Visualisation and beam technologies in medicine

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, build effective methods for extracting knowledge from large data, implement calculations based on Nvidia CUDA, build complex 3D visualization applications using stereo effects; design a visual interface for human-computer interaction; to design and develop parallel programs for computers of different architectures. Students will acquire knowledge of technologies of knowledge extraction from large data, software development skills, skills of creating graphic images based on mathematical package visualization subsystems. Students will study ready-made software solutions for solving complex problems, parallel programming technologies, the development of graphic applications using specialized high-level computer graphics environments; construction of 3D scenes.

Contents

Main topics of the discipline:

  • Information in radiodiagnosis
  • Information technologies in radiodiagnosis
  • Information systems in radiodiagnosis
  • Visualization in radiodiagnosis

Format

Laboratory works.

Assessment

Examination.