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Dynamic Shader Generation for Flexible Multi-Volume Visualization


Friedemann Rößler[1], Ralf P. Botchen[2]
  Paper    
F. Rößler, R. P. Botchen, and T. Ertl.
Dynamic Shader Generation for Flexible Multi-Volume Visualization.
In Proceedings of IEEE Pacific Visualization Symposium 2008 (PacificVis '08), pages 17-24, 2008
[pdf][3]   |   [bibtex][4]  
  Abstract    
Volume rendering of multiple intersecting volumetric objects is a difficult visualization task, especially if different rendering styles need to be applied to the components, in order to achieve the desired illustration effect. Real-time performance for even complex scenarios is obtained by exploiting the speed and flexibility of modern GPUs, but at the same time programming the necessary shaders turned into a task for GPU experts only. We foresee the demand for an intermediate level of programming abstraction where visualization specialists can realize advanced applications without the need to deal with shader programming intricacies.
In this paper, we describe a generic technique for multi-volume rendering, which generates shader code dynamically from an abstract render graph. By combining pre-defined nodes, complex volume operations can be realized. Our system efficiently creates GPU-based fragment shader and vertex shader programs ``on-the-fly'' to achieve the desired visual results. We demonstrate the flexibility of our technique by applying several dynamically generated volume rendering styles to multi-modal medical datasets.
  Video    
This video demonstrates the interactive configuration of a complex rendergraph which is detailed in the paper.

[multivol.mov, Quicktime, ~43MB][5]   |   [multivol.zip, Zipped, ~34MB][6]  
  Images    
[7] [8] [9]

Setup I: Combination of a CTA (Computed Tomography Angiography) dataset and a related MRI (Magnetic Resonance Imaging) dataset of a human head. The MRI dataset provides the skin and brain tissue. It is vertically cut and the two halves are moved away from each other to get insight to the inner structures. The CTA dataset contains the skull and the vessels which are rendered with different transfer functions. The upper images show three stages of an interactive multi-volume visualization session, the lower images show the corresponding render graphs.


[10]

Setup II: This setup shows a DVR shaded functional MRI (fMRI) dataset combined with an corresponding brain MRI dataset rendered as illuminated semi-transparent isosurface and a single 2D slice of the whole head as context information.


[11]

Setup III: This setup shows the combination of an illuminated DVR shaded MRI head with a ghosting method applied to see the inside. The interior brain is rendered as illuminated isosurface with a 3D LIC computation applied, to emphasize the curvature.


[12]

Setup IV: For this setup the upper half of the head is cut away, to lay open the brain, which is segmented and colored due to a functional brain atlas.

      Universität Stuttgart, Institut für Informatik,
Abteilung Visualisierung und Interaktive Systeme

http://www.vis.uni-stuttgart.de/ger/research/fields/current/multivol/index.html