Course content

The course will give a thorough introduction to medical ultrasound technology with a signal processing approach.

Learning outcome

Knowledge:

• Know basic signal processing, FIR-filter design and application
• Know the physics of ultrasound propagation and scattering relevant for signal processing
• Understand the use of grayscale / color graphic representation of dynamic image information
• Know the mathematical model for pulse-echo imaging systems based on signals in space and time
• Know the effects of limited bandwidth and sampling on spatial and temporal resolution
• Know the ultrasound signal processing chain from transmitted signal to displayed image
• Know techniques for image formation
• Describe dynamic images using multi-dimensional Fourier analysis
• Estimate power spectrum and autocorrelation from ultrasonic Doppler signals

Skills:

• Ultrasound acquisition design and parameter optimization
• Produce ultrasound images from raw channel data
• Estimate blood flow velocities using ultrasound recordings
• Perform numerical simulations, visualization, and presentation of results in Matlab

General knowledge:

• Programming and practical signal processing
• Be able to evaluate tradeoffs and justify design choices
• Use technical and precise language.

Learning methods and activities

Lectures, laboratory demonstrations, computer exercises, paper exercises. The students will follow the lectures in the master course MEDT4165, with lectures every week throughout the whole semester.

Recommended previous knowledge

Basic knowledge of mathematics, physics, programming and signal processing.

Required previous knowledge

Admission requirements: Master's Degree of Science or technology or equivalent education. Candidates with a lower degree will be assessed individually.

Course materials

Textbooks: Thomas L. Szabo: "Diagnostic Ultrasound Imaging: Inside Out" - Bjørn Angelsen: "Ultrasound Imaging, Waves, Signals, and Signal Processing". Additional scientific papers and lecture notes will be provided.