Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation
Reexamination Certificate
2001-07-03
2002-09-10
Jaworski, Francis J. (Department: 3737)
Surgery
Diagnostic testing
Detecting nuclear, electromagnetic, or ultrasonic radiation
Reexamination Certificate
active
06447455
ABSTRACT:
FIELD OF THE INVENTION
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
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.
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
.
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.
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.
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.
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
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.
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.
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
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.
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.
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
Bang Ji Hoon
Kim Cheol An
Jaworski Francis J.
Medison Co. Ltd.
Patel Maulin
Wiggin & Dana LLP
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