Skip to main content
SpringerLink
Log in

Reconstruction/segmentation of attenuation map in TOF-PET based on mixture models

  • Original Article
  • Published:
Annals of Nuclear Medicine Aims and scope Submit manuscript

Abstract

Attenuation correction is known as a necessary step in positron emission tomography (PET) system to have accurate and quantitative activity images. Emission-based method is known as a promising approach for attenuation map estimation on TOF-PET scanners. The proposed method in this study imposes additional histogram-based information as a mixture model prior on the emission-based approach using maximum a posteriori (MAP) framework to improve its performance and make such a nearly segmented attenuation map. To eliminate misclassification of histogram modeling, a Median root prior is incorporated on the proposed approach to reduce the noise between neighbor voxels and encourage spatial smoothness in the reconstructed attenuation map. The joint-MAP optimization is carried out as an iterative approach wherein an alteration of the activity and attenuation updates is followed by a mixture decomposition of the attenuation map histogram. Also, the proposed method can segment attenuation map during the reconstruction. The evaluation of the proposed method on the numerical, simulation and real contexts indicate that the presented method has the potential to be used as a stand-alone method or even combined with other methods for attenuation correction on PET/MR systems.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Akbarzadeh A, Ay MR, Ahmadian A, Alam NR, Zaidi H. MRI-guided attenuation correction in whole-body PET/MR: assessment of the effect of bone attenuation. Ann Nucl Med. 2013;27(2):152 – 62.

    Article  PubMed  CAS  Google Scholar 

  2. Keereman V, Mollet P, Berker Y, Schulz V, Vandenberghe S. Challenges and current methods for attenuation correction in PET/MR. Magn Reson Mater Phys Biol Med. 2013;26(1):81–98.

    Article  Google Scholar 

  3. Hofmann M, Steinke F, Scheel V, Charpiat G, Farquhar J, Aschoff P, et al. MRI-based attenuation correction for PET/MRI: a novel approach combining pattern recognition and atlas registration. J Nucl Med. 2008;49(11):1875–83.

    Article  PubMed  Google Scholar 

  4. Khateri P, Rad HS, Jafari AH, Ay MR. A novel segmentation approach for implementation of MRAC in head PET/MRI employing Short-TE MRI and 2-point Dixon method in a fuzzy C-means framework. Nucl Instrum Methods Phys Res Sect A Accel Spectrom Detect Assoc Equip. 2014;734:pp. 171–4.

    Article  CAS  Google Scholar 

  5. Khateri P, Rad HS, Jafari AH, Kazerooni AF, Akbarzadeh A, Moghadam MS, et al. Generation of a four-class attenuation map for MRI-based attenuation correction of PET data in the head area using a novel combination of STE/Dixon-MRI and FCM clustering. Mol Imaging Biol. 2015;17(6):884 – 92.

    Article  PubMed  CAS  Google Scholar 

  6. Rezaei A, Defrise M, Bal G, Michel C, Conti M, Watson C, et al. Simultaneous reconstruction of activity and attenuation in time-of-flight PET. IEEE Trans Med Imaging. 2012;31(12):2224–33.

    Article  PubMed  Google Scholar 

  7. Xu M, Cutler P, Luk W. Adaptive, segmented attenuation correction for whole-body PET imaging. IEEE Trans Nucl Sci. 1996;43(1):331–6.

    Article  Google Scholar 

  8. Nuyts J, Dupont P, Stroobants S, Benninck R, Mortelmans L, Suetens P. Simultaneous maximum a posteriori reconstruction of attenuation and activity distributions from emission sinograms. IEEE Trans Med Imaging. 1999;18(5):393–403.

    Article  PubMed  CAS  Google Scholar 

  9. Conti M. Why is TOF PET reconstruction a more robust method in the presence of inconsistent data? Phys Med Biol. 2010;56(1):155.

    Article  PubMed  Google Scholar 

  10. Defrise M, Rezaei A, Nuyts J. Time-of-flight PET data determine the attenuation sinogram up to a constant. Phys Med Biol. 2012;57(4):885.

