Visualization in Biomedicine
Credits: 4
Semester: 3
Course: Elective
Objectives
Students will learn ways to generate and organize work with large data or forms and methods of scientific visualization; the main provisions of the theory of genetic search; the structure of evolutionary algorithms; evolutionary strategies, evolutionary and genetic programming; methods and technologies of eScience and eEngineering; ways to generate and organize work with large data; forms and methods of scientific visualization; to organize a distributed computing infrastructure to support object-oriented research and the life cycle of engineering products, to build complex 3D visualization applications using stereo effects; to design a visual interface for human-computer interaction; to design and develop parallel programs for computers of different architectures; technologies of knowledge extraction from large data. Students will acquire software development skills and use of ready-made software solutions for solving complex problems, knowledge of parallel programming technologies, skills of creating graphic images based on mathematical package visualization subsystems; skills of the graphic applications development using specialized high-level computer graphics environments; construction of 3D scenes.
Contents
Main topics of the discipline:
- Basics and visualization applications
- Mathematical Foundations of Computer Graphics
- The architecture of modern graphics processors (GPU) for graphics and computations
- Methods and algorithms for modeling global illumination
- Optimization of global lighting for 3D scenes
- Stereo-visualization algorithms
- Scientific visualization
- 3D rendering algorithms
Format
Laboratory works.
Assessment
Examination.