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

Chapter 8
Conclusions
We investigated the visualization capabilities of four-dimensional cardiovascular flow as
measurable by magnetic resonance phase-contrast imaging. This thesis summarizes the
steps from the measurement process to a preprocessing toolbox to a scene-graph based
medical image viewer which we extended with advanced GPU-accelerated visualization
techniques.
Due to an accurate and intuitive workflow we were able to present the flow data
and its corresponding morphological image data directly after the measurement with
fast configurable and combinable views. To give a possible usage of these visualizations
for diagnostics, we had to aim for interactive manipulations of the scenes and hence for
highly efficient rendering algorithms. Consequently, we tested programmable graphics
hardware with different performance and a data-flow scene-graph library called Cash-
Flow. Additionally, three volume rendering approaches to present the morphological
background data were discussed with our medical partners. To them, rendering the
measured images directly with a Gauss-distribution weighted transparency value on
top of each other appeared to be the most intuitive morphological visualization.
For flow visualizations we concentrated on sparse representations of the velocity
fields. These, mostly particle trajectory based approaches, appeared to be more instructive
to our medical partners and were more suitable for acceleration techniques in
contrast to dense, texture based algorithms. We implemented glyph and color mapped
arrow plots, different kinds of direct particle rendering and stream lines and path lines,
both with illumination techniques and a stream tube impostor render upgrade, applicable
to particle trajectories. A color mapping gradient editor was developed to ease
the definition of transfer functions to characterize different flow parameter.
To evaluate the accuracy of the implemented flow visualization techniques we built a
flow phantom with an artificial narrowing to obtain a clear and concise steady flow over
time. We could demonstrate that all developed algorithms yield to a comprehensible
result. Due to a not achieved steady flow, a mathematical proof of the measured flow
values and resulting visualizations was not possible yet. This issue should get feasible
after several improvements of the flow phantom.
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