Tutorial 1 (Full day)
General Purpose Computation on Graphics Hardware

Course notes now available. Click here.

Desktop computer architecture is at a turning point. In the last two years, CPU speeds have nearly stopped increasing and all major CPU manufacturers have announced multi-core, parallel processors. Future performance improvements will predominantly come from parallelism rather than from an ever-increasing uniprocessor clock speed.

Commodity graphics processors (GPUs), in contrast, already contain many parallel processing units and are capable of sustaining computation rates greater than ten times that of a modern CPU. The GPU programming model, however, is very different from traditional CPU models. Researchers in the evolving field of general-purpose computation on graphics processors (GPGPU) are actively developing techniques to make the power of GPUs accessible to a wide range of programmers. This tutorial provides a detailed introduction and overview of GPGPU programming abstractions, modern GPU architectures, and the techniques required for attendees to apply GPUs to their own applications. This includes GPU acceleration of partial differential equation solvers, 2D and 3D image processing, and physical simulations. Also, until recently visualization has primarily focused on exploration of pre-captured data. The ability to perform GPGPU-based interactive simulation on a desktop PC, however, opens up a wealth of new visualization research possibilities. Lastly, despite recent advances in GPU programming languages, GPGPU practitioners are predominantly graphics specialists. This tutorial presents the background, tools, and implementation details required for researchers in other fields to leverage the computational power of GPUs.

Aaron Lefohn, University of California, Davis, USA
Ian Buck, NVIDIA Corporation, USA
Patrick McCormick, Los Alamos National Lab, USA
John Owens, University of California, Davis, USA
Timothy Purcell, NVIDIA Corporation, USA
Robert Strzodka, Caesar Institute, Bonn, Germany

Tutorial 2 (Half day, morning)
Visual Medicine Part 1 – Medical Imaging Techniques

Course notes now available. Click here.

Virtual endoscopy, surgery planning, surgery simulation, and diffusion tensor imaging are among the most actively researched topics in virtual and visual medicine and in medical imaging. They focus on the simulation of medical procedures for training, planning, diagnosis, and prognosis without requiring an invasive intervention. This two-part tutorial covers concepts that are used in research as well as in production systems, and this first part will give an introduction into medical imaging, covering both data acquisition and data visualization. The focus will be on the major elements of the medical imaging pipeline, such as data artifacts, the basics of volume datasets, segmentation and data analysis, registration, rendering, and navigation.

Dirk Bartz, University of Tübingen, Germany
Gordon Kindlmann, Brigham and Women's Hospital, USA
Klaus Mueller, Stony Brook University, USA

Tutorial 3 (Half day, afternoon)
Visual Medicine Part 2 – Advanced Applications of Medical Imaging

Course notes now available. Click here.

This tutorial will explore a variety of advanced topics of visual medicine, based on the foundations laid out in Tutorial 2. It will discuss virtual endoscopy, OR-fit mixed reality methods for surgery, diffusion tensor imaging, liver-surgery planning, CT reconstruction, functional imaging, and soft-tissue simulation. All of these are some of the most actively researched fields in visual medicine. Together, these topics form important components towards more realistic interaction with digital models of human bodies.

Dirk Bartz, University of Tübingen, Germany
Gordon Kindlmann, Brigham and Women's Hospital, USA
Klaus Mueller, Stony Brook University, USA
Bernhard Preim, University of Magdeburg, Germany
Markus Wacker, University of Applied Science, Dresden, Germany


Tutorial 4 (Full day)
Point Lattices in Computer Graphics and Visualization

Course notes now available. Click here.

This course is motivated by the deep connections and applications of point lattice theory in the mathematics of computer graphics and the role it plays in multidimensional signal processing and tilings. Next to an introduction to the theory and history of point lattices and the related sampling and group theories, this tutorial offers an in-depth survey from two different perspectives:

  • Signal processing – Functional analysis and sampling theory. All computational fields in science and engineering have to deal with discrete representations of continuous phenomena, and sampling theory is crucial to provide the essential link between the discrete and the continuous domain. The focus of this tutorial is on recent developments in the context of optimal lattices, as applied in image processing, medical imaging, and volume rendering, and in terms of reconstruction filter designs, wavelet techniques, medical reconstruction, discretization and rendering aspects for 2D, 3D, and 4D lattices.

  • Crystallography – Geometry and group theory. The study of the formation and structure of crystals has been the interest of scientists for many centuries. Consequently, the symmetries and translation invariant properties of point lattices have been studied and investigated thoroughly in the field of crystallography and solid-state physics. Many aspects here are also very useful to the computer graphics community, such as their incorporation into artistic expressions from ancient ornamental structures to famous works of Escher and general tiling patterns. Fundamental group theory related to point lattices will be presented, as well as geometric tools for the visualization of tilings and patterns in 2D, 3D, and 4D.

