Master's Thesis - Studierstube Augmented Reality Project - Graz ...

6.4 Scalability
(a) Viewing a human heart from above with the
pulmonary artery in the front and the vena cava
superior in the right handed background. Additionally
the morphological data is rendered by a
SimVoleon sub-tree.
(b) The flow phantom dataset shows
the artificial stenosis viewed slightly
against the flow direction.
Figure 6.2: Point based glyph overview of the human heart of subject number two
(a) and a flow-phantom view (b) displayed with a Cash-Flow render node. Both are
containing 15 measured slices.
On the GeForce 8800 graphics card all algorithms showed that they are suitable for
real-time applications except a flexible cutting plane with 1024x1024 vertices. But this
visualization subjectively gives the same information with 512x512 vertices and a bigger
buffer size may not be necessary. Figure 6.9 additionally compares the performances
with concurrently used volume rendering utilizing a SimVoleon render node to a visualization
without any morphological data rendering. Figure 6.8, 6.10 and 6.11 compare
the pure flow visualizations with ones using the slice-rendering node as presented in
section 5.3.1. As expected a more advanced volume rendering approach decreases the
achievable frame rate. A cutting plane based on a bump mapping approach is in these
figures compared noncompetitive since this technique only needs four vertices and performs
a direct texture lookup in its fragment shader. The used dataset was always the
same - 256x104 pixels x 11 slices x 2 time steps - flow phantom with emulated ECG
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