skip to main content
research-article

Visualizing what lies inside

Published:01 May 2009Publication History
Skip Abstract Section

Abstract

Medical imaging has given radiologists an ability that photography was not able to provide: it lets them see inside the human body. With the advent of 3D visualization systems, these images can be put together into crisp and impressive renderings of the human body from a variety of perspectives that were only dreamt of before, revolutionizing clinical practice.

Light transport models soon emerged to allow light interactions that, although not realistic in the physical sense, proved to be more effective for understanding the complex relationships among the anatomical structures. For instance, bone could be made semi-transparent to provide visibility of brain tissue. Skin could be removed altogether from an image to show only muscle or internal organs. However, soon it became evident that simply rendering these images in their raw form was no longer effective and the clear visualization of internal structures remains elusive.

The depiction of internal parts in the context of the enclosing space is a difficult problem that has occupied the mind of artists, illustrators and visualization practitioners. Despite the advances made in computer graphics for simulating the light transport in semi-transparent media, the problem of visualizing internal objects is no longer a rendering problem, but that of classification. Medical imaging technology obtains representations of anatomical structures via indirect ways, such as the response of tissue to X-rays or the alignment of electrons in a magnetic field. Therefore, the absence of semantic information prevents visualization practitioners from clearly marking up the regions that must be visualized. Without access to those regions, exploration becomes tedious and time-consuming. The predominant approach has been the use of transfer functions, or opacity mappings, which assign transparency properties to different intervals in the data. This method, however, does not guarantee that internal structures are visible. Other strategies must be used. In this article, I describe some visualization techniques that have emerged to obtain clear views of internal features in 3D volume data.

References

  1. S. Bruckner and M. Eduard Groller. Exploded Views for Volume Data. IEEE Transactions on Visualization and Computer Graphics 12, 5 (Sep. 2006), 1077-1084. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. S. Bruckner, S. Grimm, A. Kanitsar, and M. E. Groller, Illustrative context-preserving volume rendering. In Proceedings of EuroVis 2005, pages 69--76, 2005 Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. C. Correa, D. Silver, and M. Chen, Discontinuous displacement mapping for volume graphics. In Proc. Volume Graphics '06, 2006, pp. 9 -16.Google ScholarGoogle Scholar
  4. C. D. Correa, Deborah Silver, Min Chen, Feature Aligned Volume Manipulation for Illustration and Visualization, IEEE Transactions on Visualization and Computer Graphics, v.12 n.5, p.1069-1076, September 2006 Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. C. D. Correa and K-L. Ma. Visibility Driven Transfer Functions. IEEE VGTC Pacific Visualization Symposium 2009, Beijing, China, Apr 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. C. D. Correa, and K. Ma. 2008. Size-based Transfer Functions: A New Volume Exploration Technique. IEEE Transactions on Visualization and Computer Graphics 14, 6 (Nov. 2008), 1380-1387. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. G. Kindlmann, R. Whitaker, T. Tasdizen, and T. Moller. Curvature-based transfer functions for direct volume rendering: Methods and applications. In Proc. IEEE Visualization 2003, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Kruger, J. Schneider, R. Westermann, ClearView: An Interactive Context Preserving Hotspot Visualization Technique. IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Visualization 2006) Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. M. Levoy. Display of surfaces from volume data. IEEE Comput. Graph. 9. Appl., 8(3):29--37, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. McGuffin, L. Tancau, and R. Balakrishnan, Using deformations for browsing volumetric data. In Proceedings of IEEE Visualization 2003, pages 401--408, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. C. Rezk-Salama and A. Kolb, Opacity peeling for direct volume rendering. Computer Graphics Forum, 25 (3): 597--606, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  12. Y. Sato, C.-F. Westin, A. Bhalerao, S. Nakajima, N. Shiraga, S. Tamura, and R. Kikinis. Tissue classification based on 3d local intensity structure for volume rendering. IEEE Trans. on Visualization and Computer Graphics, 6(2):160--180, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ivan Viola, Armin Kanitsar, M. Eduard Groller, Importance-Driven Feature Enhancement in Volume Visualization, IEEE Trans. on Visualization and Computer Graphics, v.11 n.4, p.408-418, July 2005 Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D. Weiskopf, K. Engel, and T. Ertl, Interactive clipping techniques for texture-based volume visualization and volume shading. IEEE Trans. Vis. Comput. Graph., 9 (3): 298--312, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Visualizing what lies inside

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in

            Full Access

            • Published in

              cover image ACM SIGGRAPH Computer Graphics
              ACM SIGGRAPH Computer Graphics  Volume 43, Issue 2
              Building Bridges - Science, the Arts & Technology
              May 2009
              37 pages
              ISSN:0097-8930
              DOI:10.1145/1629216
              Issue’s Table of Contents

              Copyright © 2009 Author

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 1 May 2009

              Check for updates

              Qualifiers

              • research-article

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader
            About Cookies On This Site

            We use cookies to ensure that we give you the best experience on our website.

            Learn more

            Got it!