    PubMed  CAS  Google Scholar 

  2. Schillaci O. Hybrid SPECT/CT: a new era for SPECT imaging? Eur J Nucl Med Mol Imaging 2005;32(5):521–4.

    Article  PubMed  Google Scholar 

  3. Antoch G, Kanja J, Bauer S, Kuehl H, Renzing-Koehler K, Schuette J, et al. Comparison of PET, CT, and dual-modality PET/CT imaging for monitoring of imatinib (STI571) therapy in patients with gastrointestinal stromal tumors. J Nucl Med 2004;45(3):357–65.

    PubMed  CAS  Google Scholar 

  4. Slomka PJ. Software approach to merging molecular with anatomic information. J Nucl Med 2004;45(1 Suppl):36S–45S.

    PubMed  Google Scholar 

  5. Cherry SR, Louie AY, Jacobs RE. The integration of positron emission tomography with magnetic resonance imaging. Proc IEEE 2008;96(3):416–38.

    Article  CAS  Google Scholar 

  6. Pelizzari CA, Chen GT, Spelbring DR, Weichselbaum RR, Chen CT. Accurate three-dimensional registration of CT, PET, and/or MR images of the brain. J Comput Assist Tomogr 1989;13(1):20–6.

    Article  PubMed  CAS  Google Scholar 

  7. Alpert NM. The principal axes transformation—a method for image registration. J Nucl Med 1990;31(10):1717–22.

    PubMed  CAS  Google Scholar 

  8. Besl P, McKay N. A method for registration of 3D shapes. IEEE Trans Pattern Anal Machine Intell 1992;14:239–56.

    Article  Google Scholar 

  9. Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P. Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging 1997;16(2):187–98.

    Article  PubMed  CAS  Google Scholar 

  10. Wells WM, Viola P, Atsumi H, Nakajima S, Kikinis R. Multi-modal volume registration by maximization of mutual information. Med Image Anal 1996;1(1):35–51.

    Article  PubMed  Google Scholar 

  11. Meyer CR, Boes JL, Kim B, Bland PH, Zasadny KR, Kison PV, et al. Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations. Med Image Anal 1997;1(3):195–206.

    Article  PubMed  CAS  Google Scholar 

  12. Holden M. A review of geometric transformations for nonrigid body registration. IEEE Trans Med Imag 2008;27(1):111.

    Article  CAS  Google Scholar 

  13. Bookstein FL. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Machine Intell 1989;11(6):567–85.

    Article  Google Scholar 

  14. Rueckert D, Sonoda LI, Hayes C, Hill DL, Leach MO, Hawkes DJ. Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imaging 1999;18(8):712–1.

    Article  PubMed  CAS  Google Scholar 

  15. Barron JL, Fleet DJ, Beauchemin SS. Performance of optical flow techniques. Int J Comput Vis 1994;12(1):43–77.

    Article  Google Scholar 

  16. Klein GJ, Reutter BW, Huesman RH. Non-rigid summing of gated PET via optical flow. IEEE Trans Nucl Sci 1997;44(4):1509–11.

    Article  Google Scholar 

  17. Vemuri BC, Huang S, Sahni S, Leonard CM, Mohr C, Gilmore R, Fitzsimmons J. An efficient motion estimator with application to medical image registration. Med Image Anal 1998;2(1):79–98.

    Article  PubMed  CAS  Google Scholar 

  18. Strehl N, Tomei S, Rosenman J, Joshi S. Large deformation three-dimensional image registration in image-guided radiation therapy. Phys Med Biol 2005;50:5869–92.

    Article  PubMed  Google Scholar 

  19. Wang H, Dong L, O’Daniel J, Mohan R, Garden AS, Ang KK, et al. Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy. Phys Med Biol 2005;50(12):2887–905.

    Article  PubMed  CAS  Google Scholar 

  20. Tsao J. Interpolation artifacts in multimodality image registration based on maximization of mutual information. IEEE Trans Med Imaging 2003;22(7):854–64.

    Article  PubMed  Google Scholar 

  21. Wolz G, Namayr A, Hothorn T, Hornegger J, Ramer W, Bautz W, et al. Comparison of performance between rigid and non-rigid software registering CT to FDG-PET. Int J Comput Assist Radiol Surg. 2007;2(3–4):183–90.

