HI 5001 Special Topics: Scientific Visualization
The course provides a broad and practical introduction to Scientific Visualization. It will investigate what role visualization plays in science today, what challenges researchers face and how a visual interpretation can help to gain insight into scientific data.
Based on the different types and categories of data, a variety of visualization strategies will be introduced. It will be shown how these techniques can be implemented using methods from computer graphics. In practical sessions the students will develop source code that can form a basis for more complex visualization programs they might develop later for their main research. In addition we will also provide information about commercial and open-source visualization packages - examples are Gnuplot, AVS, VTK, SVT, ViPER, POVRay, OpenInventor, and OpenScenegraph.
The course will give an overview over current research topics in Scientific Visualization and will provide a brief overview of advanced display and interaction techniques like immersive visualization and haptic rendering.
The course will be useful for graduate students with a biological, clinical or computational background.
A solid background in geometry at college level is desirable. Knowledge of at least one programming language (ideally: C or C++) would be beneficial, but is not a requirement for the course.
By the end of the semester, the student will have had the opportunity to meet the following objectives:
- Can characterize the role of scientific visualization in contemporary biomedical research or medical applications.
- Demonstrates understanding of fundamental theories and methods in scientific visualization.
- Can select theories and methods appropriate to exploration, analysis, evaluation, and display of 2D and 3D data in a research or clinical environment.
- Demonstrates an understanding of the basic principles and theories in computer graphics to required for visualization solutions.
- Demonstrates a working knowledge of freely available software and algorithms to carry out independent research projects.