Skip to main content

Structure-Preserving Smoothing of Biomedical Images

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5702))

Abstract

Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood.

In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Pratt, W.: Digital Image Processing. Wiley, Chichester (1998)

    Google Scholar 

  2. Comaniciu, D., Meer, P.: Mean shift analysis and applications. In: Int.Conf. Comp. Vis., ICCV (1999)

    Google Scholar 

  3. Papari, G., Petkov, N., Campisi, P.: Artistic edge and corner enhancing smoothing. IEEE Trans. Imag. Proc. 16(10), 2449–2462 (2007)

    Article  MathSciNet  Google Scholar 

  4. Weickert, J.: A Review of Nonlinear Diffusion Filtering. In: ter Haar Romeny, B.M., Florack, L.M.J., Viergever, M.A. (eds.) Scale-Space 1997. LNCS, vol. 1252, pp. 3–28. Springer, Heidelberg (1997)

    Google Scholar 

  5. Chen, K.: Adaptive smoothing via contextual and local discontinuities. IEEE Trans. Pat. Ana. Mach. Intel. 27(10), 1552–1567 (2005)

    Article  Google Scholar 

  6. Manniesing, R., Viergever, M., Niessen, W.: Vessel enhancing diffusion a scale space representation of vessel structures. Med. Imag. Ana. 10, 815–825 (2005)

    Article  Google Scholar 

  7. Evans, L.: Partial Differential Equations. Berkeley Math. Lect. Notes (1993)

    Google Scholar 

  8. Saha, P.K., Udupa, J.: Sacle-based diffusive image filtering preserving boundary sharpness and fine structures. IEEE Trans. Med. Imag. 20, 1140–1155 (2001)

    Article  Google Scholar 

  9. Gil, D.: Geometric Differential Operators for Shape Modelling. PhD thesis, Universitat Autonoma de Barcelona (2004)

    Google Scholar 

  10. Lang, S.: Linear Algebra. Addison-Wesley, Reading (1971)

    Google Scholar 

  11. Mikolajczyk, K., Tuytelaars, T., Schmid, C., et al.: A Comparison of Affine Region Detectors. Int. J. Comp. Vis. 65, 43–72 (2005)

    Article  Google Scholar 

  12. Jähne, B.: Spatio-temporal image processing:Theory and Scientific Applications. Springer, Heidelberg (1993)

    MATH  Google Scholar 

  13. Spivak, M.: A Comprehensive Introduction to Differential Geometry, vol. 1. Publish or Perish, Inc., Houston (1999)

    Google Scholar 

  14. Cárdenes, R., Bach, M., Chi, Y., Marras, I., de Luis, R., Anderson, M., Cashman, P., Bultelle, M.: Multimodal evaluation for medical image segmentation. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds.) CAIP 2007. LNCS, vol. 4673, pp. 229–236. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  15. Tyree, M., Zimmermann, M.: Xylem structure and the ascent of sap. Springer, Heidelberg (2002)

    Google Scholar 

  16. Loepfe, L., Martinez-Vilalta, J., Piñola, J., et al.: The relevance of xylem network structure for plant hydraulic efficiency and safety. J. Th. Biol. 247, 788–803 (2007)

    Article  Google Scholar 

  17. Ciais, P., Reichstein, M., Viovy, N., et al.: Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005)

    Article  Google Scholar 

  18. Trtik, P., Dual, J., Keunecke, D., et al.: 3d imaging of microstructure of spruce wood. J. Struct. Biol. 159, 45–56 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gil, D., Hernàndez-Sabaté, A., Burnat, M., Jansen, S., Martínez-Villalta, J. (2009). Structure-Preserving Smoothing of Biomedical Images. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03767-2_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03766-5

  • Online ISBN: 978-3-642-03767-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics