CN108186050B - Doppler blood flow velocity imaging method and system based on ultrasonic channel data - Google Patents

Doppler blood flow velocity imaging method and system based on ultrasonic channel data Download PDF

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CN108186050B
CN108186050B CN201810005469.2A CN201810005469A CN108186050B CN 108186050 B CN108186050 B CN 108186050B CN 201810005469 A CN201810005469 A CN 201810005469A CN 108186050 B CN108186050 B CN 108186050B
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blood flow
flow velocity
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CN108186050A (en
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刘西耀
刘鑫
刘东权
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SHENGTAITE (CHENGDU) TECHNOLOGY CO LTD
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/06—Measuring blood flow
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/44—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device
    • A61B8/4483—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device characterised by features of the ultrasound transducer
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/488—Diagnostic techniques involving Doppler signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves

Abstract

The invention discloses a Doppler blood flow velocity imaging method and system based on ultrasonic channel data, which can independently estimate blood flow velocity through channel data corresponding to different array elements, and then improve the signal-to-noise ratio of blood flow signals in a mode of angle phase alignment and superposition so as to improve the accuracy of blood flow velocity estimation. The method comprises the following steps: transmitting ultrasonic waves, and acquiring channel data corresponding to each array element from the received echo signals; carrying out demodulation transformation on each channel data to obtain a complex signal; performing filtering processing to filter out tissue Doppler velocity components in a time direction; performing sliding window fast Fourier transform on the complex signal with the tissue Doppler velocity component removed to obtain a transformed frequency domain complex signal; and acquiring the blood flow velocity corresponding to each channel data through the converted frequency domain complex signals based on the angle between the scanning line direction of each array element and the blood vessel, and generating a blood flow image of the target area based on the blood flow velocity.

Description

Doppler blood flow velocity imaging method and system based on ultrasonic channel data
Technical Field
The invention relates to the technical field of ultrasonic imaging, in particular to a Doppler blood flow velocity imaging method and system based on ultrasonic channel data.
Background
Conventional ultrasonic doppler imaging systems are typically implemented based on the ultrasonic doppler phenomenon. For example, moving tissue or blood flow may cause the ultrasound frequency to shift, and the calculation of the frequency shift may be used to estimate the velocity of the tissue or blood flow. Typical applications include ultrasonic doppler D-mode imaging, ultrasonic doppler C-mode imaging, etc., and the results of these imaging modes have important guiding significance for cardiovascular-related diseases. In the existing ultrasonic doppler imaging technology, ultrasonic waves are transmitted through an ultrasonic transducer array element, corresponding echo signals are received to acquire channel data, beam forming is performed on the channel data, and then a sampling line is obtained to estimate the velocity of blood flow. The traditional imaging technology needs beam forming, which means that the blood flow velocity estimation at the same position needs to be obtained by accumulating ultrasonic waves emitted by array elements at different positions, and in the frequency domain change process, the problem that the blood flow velocity estimation is inaccurate due to the fact that the only included angle between the scanning direction and the blood flow direction is assumed to be the angle theta, which is obvious, and the actual included angle between the scanning direction and the blood flow direction is emitted by physical array elements.
Disclosure of Invention
At least one of the objectives of the present invention is to overcome the above problems in the prior art, and provide a doppler blood flow velocity imaging method and system based on ultrasound channel data, which can separately estimate blood flow velocity through channel data corresponding to different array elements, and then improve the signal-to-noise ratio of blood flow signals by means of angle phase alignment and superposition, thereby improving the accuracy of blood flow velocity estimation.
In order to achieve the above object, the present invention adopts the following aspects.
A method of doppler blood flow velocity imaging based on ultrasound channel data, comprising:
transmitting ultrasonic waves, and acquiring channel data corresponding to each array element from the received echo signals; carrying out demodulation transformation on each channel data to obtain a complex signal; filtering the acquired complex signals to filter tissue Doppler velocity components in the time direction; performing sliding window fast Fourier transform on the complex signal with the tissue Doppler velocity component removed to obtain a transformed frequency domain complex signal;
and acquiring the blood flow velocity corresponding to each channel data through the converted frequency domain complex signals based on the angle between the scanning line direction of each array element and the blood vessel, and generating a blood flow image of the target area based on the blood flow velocity.
A doppler blood flow velocity imaging system based on ultrasound channel data, comprising: the device comprises a transducer with a plurality of array elements, an echo signal processor, a channel data processor, a complex signal processor, a blood flow velocity processor, an image coding processor, a memory and a display which are sequentially connected with the transducer;
the transducer is used for transmitting ultrasonic waves and receiving echo signals;
the echo signal processor is used for acquiring channel data corresponding to each array element from the received echo signals;
the channel data processor is used for filtering out direct current components of the channel data in the length direction of the channel data for each channel data to obtain filtered channel data; performing data insertion on the filtered channel data to keep the phase and the signal-to-noise ratio of the channel data after the data insertion unchanged;
the complex signal processor is used for demodulating and converting the channel data after the data are inserted into the channel data to obtain complex signals; filtering the acquired complex signals to filter tissue Doppler velocity components in the time direction; performing sliding window fast Fourier transform on the complex signals to obtain frequency domain complex signals after transformation;
the blood flow velocity processor is used for acquiring the blood flow velocity corresponding to each channel data through the transformed frequency domain complex signal based on the angle between the scanning line direction of each array element and the blood vessel;
an image encoding processor for generating a blood flow image of the target region based on the blood flow velocity.
In summary, due to the adoption of the technical scheme, the invention at least has the following beneficial effects:
respectively processing the channel data corresponding to each array element to obtain corresponding frequency domain complex signals
Figure GDA0002536399660000021
And then, according to different scanning angles of each array element, the blood flow velocity corresponding to each channel is independently calculated, and the blood flow velocity of each channel is finally fused to obtain a final blood flow image, so that the accuracy of the blood flow velocity is effectively improved, and the blood flow noise is reduced.
Drawings
Fig. 1 is a flow chart of a method of doppler blood flow velocity imaging based on ultrasound channel data in accordance with an embodiment of the present invention.
FIG. 2 is a channel according to an embodiment of the inventionData Cn, filtered channel data
Figure GDA0002536399660000022
The frequency response curve of the channel data Cn' after the data insertion is shown.
Fig. 3 is a schematic diagram of an angle between a scanning line direction of an array element and a blood vessel in a conventional blood flow velocity estimation.
Fig. 4 is a schematic diagram of an angle between a scan line direction of an array element and a blood vessel used for blood flow velocity estimation according to an embodiment of the present invention.
Fig. 5 is a renal blood flow image obtained by conventional blood flow imaging.
FIG. 6 is a blood flow image acquired according to a method of an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a doppler blood flow velocity imaging system based on ultrasound channel data according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of sub-sampling gate division along a scan line direction according to an embodiment of the present invention.
Fig. 9 is a schematic diagram of vessel space sub-sampling gate partitioning according to an embodiment of the present invention.
FIG. 10 is a schematic diagram of frequency, spatial fusion, according to an embodiment of the present invention.
Fig. 11 is a schematic diagram of a blood flow spectrum obtained by a conventional blood flow imaging method.
FIG. 12 is a schematic diagram of a blood flow spectrum acquired by a method according to an embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and embodiments, so that the objects, technical solutions and advantages of the present invention will be more clearly understood. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following describes in detail a doppler blood flow velocity imaging method based on ultrasound channel data according to an embodiment of the present invention with reference to fig. 1.
Step 101: transmitting ultrasonic waves, and collecting channel data corresponding to each array element from the received echo signals
In particular, a transducer having N array elements may be used to transmit ultrasound waves, and N channel data C, of which the nth channel data is denoted by Cn, may be acquired from echo signals from N receive channels corresponding to each array element. The channel data C is a matrix of M × N, wherein M is the depth required to be detected according to ultrasound, and the length of the channel data obtained through time delay receiving is the length in the depth direction; n represents the number of actual physical channels of the ultrasound system, and N may typically be 16, 32, 64, 128, etc.
