Skip to main content
SpringerLink
Log in

Effective Anatomical Priors for Emission Tomographic Reconstruction

  • Original Article
  • Published:
Journal of Medical and Biological Engineering Aims and scope Submit manuscript

Abstract

Bayesian tomographic reconstruction with anatomical side information from other imaging modalities can improve both image quality and quantitation in emission tomography for both single-photon emission computed tomography and positron emission tomography. However, the complexity and sensitivity to registration error between function and anatomical images often limit its clinical applications. To alleviate these challenges, this study proposes two priors, anatomical median root prior (AMRP) and anatomical mean prior (AMP), with a simple scheme of incorporating anatomical information. The priors are based on a simple edge-preserving prior that aims to retain the true intensity edges without blurring, median root prior (MRP), by replacing the median value among neighboring pixels with the median or mean value in a corresponding predefined anatomical region. Digital simulations and Monte Carlo simulations were conducted to evaluate the performance of the proposed methods. As compared to MRP, the proposed priors both showed sharper edges, better uniformity, and more accurate activity recovery with well-aligned anatomical and functional images. In addition, a tolerance study in terms of the misregistration between anatomical and functional images was also performed. Acceptable results were obtained for both priors when misalignment was less than 2 pixels, which can be easily achieved in real applications. The proposed anatomical priors for emission tomographic reconstruction can improve both visual and quantitative performance, and are not sensitive to misregistration errors between anatomical and functional images.

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

Similar content being viewed by others

References

  1. Qi, J., & Huesman, R. H. (2001). Theoretical study of lesion detectability of MAP reconstruction using computer observers. IEEE Transactions on Medical Imaging, 20, 815–822.

    Article  Google Scholar 

  2. Shepp, L. A., & Vardi, Y. (1982). Maximum likelihood reconstruction for emission tomography. IEEE Transactions on Medical Imaging, 1, 113–122.

    Article  Google Scholar 

  3. Lange, K., & Carson, R. (1984). EM reconstruction algorithms for emission and transmission tomography. Journal of Computer Assisted Tomography, 8, 306–316.

    Google Scholar 

  4. Qi, J., & Leahy, R. M. (2006). Iterative reconstruction techniques in emission computed tomography. Physics in Medicine & Biology, 51, R541–R578.

    Article  Google Scholar 

  5. Green, P. J. (1990). Bayesian reconstructions from emission tomography data using a modified EM algorithm. IEEE Transactions on Medical Imaging, 9, 84–93.

    Article  Google Scholar 

  6. Alenius, S., & Ruotsalainen, U. (2002). Generalization of median root prior reconstruction. IEEE Transactions on Medical Imaging, 21, 1413–1420.

    Article  Google Scholar 

  7. Ollinger, J. M., & Fessler, J. A. (1997). Positron-emission tomography. IEEE Signal Processing Magazine, 14, 43–55.

    Article  Google Scholar 

  8. Chan, C., Fulton, R., Feng, D. D., & Meikle, S. (2009). Regularized image reconstruction with an anatomically adaptive prior for positron emission tomography. Physics in Medicine & Biology, 54, 7379–7400.

    Article  Google Scholar 

  9. Bouman, C., & Sauer, K. (1993). A generalized Gaussian image model for edge-preserving MAP estimation. IEEE Transactions on Image Processing, 2, 296–310.

    Article  Google Scholar 

  10. Lalush, D. S., & Tsui, B. (1992). Simulation evaluation of Gibbs prior distributions for use in maximum a posteriori SPECT reconstructions. IEEE Transactions on Medical Imaging, 11, 267–275.

    Article  Google Scholar 

  11. Hsiao, I.-T., Rangarajan, A., & Gindi, G. (2003). A new convex edge-preserving median prior with applications to tomography. IEEE Transactions on Medical Imaging, 22, 580–585.

    Article  Google Scholar 

  12. Chantas, G. K., Galatsanos, N. P., & Likas, A. C. (2006). Bayesian restoration using a new nonstationary edge-preserving image prior. IEEE Transactions on Image Processing, 15, 2987–2997.

    Article  MathSciNet  Google Scholar 

  13. Alenius, S., & Ruotsalainen, U. (1997). Bayesian image reconstruction for emission tomography based on median root prior. European Journal of Nuclear Medicine, 24, 258–265.

    Article  Google Scholar 

  14. Chlewicki, W., Hermansen, F., & Hansen, S. (2004). Noise reduction and convergence of Bayesian algorithms with blobs based on the Huber function and median root prior. Physics in Medicine & Biology, 49, 4717.

    Article  Google Scholar 

  15. Sakaguchi, K., Shinohara, H., Hashimoto, T., Yokoi, T., & Uno, K. (2008). An iterative reconstruction using median root prior and anatomical prior from the segmented μ-map for count-limited transmission data in PET imaging. Annals of Nuclear Medicine, 22, 269–279.

    Article  Google Scholar 

  16. Gindi, G., Lee, M., Rangarajan, A., & Zubal, I. G. (1993). Bayesian reconstruction of functional images using anatomical information as priors. IEEE Transactions on Medical Imaging, 12, 670–680.

