course: Tomographic imaging

teaching methods:
lecture with tutorials
computer based presentation, black board and chalk
responsible person:
Prof. Dr.-Ing. Georg Schmitz
Prof. Dr.-Ing. Georg Schmitz (ETIT)
offered in:
summer term

dates in summer term

  • start: Wednesday the 14.04.2021
  • lecture Wednesdays: from 08:15 to 09.45 o'clock
  • tutorial Wednesdays: from 10:15 to 11.45 o'clock


Die Angaben zu den Prüfungsmodalitäten (im WiSe 2020/2021 | SoSe 2021) erfolgen vorbehaltlich der aktuellen Situation. Notwendige Änderungen aufgrund universitärer Vorgaben werden zeitnah bekanntgegeben.

Date according to prior agreement with lecturer.

Form of exam:oral
Registration for exam:FlexNow


After successful completion of the module, students have knowledge of the most important tomographic diagnostic imaging procedures (X-ray computed tomography, magnetic resonance imaging). They know the basic technical components of the imaging systems under consideration and can explain how they work. They understand the basic physical effects (e.g. X-ray attenuation, nuclear magnetic resonance) and can discuss them. Students understand the theory of tomographic reconstruction (Fourier-Slice-Theorem, Fourier-Diffraction Theorem) and can derive and explain the structure and the achieved image quality of the different systems. They are able to implement known algorithms for image reconstruction and independently develop and evaluate new algorithms. Through the exercises in small groups, partly on computers, the students are able to apply what they have learned in a small team. They are able to explain their solutions and to present supporting arguments.


Using tomographic imaging techniques, image slices of tissue and bone structures can be reconstructed from projections, i.e. from measured, integral relationships of physical parameters. Computer tomography (CT) measures the penetration of X-rays through a volume to be imaged at different angles and reconstructs the X-ray attenuation coefficient. Magnetic resonance tomography (MR), on the other hand, uses nuclear magnetic resonance effects and images proton densities weighted by relaxation times. From the physical and mathematical basics to practically important reconstruction procedures, all steps from data acquisition to the image are taught.



recommended knowledge

Knowledge of system theory, Fourier transformation and signal processing, corresponding to those taught as basics in the lectures of the bachelor's program in Electrical Engineering and Information Technology.


  1. Morneburg, Heinz "Bildgebende Systeme für die medizinische Diagnostik", Publicis Corporate Publishing, 1995
  2. Buzug, Thorsten M. "Einführung in die Computertomographie. Mathematisch-physikalische Grundlagen der Bildrekonstruktion", Springer, 2007
  3. den Boer, Jacques A., Vlaardingerbroek, Marius T. "Magnetic Resonance Imaging. Theory and Practice", Springer, 2003
  4. Kak, Avinash C., Slaney, Malcolm "Principles of Computerized Tomographic Imaging", I.E.E.E.Press, 1989


Material for the course will be provided via Moodle. All information to access the course in Moodle will be given in the first lesson.