CN103519847A - Doppler blood flow velocity estimation method and system based on ultrasonic echo radio frequency signals - Google Patents
Doppler blood flow velocity estimation method and system based on ultrasonic echo radio frequency signals Download PDFInfo
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Abstract
The invention relates to a Doppler blood flow velocity estimation method and system based on ultrasonic echo radio frequency signals. The method includes a converting step, namely converting the entire-frame ultrasonic echo radio frequency signals into analytic signals; a segmenting step, namely segmenting the entire-frame analytic signals according to the preset window length and acquiring segmented window data segments; a product summary step, namely performing once no-offset product summary on the segmented window data segments corresponding to two adjacent frames and acquiring a target plurality; a phase calculating step, namely calculating the phase of the target plurality; and a velocity estimating step, namely utilizing the phase to calculate and acquire average moving velocity of the blood between two frame signals. According to the Doppler blood flow velocity estimation method based on the ultrasonic echo radio frequency signals, signal analytic and low-pass filtering are omitted, calculation is simplified, negative impact on results by filtering is eliminated, the calculating amount is reduced, and calculating time is shortened greatly.
Description
Technical field
The present invention relates to ultra sonic imaging field, particularly relate to a kind of Doppler blood flow velocity estimating and measuring method and system based on ultrasonic echo radiofrequency signal.
Background technology
Doppler effect refers to that the wavelength of object radiation is because wave source and observer's caused by relative motion changes.Before the wave source of motion, ripple is compressed, and it is shorter that wavelength becomes, and it is higher that frequency becomes; At the wave source of motion, in the back time, can produce contrary effect.
The Doppler effect of ultrasonic echo is used for to the measurement to artery blood flow speed, i.e. ultrasonic Doppler(Doppler) speed estimation.Because endovascular blood is mobile object, so just produce Doppler effect between the blood of ultrasound wave vibration source and relative motion.When blood vessel moves towards supersonic source, the wavelength of echo is compressed, thereby frequency increases.When blood vessel leaves sound source motion, the wavelength of echo is elongated, thereby reduces in unit interval frequency.The amount that reflection wave frequency increases or reduces, is directly proportional to blood flow running speed degree, thereby according to hyperacoustic frequency shift amount, measures the flow velocity of blood, and computing formula is as follows:
Wherein, υ is blood flow rate, and ω is Doppler frequency, ω
0for ultrasound emission frequency, c is velocity of ultrasonic sound, and θ is the angle between ultrasonic beam and blood flow direction.
Doppler ultrasound generally adopts autocorrelation technique to process Doppler signal.Specific algorithm is: first original ultrasonic rf echo signal is carried out to IQ decomposition, IQ decomposed signal is that original signal is multiplied by respectively to cos (2 π ft) and sin (2 π ft) (f is ultrasound emission frequency), through sampling after low-pass filtering, obtain In-phase and Quadrature phase two paths of signals again.IQ signal can form complex-envelope signal (complex envelope signal), In-phase signal is the real part of complex-envelope signal, Quadrature phase signal is the imaginary part of complex-envelope signal, the Doppler frequencies omega that the frequency of complex-envelope signal is corresponding blood flow rate.Front and back two frame complex-envelope signals (interval of two interframe is T) are in succession carried out to auto-correlation computation, obtain autocorrelation coefficient R, calculate R's
phase place, by Wiener-Khinchin theorem, can obtain average Doppler frequencies omega and equal
(T)/T, ω is directly proportional with blood flow rate υ, can obtain blood flow rate υ by ultrasound emission frequency f and velocity of ultrasonic sound c.Its computing formula is as follows:
Wherein, m is the position of data point in Frame, and s is frame number, and arctan () part is
(T), I, Q are respectively In-phase and Quadrature phase signal.
Traditional ultrasonic Doppler blood flow rate algorithm need to utilize software to realize IQ decomposition, and uses low pass filter in decomposing, and has greatly increased amount of calculation and computation time.
Summary of the invention
Based on this, being necessary, for traditional ultrasonic Doppler blood flow rate algorithm amount of calculation problem large and consuming time, provides a kind of Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal that can save computation time.
In addition, be also necessary to provide a kind of Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal that can save computation time.
A Doppler blood flow velocity estimating and measuring method for ultrasonic echo radiofrequency signal, comprising:
Switch process, is converted to analytic signal by the ultrasonic echo radiofrequency signal of whole frame;
Partiting step, carries out segmentation by the analytic signal of whole frame according to preset window length, obtains segmentation window data section;
Long-pending and step, to two adjacent frame signals, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number;
Phase calculation step, calculates the phase place of described target plural number;
Velocity estimation step, utilizes described phase calculation to obtain the average translational speed of blood flow in two frame signal intervals.
