[go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Application of Tikhonov Regularization to Super-Resolution Reconstruction of Brain MRI Images

  • Conference paper
Medical Imaging and Informatics (MIMI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4987))

Included in the following conference series:

  • 1491 Accesses

Abstract

This paper presents an image super-resolution method that enhances spatial resolution of MRI images in the slice-select direction. The algorithm employs Tikhonov regularization, using a standard model of imaging process and reformulating the reconstruction as a regularized minimization task. Our experimental result shows improvements in both signal-to-noise ratio and visual quality.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Greenspan, H., Oz, G., Kiryati, N., Peled, S.: MRI inter-slice reconstruction using super resolution. Magn. Reson. Imaging. 20, 437–446 (2002)

    Article  Google Scholar 

  2. Eyal, C., Siuyan, L., Noga, A., Amos, F., Daniel, F.: Resolution enhancement in MRI. Magn. Reson. Imaging 24, 133–154 (2006)

    Article  Google Scholar 

  3. Lam, E.: Noise in superresolution reconstruction. Optics Letters 28, 2234–2236 (2003)

    Article  Google Scholar 

  4. Irani, M., Peleg, S.: Motion analysis for image enhancement: resolution, occlusion, and transparency. J. Vis. Comm. Image. Rep. 4, 324–335 (1993)

    Article  Google Scholar 

  5. Peled, S., Yeshurun, Y.: Superresolution in MRI: Application to human white matter fiber tract visualization by diffusion tensor imaging. Magn. Reson. Med. 45, 29–35 (2001)

    Article  Google Scholar 

  6. Hsu, J.T., et al.: Application of wavelet-based POCS super-resolution for cardiovascular MRI image enhancement. In: Proc. of ICIG 2004, pp. 524–575 (2004)

    Google Scholar 

  7. Katsaggelos, A.K. (ed.): Digital Image Restoration Sprintger Series in Information Sciences, vol. 23. Springer, Heidelberg (2003)

    Google Scholar 

  8. Banham, M.R., Katsaggelos, A.K.: Digital Image Restoration Sig. Proc. Mag. 14, 24–41 (1997)

    Article  Google Scholar 

  9. Saad, Y.: Iterative methods for sparse linear systems, 1st edn. PWS Publ., Company, Boston, Mass (1996)

    MATH  Google Scholar 

  10. Peeters, R., et al.: The use of super-resolution techniques to reduce slice thickness in functional MRI. Int. J. of. Imag. Sys. Tech. 14, 131–138 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong,  

    Xin Zhang, Edmund Y. Lam, Ed X. Wu & Kenneth K. Y. Wong

Authors
  1. Xin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edmund Y. Lam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ed X. Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kenneth K. Y. Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Xiaohong Gao Henning Müller Martin J. Loomes Richard Comley Shuqian Luo

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, X., Lam, E.Y., Wu, E.X., Wong, K.K.Y. (2008). Application of Tikhonov Regularization to Super-Resolution Reconstruction of Brain MRI Images. In: Gao, X., Müller, H., Loomes, M.J., Comley, R., Luo, S. (eds) Medical Imaging and Informatics. MIMI 2007. Lecture Notes in Computer Science, vol 4987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79490-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-79490-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79489-9

  • Online ISBN: 978-3-540-79490-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics