Visualization of Volumetric Medical Image Data

  • K. J. Zuiderveld
  • M. A. Viergever

Abstract

This paper presents on the state-of-the-art of volume visualization methods that are tuned to visualization of medical datasets. After topics as sampling theory, data preparation, and shading, various visualization strategies are explained with an emphasis on algorithms that do not rely on special hardware. Special attention is paid to strategies that improve image generation speed, while techniques for improvement of image quality are also discussed. Finally, trends in this area of research are identified.

Keywords

Attenuation Coherence Convolution Sine Pyramid 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    F. Zonneveld, S. Lobregt, J. van der Meulen, and J. Vaandrager, “Three-dimensional imaging in craniofacial surgery,” World J. Surg, vol. 13, pp. 328–342, 1989.CrossRefGoogle Scholar
  2. 2.
    E. Fishman, D. Ney, and D. Magid, Three-Dimensional Imaging: Clinical Applications in Orthopedics, pp. 425–440. K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.CrossRefGoogle Scholar
  3. 3.
    D. Ney, E. Fishman, and D. Magid, “Three-dimensional imaging of computed tomography: Techniques and applications,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990, pp. 498–506.CrossRefGoogle Scholar
  4. 4.
    D. Ney and E. Fishman, “Editing tools for 3d medical imaging,” IEEE Computer Graphics and Applications, vol. 11, pp. 63–71, November 1991.CrossRefGoogle Scholar
  5. 5.
    S. Raya and J. Updupa, “Shape-based interpolation of multidimensional objects,” IEEE Transactions on Medical Imaging, vol. 9, pp. 32–42, March 1990.CrossRefGoogle Scholar
  6. 6.
    C. Liang, W. Lin, and C. Chen, “Intensity interpolation from serial cross-sections,” in SPIE Vol. 1092 Medical Imaging III: Image Processing, pp. 60–66, 1989.Google Scholar
  7. 7.
    J. Parker, R. Kenyon, and D. Troxel, “Comparison of interpolating methods for image resampling,” IEEE Transactions on Medical Imaging, vol. MI-2, pp. 31–39, March 1983.CrossRefGoogle Scholar
  8. 8.
    M. Levoy, “Rendering of surfaces from volume data,” IEEE Computer Graphics and Applications, vol. 8, no. 3, pp. 28–37, 1988.CrossRefGoogle Scholar
  9. 9.
    G. Frieder, D. Gordon, and R. Reynolds, “Back to front display of voxel-based objects,” IEEE Computer Graphics and Applications, vol. 5, pp. 52–59, January 1985.CrossRefGoogle Scholar
  10. 10.
    D. Cohen, A. Kaufman, R. Bakalash, and S. Bergman, “Real time discrete shading,” The Visual Computer, vol. 6, pp. 16–27, February 1990.CrossRefGoogle Scholar
  11. 11.
    A. Kaufman, R. Bakalash, D. Cohen, and R. Yagel, “A survey of architectures for volume rendering,” IEEE Engineering in Medicine and Biology, vol. 9, pp. 18–23, December 1990.CrossRefGoogle Scholar
  12. 12.
    K. Höhne, M. Bomans, A. Pommert, M. Riemer, C. Schiers, U. Tiede, and G. Wiebecke, “3d visualization of tomographic volume data using the generalized voxel model,” The Visual Computer, vol. 6, pp. 28–36, February 1990.CrossRefGoogle Scholar
  13. 13.
    A. Pommert, U. Tiede, G. Wiebecke, and K. Höhne, “Surface shading in tomographic volume visualization: A comparative study,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990, pp. 19–26.CrossRefGoogle Scholar
  14. 14.
    B. ter Haar Romeny, L. Florack, J. Koenderink, and M. Viergever, “Space space: Its natural operators and differential invariants,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990, pp. 239–255.Google Scholar
  15. 15.
    B. Phong, “Illumination for computer generated pictures,” Communications of the ACM, vol. 18, no. 6, pp. 311–317, 1975.CrossRefGoogle Scholar
