Smart Hardware- Accelerated Volume Rendering Stefan Roettger Stefan Guthe Daniel Weiskopf Wolfgang Strasser Thomas Ertl

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 2 Overview Current state of the art in direct volume rendering What can be improved? Rendering of segmented data Hardware-accelerated raycasting

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 3 Direct Volume Rendering 3D slicing approach (Akeley ‘87) Pre-integration (Max VolVis ‘90, Roettger VIS ‘00, Engel HWW ‘01) Pre-integrated material properties (Meissner GI ‘02) Hardware-accelerated pre-integration (Roettger VolVis ‘02, Guthe HWW ‘02) Multi-Dimensional TF (Kniss VIS ‘01) Volume clipping (Weiskopf VIS ‘02)

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 4 What is missing? From a medical point of view: Pre-integration is difficult to apply to segmented medical data Pre-integration quality is still not good enough 8 bit frame buffer produces artifacts on consumer graphics hardware

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 5 Pre-Integration Ray integral depends on three variables: S f, S b, and l, where l is assumed to be constant Pre-compute a table for all combinations of S f and S b and store it in a 2D dependent texture

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 6 Volume Clipping Use additional scalar clip volume C(x,y,z) Iso surface for C=0.5 defines clip geometry Adjust S f, S b, and l according to clip volume (naive approach: set l=0) for the case C f <0.5<C b w = |C b -0.5|/|C b -C f | S’ f = (1-w)*S b +w*S f l’= l*w   ’ ≈  *w C=0.5

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 7 Pre-Integration & Segmentation Segmentation with two materials is easy: Define second transfer function TF2 In the pixel shader: Make a lookup in TF1 for the blue area Blend with the lookup in TF2 for the grey area C=0.5

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 8 Quality Comparison naive clipping correct adjust- ment clipped Bonsai

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 9 Undersampling Quality Slicing artifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 10 Undersampling Quality Slicing artifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 11 Sampling Quality Slicing artifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 12 Sampling Quality Interpolation artifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 13 Supersampling Quality Still minor interpolation artifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 14 Supersampling Quality Almost correct

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 15 Drawback of Pre-Integration Linear interpolation assumed in slab But in fact the interpolation is trilinear Inside the slab one may cross a voxel boundary Lighting is also a non-linear operation Conclusion: For superior quality we need at least 2-times, better 4-times oversampling!

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 16 Ray Casting Supersampling is slow, but fortunately we do not need to supersample everywhere Define importance volume which tells where to sample more precisely Depends on 2nd deriv. of scalar volume and 1st deriv. of TF Perform adaptive ray casting on the graphics hardware

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 17 Hardware-Accelerated Ray Casting Implemented on the ATI Radeon 9700 with multiple floating point render targets: Need to process all pixels at once Cannot exploit ray coherence Early ray termination by early Z-test Exploit hierarchical Z-buffer compression Adaptive sampling includes space leaping Stop if all pixels are terminated (asynchronous occlusion query)

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 18 Hardware-Accelerated Ray Casting Store ray parameter to determine actual position Complete PS 2.0 code given in the paper

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 19 Quality Comparison 4-times oversampling 8 bit frame buffer HW ray casting full floating point

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 20 Performance Same performance as 4 times over-sampling with alpha Direct 9 drivers (about 2 seconds per frame) But already much better quality With latest drivers we achieve 2-5 frames per second due to greatly improved performance of occlusion query (12 ms vs. 100 ms)

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 21 ANFSCD: The Bonsai Note: Raw data of all three Bonsai’ is available on my homepage

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 22 Conclusions We have shown how to combine volume clipping/segmentation with pre-integrated volume rendering With respect to quality HW ray casting is superior to the traditional slicing approach and with latest drivers is also faster By reducing the number of adaptive samples frame rates can be pushed even higher while maintaining good quality Now switching to the Live Demo

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble 23 Thanks for your attention! Fin