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

over time, so the resulting datasets are four-dimensional, which implies that highperformance
interactive visualizations are required for a presentation of this data in
combination with a conventional presentation of medical data.
The desired solution is a workflow which integrates these measurement sequences
with a preprocessing software into an interactive visualization framework. Therefore,
we extended a medical image viewer with scene graph based and hardware accelerated
point based visualization algorithms to combine the measured velocity fields with the
morphological background.
Chapter 2 gives an overview of possible visualization techniques for medical data
and flow data. This approach introduces scientific visualization used for n-dimensional
flow data. Due to the high computational costs for rendering flow and anatomical
datasets, hardware acceleration techniques are required. The corresponding graphics
hardware architecture is also presented in chapter 2.
It is crucial to present interesting parts of blood flow in an instructive way, so that
a possible diagnostic use is given. The special MRI sequence which was developed to
continuously measure the movement of blood in human vessels is described in chapter 3
after a short introduction into the basics of magnetic resonance imaging.
To apply these algorithms chapter 4 defines the workflow with all preprocessing
steps for the raw data which are required until an advanced data visualization can be
performed. This workflow is one of the main attainments of this work and is outlined
in figure 1.1.
This work concentrates on point-based and sparse flow representations as defined by
[Weiskopf2007]. We implemented different types of direct particle based visualizations
and particle trajectory based line visualizations. Additionally we provide several cutting
plane visualizations and improvements of basic line approaches. All these visualization
algorithms can be combined arbitrarily and are specified in detail in chapter 5.
To reduce the development work for GUI and further overhead, a medical image
viewer called iMEDgine was extended, which is based on scene graphs as provided by
the Coin3D [SystemsInMotion2007] library. On the one hand data flow abilities were
added as provided by a scene graph extension library called Cash-flow [Kalkusch2005]
and on the other hand high-performance and parallel executed shader algorithms for
complex flow visualizations were developed. Chapter 5 describes the details for these
combinations and outlines their dependencies.
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