  16. 16.
    J. Coatrieux and C. Barillot, A survey of 3D Display Techniques to Render Medical Data, pp. 175–196. K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.CrossRefGoogle Scholar
  17. 17.
    A. Kaufman, Volume rendering. IEEE Computer Society Press, 1990.Google Scholar
  18. 18.
    R. Robb and D. Hanson, “Analyze: A software system for biomedical image analysis,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990 pp. 507–518.CrossRefGoogle Scholar
  19. 19.
    H. Fuchs, Z. Kedem, and S. Uselton, “Optimal surface reconstruction from planar contours,” Communications of the ACM, vol. 20, pp. 693–702, October 1977.MathSciNetMATHCrossRefGoogle Scholar
  20. 20.
    H. Christiansen and T. Sederberg, “Conversion of complex contour line definitions into polygonal element mosaics,” Computer Graphics, vol. 12, pp. 187–192, July 1978. Proc. Siggraph.CrossRefGoogle Scholar
  21. 21.
    Y. Shinagawa and T. Kunii, “Constructing a reeb graph automatically from cross sections,” IEEE Computer Graphics and Applications, vol. 11, pp. 44–52, November 1991.CrossRefGoogle Scholar
  22. 22.
    W. Lorensen and H. Cline, “Marching cubes: A high resolution 3d surface construction algorithm,” Computer Graphics, vol. 21, pp. 163–169, July 1987. Proc. Siggraph.CrossRefGoogle Scholar
  23. 23.
    A. Wallin, “Constructing isosurfaces from ct data,” IEEE Computer Graphics and Applications, vol. 11, pp. 28–33, November 1991.CrossRefGoogle Scholar
  24. 24.
    H. Cline, W. Lorensen, S. Ludke, C. Crawford, and B. Teeter, “Two algorithms for the threedimensional reconstruction of tomograms,” Medical Physics, vol. 15, pp. 320–327, May/June 1988.CrossRefGoogle Scholar
  25. 25.
    W. Lorensen and H. Cline, “Volume modelling,” in Volume Visualization Algorithms and Architectures, pp. 45–65, 1989.Google Scholar
  26. 26.
    H. Cline, W. Lorensen, S. Souza, R. Kikinis, G. Gerig, and T. Kennedy, “3d surface rendered mr images of the brain and its vasculature,” journal of Computer Assisted Tomography, vol. 15, no. 2, pp. 344–351, 1991.CrossRefGoogle Scholar
  27. 27.
    J. Udupa and G. Herman, “Volume rendering versus surface rendering,” Communications of the ACM, vol. 32, pp. 1364–1366, 1989.Google Scholar
  28. 28.
    G. Frieder, G. Herman, C. Meyer, and J. Udupa, “Large software problems for small computers: An example from medical imaging,” IEEE Software, vol. 2, pp. 37–47, September 1985.CrossRefGoogle Scholar
  29. 29.
    K. Höhne, M. Bomans, A. Pommert, and U. Tiede, “Voxel-based volume visualization techniques,” in Volume Visualization Algorithms and Architectures, pp. 66–83, 1989.Google Scholar
  30. 30.
    R. Drebin, L. Carpenter, and P. Hanrahan, “Volume rendering,” Computer Graphics, vol. 22, no. 4, pp. 65–74, 1988. Proc. Siggraph.CrossRefGoogle Scholar
  31. 31.
    T. Porter and T. Duff, “Compositing digital images,” Computer Graphics, vol. 18, no. 3, pp. 253–259, 1984. Proc. Siggraph.CrossRefGoogle Scholar
  32. 32.
    D. Ney, E. Fishman, D. Magid, and R. Drebin, “Volumetric rendering of computed tomography data: Principles and techniques,” IEEE Computer Graphics and Applications, vol. 9, no. 2, pp. 24–32, 1990.CrossRefGoogle Scholar
  33. 33.
    K. Höhne, M. Bomans, A. Pommert, M. Riemer, U. Tiede, and G. Wiebecke, Rendering Tomographic Volume Data: Adequacy of Methods for Different Modalities and Organs, pp. 197–216. K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.CrossRefGoogle Scholar
  34. 34.
    A. Levinthal and T. Porter, “Chap — a simd graphics processor,” Computer Graphics, vol. 18, pp. 77–82, July 1984. Proc. Siggraph.CrossRefGoogle Scholar
  35. 35.
