Virtual Angioscopy Based on Implicit Vasculatures

  • Qingqi Hong
  • Qingde Li
  • Jie Tian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6785)


Virtual endoscopy is among the most active areas in medical data visualization, which focuses on the simulated visualizations of specific hollow organs for the purposes of training and diagnosis. In this paper, we present a virtual angioscopy technique based on vasculature geometry reconstructed using skeleton-based implicit splines (SIS). The highly accurate implicit representation of the vasculature not only makes it possible to achieve high visual quality of perspective view inside the vessel structures, but also makes the implementation of an interactive virtual angioscopy a much easier task, as the issue of collision detection of virtual camera with vascular objects can be easily solved when the vasculature is represented in implicit form. Some experiments have been carried out to demonstrate the strengths of our technique.


Virtual endoscopy Virtual angioscopy Implicit modeling Interactive navigation 


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  1. 1.
    Bartz, D.: Virtual endoscopy in research and clinical practice. Computer Graphics Forum 24(1), 111–126 (2005)CrossRefGoogle Scholar
  2. 2.
    Wickham, J.: Minimally invasive surgery: Future developments. BMJ 308, 193–196 (1994)CrossRefGoogle Scholar
  3. 3.
    Hong, L., Muraki, S., Kaufman, A., Bartz, D., He, T.: Virtual voyage: Interactive navigation in the human colon. In: Proceedings of ACM SIGGRAPH, pp. 27–34 (1997)Google Scholar
  4. 4.
    Bartrolí, A.V.: Visualization Techniques for Virtual Endoscopy. PhD thesis, Technischse Universitä Wien (2001)Google Scholar
  5. 5.
    Ferretti, G.R., Vining, D.J., Knoplioch, J., Coulomb, M.: Tracheobronchial tree: Three-dimensional spiral ct with bronchoscopic perspective. Journal of Computer Assisted Tomography 20(5), 777–781 (1996)CrossRefGoogle Scholar
  6. 6.
    Auer, D.P., Auer, L.M.: Virtual endoscopy - a new tool for teaching and training in neuroimaging. International Journal of Neuroradiology 4, 3–14 (1998)CrossRefGoogle Scholar
  7. 7.
    Bartz, D., Skalej, M., Welte, D., Straßr, W., Duffner, F.: A virtual endoscopy system for the planning of endoscopic interventions in the ventricle system of the human brain. In: Proc. of BiOS 1999: Biomedical Diagnostics, Guidance and Surgical Assist Systems (1999)Google Scholar
  8. 8.
    Davis, C.P., Ladds, M.E., Romanowski, B.J., Wildermuth, S., Kopflioch, J.F., Debatin, J.F.: Human aorta: Preliminary results with virtual endoscopy based on three-dimensional mr imaging data sets. Radiology 199, 37–40 (1996)CrossRefGoogle Scholar
  9. 9.
    Gobbetti, E., Pili, P., Zorcolo, A., Tuveri, M.: Interactive virtual angioscopy. In: Proc. of IEEE Visualization, pp. 435–438 (1998)Google Scholar
  10. 10.
    Bartz, D., Straßr, W., Skalej, M., Welte, D.: Interactive exploration of extra and intracranial blood vessels. In: Proc. of IEEE Visualization, pp. 389–392 (1999)Google Scholar
  11. 11.
    Preim, B., Oeltze, S.: 3d visualization of vasculature: An overview. Visualization in Medicine and Life Science, 39–59 (2007)Google Scholar
  12. 12.
    Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. In: Proc. of ACM SIGGRAPH, pp. 163–169 (1987)Google Scholar
  13. 13.
    Hong, Q., Li, Q., Tian, J.: Implicit reconstruction of vasculatures using implicit splines. submitted to IEEE Transactions on Medical Imaging (2011)Google Scholar
  14. 14.
    Elvins, T.: A survey of algorithms for volume visualization. Computer Graphics ACM Siggraph Quarterly 26(3), 194–201 (1992)CrossRefGoogle Scholar
  15. 15.
    Lorensen, W., Jolesz, F., Kikinis, R.: The exploration of cross-sectional data with a virtual endoscope. In: Satava, R., Morgan, K. (eds.) Interactive Technology and New Medical Paradigms for Health Care, pp. 221–230 (1995)Google Scholar
  16. 16.
