An Improved Approach to Super Resolution Based on PET Imaging

  • P. M. Yan
  • Meng Yang
  • Hui Huang
  • J. F. Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7667)


The low spatial resolution of Positron Emission Tomography imaging (PET) is due to the width of detector and some physical parameters (such as scattering fraction, counting statistics, positron range and patient’s motion). To overcome this problem and improve the resolution of PET image, a high effective sub-pixel registration algorithm based on Keren’s method is proposed, and a new iteration algorithm of registration is introduced to improve the registration accuracy. Compared with Keren’s method, this method can improve the registration accuracy highly. This new registration algorithm is applied into super-resolution PET imaging. What’s more, this new super-resolution approach will be demonstrated in this paper.


PET imaging registration Keren’s method super-resolution sinogram images 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Park, S.C., Park, M.K., Kang, M.K.: Super-resolution image reconstruction: A technical overview. IEEE Signal Process. 20(3), 21–36 (2003)CrossRefGoogle Scholar
  2. 2.
    Kennedy, J.A., Israel, O., Frenkel, A., Bar-Shalom, R., Azhari, H.: Improved image fusion in PET/CT using hybrid image reconstruction and super-resolution. Int. J. Biomed. Imag. 46, 846 (2007)Google Scholar
  3. 3.
    Kennedy, J.A., Israel, O., Frenkel, A., Bar-Shalom, R., Azhari, H.: Super-resolution in PET imaging. IEEE Trans. Med. Imag. 25(2), 137–147 (2006)CrossRefGoogle Scholar
  4. 4.
    Chang, G.P., Pan, T., Qiao, F., Clark Jr., J.W., Mawlawi, O.R.: Comparison between two super-resolution implementations in PET imaging. J. Nucl. Med. 49, 63 (2008)Google Scholar
  5. 5.
    Chang, G.P., M.S.: A new implementation of Super Resolution technique in PET imaging. Rice University, AAT 1455224 (2008) Google Scholar
  6. 6.
    Zhi, Y., Alireza, A., Yan, P.M., Kamata, S.: Image registration based on genetic algorithm and weighted feature correspondences. In: International Symposium on Consumer Electronics, pp. 42–46 (2009)Google Scholar
  7. 7.
    Kye, Y.J., Kyuha, C., Woo, H.N., Ji, H.K., Jong, B.R.: Image resolution improvement based on sinogram super-resolution in PET. Engineering in Medicine and Biology Society (EMBC), pp. 5712–5715 (2010)Google Scholar
  8. 8.
    Chang, G., Pan, T., Clark Jr., J.W., Mawlawi, O.R.: Optimization of super-resolution processing using incomplete image sets in PET imaging. J. Nucl. Med. 49(suppl. 1), 393 (2008)Google Scholar
  9. 9.
    Keren, D., Peleg, S., Brada, R.: Image Sequence Enhancement Using Sub-Pixel Displacement. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, pp. 742–746 (1988)Google Scholar
  10. 10.
    Lu, Y., Inamura, M., Valdes, M.: Super-resolution of the undersampled and subpixel shifted image sequence by a neural network. Int. J. Imag. Syst. Technol. 14(1), 8–15 (2004)CrossRefGoogle Scholar
  11. 11.
    Chang, G., Pan, T., Qiao, F., Clark Jr., J.W., Mawlawi, O.R.: Improving PET image resolution and SNR using super resolution postprocessing. J. Nucl. Med. 48, 411 (2007)Google Scholar
  12. 12.
    Chang, G., Pan, T., Qiao, F., Clark Jr., J.W., Mawlawi, O.R.: Reducing PET scan duration by improving SNR using super-resolution techniques. Med. Phys. 34(6), 2354 (2007)CrossRefGoogle Scholar
  13. 13.
  14. 14.
    Zhi, Y., Yan, P.M., Li, S.: Super resolution based on scale invariant feature transform. In: 7-9th International Conference on Audio, Language and Image Processing, pp. 1550–1554 (2008)Google Scholar
  15. 15.
    Fessler, J.A.: Image reconstruction toolbox,
  16. 16.
    Matlab toolbox superresolution_v_2.0,

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • P. M. Yan
    • 1
  • Meng Yang
    • 1
  • Hui Huang
    • 1
  • J. F. Li
    • 1
  1. 1.School of Communication and Information EngineeringShanghai UniversityShanghaiChina

Personalised recommendations