    M. Levoy, “Volume rendering by adaptive refinement,” The Visual Computer, vol. 6, pp. 2–7, February 1990.CrossRefGoogle Scholar
  36. 36.
    M. Levoy, “Efficient ray tracing of volume data,” ACM Transactions on Graphics, vol. 9, pp. 245–261, July 1990.MATHCrossRefGoogle Scholar
  37. 37.
    L. Westover, “Footprint evaluation for volume rendering,” Computer Graphics, vol. 24, pp. 367–376, August 1990. Proc. Siggraph.CrossRefGoogle Scholar
  38. 38.
    E. Fishman, R. Drebin, D. Magid, W. Scott, D. Ney, A. Brooker, L. Riley, A. Ville, E. Zerhouni, and S. Siegelman, “Volumetric rendering techniques: Applications for threedimensional imaging of the hip,” Radiology, vol. 163, no. 6, pp. 737–738, 1987.Google Scholar
  39. 39.
    J. Siebert, T. Rosenbaum, and J. Pernicone, “Automated segmentation and presentation algorithms for 3d mr angiography.” SMRM Poster 758, 1991.Google Scholar
  40. 40.
    F. Hottier and A. Billon, 3D Echography: Status and Perspective, pp. 21–41. K. Höhne, H. Fuchs, and S. Pizer, eds., 1990.K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990Google Scholar
  41. 41.
    J. Udupa and H. Hung, “Surface versus volume rendering: A comparative assessment,” in First Conference on Visualization in Biomedical Computing, pp. 83–91.Google Scholar
  42. 42.
    Kalender, Seibler, Klotz, and Vork, “Single-breathold spiral volumetric computed tomography by continuous patient translation and scanner rotation,” in Abstracts 75th annual meeting RSNA, (Chicago), p. paper No. 1370, 1989.Google Scholar
  43. 43.
    R. Ohbuchi and H. Fuchs, “Incremental volume rendering algorithm for interactive 3d ultrasound imaging,” in A. Colchester and D. Hawkes, eds., Information Processing in Medical Imaging, Springer-Verlag July 1991, pp. 486–450.CrossRefGoogle Scholar
  44. 44.
    J. Wilhelms and A. Van Gelder, “Octrees for faster isosurface generation,” Computer Graphics, vol. 25, pp. 57–62, November 1990. San Diego Workshop on Volume Visualization.CrossRefGoogle Scholar
  45. 45.
    D. Laur and P. Hanrahan, “Hierarchical splatting: A progressive refinement algorithm for volume rendering,” Computer Graphics, vol. 25, no. 4, pp. 285–288, 1991. Proc. Siggraph.CrossRefGoogle Scholar
  46. 46.
    J. Udupa and D. Odhner, “Fast visualization, manipulation, and analysis of binary volumetric objects,” IEEE Computer Graphics and Applications, vol. 11, pp. 53–62, November 1991.CrossRefGoogle Scholar
  47. 47.
    T. Foley, D. Lane, and G. Nielson, “Toward animating raytraced volume visualization,” The Journal of Visualization and Computer Animation, vol. 1, pp. 2–8, February 1990.CrossRefGoogle Scholar
  48. 48.
    B. Gudmundsson and M. Randén, “Incremental generation of projections of ct-volumes,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990, pp. 27–34.CrossRefGoogle Scholar
  49. 49.
    A. Pommert, U. Tiede, G. Wiebecke, and K. Höhne, Image Quality in Voxel-Based Surface Shading, pp. 737–741. Computer Assisted Radiology, Berlin: Springer-Verlag, 1989.Google Scholar
  50. 50.
    A. Pommert, W. Höltje, N. Holzknecht, U. Tiede, and K. Höhne, “Accuracy of images and measurements in 3d bone imaging,” in H. Lemke, M. Rhodes, C. Jaffe, and R. Felix, eds., Computer Assisted Radiology, Springer-Verlag, 1991, pp. 209–215.Google Scholar
  51. 51.
    M. Levoy, H. Fuchs, S. Pizer, J. Rosenman, E. Chaney, G. Sherouse, V. Interrante, and J. Kiel, “Volume rendering in radiation treatment planning,” in First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990, pp. 4–10.CrossRefGoogle Scholar
  52. 52.
    J. Foley, A. van Dam, S. Feiner, and J. Hughes, Computer Graphics — Principles and Practice. Addison-Wesley, second ed., 1990.Google Scholar