    Article  PubMed  Google Scholar 

  11. Mumcuoglu EU, Leahy R, Cherry SR, Zhou Z. Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images. IEEE Trans Med Imaging. 1994;13(4):687–701.

    Article  PubMed  CAS  Google Scholar 

  12. Nuyts J, De Man B, Dupont P, Defrise M, Suetens P, Mortelmans L. Iterative reconstruction for helical CT: a simulation study. Phys Med Biol. 1998;43(4):729.

    Article  PubMed  CAS  Google Scholar 

  13. Hathaway RJ. Another interpretation of the EM algorithm for mixture distributions. Stat Probab Lett. 1986;4(2):53 – 6.

    Article  Google Scholar 

  14. Hsiao T, Rangarajan A, Gindi G. Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior. IEEE Trans Image Process. 2002;11(12):1466–77.

    Article  PubMed  Google Scholar 

  15. Jakoby B, Bercier Y, Conti M, Casey M, Bendriem B, Townsend D. Physical and clinical performance of the mCT time-of-flight PET/CT scanner. Phys Med Biol. 2011;56(8):2375.

    Article  PubMed  CAS  Google Scholar 

  16. Jan S, Santin G, Strul D, Staelens S, Assie K, Autret D, et al. GATE: a simulation toolkit for PET and SPECT. Phys Med Biol. 2004;49(19):4543.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Goertzen AL, Bao Q, Bergeron M, Blankemeyer E, Blinder S, Cañadas M, et al. NEMA NU 4-2008 comparison of preclinical PET imaging systems. J Nucl Med. 2012;53(8):1300–9.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Watson CC, Casey ME, Eriksson L, Mulnix T, Adams D, Bendriem B. NEMA NU 2 performance tests for scanners with intrinsic radioactivity. J Nucl Med. 2004;45(5):822–6.

    PubMed  CAS  Google Scholar 

  19. Ollinger JM. Model-based scatter correction for fully 3D PET. Phys Med Biol. 1996;41(1):153.

    Article  PubMed  CAS  Google Scholar 

  20. Liang Z, Jaszczak RJ, Coleman RE. Parameter estimation of finite mixtures using the EM algorithm and information criteria with application to medical image processing. IEEE Trans Nucl Sci. 1992;39(4):1126–33.

    Article  CAS  Google Scholar 

  21. Richardson S, Green PJ. On Bayesian analysis of mixtures with an unknown number of components (with discussion). J R Stat Soc Ser B (Stat Methodol). 1997;59(4):731 – 92.

    Article  Google Scholar 

  22. Boellaard R, Hofman M, Hoekstra O, Lammertsma A. Accurate PET/MR quantification using time of flight MLAA image reconstruction. Mol Imaging Biol. 2014;16(4):469 – 77.

    Article  PubMed  CAS  Google Scholar 

  23. Berker Y, Kiessling F, Schulz V. Scattered PET data for attenuation-map reconstruction in PET/MRI. Med Phys. 2014;41(10):102502.

    Article  PubMed  CAS  Google Scholar 

  24. Hemmati H, Kamali-Asl A, Ay M, Ghafarian P. Compton scatter tomography in TOF-PET. Phys Med Biol. 2017;62(19):7641.

    Article  PubMed  Google Scholar 

  25. Rothfuss H, Panin V, Moor A, Young J, Hong I, Michel C, et al. LSO background radiation as a transmission source using time of flight. Phys Med Biol. 2014;59(18):5483.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medical Radiation Engineering, Shahid Beheshti University, Evin, Tehran, 1983969411, Iran

    Hamidreza Hemmati & Alireza Kamali-Asl

  2. Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Pardis Ghafarian

  3. PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Pardis Ghafarian

  4. Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Ay

  5. Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran

    Mohammad Reza Ay

Authors
  1. Hamidreza Hemmati
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alireza Kamali-Asl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pardis Ghafarian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohammad Reza Ay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alireza Kamali-Asl.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hemmati, H., Kamali-Asl, A., Ghafarian, P. et al. Reconstruction/segmentation of attenuation map in TOF-PET based on mixture models. Ann Nucl Med 32, 474–484 (2018). https://doi.org/10.1007/s12149-018-1270-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12149-018-1270-z

Keywords

Search

Navigation