Signal Processing - May 2017 - 99

Peak Systole
16

Axial Distance (mm)

18
20
22
24
26
28
30
1 m/s

32
-10

-5
0
Lateral Distance (mm)

figure 4. The velocity images of flow in the carotid bifurcation in the neck of a 52-year-old healthy individual. The arrows indicate direction and magnitude and the color indicates direction with intensity proportional
to velocity magnitude. The frame is taken at the peak systolic phase in the cardiac cycle.

tissue signal easier. This has especially
been demonstrated for plane wave flow
imaging [12].

Discussion and conclusions
Velocity imaging in ultrasound has,
since the 1980s, been used for easily
accessible diagnosis of the human circulation for both peripheral and deep
vessels as well as the heart. There has
been a steady increase in the accuracy
of the investigations. Two-dimensional
vector flow imaging has been commercially introduced recently. The development is spurred by advances in signal
processing combined with novel and
precise digital beamforming methods.
The field is very broad and spans more
than 50 years of development reported
in more than 1,000 articles. Space constraints in this article do not allow us to
include more references, but consulting
recent reviews can give a broader introduction to the literature.
Entirely new acquisition methods
are being developed by researchers for
clinical implementations. The fast SA
spherical and plane wave images can
easily reveal vortices and fast transitory
events in the human circulation without
preparation of the patient or injection
of contrast agents [9]. The quantitative
results also make it possible to derive

diagnostic measures from the data. Peak
velocities and velocity ratios before and
after a constriction or stenosis can be
used for grading the severity.
The continuous data make it possible
to have very long echo-canceling filters
to remove the signal from the tissue.
Essentially, any filter can be used, and the
effects of filter initialization are avoided.
In this case, many emissions can be combined to reduce noise, and the SA and
plane wave flow images are more sensitive to low velocity flow. This was used
to map out the vasculature of the rat brain
for, e.g., detecting the brain activity, when
stimulating a single whisker, mapping
out an epileptic seizure, and revealing the
influence of odors on the brain [12].
There are still many challenges in
ultrasound flow estimation, but the
integrated approach by combining signal processing, estimator development
with advanced acoustics, and new digital beamforming seems promising to
yield full 3-D volumetric vector flow
imaging in real time for both low and
high velocity flows at many hundred
volumes per second.

Authors
Jørgen Arendt Jensen (jaj@elektro.dtu
.dk) received his M.S. and Ph.D. degrees
in 1985 and 1989, respectively, from the
IEEE Signal Processing Magazine

May 2017

Technical University of Denmark and
the Dr.Techn. degree from the same
university in 1996. Since 1993, he has
been a full professor of biomedical signal
processing in the Department of Electrical Engineering at the Technical University of Denmark, and the head of the
Center for Fast Ultrasound Imaging
since its inauguration in 1998. He has
published more than 400 journal and
conference papers on signal processing
and medical ultrasound. His research
focus is on the simulation of ultrasound
imaging, synthetic aperture imaging, vector blood flow estimation, and construction of ultrasound research systems. He is
a Fellow of the IEEE.
Carlos A. Villagómez Hoyos (cavh
@elektro.dtu.dk) received his B.S. degree
in electronic engineering in 2008 and his
M.S. degree in digital signal processing in
January 2013, both from the National
Autonomous University of Mexico. He
spent six months at the Ultrasound
Laboratory at the Federal University of
Rio de Janiero in 2012. He obtained his
Ph.D. degree in biomedical engineering
from the Center for Fast Ultrasound
Imaging at the Technical University of
Denmark in 2016, where he is currently a
postdoctoral researcher.
Simon Holbek (sholbek@elektro
.dtu.dk) received his M.S. degree in physics in 2013 from the Niels Bohr Institute,
University of Copenhagen, Denmark,
and his Ph.D. degree from the Technical
University of Denmark in 2017. He is
currently a postdoctoral researcher with
the Center for Fast Ultrasound Imaging in the Department of Electrical
Engineering, Technical University of
Denmark. His current research topic
is within three-dimensional vector
flow imaging.
Kristoffer Lindskov Hansen (lindskov
@gmail.com) received his M.D. a n d
Ph.D. degrees from Copenhagen University, Denmark, in 2003 and 2010,
respectively, and became a medical
specialist in diagnostic radiology in
2014. He is currently with the De partment of Radiology, Copenhagen
University Hospital, Denmark, and is
an associate professor at Copenhagen
University. His research interest focuses on
advanced ultrasound techniques with
99

http://elektro.dtu.dk http://www.dtu.dk http://www.gmail.com

Table of Contents for the Digital Edition of Signal Processing - May 2017