Step 102: for each channel data, filtering out the direct current component of the channel data in the length direction of the channel data, and obtaining the filtered channel data
Since the dc component is a constant independent of time and is different from a signal having a periodic characteristic, and the dc component is meaningless signal noise, the accuracy of subsequent calculation can be improved by removing the dc component in the M direction. Specifically, for the nth channel data Cn in the N channel data C, the classical butterworth filter is used to filter out the dc component, and the obtained filtered channel data
Figure GDA0002536399660000031
Is represented as follows:
Figure GDA0002536399660000032
where K is a delay parameter and the typical value is 5, the typical values of the parameter phasors a and b are obtained as follows:
Figure GDA0002536399660000033
Figure GDA0002536399660000034
step 103: performing data insertion on the filtered channel data to keep the phase and the signal-to-noise ratio of the channel data after data insertion unchanged
Due to filtered channel data
Figure GDA0002536399660000035
The data length of the data channel Cn is reduced by K compared to the data length before filtering, which means that the phase of the data is tampered, which directly affects the signal to noise ratio of the signal and needs to be realigned. The channel data insertion method of the embodiment can effectively keep the signal length, simultaneously does not distort the phase of the data and keeps the signal-to-noise ratio of the data. In particular, the filtered channel data may be filtered using a repmat function
Figure GDA0002536399660000045
The matrix copies K blocks as elements of data-inserted channel data Cn' consisting of K filtered channel data
Figure GDA0002536399660000046
Is formed by laying, and the expression is
Figure GDA0002536399660000041
Curves 21, 22 and 23 in FIG. 2 show the nth channel data Cn and the filtered channel data Cn, respectively
Figure GDA0002536399660000047
The frequency response curve of the channel data Cn' after the data insertion. Cn' and can be clearly observed
Figure GDA0002536399660000048
The signal-to-noise ratios of the frequency responses after the direct-current components are filtered are consistent and are all higher than Cn.
Step 104: demodulating and converting the channel data after inserting the data to obtain a complex signal
Specifically, the channel data Cn' after the data insertion can be demodulated and transformed using hilbert transform (Hilberttransform):
Figure GDA0002536399660000042
Figure GDA0002536399660000043
where Fc is the center frequency of the transmitted signal and Fs is the sampling rate of the system.
Demodulating the nth channel data to obtain complex signals In and Qn which are represented as IQn signals, representing IQn obtained at the time T of the nth channel as IQn, T, and obtaining a complex signal IQ of a three-dimensional matrix In continuous time periods T, wherein the magnitude of the complex signal IQ is M × N × T, and M is the length of the nth channel data at the time T.
Step 105: filtering the acquired complex signals to remove tissue Doppler velocity components in the time direction
The acquired IQ signal contains a large amount of tissue motion velocity, but since tissue doppler imaging and doppler blood flow velocity imaging are two different imaging contents, the tissue doppler velocity component can be filtered out in blood flow imaging, and therefore, this step 105 is an optional step of the preferred embodiment. Taking doppler blood flow velocity imaging as an example, an infinite impulse response IIR high-pass filter is used to filter the tissue doppler velocity component in the time direction, and the formula is as follows:
Figure GDA0002536399660000044
wherein Z is a delay parameter, a typical value is 3, and the corresponding parameter vectors a and b typically have values as follows:
a＝[1.0000,-2.374094743709352,1.929355669091215,-0.532075368312092]
b＝[0.729440722639082,-2.188322167917248,2.188322167917248,-0.729440722639082]
step 106: performing sliding window fast Fourier transform on the complex signal with the tissue Doppler velocity component removed to obtain a transformed frequency domain complex signal
In particular, the complex signal of tissue Doppler velocity component is filtered
Figure GDA0002536399660000053
In the time direction, a sliding window fast fourier transform (slidingwindow fft) is performed, which is expressed as follows:
Figure GDA0002536399660000051
where U is the data length of the sliding window fast Fourier transform,
Figure GDA0002536399660000054
is a transformed frequency domain complex signal.
The present embodiment employs a Fast Fourier Transform (FFT) with a complexity of O (Nlog (N)/2); in other embodiments, a discrete Fourier transform DFT may be used, with a complexity of O (N2). More specifically, the present embodiment uses a time-domain extracted fast fourier transform, which needs to perform a bit flipping (bitreverse) operation on the input signal, but the output signal is a positive sequence signal, which has a great significance (can effectively save the storage space).
