U.S. patent application number 09/898783 was filed with the patent office on 2002-02-14 for ultrasound diagnostic apparatus and method for measuring blood flow velocity using doppler effect.
This patent application is currently assigned to Medison Co., Ltd.. Invention is credited to Bang, Ji Hoon, Kim, Cheol An.
Application Number | 20020019590 09/898783 |
Document ID | / |
Family ID | 19676959 |
Filed Date | 2002-02-14 |
United States Patent
Application |
20020019590 |
Kind Code |
A1 |
Bang, Ji Hoon ; et
al. |
February 14, 2002 |
Ultrasound diagnostic apparatus and method for measuring blood flow
velocity using doppler effect
Abstract
An ultrasound diagnostic system and a method for the same update
a pulse repetition frequency (PRF) by sensing an aliasing of a
sampled data. A sample data generator generates sample data by
transmitting an ultrasound signal into a human body and sampling a
reflected signal of the ultrasound signal. A frequency distribution
data generator generates a frequency distribution data by
processing the sample data. A blood flow velocity detector
determines a blood flow velocity on the basis of the frequency
distribution data. An aliasing detector detects whether or not an
aliasing occurs in the frequency distribution data. The aliasing
detector computes a peak index corresponding to the fastest blood
flow velocity component among the frequency components comprising
the frequency distribution data, selects a frequency range having
the largest sum of power levels of the frequency components between
a positive frequency range and a negative frequency range, compares
the selected frequency range with the peak index, and determines
whether an aliasing occurs or not.
Inventors: |
Bang, Ji Hoon; (Gyeonggi-do,
KR) ; Kim, Cheol An; (Seoul, KR) |
Correspondence
Address: |
WIGGIN & DANA LLP
ATTENTION: PATENT DOCKETING
ONE CENTURY TOWER, P.O. BOX 1832
NEW HAVEN
CT
06508-1832
US
|
Assignee: |
Medison Co., Ltd.
|
Family ID: |
19676959 |
Appl. No.: |
09/898783 |
Filed: |
July 3, 2001 |
Current U.S.
Class: |
600/454 |
Current CPC
Class: |
G01S 15/8979 20130101;
A61B 8/06 20130101 |
Class at
Publication: |
600/454 |
International
Class: |
A61B 008/02 |
Foreign Application Data
Date |
Code |
Application Number |
Jul 8, 2000 |
KR |
2000-39086 |
Claims
What is claimed is:
1. An ultrasound diagnostic apparatus, comprising: means for
generating sample data by transmitting an ultrasound signal into a
human body and sampling a reflected signal of the ultrasound
signal; means for generating frequency distribution data by
processing the sample data, wherein the frequency distribution data
includes a number of frequency components, each of the frequency
components having a corresponding power level; means for
determining a blood flow velocity on the basis of the frequency
distribution data; and means for detecting whether or not an
aliasing occurs in the frequency distribution data, wherein the
aliasing detecting means computes a peak index corresponding to the
fastest blood flow velocity component among frequency components
comprising the frequency distribution data, selects a frequency
range having the largest sum of power levels of the frequency
components between a positive frequency range and a negative
frequency range of the frequency distribution data, compares the
selected frequency range with the peak index, and determines
whether an aliasing occurs or not.
2. The ultrasound diagnostic apparatus of claim 1, further
comprising: means for updating a pulse repetition frequency (PRF)
of the sample data in case of sensing the aliasing.
3. The ultrasound diagnostic apparatus of claim 2, wherein the
updating means updates the pulse repetition frequency (PRF)
according to the following equation: 3 PRF new = PRF old ( 2 -
peak_index N old ) where, PRF.sub.new is an updated PRF for
preventing the aliasing, PRF.sub.old is an old PRF before updating,
peak_index is the peak frequency index corresponding to the fastest
blood flow velocity component, and N.sub.old is the largest
frequency index of a frequency distribution data generated from the
PRF.sub.old.
4. The ultrasound diagnostic apparatus of claim 1, wherein the
blood flow velocity detecting means determines that a reliability
of a detected blood flow velocity is very low in case that the
aliasing detecting means detects the aliasing.
