course: Ultrasound imaging

number:
141225
teaching methods:
lecture with tutorials
media:
overhead transparencies, computer based presentation, black board and chalk
responsible person:
Prof. Dr.-Ing. Georg Schmitz
Lecturers:
Prof. Dr.-Ing. Georg Schmitz (ETIT), Dr.-Ing. Stefanie Dencks (ETIT)
language:
german
HWS:
4
CP:
5
offered in:
winter term

dates in winter term

  • start: Thursday the 17.10.2019
  • lecture Thursdays: from 08:15 to 09.45 o'clock in ID 03/445
  • tutorial Fridays: from 08:15 to 09.45 o'clock in ID 03/445

Exam

Date according to prior agreement with lecturer.

Form of exam:oral
Registration for exam:FlexNow
Duration:30min

goals

The students acquire knowledge in the area of ultrasonic imaging. They know the basic linearized equations for acoustic wave propagation and the basic formulas for the calculation of fields. They are able to calculate acoustic fields in simple geometric situations. The students can treat one-dimensional transducer setups mathematically and use equivalent circuits. The students understand the array beamforming and reconstruction methods and the main determinants and characteristics of image quality.

content

Ultrasound techniques for diagnostic imaging and therapy an important field in medical engineering. In this course the physics of ultrasound fields is treated first. Based on this, technical systems like ultrasonic transducers and beamformers as well as the reconstruction techniques and the relevant applications in diagnosis and therapy are presented. Several topics treated can be applied in industrial ultrasound as well, e.g. in non-destructive testing.

Main topics of the course are:

  • Acoustic wave propagation in fluids and solids
  • Acoustical properties of tissues
  • The piezoelectric effect
  • Ultrasound transducers and their equivalent circuits
  • Ultrasonic imaging (array beamforming, reconstruction)
  • Doppler-flow
  • Ultrasound contrast media
  • Special topics (elastography, photoacoustic, harmonic imaging, HIFU-therapy, superresolution-imaging)

requirements

keine

recommended knowledge

Knowledge of linear systems theory, Fourier-transformation, and signal processing that are comparable to the ones acquired by the Bachelor degree in electrical engineering and information sciences