    Article  Google Scholar 

  22. Slomka PJ, Dey D, Przetak C, Aladl UE, Baum RP. Automated 3-dimensional registration of stand-alone (18)F-FDG whole-body PET with CT. J Nucl Med. 2003;44(7):1156–67.

    PubMed  Google Scholar 

  23. Levin D, Dey D, Slomka PJ. Acceleration of nonlinear warping using standard video graphics hardware: implementation and initial validation. Comput Med Imaging Graph 2004;28:471–83.

    Article  PubMed  Google Scholar 

  24. Lu W, Chen M-L, Olivera GH, Ruchala KJ, Mackie TR. Fast free-form deformable registration via calculus of variations. Phys Med Biol 2004;49(14):3067–87.

    Article  PubMed  Google Scholar 

  25. Goerres GW, Kamel E, Seifert B, Burger C, Buck A, Hany TF, et al. Accuracy of image coregistration of pulmonary lesions in patients with non-small cell lung cancer using an integrated PET/CT system. J Nucl Med 2002;43(11):1469–75.

    PubMed  Google Scholar 

  26. Nehmeh SA, Erdi YE, Pan T, Pevsner A, Rosenzweig KE, Yorke E, et al. Four-dimensional (4D) PET/CT imaging of the thorax. Med Phys 2004;31(12):3179–86.

    Article  PubMed  CAS  Google Scholar 

  27. Kim JH, Czernin J, Allen-Auerbach MS, Halpern BS, Fueger BJ, Hecht JR, et al. Comparison between 18F-FDG PET, in-line PET/CT, and software fusion for restaging of recurrent colorectal cancer. J Nucl Med 2005;46(4):578–95.

    Google Scholar 

  28. West J, Fitzpatrick JM, Wang MY, Dawant BM, Maurer CR, Kessler RM, et al. Retrospective intermodality registration techniques for images of the head: surface-based versus volume-based. IEEE Trans Med Imaging 1999;18(2):144–50.

    Article  PubMed  CAS  Google Scholar 

  29. West J, Fitzpatrick JM, Wang MY, Dawant BM, Maurer CR, Kessler RM, et al. Comparison and evaluation of retrospective intermodality brain image registration techniques. J Comput Assist Tomogr 1997;21(4):554–66.

    Article  PubMed  CAS  Google Scholar 

  30. Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC. Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput.Assist.Tomogr 1998;22(1):139–52.

    Article  PubMed  CAS  Google Scholar 

  31. Woods RP, Mazziotta JC, Cherry SR. MRI-PET registration with automated algorithm. J Comput Assist Tomogr 1993;17(4):536–46.

    Article  PubMed  CAS  Google Scholar 

  32. Strother SC, Anderson JR, Xu XL, Liow JS, Bonar DC, Rottenberg DA. Quantitative comparisons of image registration techniques based on high-resolution MRI of the brain. J Comput Assist Tomogr 1994;18(6):954–62.

    Article  PubMed  CAS  Google Scholar 

  33. Levin DN, Pelizzari CA, Chen GT, Chen CT, Cooper MD. Retrospective geometric correlation of MR, CT, and PET images. Radiology 1988;169(3):817–23.

    PubMed  CAS  Google Scholar 

  34. Turkington TG, Hoffman JM, Jaszczak RJ, MacFall JR, Harris CC, Kilts CD, et al. Accuracy of surface fit registration for PET and MR brain images using full and incomplete brain surfaces. J Comput.Assist Tomogr 1995;19(1):117–24.

    Article  PubMed  CAS  Google Scholar 

  35. Andersson JL, Sundin A, Valind S. A method for coregistration of PET and MR brain images. J Nucl Med 1995;36(7):1307–15.

    PubMed  CAS  Google Scholar 

  36. Studholme C, Hill DL, Hawkes DJ. Automated 3-D registration of MR and CT images of the head. Med Image Anal 1996;1(2):163–75.

    Article  PubMed  CAS  Google Scholar 

  37. Hawkes DJ. Algorithms for radiological image registration and their clinical application. J Anat 1998;193(Pt 3):347–61.

    Article  PubMed  Google Scholar 

  38. Maintz JB, Viergever MA. A survey of medical image registration. Med Image Anal 1998;2(1):1–36.

    Article  PubMed  CAS  Google Scholar 

  39. Hill DL, Batchelor PG, Holden M, Hawkes DJ. Medical image registration. Phys Med Biol 2001;46(3):R1–45.

    Article  PubMed  CAS  Google Scholar 

  40. Hutton BF, Braun M. Software for image registration: algorithms, accuracy, efficacy. Semin Nucl Med 2003;33(3):180–92.