Torsten Möller, Simon Fraser University, Canada
Reza Entezari, Simon Fraser University, Canada
Jim Morey, The University of Western Ontario, Canada
Klaus Mueller, Stony Brook University, USA
Victor Ostromoukhov, University of Montreal, Canada
Dimitri Van De Ville, Swiss Federal Institute of Technology Lausanne, Switzerland

Tutorial 5 (Full day)
Illustrative Visualization

Course notes now available. Click here.

The tutorial presents state-of-the-art visualization techniques inspired by traditional technical and medical illustrations. Such techniques exploit the perception of the human visual system and provide effective visual abstractions to make the visualization clearly understandable. Visual emphasis and abstraction has been used for expressive presentation from prehistoric paintings to nowadays scientific and medical illustrations. Many of the expressive techniques used in art are adopted in computer graphics, and are denoted as illustrative or non-photorealistic rendering. The discussed techniques in the context of scientific visualization are based on iso-surfaces and volume rendering. The visibility of prominent features can be also be achieved by cut-away, ghosted, or exploded views, or other types of deformation. Discussed non-photorealistic and illustrative techniques from visualization and graphics are shown from the perspective as tools for illustrators from medicine, botany, archeology, and zoology. The limitations of existing NPR systems for science illustration are highlighted, and proposals for possible new directions are made. Illustrative visualization is demonstrated via application-specific tasks in medical visualization. An important aspect as compared to traditional medical illustrations is the interactivity and real-time manipulation of the acquired patient data. This can be very useful in anatomy education. Another application area is surgical planning which is demonstrated with two case studies: neck dissection and liver surgery planning.

Ivan Viola, Vienna University of Technology, Austria
Eduard Gröller, Vienna University of Technology, Austria
Markus Hadwiger, VRVis Research Center, Vienna, Austria
Bernhard Preim, University of Magdeburg, Germany
Mario Costa Sousa, University of Calgary, Canada
David Ebert, Purdue University, USA
Don Stredney, The Ohio State University, USA


Tutorial 6 (Full day)
Level Set and PDE Methods for Visualization

Course notes now available. Click here.

This tutorial presents the underlying concepts, equations and numerical methods for level set and partial differential equation methods. It describes their use in a variety of visualization applications, including image processing, geometric modeling, dataset segmentation, model processing, surface reconstruction, anisotropic geometric diffusion, flow field post-processing and vector visualization. Additionally, techniques and data structures for implementing these methods on GPUs will be described.

David Breen, Drexel University, USA
Mike Kirby, University of Utah, USA
Aaron Lefohn, University of California, Davis, USA
Ken Museth, Linkoeping University, Sweden
Tobias Preusser, CeVis - University of Bremen, Germany
Guillermo Sapiro, University of Minnesota, USA
Ross Whitaker, University of Utah, USA


Tutorial 7 (Half day, morning)
Visualization and Mining of Temporal Data

Temporal data are ubiquitous; large volumes of such data are routinely created in scientific, industrial, entertainment, medical and biological domains. Examples include gene expression data, electrocardiograms, electroencephalograms, gait analysis, stock market quotes, space telemetry, metrological data, etc. Short sequences of temporal data (hereafter used interchangeably with "time series") can be visualized directly, for example, a few heartbeats or a week of stock movements. However time series data collections are often large in one of two ways: They may be many objects, for example tens of thousands of gene expression profiles, or they may be very long, for example, many NASA datasets may have more than billion data points per time series.

Two potential ways to glean knowledge from such datasets are data mining, and visualization, however these two fields have had surprisingly little intersection for temporal data thus far. The central thesis of this tutorial is that data mining can benefit from visualization, and visualization can benefit from data mining.

Eamonn Keogh, University of California, Riverside, USA

Tutorial 8 (Half day, afternoon)
Color in Information Display

Course notes now available. Click here.

Color is a key component of information display that is easy to use badly. As a result, Edward Tufte's key principle for color design is "do no harm." While inspired color design is an art, the principles that underlie good color design have their roots in human perception and a deep understanding of the color properties of different media. This course is designed to introduce the technical community to the visual principles that inform good design, and the advances in color science, color technology, and color appearance modeling that can be applied to the problem of using color effectively in information display.

Maureen C. Stone, StoneSoup Consulting, USA

 © 2005 IEEE | Credits