Course detail

Biomedical Data Visualization

FEKT-FVIZAcad. year: 2016/2017

The course is oriented to knowledge on computer graphics applied to biomedical data. The main focus is visualization of 3D image data acquired using magnetic resonance imaging, CT tomography, PET and SPECT. It is the use of OpenGL methods for basic graphic primitives and creating of 3D scenes. Furthermore, methods for visualization of higher-dimension data are included.

Language of instruction


Number of ECTS credits


Mode of study

Not applicable.

Learning outcomes of the course unit

Former student is able to:
- Describe color spaces in computer graphics
- Describe basic principles of image compression
- Describe principles of 3D scene creation
- Create basic graphic primitives in OpenGL
- Describe light model in 3D scenes
- Describe methods of 3D images creation from volume data (CT, MRI)
- Modify properties of OpenGL rendering


The subject knowledge of programing and algorithms on the Bachelor´s degree level is requested. Knowledge and the ability to use cycles for, while, structures if, switch-case, basic variables data types and basic image processing methods.


Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Up to 30 point in computer exercises (test and project)
Up to 70 points in final exam (written)
Final exam is focused on orientation in principles used in computer graphics, methods for rendering using OpenGL and options in scene properties.

Course curriculum

1. Classification of visualization techniques
2. Color spaces.
3. Representation of basic 2D objects.
4. Area borders, filling of geometric and raster defined area.
5. Curves – properties, generating, modeling.
6. Planes – properties, generating, modeling.
7. Surface and volume representation of 3D objects.
8. Shadows in computer graphics.
9. Textures and texturing.
10. Projecting methods
11. Reflection models
12. Technical resources for visualization.

Work placements

Not applicable.


Knowledge of representation of simple geometrical objects and their use for description of real objects in medical imaging. Knowledge of methods used in visualization of biomedical data.

Specification of controlled education, way of implementation and compensation for absences

Limitations of controlled teaching and its procedures are specified by a regulation issued by the lecturer responsible for the course and updated for every year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

ŽÁRA, J., BENEŠ, B., SOCHOR, J., FELKEL, P: Moderní počítačová grafika (2. vydání). Computer Press, 2005, ISBN 80-251-0454-0. (CS)
UDUPA, J. K., HERMAN, G. T.: 3D imaging in medicine (2nd edition). CRC Press, 1991, ISBN:0-8493-4294-5 (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme BTBIO-F Master's

    branch F-BTB , 2. year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch ET-CZV , 1. year of study, winter semester, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer


1. Introduction to visualization of biomedical data. Classification of visualization methods. Examples of use in medical applications.
2. Representation of elementary 2D objects: piecewise linear, circular and elliptical objects, interpolation and approximation of curves, region objects.
3. 3D object surface representation I: polygon representation, parametric surface representation (Bezier surfaces, B-spline surfaces).
4. 3D object surface representation II: set of outlines in parallel planes, implicit surfaces.
5. Representation of 3D objects: border representation, sweeping, octrees, constructive solid geometry.
6. Transformation of 3D image data to surface representation: methods of marching cubes, marching tetrahedra, dividing cubes.
7. Basics of visualization of 3D data: parallel and perspective projection, viewing transformations, theory of light.
8. Illumination models for surface rendering: diffuse scattering and reflection components of light, physical and empirical models.
9. Illumination models for volume rendering: methods of ray casting, formulation of light absorption, scattering and reflection on various levels of complexity.
10. Models of light sources and shading: point, surface, parallel, reflector, skye light sources; constant, Gouraud and Phong shading.
11. Virtual reality: stereoscopic view generation, DESCRIPTION of VRML language for modeling of virtual reality.
12. Methods for visualization of higher-dimension data for classification based on feature description.
13. Hardware means for visualization: hardware means for acceleration of graphical computing, technology of displays and 3D visualization systems.

Exercise in computer lab

39 hours, compulsory

Teacher / Lecturer


1. Introduction to laboratory lessons. Formats of image data.
2. Representation of elementary 2D objects - implementation of interpolation and approximation curves (Matlab).
3. Polygon representation of surface of a simple 3D object (Matlab).
4. Parametric representation of surface of a simple 3D object (Matlab).
5. Transformation of 3D image data to surface representation using marching cubes method, application to real data (Matlab, VTK).
6. Practical test 1.
7. Implementation of a simple illumination model for surface rendering (Matlab).
8. Comparison of illumination models for surface rendering (VTK Designer)
9. Implementation of a simple illumination model for volume rendering (Matlab).
10. Comparison of illumination models for volume rendering (VTK Designer)
11. Experimental acquisition of stereoscopic scenes, visualization using anaglyphs and active 3D glasses.
12. Calibration and quality measurement of LCD displays used in radiology.
13. Practical test 2.