    Article  PubMed  Google Scholar 

  41. Pluim JPW, Maintz JBA, Viergever MA. Mutual-information-based registration of medical images: a survey. IEEE Trans Med Imaging 2003;22(8):986–1004.

    Article  PubMed  Google Scholar 

  42. Studholme C, Hawkes DJ, Hill DL. A normalized entropy measure for multimodality image alignment. SPIE Phys Med Imaging 1998;3338:132–43.

    Google Scholar 

  43. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994;18(2):192–205.

    Article  PubMed  CAS  Google Scholar 

  44. Woods RP, Grafton ST, Watson JD, Sicotte NL, Mazziotta JC. Automated image registration: II. Intersubject validation of linear and nonlinear models. J Comput Assist Tomogr 1998;22(1):153–65.

    Article  PubMed  CAS  Google Scholar 

  45. Radau PE, Slomka PJ. Constrained localized warping reduced registration errors due to lesions in functional neuroimages. SPIE Proc SPIE Med Imaging 2001;4322:588–601.

    Google Scholar 

  46. Radau PE, Slomka PJ, Julin P, Svensson L, Wahlund LO. Evaluation of linear registration algorithms for brain SPECT and the errors due to hypoperfusion lesions. Med Phys 2001;28(8):1660–8.

    Article  PubMed  CAS  Google Scholar 

  47. Radau PE, Linke R, Slomka PJ, Tatsch K. Optimization of automated quantification of 123I-IBZM uptake in the striatum applied to parkinsonism. J Nucl Med 2000;41(2):220–7.

    PubMed  CAS  Google Scholar 

  48. Meltzer CC, Kinahan PE, Greer PJ, Nichols TE, Comtat C, Cantwell MN, et al. Comparative evaluation of MR-based partial-volume correction schemes for PET. J Nucl Med 1999;40(12):2053–65.

    PubMed  CAS  Google Scholar 

  49. Fried I, Nenov VI, Ojemann SG, Woods RP. Functional MR and PET imaging of Rolandic and visual cortices for neurosurgical planning. J Neurosurg 1995;83(5):854–61.

    Article  PubMed  CAS  Google Scholar 

  50. Lewis PJ, Siegel A, Siegel AM, Studholme C, Sojkova J, Roberts DW, et al. Does performing image registration and subtraction in ictal brain SPECT help localize neocortical seizures? J Nucl Med 2000;41(10):1619–26.

    PubMed  CAS  Google Scholar 

  51. Ledezma CJ, Chen W, Sai V, Freitas B, Cloughesy T, Czernin J, Pope W. 18F-FDOPA PET/MRI fusion in patients with primary/recurrent gliomas: initial experience. Eur J Radiol 2008;(in press).

  52. Hesse S, Barthel H, Schwarz J, Sabri O, Müller U. Advances in in vivo imaging of serotonergic neurons in neuropsychiatric disorders. Neurosci Biobehav Rev 2004;28(6):547–63.

    Article  PubMed  CAS  Google Scholar 

  53. Pan T, Mawlawi O, Nehmeh SA, Erdi YE, Luo D, Liu HH, et al. Attenuation correction of PET images with respiration-averaged CT images in PET/CT. J Nucl Med 2005;46(9):1481–7.

    PubMed  Google Scholar 

  54. Cai J, Chu JC, Recine D, Sharma M, Nguyen C, Rodebaugh R, et al. CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching method. Int J Radiat Oncol Biol Phys 1999;43(4):883–91.

    PubMed  CAS  Google Scholar 

  55. Yu JN, Fahey FH, Harkness BA, Gage HD, Eades CG, Keyes JW. Evaluation of emission-transmission registration in thoracic PET. J Nucl Med 1994;35(11):1777–80.

    PubMed  CAS  Google Scholar 

  56. Yu JN, Fahey FH, Gage HD, Eades CG, Harkness BA, Pelizzari CA, Keyes JW. Intermodality, retrospective image registration in the thorax. J Nucl Med 1995;36(12):2333–8.

    PubMed  CAS  Google Scholar 

  57. Wahl RL, Quint LE, Cieslak RD, Aisen AM, Koeppe RA, Meyer CR. Anatometabolic tumor imaging: fusion of FDG PET with CT or MRI to localize foci of increased activity. J Nucl Med 1993;34(7):1190–7.