5. An ultrasound diagnostic method for measuring a blood flow
velocity, comprising the steps of: (a) generating sample data by
transmitting an ultrasound signal into a human body and sampling a
reflected signal of the ultrasound signal; (b) generating frequency
distribution data by processing the sample data, wherein the
frequency distribution data includes a number of frequency
components, each of the frequency components having a corresponding
power level; (c) determining a blood flow velocity on the basis of
the frequency distribution data; and (d) determining whether or not
an aliasing occurs in the frequency distribution data, wherein the
step for determining the aliasing computes a peak index
corresponding to the fastest blood flow velocity component among
the frequency components comprising the frequency distribution
data, selects a frequency range having the largest sum of power
levels of the frequency components between a positive frequency
range and a negative frequency range, compares the selected
frequency range with the peak index, and determines whether an
aliasing occurs or not.
6. The ultrasound diagnostic method of claim 5, further comprising
the step (e) for updating a pulse repetition frequency (PRF) of the
sample data in case of sensing the aliasing.
7. The ultrasound diagnostic method of claim 6, wherein the step
(e) updates the pulse repetition frequency (PRF) according to a
following equation: 4 PRF new = PRF old ( 2 - peak_index N old )
where, PRF.sub.new is an updated PRF for preventing the aliasing,
PRF.sub.old is an old PRF before updating, peak_index is the peak
frequency index corresponding to the fastest blood flow velocity
component, and N.sub.old is the largest frequency index of a
frequency distribution data generated from the PRF.sub.old.
8. The ultrasound diagnostic method of claim 5, wherein the step
(c) for detecting the blood flow velocity determines that a
reliability of a detected blood flow velocity is very low in case
that the step (d) detects the aliasing.
Description
FIELD OF THE INVENTION
[0001] The present invention relates to an ultrasound diagnostic
apparatus and method for measuring a blood flow velocity using
Doppler effect. More particularly, the invention relates to an
ultrasound diagnostic apparatus and method that update a pulse
repetition frequency (PRF) so as to prevent an aliasing in
measuring a blood flow velocity using Doppler effect.
BACKGROUND OF THE INVENTION
[0002] An ultrasound diagnostic apparatus using the Doppler effect
is widely used in measuring the velocity of blood flow in the human
body. In such a system, an ultrasound transducer array transmits an
ultrasound signal toward a moving object, e.g., red blood cells,
and receives a reflected signal from the object. The apparatus
computes the frequency shift or phase shift of the reflected signal
with respect to the transmitted signal in order to determine the
velocity of the moving object.
[0003] FIG. 1 is a block diagram of a conventional ultrasound
diagnostic apparatus 10 for measuring the velocity of blood flow in
a human body. The apparatus 10 comprises a transducer array 103, a
pre-amplifier 104, a time-variable gain compensator (TGC) amplifier
105, an analog-to-digital (A/D) converter 106, a quadrature
demodulator 107, a digital signal processor 108, a display device
109, and a peak blood flow velocity detector 110.
[0004] Specifically, the transducer array 103 first transmits an
ultrasound signal to an object (not shown), e.g., red blood cells
in a human body, and receives a reflected signal from the object
possibly with noise. The received signal is then applied to the
pre-amplifier 104 for pre-amplification. The output of the
pre-amplifier 104 is amplified at the TGC amplifier 105 with a
time-varying gain in order to compensate attenuation due to
propagation distance of the ultrasound signal in the human body.
The output of the TGC amplifier 105 is converted to a digital
signal at the analog-to-digital (A/D) converter 106. The digital
signal is demodulated at a quadrature demodulator 107. The
demodulated signal is applied to the digital signal processor 108
where the velocity of the object is computed. The velocity is
displayed at the display device 109 for human users.
[0005] In the digital signal processor 108, the demodulated signal
undergoes clutter filtering, fast Fourier transforming (FFT) and
post-processing to obtain the velocity distribution spectrum. That
is, the clutter that is reflected from slowly moving organ and
muscle compared to the blood is removed from the demodulated signal
by a high-pass filter (not shown). Then, in the digital signal
processor 108, frequency distribution data of 2N frequency
components is generated from the filtered signal by using a well
known FFT technique. Finally, as post-processing, a known signal
processing such as the log compression and base line shifting is
performed on the frequency distribution data corresponding to the
velocity distribution spectrum.