In an embodiment, before described switch process, also comprise therein:
Piecemeal step, is divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal;
Described switch process comprises:
The ultrasonic echo radiofrequency signal of the whole frame of each data matrix is converted to analytic signal;
After described velocity estimation step, also comprise:
Two-dimension speed distributed image step, according to calculating in a plurality of data matrixes in each data matrix the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
In an embodiment, described switch process comprises therein:
Adopt Fourier transformation and inverse transformation to obtain analytic signal the ultrasonic echo radiofrequency signal of whole frame.
Therein in an embodiment, described switch process adopts the first kernel function being realized by graphic process unit to process, the line number that the block number of described the first kernel function is data matrix, the columns that the thread number of described the first kernel function is data matrix.
In an embodiment, described the second kernel function long-pending and that step, phase calculation step and the employing of velocity estimation step are realized by graphic process unit is calculated therein; The line number that the block number of described the second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of described segmentation window number by described data matrix and window width poor divided by step-length, then adds 1 and obtain.
A Doppler blood flow velocity estimating system for ultrasonic echo radiofrequency signal, comprising:
Modular converter, for being converted to analytic signal by the ultrasonic echo radiofrequency signal of whole frame;
Divide module, for the analytic signal of whole frame is carried out to segmentation according to preset window length, obtain segmentation window data section;
Long-pending and module, for two frame signals to adjacent, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number;
Phase calculation module, for calculating the phase place of described target plural number;
Velocity estimation module, for utilizing described phase calculation to obtain the average translational speed of two frame signal interval blood flows.
In an embodiment, described system also comprises piecemeal module and two-dimension speed distributed image module therein,
Described piecemeal module is for being divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal;
Described modular converter is also for being converted to analytic signal by the ultrasonic echo radiofrequency signal of the whole frame of each data matrix;
Described two-dimension speed distributed image module, for according to calculating in each data matrix of a plurality of data matrixes the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
In an embodiment, described modular converter is also for adopting Fourier transformation and inverse transformation to obtain analytic signal the ultrasonic echo radiofrequency signal of whole frame therein.
Therein in an embodiment, described modular converter adopts the first kernel function being realized by graphic process unit to process, the line number that the block number of described the first kernel function is data matrix, the columns that the thread number of described the first kernel function is data matrix.
In an embodiment, described the second kernel function long-pending and that module, phase calculation module and the employing of velocity estimation module are realized by graphic process unit is calculated therein; The line number that the block number of described the second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of described segmentation window number by described data matrix and window width poor divided by step-length, then adds 1 and obtain.
The above-mentioned Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal, the ultrasonic echo radiofrequency signal of whole frame is once converted to analytic signal, improved greatly computational speed, do not need to carry out signal decomposition and low-pass filtering, both simplified calculating, also eliminate the negative effect of filtering to result, reduced amount of calculation, greatly shortened computation time.
In addition, the ultrasonic echo radiofrequency signal of whole frame is once carried out to Fourier transformation and an inverse Fourier transform, than segmentation rear hatch data segment being carried out to tens times to hundreds of inferior Fourier transformation and inverse Fourier transform, improved greatly computational speed; When adopting graphic process unit to realize, can utilize a plurality of block numbers and thread to count parallel processing, improved treatment effeciency.
Accompanying drawing explanation
Fig. 1 is the flow chart of the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal in an embodiment;
Fig. 2 is separately the flow chart of the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal in an embodiment;
Fig. 3 is the structured flowchart of the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal in an embodiment;
Fig. 4 is the structured flowchart of the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal in an embodiment.
The specific embodiment
In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
Fig. 1 is the flow chart of the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal in an embodiment.Be somebody's turn to do the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal, comprise the following steps:
In the present embodiment, adopt Fourier transformation and inverse transformation to obtain analytic signal the ultrasonic echo radiofrequency signal of whole frame, be about to real number signal and be converted to complex signal.Concrete transformation process is: first by Fourier transformation, transfer time-domain signal to frequency-region signal, then the real part of frequency-region signal is multiplied by 2, imaginary part sets to 0, and then gained signal is carried out to inverse Fourier transform, obtains the analytic signal of corresponding original time-domain signal.The ultrasonic echo radiofrequency signal of whole frame is once carried out to Fourier transformation and an inverse Fourier transform, than segmentation rear hatch data segment being carried out to tens times to hundreds of inferior Fourier transformation and inverse Fourier transform, improved greatly computational speed.
Concrete, preset window length can be set as required.
Concrete, first corresponding data segment is carried out to complex multiplication, the more all products that obtain are added, obtain a plural form and a+jb, i.e. target plural number.Wherein, a, b are real number, and j is imaginary part identifier.The n of the first frame segmentation window data section x for example
1+ jy
1... x
n+ jy
n, the n of the second frame segmentation window data section z
1+ jc
1... z
n+ jc
n, a+jb=(x
1+ jy
1) * (z
1+ jc
1)+... + (x
n+ jy
n) * (z
n+ jc
n).
