Signal Processing - May 2017 - 98
Emission
(n -3)
Emission
(n -2)
Emission
(n -1)
Emission
(n )
(a)
2 ∆z
Low-Resolution Images
(b)
L(n−2)
L(n−1)
L(n)
2 ∆z
2 ∆z
L(n−3)
(c)
H(n−3)
H(n−2)
H(n−1)
High-Resolution Images
H(n)
figure 3. An STA imaging sequence with two emissions that are repeated: (a) the probe and from
where the spherical emission emanates, (b) the PSF for each emission is indicated, and (c) the
combination from several emissions is shown. (Figure used courtesy of [8].)
thus, available, and the data for velocity estimation can be averaged over as
many emissions as the blood velocity is
roughly stationary [11].
There is, however, one complication
to this imaging scheme, as the scatterers
move between emissions. This is illustrated in Figure 3. Figure 3(a) shows
the probe and from where the spherical
emission emanates. The sequence only
consists of two emissions from the first
and last elements of the probe. In (b), the
elliptically shaped point spread function
(PSF) beamformed from one emission
is shown, and (c) shows the summation of several emissions. For each
emission a low-resolution image (not
focused in transmit) can be generated
for the whole region. This is combined
with the other emissions in (c) to yield a
high-resolution image (HRI), but these
are not fully in phase due to the motion.
The PSF for different HRIs H (n) are
slightly different. The HRI PSFs are,
however, the same, if the emissions
sequence is the same, so the pair H (n -3)
and H (n -1), and the pair H (n -2) and
H (n) have the same PSF, apart from a
translation due to the motion. There is,
98
thus, full correlation between the pairs
H (n -3) and H (n -1) and H (n -2) and H (n) .
This might seem like a small detail, but
it has a widespread impact on velocity imaging. The correlation of HRI
data for time-shift estimation using (5)
will yield the same correlation functions
as long as the blood velocity is constant,
and these correlation functions can
be averaged to improve the velocity estimate. The continuous data, therefore,
makes it possible to correlate the data
over the time period the blood velocity can be considered constant, so it is
the acceleration that limits observation
time. The imaging can be conducted
using either spherical [11] or plane
waves [12].
The continuous data also decouples
the number of imaging directions and
accuracy, as any arbitrary number of
directions can be beamformed from the
acquired data. The standard deviation
on the velocity estimates can be kept
low by the averaging of a long period of
time. The received data can be beamformed everywhere, and frame rates of
hundreds to thousands of images per
second with fully quantitative flow can
IEEE Signal Processing Magazine
|
May 2017
|
be attained. The availability of data
everywhere also makes it possible to
introduce new advanced focusing methods. The TO method can be employed,
and it is also possible to focus along the
flow direction. This makes it possible
to track the blood scatterers along their
motion path and avoid decorrelation
from motion in or out of the ultrasound
beam to further increase the velocity accuracy. Another important aspect
from continuously available data is the
ability to use any echo canceling filter
without being affected by initialization
effects. This makes the suppression of
the strong tissue signal much more efficient. These factors reduce the standard
deviation (SD) by roughly a factor of ten
to yield very accurate estimates with a
relative SD lower than 1%.
An example of STA flow imaging
is seen in Figure 4 and is taken at the
carotid bifurcation in the neck. The
sequence generates 2,500 images/s
with fully quantitative magnitudes and
directions. Experiments in a flow rig
indicated an angle determination precision lower than 1.4c, and the relative
SD for the magnitude was between
1.9 and 4.7% for this imaging method.
The image is taken at the peak systole
(maximum contraction of the heart).
Flow with a magnitude around 1 m/s
is seen in both vessel branches and the
lower branch corresponding to the internal carotid artery also contains a vortex.
It is formed upstream in the beginning
of the heart contraction near the bifurcation and moves downstream along
the outer vessel wall during the systolic
phase. Such a vortex is found in nearly all
healthy people, and it appears for roughly
100 ms, whereafter the flow again usually becomes laminar in both branches.
During the diastolic phase, when the
heart relaxes, the velocity decreases
to below 0.2-0.1 m/s depending on the
spatial position. The synthetic aperture
(SA) flow imaging method can capture
the high as well as low velocities due to
both the fast image acquisition rate and
the continuous available data. Fast flow
can be tracked over a short period of time
and low velocity flow, which is difficult
to detect, can be observed over a longer
period of time making removal of the
Table of Contents for the Digital Edition of Signal Processing - May 2017
Signal Processing - May 2017 - Cover1
Signal Processing - May 2017 - Cover2
Signal Processing - May 2017 - 1
Signal Processing - May 2017 - 2
Signal Processing - May 2017 - 3
Signal Processing - May 2017 - 4
Signal Processing - May 2017 - 5
Signal Processing - May 2017 - 6
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Signal Processing - May 2017 - 101
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Signal Processing - May 2017 - 106
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Signal Processing - May 2017 - 111
Signal Processing - May 2017 - 112
Signal Processing - May 2017 - Cover3
Signal Processing - May 2017 - Cover4
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