[0006] In order to measure a blood flow velocity of the human body
by using the Doppler effect, it is desirable to measure the mean
velocity and the peak velocity of the blood flow because blood flow
is actually a collection of many blood cells that do not move
uniformly in one direction. In other words, at one instant of time,
blood cells exhibit different velocities and moving directions. As
a result, when an ultrasound signal of a given frequency is
transmitted to these cells, its reflected ultrasound signal from
the cells would be composed of many different frequencies around
the given frequency because these different velocities would bring
about different Doppler frequency shifts. Further, the reflected
ultrasound signal inevitably includes noise in addition to an
ideally reflected signal from the object. The noise, of course,
should be isolated from the reflected signal components to
accurately determine the mean and peak velocities of the blood
flow. Typically, to isolate the noise from the reflected signal, a
noise threshold is established so that frequency components of the
reflected signal whose power levels are below the noise threshold
could be discarded as noise.
[0007] FIG. 2 is a frequency distribution of the reflected
ultrasound signal from a target blood flow. Note that the center
frequency has been shifted to zero in order to graphically
illustrate the directions of blood cells. Frequency components in
the negative domain represent frequency shifts of the ultrasound
signal that reflected off blood cells that move away from the
transducer shown in FIG. 1. Conversely, those in the positive
domain represent frequency shifts of the ultrasound that reflected
off those blood cells that move toward the transducer. It is well
known in the art that, if a frequency shift is detected, then the
velocity of a moving object that caused the shift can be computed
as they are proportional to each other. In the graph of FIG. 2, a
velocity corresponding to f.sub.p is considered as the peak
velocity because it is farthest from the center frequency (thus
being greatest frequency shift) and its power is above the noise
threshold 203. The peak velocity is detected at the peak blood flow
velocity detector 110 shown in FIG. 1. And, the mean velocity is
obtained by computing the mean of all the velocities corresponding
to the frequency components whose power levels are above the noise
threshold.
[0008] As described above, it is important to accurately determine
the noise threshold, i.e., the power level that discriminates
between the noise and the purely reflected signal, in the
computation of the mean and peak velocities of the blood flow. One
of known methods for determining a noise threshold is to use the
mean power of frequency components in a selected frequency range
far higher than the transmitted frequency, i.e., in a frequency
range where no reflected frequency components are expected. For
example, the mean of power levels of highest frequencies from the
frequency distribution of a received signal was used as the noise
threshold. The hypothesis behind this conventional method is that
random noise tends to have a flat power spectrum so that the power
levels of frequencies where desired signals are not present would
be that of the noise.
[0009] However, the conventional method failed take into
consideration whether those frequency components used to determine
the noise threshold are in the positive frequency domain or
negative frequency domain. Furthermore, it was based on the
hypothesis that no purely-reflected signal would exist in the far
end ranges of the frequency distribution. However, such an
assumption is useful only if a PRF (pulse repetition frequency) is
sufficiently higher than the blood flow velocity. If not, aliasing
occurs. That is, some of the highest negative frequency components
appear in the positive frequency domain and vice versa. The
aliasing will result in the setting of a noise threshold that is
actually not just the power of noise but includes some signal
components.
SUMMARY OF THE INVENTION
[0010] It is, therefore, an objective of the present invention to
provide an ultrasound diagnostic apparatus and method that
determine whether or not an aliasing occurs in sample data in
measuring a blood flow velocity of human body.
[0011] It is another objective of the present invention to provide
an ultrasound diagnostic apparatus and method for updating a pulse
repetition frequency (PRF) so as to prevent an aliasing of sample
data in measuring blood flow velocity of human body.
[0012] In order to achieve these objectives, an ultrasound
diagnostic apparatus for measuring a blood flow velocity using the
Doppler effect includes: means for generating sample data by
transmitting an ultrasound signal into a human body and sampling a
reflected signal of the ultrasound signal; means for generating
frequency distribution data by processing the sample data, wherein
the frequency distribution data includes a number of frequency
components, each of the frequency components having a corresponding
power level; means for detecting a blood flow velocity on the basis
of the frequency distribution data; and means for detecting whether
or not an aliasing occurs in the frequency distribution data,
wherein the means for detecting the aliasing computes a peak index
corresponding to the fastest blood flow velocity component among
the frequency components comprising the frequency distribution
data, selects a frequency range having the largest sum of power
levels of the frequency components between a positive frequency
range and a negative frequency range, compares the selected
frequency range with the peak index, and determines whether an
aliasing occurs or not.