    Nain, D., Haker, S., Kikinis, R., Grimson, W.: An interactive virtual endoscopy tool. In: Proceedings of Workshop on Interactive Medical Image Visualization and Analysis (2001)Google Scholar
  17. 17.
    Bruckner, S.: Efficient volume visualization of large medical datasets. Master’s thesis, Computer Science Department, Technical University of Vienna (2003)Google Scholar
  18. 18.
    Vining, D., Stelts, D., Ahn, D., Hemler, P., Ge, Y., Hunt, G., Siege, C., McCorquodale, D., Sarojak, M., Ferretti, G.: Freeflight: A virtual endoscopy system. In: Troccaz, J., Mösges, R., Grimson, W.E.L. (eds.) CVRMed-MRCAS 1997, CVRMed 1997, and MRCAS 1997. LNCS, vol. 1205, pp. 413–416. Springer, Heidelberg (1997)Google Scholar
  19. 19.
    Tuy, H., Tuy, L.: Direct 2-d display of 3-d objects. IEEE Computer Graphics and Applications 4(10), 29–33 (1984)CrossRefGoogle Scholar
  20. 20.
    Westover, L.: Footprint evaluation for volume rendering. Computer Graphics 24(4), 367–376 (1990)CrossRefGoogle Scholar
  21. 21.
    Cabral, B., Cam, N., Foran, J.: Accelerated volume rendering and tomographic reconstruction using texture mapping hardware. In: 1994 Symposium on Volume Visualization, Conference Proceedings, ACM SIGGRAPH, pp. 91–98 (1994)Google Scholar
  22. 22.
    Serlie, I., Vos, F., Gelder, R.v., Post, F., Nio, Y., Gerritsen, F., Truyen, R., Stoker, J.: Improved visualization in virtual colonoscopy using image-based rendering. In: Data Visualization (Proceedings of Symposium on Visualization), pp. 137–146 (2001)Google Scholar
  23. 23.
    Beier, J., Diebold, T., Vehse, H., Biamino, G., Fleck, E., Felix, R.: Virtual endoscopy in the assessment of implanted aortic stents. Computer Assisted Radiology, 183–188 (1997)Google Scholar
  24. 24.
    Schumann, C., Oeltze, S., Bade, R., Preim, B., Peitgen, H.O.: Model-free surface visualization of vascular trees. In: IEEE/Eurographics Symposium on Visualization 2007, pp. 283–290 (2007)Google Scholar
  25. 25.
    Nakajima, N., Wada, J., Miki, T., Haraoka, J., Hata, N.: Surface rendering-based virtual intraventricular endoscopy: Retrospective feasibility study and comparison to volume rendering-based approach. NeuroImage 37 (suppl. 1), 89–99 (2007)CrossRefGoogle Scholar
  26. 26.
    Vilanova, A., Köig, A., Gröler, E.: Viren: A virtual endoscopy system. Journal Machine Graphics and Vision 8(3), 469–487 (1999)Google Scholar
  27. 27.
    Li, Q., Tian, J.: 2d piecewise algebraic splines for implicit modeling. ACM Transactions on Graphics 28(2) (2009)Google Scholar
  28. 28.
    Li, Q.: Smooth piecewise polynomial blending operations for implicit shapes. Computer Graphics forum 26(2), 157–171 (2007)CrossRefGoogle Scholar
  29. 29.
    Oeltze, S., Preim, B.: Visualization of vascular structures with convolution surfaces: Method, validation and evaluation. IEEE Transactions on Medical Imaging 25(3) (2005)Google Scholar
  30. 30.
    Lin, M., Gottschalk, S.: Collision detection between geometric models: A survey. In: Proc. of IMA Conference on Mathematics of Surfaces (1998)Google Scholar
  31. 31.
    Osher, S., Fedkiw, R.: Level Set Methods and Dynamic Implicit Surfaces. Springer, New York (2002)zbMATHGoogle Scholar
  32. 32.
    Sethian, J.A.: Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge University Press, Cambridge (1999)Google Scholar
  33. 33.
    Louisa, N., Bruguiereb, E., Kobeiterb, H., Desgrangesa, P., Allairea, E., Kirschc, M., Becquemina, J.: Virtual angioscopy and 3-dimensional navigation findings of the aortic arch after vascular surgery. European Journal of Vascular and Endovascular Surgery 40(3), 340–347 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Qingqi Hong
    • 1
  • Qingde Li
    • 1
  • Jie Tian
    • 2
  1. 1.Department of Computer ScienceUniversity of HullHullUK
  2. 2.Institute of Automation, Chinese Academy of SciencesBeijingChina

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