Step 107: based on the angle between the scanning line direction of each array element and the blood vessel, obtaining the blood flow velocity corresponding to each channel data through the transformed frequency domain complex signal, and generating the blood flow image of the target area based on the blood flow velocity
By aligning frequency domain complex signals
Figure GDA0002536399660000055
And (4) taking a model to obtain an estimated value of the blood flow velocity. Specifically, a frequency domain complex signal obtained for the nth channel data
Figure GDA0002536399660000056
The included angle between the scanning line direction of the array element n and the blood vessel is theta n, so that the blood flow velocity of the focusing point at the time t can be obtained according to the following formula:
Figure GDA0002536399660000052
where V (x, y) is the blood flow velocity at which the target region is located at x, y, k is the weighted radius, ω is the weight function; regarding the included angle θ n, taking a 40mm linear array 128 array element as an example, the array element spacing is 0.3125mm, the focusing position with the center position depth Dmm is set, the included angle θ n between the scanning line direction of the nth array element and the blood vessel is in bilateral symmetry, and θ n is pi/2-arctan (n is 0.3125/D).
Through the calculation of the formula, the blood flow velocity data of each focus point of the target area can be accurately calculated, and then a blood flow image is generated through image coding processing and can be displayed through a display or stored through a memory.
The conventional blood flow velocity estimation is shown in fig. 3, which assumes that the array element scan line direction 31 is unique and has an angle θ with the blood vessel 32, and thus is determined by the angle θ between the scan line direction and the blood vessel
Figure GDA0002536399660000057
The estimated blood flow velocity is finally obtained by multiplying cos (theta) on the signal, and the estimation error of the blood flow velocity is larger due to the obvious estimation error of the included angle. In fact, as shown in fig. 4, the N elements in the transducer are not physically located at the same position, which results in the scan line direction being at a different angle than the blood vessel. In the above embodiments of the present invention, the channel data corresponding to each array element is processed to obtain the corresponding frequency domain complex signal
Figure GDA0002536399660000061
And then, according to different scanning angles of each array element, the blood flow velocity corresponding to each channel is independently calculated, and the blood flow velocity of each channel is finally fused to obtain a final blood flow image, so that the accuracy of the blood flow velocity is effectively improved, and the blood flow noise is reduced.
Fig. 5 is a renal blood flow image obtained by the conventional blood flow imaging method, which has inaccurate detail expression and high inaccurate estimation speed due to an angle error. Fig. 6 is a blood flow image obtained by the method according to the embodiment of the present invention, and it can be obviously observed that the blood flow velocity is accurate, the small blood vessels are full, and the blood flow noise caused by the estimation error is less.
Figure 7 illustrates a doppler blood flow velocity imaging system based on ultrasound channel data in accordance with an embodiment of the present invention. The system comprises: the device comprises a transducer with a plurality of array elements, an echo signal processor, a channel data processor, a complex signal processor, a blood flow velocity processor, an image coding processor, a memory and a display which are sequentially connected with the transducer.
The transducer is used for transmitting ultrasonic waves and receiving echo signals;
the echo signal processor is used for acquiring channel data corresponding to each array element from the received echo signals;
the channel data processor is used for filtering out direct current components of the channel data in the length direction of the channel data for each channel data to obtain filtered channel data; performing data insertion on the filtered channel data to keep the phase and the signal-to-noise ratio of the channel data after the data insertion unchanged;
the complex signal processor is used for demodulating and converting the channel data after the data are inserted into the channel data to obtain complex signals; filtering the acquired complex signals to filter tissue Doppler velocity components in the time direction; performing sliding window fast Fourier transform on the complex signals to obtain frequency domain complex signals after transformation;
the blood flow velocity processor is used for acquiring the blood flow velocity corresponding to each channel data through the transformed frequency domain complex signal based on the angle between the scanning line direction of each array element and the blood vessel;
an image encoding processor for generating a blood flow image of the target region based on the blood flow velocity.