    PubMed  CAS  Google Scholar 

  58. Erdi AK, Hu YC, Chui CS. Using mutual information (MI) for automated 3D registration in the pelvis and thorax region for radiotherapy treatment planning. SPIE Med Imaging 2000: Image Proc 2000;3979:416–25.

    Google Scholar 

  59. Dey D, Slomka PJ, Hahn LJ, Kloiber R. Automatic three-dimensional multimodality registration using radionuclide transmission CT attenuation maps: a phantom study. J Nucl Med 1999;40(3):448–55.

    PubMed  CAS  Google Scholar 

  60. Shekhar R, Walimbe V, Raja S, Zagrodsky V, Kanvinde M, Wu G, et al. Automated 3-dimensional elastic registration of whole-body PET and CT from separate or combined scanners. J Nucl Med 2005;46(9):1488–96.

    PubMed  Google Scholar 

  61. Halpern BS, Schiepers C, Weber WA, Crawford TL, Fueger BJ, Phelps ME, et al. Presurgical staging of non-small cell lung cancer* positron emission tomography, integrated positron emission tomography/CT, and software image fusion. Chest 2005;128(4):2289–97.

    Article  PubMed  Google Scholar 

  62. Wolthaus JWH, van Herk M, Muller SH, Belderbos JSA, Lebesque JV, de Bois JA, et al. Fusion of respiration-correlated PET and CT scans: correlated lung tumour motion in anatomical and functional scans. Phys Med Biol 2005;50(7):1569–83.

    Article  PubMed  CAS  Google Scholar 

  63. Mattes D, Haynor DR, Vesselle H, Lewellen TK, Eubank W. PET-CT image registration in the chest using free-form deformations. IEEE Trans Med Imag 2003;22(1):120–8.

    Article  Google Scholar 

  64. Nimmagadda S, Ford EC, Wong JW, Pomper MG. Targeted molecular imaging in oncology: focus on radiation therapy. Semin Radiat Oncol 2008;18(2):136.

    Article  PubMed  Google Scholar 

  65. Nishioka T, Shiga T, Shirato H, Tsukamoto E, Tsuchiya K, Kato T, et al. Image fusion between 18FDG-PET and MRI/CT for radiotherapy planning of oropharyngeal and nasopharyngeal carcinomas. Int J Radiat Oncol Biol Phys 2002;53(4):1051–7.

    PubMed  Google Scholar 

  66. Brock KK, Sharpe MB, Dawson LA, Kim SM, Jaffray DA. Accuracy of finite element model-based multi-organ deformable image registration. Med Phys 2005;32(6):1647–59.

    Article  PubMed  CAS  Google Scholar 

  67. Jaffray D. Emergent technologies for 3-dimensional image-guided radiation delivery. Semin Radiat Oncol 2005;15(3):208–16.

    Article  PubMed  Google Scholar 

  68. Erdi YE, Rosenzweig K, Erdi AK, Macapinlac HA, Hu YC, Braban LE, et al. Radiotherapy treatment planning for patients with non-small cell lung cancer using positron emission tomography (PET). Radiother Oncol 2002;62(1):51–60.

    Article  PubMed  Google Scholar 

  69. Koshy M, Paulino AC, Howell R, Schuster D, Halkar R, Davis LW. F-18 FDG PET-CT fusion in radiotherapy treatment planning for head and neck cancer. Head Neck 2005;27(6):494–502.

    Article  PubMed  Google Scholar 

  70. Bradley J, Thorstad WL, Mutic S, Miller TR, Dehdashti F, Siegel BA, et al. Impact of FDG-PET on radiation therapy volume delineation in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2004;59(1):78–86.

    PubMed  Google Scholar 

  71. Seiboth L, Van Nostrand D, Wartofsky L, Ousman Y, Jonklaas J, Butler C, et al. Utility of PET/Neck MRI digital fusion images in the management of recurrent or persistent thyroid cancer. Thyroid 2008;18(2):103–11.

    Article  PubMed  Google Scholar 

  72. Slomka PJ, Berman DS, Germano G. Applications and software techniques for integrated cardiac multimodality imaging. Expert Rev Cardiovasc Ther 2008;6(1):27–41.