    Article  Google Scholar 

  17. Lipinski, B., Herzog, H., Rota Kops, E., Oberschelp, W., & Müller-Gärtner, H. W. (1997). Expectation maximization reconstruction of positron emission tomography images using anatomical magnetic resonance information. IEEE Transactions on Medical Imaging, 16, 129–136.

    Article  Google Scholar 

  18. Comtat, C., Kinahan, P. E., Fessler, J. A., Beyer, T., Townsend, D., Defrise, M., & Michel, C. (2002). Clinically feasible reconstruction of 3D whole-body PET/CT data using blurred anatomical labels. Physics in Medicine & Biology, 47, 1–20.

    Article  Google Scholar 

  19. Mameuda, Y., & Kudo, H. (2007). New anatomical-prior-based image reconstruction method for PET/SPECT. Proceedings IEEE Nuclear Science Symposium and Medical Imaging Conference, 6, 4142–4148.

    Google Scholar 

  20. Nuyts, J., Baete, K., Bequé, D., & Dupont, P. (2005). Comparison between MAP and postprocessed ML for image reconstruction in emission tomography when anatomical knowledge is available. IEEE Transactions on Medical Imaging, 24, 667–675.

    Article  Google Scholar 

  21. Bruyant, P. P., Gifford, H. C., Gindi, G., & King, M. (2004). Numerical observer study of MAP-OSEM regularization methods with anatomical priors for lesion detection in 67-Ga images. IEEE Transactions on Nuclear Science, 51, 193–197.

    Article  Google Scholar 

  22. Bowsher, J. E., Johnson, V. E., Turkington, T. G., Jaszczak, R., Floyd, C., & Coleman, R. E. (1996). Bayesian reconstruction and use of anatomical a priori information for emission tomography. IEEE Transactions on Medical Imaging, 15, 673–686.

    Article  Google Scholar 

  23. Gonzalez, R. C., & Woods, R. E. (2008). Digital Image Processing. Harlow: Prentice Hall.

    Google Scholar 

  24. Zubal, I. G., Harrell, C. R., Smith, E. O., Rattner, Z., Gindi, G., & Hoffer, P. (1994). Computerized three-dimensional segmented human anatomy. Medical Physics, 21, 299–302.

    Article  Google Scholar 

  25. Lin, K.-J., Weng, Y.-H., Wey, S. P., Hsiao, I.-T., Lu, C.-S., Skovronsky, D., et al. (2010). Whole-body biodistribution and radiation dosimetry of 18F-FP-(+)-DTBZ (18F-AV-133): A novel vesicular monoamine transporter 2 imaging agent. Journal of Nuclear Medicine, 51, 1480–1485.

    Article  Google Scholar 

  26. Jan, S., Benoit, D., Becheva, E., Carlier, T., Cassol, F., Descourt, P., et al. (2011). GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy. Physics in Medicine & Biology, 56, 881–901.

    Article  Google Scholar 

  27. Rapisarda, E., Bettinardi, V., Thielemans, K., & Gilardi, M. C. (2010). Evaluation of a new regularization prior for 3D PET reconstruction including PSF modelling. Proceedings. IEEE Nuclear Science Symposium and Medical Imaging Conference, 3495–3500. doi:10.1109/NSSMIC.2010.5874456.

  28. Hsiao, I.-T., & Huang, H.-M. (2010). An accelerated ordered subsets reconstruction algorithm using an accelerating power factor for emission tomography. Physics in Medicine & Biology, 55, 599–614.

    Article  Google Scholar 

  29. Leahy, R., & Yan, X. (1991). Incorporation of anatomical MR data for improved functional imaging with PET. Information Processing in Medical Imaging, 511, 105–120.

    Google Scholar 

  30. Ouyang, X., Wong, W., Johnson, V. E., Hu, X., & Chen, C. T. (1994). Incorporation of correlated structural images in PET image reconstruction. IEEE Transactions on Medical Imaging, 13, 627–640.

    Article  Google Scholar 

  31. Lee, S.-J., Hsiao, I.-T., & Gindi, G. (1997). The thin plate as a regularizer in Bayesian SPECT reconstruction. IEEE Transactions on Nuclear Science, 44, 1381–1387.

    Article  Google Scholar 

  32. Somayajula, S., Panagiotou, C., Rangarajan, A., Li, Q., Arridge, S. R., & Leahy, R. M. (2011). PET image reconstruction using information theoretic anatomical priors. IEEE Transactions on Medical Imaging, 30, 537–549.

    Article  Google Scholar 

  33. Bowsher, J. E., Yuan, H., Hedlund, L. W., Turkington, T. G., Akabani, G., Badea, A., et al. (2004). Utilizing MRI information to estimate F18-FDG distributions in rat flank tumors. Proceedings IEEE Nuclear Science Symposium and Medical Imaging Conference, 4, 2488–2492.

    Google Scholar 

  34. Rangarajan, A., Hsiao, I.-T., & Gindi, G. (2000). A Bayesian joint mixture framework for the integration of anatomical information in functional image reconstruction. Journal of Mathematical Imaging and Vision, 12, 199–217.

    Article  MATH  Google Scholar 

  35. Meltzer, C. C., Leal, J. P., Mayberg, H. S., Wagner, H. N, Jr, & Frost, J. J. (1990). Correction of PET data for partial volume effects in human cerebral cortex by MR imaging. Journal of Computer Assisted Tomography, 14, 561–570.

    Article  Google Scholar 

  36. Muller-Gartner, H. W., Links, J. M., Prince, J. L., Bryan, R. N., McVeigh, E., Leal, J. P., et al. (1992). Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects. Journal of Cerebral Blood Flow and Metabolism, 12, 571–583.

    Article  Google Scholar 

  37. Rousset, O. G., Ma, Y., & Evans, A. C. (1998). Correction for partial volume effects in PET: principle and validation. Journal of Nuclear Medicine, 39, 904–911.

    Google Scholar 

  38. Videen, T. O., Perlmutter, J. S., Mintun, M. A., & Raichle, M. (1988). Regional correction of positron emission tomography data for the effects of cerebral atrophy. Journal of Cerebral Blood Flow and Metabolism, 8, 662–670.

    Article  Google Scholar 

  39. Findlay, M., Young, H., Cunningham, D., Iveson, A., Cronin, B., Hickish, T., et al. (1996). Noninvasive monitoring of tumor metabolism using fluorodeoxyglucose and positron emission tomography in colorectal cancer liver metastases: correlation with tumor response to fluorouracil. Journal of Clinical Oncology, 14, 700–708.

    Google Scholar 

  40. Hsiao, I.-T., Huang, C.-C., Hsieh, C.-J., Hsu, W.-C., Wey, S.-P., Yen, T.-C., et al. (2012). Correlation of early-phase 18 F-florbetapir (AV-45/Amyvid) PET images to FDG images: Preliminary studies. European Journal of Nuclear Medicine and Molecular Imaging, 39, 1–8.

    Google Scholar 

  41. Lin, K.-J., Hsu, W.-C., Hsiao, I.-T., Wey, S.-P., Jin, L.-W., Skovronsky, D., et al. (2010). Whole-body biodistribution and brain PET imaging with [18F] AV-45, a novel amyloid imaging agent–a pilot study. Nuclear Medicine and Biology, 37, 497–508.

    Article  Google Scholar 

  42. Caldeira, L., Scheins, J., Almeida, P., Seabra, J., & Herzog, H. (2011). Modified median root prior reconstruction of PET/MR data acquired simultaneously with the 3TMR-BrainPET. Proceedings IEEE Nuclear Science Symposium and Medical Imaging Conference, 4039–4043. doi:10.1109/NSSMIC.2011.6153768.

  43. Drzezga, A., Grimmer, T., Henriksen, G., Stangier, I., Perneczky, R., Diehl-Schmid, J., et al. (2008). Imaging of amyloid plaques and cerebral glucose metabolism in semantic dementia and Alzheimer’s disease. Neuroimage, 39, 619–633.

    Article  Google Scholar 

  44. Casteels, C., Vermaelen, P., Nuyts, J., Van Der Linden, A., Baekelandt, V., Mortelmans, L., et al. (2006). Construction and evaluation of multitracer small-animal PET probabilistic atlases for voxel-based functional mapping of the rat brain. Journal of Nuclear Medicine, 47, 1858–1866.

    Google Scholar 

  45. Eberl, S., Kanno, I., Fulton, R. R., Ryan, A., Hutton, B. F., & Fulham, M. J. (1996). Automated interstudy image registration technique for SPECT and PET. Journal of Nuclear Medicine, 37, 137–145.

    Google Scholar 

  46. Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry-the methods. Neuroimage, 11, 805–821.

    Article  Google Scholar 

  47. Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26, 839–851.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Science Council of Taiwan under grants NSC 97-2314-B-182-029-MY3 and NSC 101-2314-B-182-061-MY2 and by the Research Fund of Chang Gung Memorial Hospital, Taiwan, under Grants CMRPD1C0671 and CMRPD1C0672.

Author information

Authors and Affiliations

  1. Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, 259 Wen-Hwa 1st Road, Kwei-Shan, Taoyuan, 333, Taiwan

    Yu-Jung Tsai, Hsuan-Ming Huang & Ing-Tsung Hsiao

  2. Department of Bioindustrial Mechatronics Engineering, National Taiwan University, Taipei, Taiwan

    Cheng-Ying Chou

  3. Department of Mathematics, National Taiwan University, Taipei, Taiwan

    Weichung Wang

  4. Institute of Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan

    Ing-Tsung Hsiao

Authors
  1. Yu-Jung Tsai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hsuan-Ming Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cheng-Ying Chou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weichung Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ing-Tsung Hsiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ing-Tsung Hsiao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tsai, YJ., Huang, HM., Chou, CY. et al. Effective Anatomical Priors for Emission Tomographic Reconstruction. J. Med. Biol. Eng. 35, 52–61 (2015). https://doi.org/10.1007/s40846-015-0005-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40846-015-0005-z

Keywords

Search

Navigation