Skip to main content
Log in

Visualizing diffusion tensor fields on streamsurfaces with merging ellipsoids and LIC texture

  • Published:
Applied Mathematics-A Journal of Chinese Universities Aims and scope Submit manuscript

Abstract

Streamsurfaces in diffusion tensor fields are used to represent structures with primarily planar diffusion. So far, however, no effort has been made on the visualization of the anisotropy of diffusion on them, although this information is very important to identify the problematic regions of these structures. We propose two methods to display this anisotropy information. The first one employs a set of merging ellipsoids, which simultaneously characterize the local tensor details — anisotropy — on them and portray the shape of the streamsurfaces. The weight between the streamsurfaces continuity and the discrete local tensors can be interactively adjusted by changing some given parameters. The second one generates a dense LIC (line integral convolution) texture of the two tangent eigenvector fields along the streamsurfaces firstly, and then blends in some color mapping indicating the anisotropy information. For high speed and high quality of texture images, we confine both the generation and the advection of the LIC texture in the image space. Merging ellipsoids method reveals the entire anisotropy information at discrete points by exploiting the geometric attribute of ellipsoids, and thus suits for local and detailed examination of the anisotropy; the texture-based method gives a global representation of the anisotropy on the whole streamsurfaces with texture and color attributes. To reveal the anisotropy information more efficiently, we integrate the two methods and use them at two different levels of details.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. B Cabral, L C Leedom. Imaging vector fields using line integral convolution, SIGGRAPH’93, 1993, 263–270.

    Google Scholar 

  2. C F Westin, S Peled, H Gubjartsson, et al. Geometrical diffusion measures for MRI from tensor basis analysis, Proc Int Soc Magnetic Resonance Med (ISMRM), 1997.

    Google Scholar 

  3. C Pierpaoli, P J Basser. Toward a quantitative assessment of diffusion anisotropy, Magnetic Resonance Med, 1996, 36: 893–906.

    Article  Google Scholar 

  4. D Stalling. LIC on surfaces, SIGGRAPH’97, 1997, 51–64.

    Google Scholar 

  5. D Stalling, H C Hege. Fast and resolution independent line integral convolution, SIGGRAPH’95, 1995, 249–256.

    Google Scholar 

  6. E Hsu. Generalized line integral convolution rendering of diffusion tensor fields, Proc ISMRM, 2001, pp790.

    Google Scholar 

  7. G Turk. Re-tiling polygonal surfaces, SIGGRAPH’92, 1992, 55–64.

    Google Scholar 

  8. J J van Wijk. Spot noise-texture synthesis for data visualization, SIGGRAPH’91, 1991, 309–318.

    Google Scholar 

  9. J J van Wijk. Image based flow visualization, IEEE Trans Graph, 2002, 21(3): 745–754.

    Google Scholar 

  10. J J van Wijk. Image based flow visualization for curved surfaces, Proc IEEE Vis 2003, 2003, 123–130.

    Google Scholar 

  11. J Palacios, E Zhang. Interactive visualization of rotational symmetry fields on surfaces, IEEE Trans Vis Comput Graph, 2011, 17(7): 947–955.

    Article  Google Scholar 

  12. M Brill, H Hagen, H C Rodrian, et al. Streamball techniques for flow visualization, Proc Conf Vis’94, 1994, 225–231.

    Google Scholar 

  13. P J Basser, J Mattiello, D Lebihan. Estimation of the effective self-diffusion tensor from the NMR Spin-Echo, J Magnetic Resonance B, 1994, 103(3): 247–254.

    Article  Google Scholar 

  14. R S Laramee, B Jobard, H Hauser. Image space based visualization of unsteady flow on surfaces, Proc IEEE Vis 2003, 2003, 131–138.

    Google Scholar 

  15. R Sondershaus, S Gumhold. Meshing of diffusion surfaces for point-based tensor field visualization, Proc 12th Int Meshing Roundtable, 2003, 177–188.

    Google Scholar 

  16. S Eichelbaum. Image space tensor field visualization using a LIC-like method, Diploma Thesis, University of Leipzig, 2009.

    Google Scholar 

  17. S Zhang, C Demiralp, D Laidlaw. Visualizing diffusion tensor MR images using streamtubes and streamsurfaces, IEEE Trans Vis Comput Graph, 2003, 9(4): 454–462.

    Article  Google Scholar 

  18. W Chen, S Zhang, S Correia, et al. Visualizing diffusion tensor imaging data with merging ellipsoids, 2009 IEEE Pac Vis Symp, 2009, 145–151.

    Chapter  Google Scholar 

  19. W E Lorenson, H E Cline. Marching cubes: a high resolution 3D surface construction algorithm, Comput Graph, 1987, 21(3): 163–169.

    Article  Google Scholar 

  20. W J Song, J Z Cui, Z L Ye. Visualizing 3-D symmetric tensor fields using a type of surface icons, IEEE CAD/Graphics’09, 2009, 627–631.

    Google Scholar 

  21. Y Xu, R Z Hu, C Gotsman, et al. Blue noise sampling of surfaces, Comput Graph, 2012, 36(4): 232–240.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei-jie Song.

Additional information

Supported by the National Natural Science Foundation of China (61070233) and the Natural Science Foundation of Shaanxi Province, China (2011JM1006).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, Wj., Chen, W., Chen, Hd. et al. Visualizing diffusion tensor fields on streamsurfaces with merging ellipsoids and LIC texture. Appl. Math. J. Chin. Univ. 29, 399–409 (2014). https://doi.org/10.1007/s11766-014-3234-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11766-014-3234-y

MR Subject Classification

Keywords

Navigation