    Article  PubMed  Google Scholar 

  73. Berman DS, Hachamovitch R, Shaw LJ, Friedman JD, Hayes SW, Thomson LEJ, et al. Roles of nuclear cardiology, cardiac computed tomography, and cardiac magnetic resonance: assessment of patients with suspected coronary artery disease. J Nucl Med 2006;47(1):74–82.

    PubMed  Google Scholar 

  74. Gaemperli O, Schepis T, Valenta I, Husmann L, Scheffel H, Duerst V, et al. Cardiac image fusion from stand-alone SPECT and CT: clinical experience. J Nucl Med 2007;48(5):696–703.

    Article  PubMed  Google Scholar 

  75. Slomka P, Suzuki Y, Elad Y, S VK, Kavanagh P, Gutstein A, Karlsberg R, Berman DS, Germano G. Software fusion of 64-slice CT angiography and myocardial perfusion SPECT: evidence of synergy [abstract]. J Nucl Med. Washington, DC: Journal of Nuclear Medicine; 2007.

  76. Rispler S, Keidar Z, Ghersin E, Roguin A, Soil A, Dragu R, et al. Integrated single-photon emission computed tomography and computed tomography coronary angiography for the assessment of hemodynamically significant coronary artery lesions. J Am Coll Cardiol 2007;49(10):1059–67.

    Article  PubMed  Google Scholar 

  77. Flohr TG, McCollough CH, Bruder H, Petersilka M, Gruber K, Süß C, et al. First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 2006;16(2):256–68.

    Article  PubMed  Google Scholar 

  78. Dewey M, Zimmermann E, Laule M, Rutsch W, Hamm B. Three-vessel coronary artery disease examined with 320-slice computed tomography coronary angiography. Eur Heart J 2008;(In press).

  79. Garcia EV, Gropler RJ. Eighth nuclear cardiology invitational conference Annapolis, MD 2008. J Nucl Cardiol 2008;(in press).

  80. Schepis T, Gaemperli O, Koepfli P, Rüegg C, Burger C, Leschka S, et al. Use of coronary calcium score scans from stand-alone multislice computed tomography for attenuation correction of myocardial perfusion SPECT. Eur J Nucl Med Mol Imaging. 2007;34(1):11–9.

    Article  PubMed  Google Scholar 

  81. Behloul F, Janier M, Croisille P, Poirier C, Boudraa A, Unterreiner R, et al. Automatic assessment of myocardial viability based on PET-MRI datafusion. Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE, p 492–495.

  82. Slomka PJ, Fieno D, Thomson L, Friedman JD, Hayes SW, Germano G, et al. Automatic detection and size quantification of infarcts by myocardial perfusion SPECT: clinical validation by delayed-enhancement MRI. J Nucl Med 2005;46(5):728–35.

    PubMed  Google Scholar 

  83. Aladl UE, Hurwitz GA, Dey D, Levin D, Drangova M, Slomka PJ. Automated image registration of gated cardiac single-photon emission computed tomography and magnetic resonance imaging. J Magn Reson Imaging 2004;19(3):283–90.

    Article  PubMed  Google Scholar 

  84. Rudd JH, Warburton EA, Fryer TD, Jones HA, Clark JC, Antoun N, et al. Imaging atherosclerotic plaque inflammation with [18F]-fluorodeoxyglucose positron emission tomography. Circulation 2002;105(23):2708–11.

    Article  PubMed  CAS  Google Scholar 

  85. Dey D, Slomka P, Chien D, Fieno D, Abidov A, Saouaf R, et al. Direct quantitative in vivo comparison of calcified atherosclerotic plaque on vascular MRI and CT by multimodality image registration. J Magn Reson Imaging 2006;23(3):345–54.

    Article  PubMed  Google Scholar 

  86. Hajnal JV, Saeed N, Oatridge A, Williams EJ, Young IR, Bydder GM. Detection of subtle brain changes using subvoxel registration and subtraction of serial MR images. J Comput Assist Tomogr 1995;19(5):677.

    Article  PubMed  CAS  Google Scholar 

  87. Fox NC, Crum WR, Scahill RI, Stevens JM, Janssen JC, Rossor MN. Imaging of onset and progression of Alzheimer’s disease with voxel-compression mapping of serial magnetic resonance images. Lancet 2001;358(9277):201–5.

    Article  PubMed  CAS  Google Scholar 

  88. Mackie TR, Kapatoes J, Ruchala K, Lu W, Wu C, Olivera G, et al. Image guidance for precise conformal radiotherapy. Int J Radiat Oncol Biol Phys 2003;56(1):89–105.

    PubMed  Google Scholar 

  89. Shi J, Sahiner B, Chan HP, Hadjiiski L, Zhou C, Cascade PN, et al. Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching. Med Phys 2007;34:1336.

    Article  PubMed  Google Scholar 

  90. Benz MR, Evilevitch V, Allen-Auerbach MS, Eilber FC, Phelps ME, Czernin J, et al. Treatment monitoring by 18F-FDG PET/CT in patients with sarcomas: interobserver variability of quantitative parameters in treatment-induced changes in histopathologically responding and nonresponding tumors. J Nucl Med 2008;49(7):1038.

    Article  PubMed  Google Scholar 

  91. Faber TL, Modersitzki J, Folks RD, Garcia EV. Detecting changes in serial myocardial perfusion SPECT: a simulation study. J Nucl Cardiol 2005;12(3):302–10.

    Article  PubMed  Google Scholar 

  92. Zifko UA, Slomka PJ, Reid RH, Young GB, Remtulla H, Bolton CF. The cortical representation of somatosensory evoked potentials of the phrenic nerve. J Neurol Sci 1996;139(2):197–202.

    Article  PubMed  CAS  Google Scholar 

  93. Siddique MS, Fernandes HM, Wooldridge TD, Fenwick JD, Slomka P, Mendelow AD. Reversible ischemia around intracerebral hemorrhage: a single-photon emission computerized tomography study. J Neurosurg 2002;96(4):736–41.

    PubMed  Google Scholar 

  94. Voruganti LNP, Slomka P, Zabel P, Mattar A, Awad AG. Cannabis induced dopamine release: an in-vivo SPECT study. Psychiatry Res: Neuroimaging. 2001;107(3):173–7.

    Article  PubMed  CAS  Google Scholar 

  95. Schepis T, Gaemperli O, Koepfli P, Rüegg C, Burger C, Leschka S, et al. Use of coronary calcium score scans from stand-alone multislice computed tomography for attenuation correction of myocardial perfusion SPECT. Eur J Nucl Med Mol Imaging 2007;34(1):11–9.

    Article  PubMed  Google Scholar 

  96. Beyer T, Weigert M, Quick HH, Pietrzyk U, Vogt F, Palm C, et al. MR-based attenuation correction for torso-PET/MR imaging: pitfalls in mapping MR to CT data. Eur J Nucl Med Mol Imaging 2008;35(6):1142–6.

    Article  PubMed  Google Scholar 

  97. Gould KL, Pan T, Loghin C, Johnson NP, Guha A, Sdringola S. Frequent diagnostic errors in cardiac PET/CT due to misregistration of CT attenuation and emission PET images: a definitive analysis of causes, consequences, and corrections. J Nucl Med 2007;48(7):1112.

    Article  PubMed  Google Scholar 

  98. Emanuel EJ, Fuchs VR. The perfect storm of overutilization. JAMA 2008;299(23):2789.

    Article  PubMed  CAS  Google Scholar 

  99. Cascade PN. Unnecessary imaging and radiation risk: the perfect storm for radiologists. J Am Coll Radiol 2004;1(10):709–11.

    Article  PubMed  Google Scholar 

  100. Einstein AJ, Moser KW, Thompson RC, Cerqueira MD, Henzlova MJ. Radiation dose to patients from cardiac diagnostic imaging. Circulation 2007;116(11):1290–305.

    Article  PubMed  Google Scholar 

  101. Franzius C, Juergens KU, Schober O. Is PET/CT necessary in paediatric oncology? Eur J Nucl Med Mol Imaging 2006;33(8):960–5.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. AIM Program/Department of Imaging #A047, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA, 90048, USA

    Piotr J. Slomka

  2. David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    Piotr J. Slomka

  3. Department of Nuclear Medicine, Center for PET, Zentralklinik Bad Berka, Bad Berka, Germany

    Richard P. Baum

Authors
  1. Piotr J. Slomka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Richard P. Baum
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Piotr J. Slomka.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Slomka, P.J., Baum, R.P. Multimodality image registration with software: state-of-the-art. Eur J Nucl Med Mol Imaging 36 (Suppl 1), 44–55 (2009). https://doi.org/10.1007/s00259-008-0941-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-008-0941-8

Keywords

Search

Navigation