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Importance Driven Volume Rendering

Authors: I. Viola, A. Kanitsar, M. Gr ö ler Institute of Computer Graphics and Algorithms Vienna University of Technology, Austria. Importance Driven Volume Rendering. Introduction (problem). Volume visualization has inherent difficulties with occlusion

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Importance Driven Volume Rendering

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  1. Authors: I. Viola, A. Kanitsar, M. GrölerInstitute of Computer Graphics and Algorithms Vienna University of Technology, Austria Importance Driven Volume Rendering

  2. Introduction (problem) • Volume visualization has inherent difficulties with occlusion • Exterior objects occlude interior objects • Interior objects might be more interesting or important

  3. Introduction (motivation) • 3D medical image visualization in general • Specific example: liver tumor visualization • For radiotherapy planning • For surgery planning • Need to clearly see: • Tumor location, size, shape • Blood vessel tree • Parenchyma http://www.vislab.uq.edu.au/research/liver/images/3D_liver_model.jpg

  4. Introduction (solution) • object importance • level of sparseness • make interesting objects occluded clearly visible Artistic medical illustration Method proposed in this paper

  5. Related Work • Transfer Function • Incorporate first and second derivatives (gradient and curvature values) • Degree of interest (Hauser & Mlejnek) • Focus +Context Rendering • Focus: Render that part with more detail, with magnification, or other enhancement • Context: according to Distance to focal point, detail or magnification gradually fades as distance increases

  6. Related Work • Sparse Representation • Interior structures — fully opaque • Enclosing objects — curvature-directed lines • Cut-Away Views

  7. Importance Driven Rendering • Importance is widely used in other graphics fields • Employ as additional dimension to improve the behavior of traditional approaches • Apply this in volume rendering

  8. Importance Driven Volume Rendering • Object Importance • Importance Compositing • Levels of sparseness

  9. Object Importance • Additional property besides color and opacity • Positive scalar value to show priority of each object importance • Constant for the whole object

  10. Levels of sparseness • Various different representations of a certain object from dense to sparse

  11. Importance Compositing • Specify the level of sparseness • Simple way:Maximum importance projection (MImP) • Average Importance Compositing

  12. Importance Compositing • Mode 1: Maximum Importance Projection • highest importance—visible • Highest sparseness—transparent • Assign sparseness level of 0 or 1 to each point 1 1 0

  13. Problems with MImP • The spatial management of structures is not readily apparent.

  14. Improved MImP • Consider MImP as a cut-away view Cylindrical Conical Countersink

  15. Importance Compositing • Mode 2: Average Importance Compositing • Compute sum of object importances along a ray • Each surface point intersected by the ray is assigned a sparseness level based on the ratio of its importance to the sum of all intersected surface importances 2 1 0

  16. Smooth Transition with level of sparseness • With Avg. Importance Compositing, generate jaggy object boundaries • Color and Opacity Modulation • Screen-Door Transparency • Volume Thinning

  17. Color and Opacity Modulation • Use transfer function to modulation the saturation of color and opacity 0.25 0.50 0.75

  18. Screen-Door Transparency • Semi-transparency • Object is Visible through the holes • Mesh occludes the object behind 0.25 0.50 0.75

  19. Volume Thinning • Render objects using a set of iso-surfaces 0.25 0.50 0.75

  20. Results • Pre-segmented objects • Leopard Gecko 512*512*87 • Monster Study 256*256*610

  21. Conclusion • A new factor to traditional volume rendering—object importance • Apply level of sparseness if interesting structures are occlude • Methods to smooth transitions

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