[0013] The ultrasound diagnostic apparatus further includes means
for updating a pulse repetition frequency (PRF) generating the
sample data when the means for detecting the aliasing detects the
aliasing of sample data, in order to prevent the aliasing.
[0014] An ultrasound diagnostic method for measuring a blood flow
velocity includes the steps of: (a) generating sample data by
transmitting an ultrasound signal into a human body and sampling a
reflected signal of the ultrasound signal; (b) generating frequency
distribution data by processing the sample data, wherein the
frequency distribution data includes a number of frequency
components, each of the frequency components having a corresponding
power level; (c) detecting a blood flow velocity on the basis of
the frequency distribution data; and (d) determining whether or not
an aliasing occurs in the frequency distribution data, wherein the
step for determining the aliasing computes a peak index
corresponding to the fastest blood flow velocity component among
the frequency components comprising the frequency distribution
data, selects a frequency range having the largest sum of power
levels of the frequency components between a positive frequency
range and a negative frequency range, compares the selected
frequency range with the peak index, and determines whether an
aliasing occurs or not.
[0015] The ultrasound diagnostic method further includes the step
(e) for updating a pulse repetition frequency (PRF) of the sample
data if the aliasing occurs.
BRIEF DESCRIPTIONS OF THE DRAWINGS
[0016] The above and other objects and features of the present
invention will become apparent from the following description of
preferred embodiments given in conjunction with the accompanying
drawings, in which:
[0017] FIG. 1 is a block diagram of a conventional ultrasound
diagnostic apparatus for measuring blood flow velocities;
[0018] FIG. 2 illustrates the frequency distribution of a reflected
ultrasound signal;
[0019] FIG. 3 is a block diagram of an ultrasound diagnostic
apparatus for measuring blood flow velocities according to the
present invention;
[0020] FIG. 4 is a graph displaying the frequency distribution data
at a few instants of time;
[0021] FIG. 5 is a graph displaying the frequency distribution in
case of aliasing occurrence;
[0022] FIG. 6 shows a flow chart for explaining a method of
computing the peak index of a scan line in accordance with the
present invention; and
[0023] FIG. 7 shows a flow chart for explaining a method of
updating the PRF of a scan line in accordance with the present
invention.
DETAILED DESCRIPTION OF THE PRESENT INVENTION
[0024] An embodiment of the present invention will now be described
in detail in reference to the accompanying drawings.
[0025] The present invention shown in FIG. 3 is similar to the
conventional ultrasound diagnostic system described in the
Background of the Invention in that a reflected ultrasound signal,
originally transmitted to blood in the human body by a transducer
array, is amplified and demodulated. The apparatus 30 comprises a
transducer array 303, a pre-amplifier 304, a time-variable gain
compensator (TGC) amplifier 305, an analog-to-digital (A/D)
converter 306, a quadrature demodulator 307, a digital signal
processor 308, a display device 309, and a peak blood flow velocity
detector 310.
[0026] The received signals undergoes clutter filtering, fast
Fourier transforming (FFT) and post-processing to obtain the
frequency distribution spectrum. Specifically, the clutter
reflected from slowly moving organ and muscle compared to the blood
is removed from the demodulated signal by a high-pass filter before
the frequency distribution data of 2N frequency components are
generated from the filtered signal by using a well known FFT
technique.
[0027] FIG. 4 is a graph displaying the frequency distribution of a
reflected ultrasound signal at each instant of time on a display
device 309 of an ultrasound diagnostic system 30 shown in FIG. 3.
In FIG. 4, each of scan lines is a graphical representation of 2N
frequency distribution data of the reflected ultrasound signal at
an instant of time. For example, an M-th scan line represents a set
of 2N frequency components obtained at a particular time t.sub.M.
The power level of a frequency f.sub.i on the M-th scan line is
here denoted by x(i, t.sub.M) and usually indicated on the display
screen in gray scale. The higher the power level is the brighter
the point is. By definition, x(i, t.sub.M) also represents a
velocity of the blood flow at time t.sub.M.