In a preferred embodiment of the present invention, the step 106 of acquiring the transformed frequency domain complex signal in the above embodiment may be completed by dividing the sub-sampling gate and performing spatial, temporal and frequency domain fusion on the complex signal in the sub-sampling gate to improve the signal-to-noise ratio of the blood flow spectrum, thereby further improving the accuracy and the signal-to-noise ratio of the blood flow velocity in the blood flow image.
Step 201: dividing the blood vessel into a plurality of sub-sampling gates along the scanning line direction of the array element, and respectively carrying out space domain fusion on the complex signal in each sub-sampling gate to obtain a space fusion complex signal
As shown in fig. 8, the blood vessel can be divided into N + N ' Sub-sampling Gates (Sub-Gates) from 1 to N and 1 ' to N ' along the scanning line direction of the array element, and the complex signals in each Sub-sampling gate can be respectively divided into
Figure GDA0002536399660000062
And performing spatial domain fusion. Wherein, the channel data length is M complex signal
Figure GDA0002536399660000071
Are equally distributed into N + N' sample gates, each of which has a size defined as R1 and a radius defined as R for the entire blood vessel, as shown in fig. 9.
Step 202: respectively carrying out time domain fusion on the space fusion complex signals in each sub-sampling gate to obtain blood flow spectrum data corresponding to each sub-sampling gate
In particular, the spatially fused complex signals in N + N' sub-sampling gates may be fused
Figure GDA0002536399660000072
And performing Fourier transform in the time direction to obtain N + N' pieces of blood flow spectrum data.
Step 203: respectively fusing the blood flow frequency spectrum data in each sub-sampling gate in the frequency domain to obtain a transformed frequency domain complex signal
As shown in fig. 10, the obtained N + N' bloodstream spectrums are fused again in the frequency domain, so that the bloodstream speckle noise can be effectively suppressed, and the bloodstream signal-to-noise ratio can be improved. The FFT with sliding window strongly depends on the PRF (pulse repetition frequency), which is a very important parameter in blood flow analysis and can be chosen as 2KHz or KHzPRF 4 KHz. For example, a 64-point complex signal may be matched using a Jump 16 sliding window
Figure GDA0002536399660000073
And performing a 128-point base 2 time domain decimation FFT to obtain a spectrum line, and obtaining a frame of blood flow spectrum through multiple sliding calculations. Compared with the blood flow spectrum obtained by the conventional method shown in fig. 11, the blood flow spectrum obtained by the embodiment of the present invention is shown in fig. 12, which has a high blood flow signal-to-noise ratio and is less affected by blood flow noise.
Step 204: and acquiring the blood flow velocity corresponding to each sub-sampling gate through the converted frequency domain complex signals based on the angle between the scanning line direction of each array element and the blood vessel, and generating a blood flow image of the target area based on the blood flow velocity.
The foregoing is merely a detailed description of specific embodiments of the invention and is not intended to limit the invention. Various alterations, modifications and improvements will occur to those skilled in the art without departing from the spirit and scope of the invention.

Claims (10)

1. A method of doppler blood flow velocity imaging based on ultrasound channel data, the method comprising:
transmitting ultrasonic waves, and acquiring channel data corresponding to each array element from the received echo signals; carrying out demodulation transformation on each channel data to obtain a complex signal; filtering the acquired complex signals to filter tissue Doppler velocity components in the time direction; performing sliding window fast Fourier transform on the complex signal with the tissue Doppler velocity component removed to obtain a transformed frequency domain complex signal;
and acquiring the blood flow velocity corresponding to each channel data through the converted frequency domain complex signals based on the angle between the scanning line direction of each array element and the blood vessel, and generating a blood flow image of the target area based on the blood flow velocity.
2. The method of claim 1, further comprising: before demodulation and conversion are carried out, filtering out direct current components of the channel data in the length direction of the channel data for each channel data to obtain filtered channel data; and performing data insertion on the filtered channel data to keep the phase and the signal-to-noise ratio of the channel data after the data insertion unchanged.
3. The method of claim 2, wherein the method comprises:
for the nth channel data C in the N channel data CnFiltering out DC component by using classic Butterworth filter to obtain filtered channel data
Figure FDA0002839184130000011
Expressed as:
Figure FDA0002839184130000012
wherein K is a time delay parameter, and a and b are parameter phasors; m is the length of channel data obtained by delay reception according to the depth of the ultrasonic probe.
