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: Sf,

Sb, and l, where l is assumed to be constant

• Pre-compute a table for all combinations of Sf and Sb 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 Sf, Sb, and l according to clip volume (naive approach: set l=0)

• for the case Cf<0.5<Cb

• w = |Cb-0.5|/|Cb-Cf|

• S’f = (1-w)*Sb+w*Sf

• 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

7Pre-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

naiveclipping

correctadjust-ment

clippedBonsai

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

9

Undersampling Quality

Slicingartifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

10

Undersampling Quality

Slicingartifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

11

Sampling Quality

Slicingartifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

12

Sampling Quality

Interpolationartifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

13

Supersampling Quality

Still minorinterpolationartifacts

Smart Hardware-Accelerated Volume Rendering VisSym ‘03 Stefan Roettger, University of Erlangen - Stefan Guthe, University of Tübingen Grenoble

14

Supersampling Quality

Almostcorrect

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

17Hardware-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

18Hardware-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 Comparison4-times oversampling

8 bit frame bufferHW 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