The size of volumetric datasets used in medical environments is increasing at a rapid pace. Due to excessive pre-computation and memory demanding data structures, most current approaches for volume visualization do not meet the requirements of daily clinical routine. In this diploma thesis, an approach for interactive high-quality rendering of large medical data is presented. It is based on image-order raycasting with object-order data traversal, using an optimized cache coherent memory layout. New techniques and parallelization strategies for direct volume rendering of large data on commodity hardware are presented. By using new memory efficient acceleration data structures, high-quality direct volume rendering of several hundred megabyte sized datasets at sub-second frame rates on a commodity notebook is achieved.

Examining irregularly sampled data sets usually requires gridding that data set. How-ever, examination of a data set at one particular resolution may not be adequate since either fine details will be lost, or coarse details will be obscured. In either case, the original data set has been lost. We present an algorithm to create a regularly sampled data set from an irregular one. This new data set is not only an approximation to the original, but allows the original points to be accurately recovered, while still remain-ing relatively small. This result is accompanied by an efficient ‘zooming ’ operation that allows the user to increase the resolution while gaining new details, all without re-gridding the data. The technique is presented in N-dimensions, but is particu-larly well suited to Fourier Volume Rendering, which is the fastest known method of direct volume rendering. Together, these techniques allow accurate and efficient, multi-resolution exploration of volume data.

For applications of volume visualization in medicine, it is important to assure that the 3D images show the true anatomical situation, or at least to know about their limitations. In this paper, various methods for evaluation of image quality are reviewed. They are classified based on the fundamental terms of intelligibility and fidelity, and discussed with respect to the question what clues they provide on how to choose parameters, or improve imaging and visualization procedures.

This paper presents a user study of the visual quality of an imaging pipeline employing the optimal body-centered cubic (BCC) sampling lattice. We provide perceptual evidence supporting the theoretical expectation that sampling and reconstruction on the BCC lattice offer superior imaging quality over the traditionally popular Cartesian cubic (CC) sampling lattice. We asked 12 participants to choose the better of two images: one image rendered from data sampled on the CC lattice and one image that is rendered from data sampled on the BCC lattice. We used both synthetic and CT volumetric data, and confirm that the theoretical advantages of BCC sampling carry over to the perceived quality of rendered images. Using 25 % to 35 % fewer samples, BCC sampled data result in images that exhibit comparable visual quality to their CC counterparts.

In this paper, a simple and efficient solution for combining shear-warp volume rendering and the hardware graphics pipeline is presented. The approach applies an inverse warp transformation to the Z-Buffer, containing the rendered geometry. This information is used for combining geometry and volume data during compositing. We present applications of this concept which include hybrid volume rendering, i.e., concurrent rendering of polygonal objects and volume data, and volume clipping on convex clipping regions. Furthermore, it can be used to efficiently define regions with different rendering modes and transfer functions for focus+context volume rendering. Empirical results show that the approach has very low impact on performance. 1

The tools used in many scientific fields for the quantization of three-dimensional objects yield volumetric data sets. These data sets are often stored as scalar fields along a three-dimensional rectilinear grid. Non-rectilinear grids are often resampled to a rectilinear grid to allow efficient processing. Each cubic, face-adjacent cell composed by the grid is

Atmospheric simulation is an important means of understanding the environment around us. Through the collection of large amounts of atmospheric data and computer modeling one can predict how variuos particulates such as dirt, smog, and fire can affect our cities and overall public health. However, gleaning insight from numerical

This work reports the development of a CPU-based Direct Volume Rendering (DVR) software, which was implemented for medical visualisation in the field of CT-Angiography. An interactive DVR-plugin was finally added to the so called AngioVis-Toolbox, a software for post-processing and visualisation of CTA datasets. This work was focusing on finding adequate solutions to provide an interactive behaviour of the DVR-tool. This was accomplished by investigating several acceleration strategies, which were assessed with respect to their effectivity. Further this work sketches an alternative efficient solution for vessel-tree related focus and context visualisation referring to the so-called concept of ”VesselGlyph”, which was proposed before by members of the AngioVis-Project.

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For about twenty years the standard color sampling method for RGBA volume data has been the interpolation of opacity-weighted colors. In this work, we discuss the underlying approximations and derive an improved sampling method, which avoids some of these approximations. With the help of several examples and experiments we demonstrate that our new technique is in fact preferable for direct volume rendering of RGBA data. Moreover, we show that the same improvement can be applied to downsampling filters. Finally, we propose a procedure to design improved downsampling filters for the generation of pyramid RGBA volume data such as mipmap volume textures. 1