[0028] As briefly mentioned in the Background of the Invention
above, if a PRF (pulse repetition frequency) is not sufficiently
higher than the blood flow velocity, aliasing occurs. The aliasing
causes a mirror image of high negative frequencies to appear in the
high frequency domain, which is a phenomenon well known in a
digital signal processing technology. In this situation, an
accurate estimation of a noise level is not possible because
reflected signal components would be influence the noise threshold.
As a result, a method for detecting whether or not an aliasing
occurs in a sample data about one scan line and a method for
updating the PRF in order to prevent the aliasing should be needed
to the prior art. For this purpose, as shown in FIG. 3, the
ultrasound diagnostic apparatus 30 further comprises a PRF update
unit 311 that automatically updates the PRF to avert the occurrence
of aliasing.
[0029] The PRF is automatically updated by the PRF update unit 311
such that the aliasing does not occur. This aspect of the present
invention will be described referring to FIG. 5 showing a graph
displaying the frequency distribution in case of occurrence of
aliasing, where the X and Y axes represent time and frequency,
respectively. For the sake of convenience, the frequency here is
identified by the index in the frequency distribution, i.e., one of
2N numbers.
[0030] Shaded areas in FIG. 5 correspond to their frequency
components whose power levels are above the noise threshold.
Bearing in mind that the peak index in a given scan line
corresponds to the fastest components of blood flowing in a same
direction, the sign of the peak index would be inconsistent with
the direction of the blood flow when aliasing occurs because the
highest frequency portion folds over to the other frequency domain.
Thus, by comparing the direction of blood flow with the sign of the
peak index, one can tell whether aliasing has occurred. In other
words, the sign of a frequency domain which was determined to
include reflected signal components (the sign indicating the
direction of blood flow) is compared with the sign of the peak
index to determine the occurrence of aliasing. When aliasing is
detected to have occurred, the PRF is updated depending on the
magnitude of the peak index in such a way that the alias does not
occur.
[0031] To elaborate on this inventive feature, FIG. 5 is further
explained. The peak index for an j-th scan line is 80. For the j-th
scan line, it is seen that the alias did not occur the peak
frequency as well as the rest of frequency components above the
threshold are all positive. Now let's examine the i-th scan line.
Despite that the sum of the power levels of the positive frequency
components is greater than that of the negative components, the
peak index is negative, indicating that aliasing occurred. In other
words, the frequency components shown in the negative domain are
not because of blood cells flowing away from the transducer but
because of folding over the positive higher frequency components.
In this case, the detected blood flow velocities are considered to
have reliabilities. The largest absolute frequency index, i.e., the
half of the frequency distribution 2N, is shown to be 128 in FIG. 5
When the blood flow is slow, aliasing does not occur, for example,
at the j-th instant. It follows that the PRF for the j-th scan line
does not need to be adjusted. But at the i-th scan line, the PRF
should be increased to increase the largest index. In other words,
the new largest frequency index N.sub.new to avoid the alias is
determined as follows:
N.sub.new=N.sub.old+(N.sub.old-.vertline.peak.sub.--index.vertline.)=2N.su-
b.old-.vertline.peak.sub.--index.vertline. Eq. (1)
[0032] where N.sub.old is a current largest frequency index. For
example, in FIG. 5, because N.sub.old is 128 corresponding to the
half of the frequency distribution 2N, and the peak index of the
i-th scan line is -80, N.sub.new is computed to be 176 according to
the above equation. That is, the largest frequency index should be
increased to 176 in order to avoid aliasing. Because the largest
frequency index is proportional to the PRF, the PRF for avoiding
the alias gets increased as determined by the following equation: 1
PRF new = PRF old N new N old Eq . ( 2 )
[0033] Where, PRF.sub.new is an updated PRF for preventing the
aliasing, and PRF.sub.old is an old PRF before updating.
[0034] If the Eq. (1) is applied to the Eq. (2), the current PRF
value PRF.sub.old can be updated to a new PRF PRF.sub.new for
avoiding aliasing according to the following equation (3): 2 PRF
new = PRF old ( 2 - peak_index N old ) Eq . ( 3 )
[0035] Where, .vertline.peak_index.vertline. is the absolute value
of a peak frequency index, and N.sub.old is the largest frequency
index of a frequency distribution data generated from the
PRF.sub.old.
