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Volume Visualization

Volume Visualization. Acknowledgements: Torsten M öller (SFU). Parallel Coordinates. Direct Volume Rendering. Hauser et al. Fua et al. Isosurfaces. Glyphs. Scatter Plots. Line Integral Convolution. Node-link Diagrams. Cabral & Leedom. Streamlines. Lamping et al. Verma et al.

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Volume Visualization

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  1. Volume Visualization Acknowledgements: Torsten Möller (SFU)

  2. Parallel Coordinates Direct Volume Rendering Hauser et al. Fua et al. Isosurfaces Glyphs Scatter Plots Line Integral Convolution Node-link Diagrams Cabral & Leedom Streamlines Lamping et al. Verma et al. SciVis InfoVis

  3. Overview • Data & Applications • Slicer tools • Iso-surfaces • Direct Volume Rendering • Challenges

  4. Medical Scanning • MRI, CT, SPECT, PET, ultrasound

  5. Medical Scanning - Applications • Diagnosis • Surgery planning • Tele-medicine • Inter-operative visualization in brain surgery, biopsies, etc.

  6. Medical Scanning - Applications • Medical education for anatomy, surgery, etc. • Illustration of medical procedures to the patient

  7. Biological Scanning • Scanners: Biological scanners, electronic microscopes, confocal microscopes • Apps – physiology, paleontology, microscopic analysis…

  8. Industrial Scanning • Planning (e.g., log scanning) • Quality control • Security (e.g. airport scanners)

  9. Scientific Computation - Domain • Mathematical analysis • ODE/PDE (ordinary and partialdifferential equations) • Finite element analysis (FE) • Supercomputer simulations

  10. Compassis.com Tecplot.com Scientific Computation - Apps • Flow Visualization(next week)

  11. Data Dimensionality • 3D (spatial data) or 4D (3D spatial + time) • May be multivariate (several data values at each point) Voxel

  12. Overview • Data & Applications • Slicer tools • Iso-surfaces • Direct Volume Rendering • Challenges

  13. Volume Slicer 3D Slicer McGuffin et al.

  14. Overview • Data & Applications • Slicer tools • Iso-surfaces • Direct Volume Rendering • Challenges

  15. Isosurfaces - Examples Isolines Isosurfaces Tecplot.com

  16. Isosurface Extraction 0 1 1 3 2 • by contouring • “marching cubes” is most common method 1 3 6 6 3 3 7 9 7 3 2 7 8 6 2 1 2 3 4 3 Iso-value = 5

  17. MC: Classify Each Voxel • Each voxel is either- outside the surface (> isovalue) - inside the surface (<= isovalue) 10 10 Iso=9 5 5 10 8 Iso=7 8 8 =inside =outside

  18. MC: Assign Triangles • all 256 cases can be derived from 15 base cases

  19. c a b MC: Example

  20. MC: Find Edge Locations • For each triangle edge, find the vertex location along the edge using linear interpolation of the voxel values i+1 i x =10 =0 Isovalue = 3 Isovalue = 8

  21. MC: Compute Normals • Calculate the normal at each cube vertex using central differencing: • Use linear interpolation to compute the polygon vertex normal

  22. MC: Render!

  23. Overview • Data & Applications • Slicer tools • Iso-surfaces • Direct Volume Rendering • Challenges

  24. Direct Volume Rendering Examples

  25. Rendering Pipeline Classify

  26. Classification • original data set has application specific values (temperature, velocity, proton density, etc.) • assign these to color/opacity values to make sense of data • achieved through transfer functions

  27. opacity RGB Shading, Compositing… Human Tooth CT Transfer Functions RGB • Simple (usual) case: Map data value to color and opacity opacity Data Value Gordon Kindlmann

  28. Transfer Functions • Setting transfer functions is difficult and unintuitive University of Utah

  29. Transfer Function Challenges • Better interfaces: • Make space of TFs less confusing • Remove excess “flexibility” • Provide guidance • Automatic / semi-automatic transfer function generation • Typically highlight boundaries

  30. Rendering Pipeline Classify Shade

  31. Light Effects • Usually only consider reflected part Light reflected specular Light absorbed ambient diffuse transmitted Light=refl.+absorbed+trans. Light=ambient+diffuse+specular

  32. Rendering Pipeline Classify Shade Interpolate

  33. 1D • Given: • Needed: • Needed: Interpolation • Given: 2D

  34. Interpolation • Accuracy is important • Expensive => done very often for one image Linear Nearest neighbor

  35. Rendering Pipeline Classify Shade Interpolate Composite

  36. Volumetric Ray Tracing color opacity object (color, opacity)

  37. Ray Traversal Schemes Intensity Max Average Accumulate First Depth

  38. Ray Traversal - First • First: extracts iso-surfaces (again!)done by Tuy&Tuy ’84 Intensity First Depth

  39. Ray Traversal - Average • Average: produces basically an X-ray picture Intensity Average Depth

  40. Ray Traversal - MIP • Max: Maximum Intensity Projectionused for Magnetic Resonance Angiogram Intensity Max Depth

  41. Ray Traversal - Accumulate • Accumulate: make transparent layers visible! Intensity Accumulate V. Anupam et al. Depth

  42. 1.0 Volumetric Ray Integration color opacity V. Anupam et al. object (color, opacity)

  43. Isosurface Slicer Direct Volume Rendering

  44. Overview • Data & Applications • Slicer tools • Iso-surfaces • Direct Volume Rendering • Challenges

  45. Challenges - Accuracy • Need metrics -> perceptual metric Original Bias-added Edge-distorted

  46. Challenges - Accuracy • Deal with unreliable data (e.g., Ultrasound data is noisy)

  47. Challenges - Speed/Size • Efficient algorithms • Hardware developments (VolumePro) • Utilize current hardware (nvidia, ATI) • Compression schemes • Tera-byte data sets

  48. Challenges - HCI • Need better interfaces for specifying parameters • Which method is best?

  49. Challenges - HCI • Virtual and Augmented reality • Explore novel I/O devices Schkolne et al. Konieczny et al., Vis 2005

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