4. The method of claim 3, wherein the method comprises:
filtered channel data using a repmat function
Figure FDA0002839184130000013
Matrix copy K blocks as channel data C 'after data insertion'nAnd by the formula
Figure FDA0002839184130000014
Acquiring channel data C 'after data insertion'n。
5. The method of claim 4, wherein the method comprises:
channel data C 'into which data is inserted by using Hilbert transform'nCarrying out demodulation transformation:
Figure FDA0002839184130000015
Figure FDA0002839184130000016
wherein F iscIs the center frequency of the transmitted signal, FsIs the sampling rate of the system; demodulating the nth channel data to obtain a complex signal InAnd QnDenoted as IQnSignal, IQ obtained by n channel at time tnDenoted as IQn，tAnd obtaining a complex signal IQ of the three-dimensional matrix in a continuous time period T, wherein the magnitude of the complex signal IQ is M × N × T, and M is the length of the nth channel data at the time T.
6. The method of claim 5, wherein the method comprises:
filtering the tissue Doppler velocity component in the time direction by using an Infinite Impulse Response (IIR) high-pass filter to obtain a complex signal for filtering the tissue Doppler velocity component
Figure FDA0002839184130000021
And is
Figure FDA0002839184130000022
Wherein Z is a time delay parameter, and a and b are parameter vectors.
7. The method of claim 6, wherein the method comprises:
for complex signals with tissue Doppler velocity component filtered
Figure FDA0002839184130000023
In the time direction, performing sliding window fast Fourier transform to obtain the transformed frequency domain complex signal
Figure FDA0002839184130000024
Figure FDA0002839184130000025
Where U is the data length of the sliding window fast fourier transform.
8. The method of claim 7, wherein the method comprises:
frequency domain complex signal obtained for nth channel data
Figure FDA0002839184130000026
The included angle between the array element n scanning line direction and the blood vessel is thetanOf the through type
Figure FDA0002839184130000027
Calculating blood flow velocity V (x, y) of the target region at x, y;
where k is the weighted radius and ω is the weight function.
9. The method according to claim 1, characterized in that it comprises:
dividing the blood vessel into a plurality of sub-sampling gates along the scanning line direction of the array element, and respectively carrying out space domain fusion on the complex signals in each sub-sampling gate to obtain space fusion complex signals; respectively carrying out time domain fusion on the space fusion complex signals in each sub-sampling gate to obtain blood flow spectrum data corresponding to each sub-sampling gate; respectively fusing the blood flow frequency spectrum data in each sub-sampling gate in a frequency domain to obtain a transformed frequency domain complex signal; and acquiring the blood flow velocity corresponding to each sub-sampling gate through the converted frequency domain complex signals based on the angle between the scanning line direction of each array element and the blood vessel, and generating a blood flow image of the target area based on the blood flow velocity.
10. A doppler blood flow velocity imaging system based on ultrasound channel data, the system comprising: the device comprises a transducer with a plurality of array elements, an echo signal processor, a channel data processor, a complex signal processor, a blood flow velocity processor, an image coding processor, a memory and a display which are sequentially connected with the transducer;
the transducer is used for transmitting ultrasonic waves and receiving echo signals;
the echo signal processor is used for acquiring channel data corresponding to each array element from the received echo signals;
the channel data processor is used for filtering out direct current components of the channel data in the length direction of the channel data for each channel data to obtain filtered channel data; performing data insertion on the filtered channel data to keep the phase and the signal-to-noise ratio of the channel data after the data insertion unchanged;
the complex signal processor is used for demodulating and converting the channel data after the data are inserted into the channel data to obtain complex signals; filtering the acquired complex signals to filter tissue Doppler velocity components in the time direction; performing sliding window fast Fourier transform on the complex signals to obtain frequency domain complex signals after transformation;
the blood flow velocity processor is used for acquiring the blood flow velocity corresponding to each channel data through the transformed frequency domain complex signal based on the angle between the scanning line direction of each array element and the blood vessel;
an image encoding processor for generating a blood flow image of the target region based on the blood flow velocity.
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