  53. 53.
    H. van der Voort, G. Brakenhoff, G. Janssen, J. Valkenburg, and N. Nanninga, “Confocal scanning fluorescence and reflection microscopy: Measurements of the 3-d image formation and application in biology,” in Proceedings SPIE vol. 808, pp. 138–143, 1987.Google Scholar
  54. 54.
    M. Levoy, “A hybrid ray tracer for rendering polygon and volume data,” IEEE Computer Graphics and Applications, vol. 10, pp. 33–40, March 1990.CrossRefGoogle Scholar
  55. 55.
    M. Levoy, Display of Surfaces from Volume Data. PhD thesis, University of North Carolina, Chapel Hill, May 1989.Google Scholar
  56. 56.
    J. Kajiya, “The rendering equation,” Computer Graphics, vol. 20, pp. 143–149, August 1986. Proc. Siggraph.CrossRefGoogle Scholar
  57. 57.
    P. Heckbert, “Adaptive radiosity textures for bidirectional ray tracing,” Computer Graphics, vol. 24, pp. 145–154, August 1990. Proc. Siggraph.CrossRefGoogle Scholar
  58. 58.
    H. Meinzer, K. Meetz, D. Scheppelmann, U. Engelmann, and H. Baur, “The heidelberg ray tracing model,” IEEE Computer Graphics and Applications, vol. 11, pp. 34–43, November 1991.CrossRefGoogle Scholar
  59. 59.
    M. Hagen, “How to make a visually realistic 3d display,” Computer Graphics, vol. 25, pp. 76–81, April 1991.CrossRefGoogle Scholar
  60. 60.
    M. Levoy, “Gaze-directed volume rendering,” Computer Graphics, vol. 24, no. 2, pp. 217–223, 1990.CrossRefGoogle Scholar
  61. 61.
    L. Williams, “Pyramidal parametrics,” Computer Graphics, vol. 17, pp. 1–11, July 1984. Proc. Siggraph.CrossRefGoogle Scholar
  62. 62.
    K. Novins, F. Sillion, and D. Greenberg, “An efficient method for volume rendering using perspective projection,” Computer Graphics, vol. 24, no. 5, pp. 95–102, 1990.CrossRefGoogle Scholar
  63. 63.
    A. Kaufman, R. Yagel, and D. Cohen, Intermixing Surface and Volume Rendering, pp. 217–228. K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.CrossRefGoogle Scholar
  64. 64.
    A. Kaufman, “Efficient algorithms for 3d scan-conversion of parametric curves, surfaces and volumes,” Computer Graphics, vol. 21, pp. 171–179, July 1987. Proc. Siggraph.MathSciNetCrossRefGoogle Scholar
  65. 65.
    H. Fuchs, M. Levoy, and S. Pizer, “Interactive visualization of 3D medical data,” IEEE Computer, pp. 46–51, August 1989.Google Scholar
  66. 66.
    X. Hu, K. Tan, D. Levin, C. Pelizari, and G. Chen, A Volume-Rendering Technique for Integrated Three-Dimensional Display of MR and PET Data, pp. 379–398. K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.CrossRefGoogle Scholar
  67. 67.
    P. van den Elsen and M. Viergever, “Fusion of electromagnetic source data and tomographic image data,” in H. Lemke, M. Rhodes, C. Jaffe, and R. Felix, eds., Computer Assisted Radiology, Springer-Verlag, 1991, pp. 240–246.Google Scholar
  68. 68.
    K. Höhne, H. Fuchs, and S. Pizer, eds., 3D Imaging In Medicine, vol. 60 of series F: Computer and System Sciences. Springer-Verlag, 1990.Google Scholar
  69. 69.
    IEEE Computer Science Society, First Conference on Visualization in Biomedical Computing, (Atlanta), IEEE Computer Society Press, 1990.Google Scholar
  70. 70.
    A. Colchester and D. Hawkes, eds., Information Processing in Medical Imaging, Springer-Verlag, July 1991.MATHGoogle Scholar
  71. 71.
    H. Lemke, M. Rhodes, C. Jaffe, and R. Felix, eds., Computer Assisted Radiology, Springer-Verlag, 1991.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1992

Authors and Affiliations

  • K. J. Zuiderveld
    • 1
  • M. A. Viergever
    • 1
  1. 1.Computer Vision Research GroupUniversity Hospital UtrechtUtrechtThe Netherlands

Personalised recommendations