IEEE Ultrasonics
Symposium,
Short Course 6A: Estimation and Imaging of Blood Flow Velocity
Hans Torp and Lasse Løvstakken
Department of Circulation and
E-mail:
Hans.Torp(at)ntnu.no, Lasse.Lovstakken(at)ntnu.no
Course summary:
This course provides a basic understanding of the physical principles
and signal processing methods for estimation of blood flow velocity. The course
begins with an overview of currently used techniques for velocity estimation
using pulsed- and continuous-wave Doppler, and color flow imaging. Fundamental
challenges related to data acquisition will be presented. Further, statistical
models for the received signal as well as commonly used velocity estimators
will be developed. The suppression of clutter from slowly moving targets is
central to all processing schemes and will be given special attention. Finally,
and introduction to advanced topics such as adaptive clutter filtering and 2-D
/ 3-D vector velocity estimation techniques will be given. Principles and
practical limitations will be discussed, and potential clinical applications
will be shown.
Hans Torp received the MS degree
in mathematics in 1978, and the Dr. Techn. Degree in electrical engineering in
1992; both from the University of Trondheim, Norway. Since 1980 he has been
working with ultrasound technology applied to blood flow measurements and
imaging at the
Lasse Løvstakken received the
Masters degree in Engineering Cybernetics in 2002 and a PhD in Medical
Technology in 2007, both at the
Slides from the short course:
Doppler Short Course 2009 slides (pdf format) (Lectures 1-4)
Relevant litterature:
1.
H. Torp: Signal
processing in ultrasound Doppler and Color Flow Imaging. NTNU 2002 (pdf)
2.
L. Løvstakken:
Signal processing in diagnostic ultrasound – algorithms for real-time
estimation and visualization of blood flow velocity, chapter 2 – Background,
NTNU 2007 (pdf)
Matlab demonstrations
1.
Continuous wave signal from moving scatterer (cwdoppler.m)
2.
Pulsed wave signal from moving reflector (pwdoppler.m)
3.
Complex Gaussian process demonstration (Csignaldemo.m)
4. Doppler spectrum estimation (Dopplerspectrum.m)
5. Doppler signal examples (dopplersignal1.mat dopplersignal2.mat)
6.
Autocorrelation method applied to simulated signal (AcorrEst.m)
7.
Autocorrelation method, effect of averaging (AcorrAverage.m)
Download all Matlab demonstration files: matlabdemo.zip
Last
update: Sept 7, 2009