[0036] FIG. 6 shows a flow chart for explaining a method of
computing the peak index of a scan line in accordance with the
present invention. Here, i represents the frequency index and x[i]
represents the power level of the i-th frequency component. The
largest positive frequency index of the scan line is N-1 and the
largest negative frequency index of the scan line is -N.
[0037] First, i is initialized to 0 (S701). Next whether a
reflected signal exists within the positive frequency range or
negative range is determined (S702). If in the positive frequency
range (S702), it is inspected whether x[i] is above the noise
threshold (S703) and, if so, the peak index is updated to i (S704).
Otherwise it is determined whether i is equal to -1 (S705) and, if
so, it signals that the peak index has been found. If i is not
equal to -1 (S705), then it is further checked whether i=N-1 or not
(S706). If i=N-1 (S706), i is set to -N (S707). If not, i is
increased by one (S708). The power level of the new index value is
computed in the same way.
[0038] If the reflected signal existed in the negative frequency
range, the same peak index is determined in the same manner except
that the index i is decreased from zero to -N and then from N-1 to
1. That is, if the reflected signal existed in the negative
frequency range (S702), it is inspected whether x[i] is above the
noise threshold (S710) and, if so, the peak index is updated to i
(S711). Otherwise it is determined whether i is equal to 1 (S712)
and, if so, it signals that the peak index has been found. If i is
not equal to 1 (S712), then it is further checked whether i=-N or
not (S713). If i=-N (S713), i is set to N-1 (S714). If not, i is
decreased by one (S715).
[0039] To further understand the above concept of FIG. 6, let's
apply the concept of FIG. 6 to FIG. 5.
[0040] For the j-th scan line of FIG. 5, because x[i] is above the
noise threshold for i from 0 to 80, the peak index is updated. But
for i from 81 to N-1 and -N to -1, x[i] is not above the noise
threshold, the peak index is not updated. Accordingly, after the
power levels of all the indices are considered, the peak index is
determined to be 80. On the other hand, for the i-th scan line
shown in FIG. 5, the peak index is updated while i=0 to i=N-1 and
i=-N to i=-80. But for i=-79 to -1, the peak index is not updated.
Accordingly, after checking power levels for all the indices, the
peak index becomes -80.
[0041] FIG. 7 offers a flow chart for explaining a method of
updating the PRF of a scan line in accordance with the present
invention. The peak index is computed (S801) as is shown in FIG. 6.
Then it is determined (S802) whether the signal exists in the
positive frequency range or the negative frequency range. If the
signal exists in the positive frequency range, it is further
checked whether the sign of the peak index is positive (S803) and,
if so, the PRF is not updated. That is, if a real signal component
exists in a positive frequency range and the peak index is
positive, it signals that the aliasing does not occur. Accordingly,
without updating the PRF, a program is terminated (S807).
[0042] If the peak index is negative, this signals that the
aliasing occurs. Accordingly, a new upper bound of the frequency
index, i.e., N.sub.new in Eq. (1), is computed (S805), a new
PRF.sub.new not causing the aliasing according to Eq. (2) is
computed (S806), and then a program is terminated (S807).
[0043] Meanwhile if the signal existed in the negative frequency
range (S802), it is further checked whether the sign of the peak
index is negative (S804) and, if so, the PRF is not updated. If the
sign is positive (S802), a new upper bound of the frequency index,
i.e., N.sub.new in Eq. (1), is computed (S805). Using the new
largest frequency index, a new PRF, i. e., PRF.sub.new in Eq. (3),
is computed.
[0044] Although FIG. 7 firstly employs the Eq. (1) in the step
(S805) and then employs the Eq. (2) in the step (S806), the
PRF.sub.new can be computed by using Eq. (2) not the Equations
(1,2).
[0045] As described above, the inventive ultrasound diagnostic
apparatus and method detect whether the aliasing occurs in sample
data in measuring a blood flow velocity. If the aliasing occurs,
the inventive ultrasound diagnostic apparatus and method determine
an optimum PRF by updating a current PRF such that the aliasing
does not occur.
[0046] While there has been described and illustrated system and
method for updating a pulse repetition frequency (PRF) to avoid
aliasing, it will be apparent to those skilled in the art that
variations and modifications are possible without deviating from
the broad principles and teachings of the present invention which
should be limited solely by the spirit and scope of the claims
appended hereto.
* * * * *