Visualization of Medical Data

Credits: 2

Semester: 2

Course: Core

Language of the course: Russian


Andrey Karsakov


Students will learn ways to generate and organize work with big 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 big 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 big 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.


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


lectures and practical classes