Concrete, the phase place of target plural number
Concrete, the computing formula of the average translational speed of blood flow is:
Wherein, υ is blood flow rate, and c is velocity of ultrasonic sound, and f is ultrasound emission frequency, and θ is the angle between ultrasonic beam and blood flow direction,
for phase place, T is the interval of two frame signals.
The above-mentioned Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal, the ultrasonic echo radiofrequency signal of whole frame is once converted to analytic signal, improved greatly computational speed, do not need to carry out signal decomposition and low-pass filtering, both simplified calculating, also eliminate the negative effect of filtering to result, reduced amount of calculation, greatly shortened computation time.
As shown in Figure 2, be the flow chart of the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal in another embodiment.In an embodiment, before this switch process, also comprise therein:
Step 202, piecemeal step, is divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal.
Concrete, ultrasonic echo radiofrequency signal is divided into N data matrix by side direction collection position, each data matrix size is row * col, represents to comprise row frame data (time orientation), every frame has col element (depth direction).
Step 204, switch process, is converted to analytic signal by the ultrasonic echo radiofrequency signal of the whole frame of each data matrix.
Switch process adopts the first kernel function being realized by graphic process unit (Graphics Process Unit, GPU) to process, the line number that the block number of the first kernel function is data matrix, the columns that the thread number of the first kernel function is data matrix.
Concrete, adopt GPU optimal design, Fourier transformation and inverse Fourier transform are all used CUDA(CPU+GPU) CUFFT built-in function cufftExecC2C.Processing for frequency-region signal adopts kernel function kernel_1 to realize.CPU is Central Processing Unit, central processing unit.
The first kernel function call order: 1) cufftExecC2C(direct transform); 2) kernel_1; 3) cufftExecC2C(inverse transformation).
The blocks quantity of the first kernel function is identical with threads quantity, is blocks=dim3 (input-> rows); Threads=dim3 (input-> cols), input-> rows is the line number of data matrix, input-> cols is the columns of data matrix.
Step 206, partiting step, carries out segmentation by the analytic signal of whole frame according to preset window length, obtains segmentation window data section.
Concrete, on depth direction, the analytic signal of whole frame is carried out to segmentation according to preset window length.Wherein, preset window length can be set as required.
Step 208, long-pending and step, to two adjacent frame signals, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number.
Concrete, to two frame signals adjacent on time orientation, segmentation window data section corresponding on depth direction is carried out once, without the amassing and computing of skew, obtaining target plural number.
Step 210, phase calculation step, calculates the phase place of this target plural number.
Concrete, the phase place of target plural number
Step 212, velocity estimation step, utilizes this phase calculation to obtain the average translational speed of blood flow in two frame signal intervals.
Step 214, two-dimension speed distributed image step, according to calculating in a plurality of data matrixes in each data matrix the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
Concrete, according to step 204, can obtain to each the segmentation window data section on depth direction the average translational speed of blood flow in adjacent two frame data intervals to 212.So can obtain average translational speed matrix size is (row-1) * Win_Num, and wherein, Win_Num is segmentation window number.
In one embodiment, long-pending and step, phase calculation step and velocity estimation step adopt the second kernel function being realized by graphic process unit (Graphics Process Unit, GPU) to calculate; The line number that the block number of this second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of this segmentation window number by this data matrix and window width poor divided by step-length, then adds 1 and obtain.
Concrete, the second kernel function adopts ComputeVel.Segmentation window number WinNum=(InputWidth-WindowHW)/Step+1, wherein, WindowHW is window width, step-length is Step, the columns that InputWidth is data matrix.
The thread(that the second kernel function ComputeVel designs each block is Thread Count) equal segmentation window number WinNum, the calculating of whole matrix is realized by (rows-1) individual block, and each block calculates the average translational speed of blood flow in one group of two adjacent frame signal interval.Therefore kernel function Thread Count is as follows:
The second kernel function Thread Count ComputeVel<<<blocks, threads>>>(), wherein, blocks=dim3 (rows-1); Threads=dim3 (WinNum).Wherein,<<<,>>>be CUDA grammatical symbol, represent that GPU carries out the Thread Count that kernel need to start, occupation mode:<<<represent the block quantity of startup, represent the Thread Count of 1 block the inside>>>.Input is a structure type, and an element of structure is got in-> expression.Adopt a plurality of block numbers and thread to count parallel processing, improved treatment effeciency.
As shown in Figure 3, be the structured flowchart of the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal in an embodiment.Be somebody's turn to do the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal, comprise modular converter 310, divide module 320, amass and module 330, phase calculation module 340 and velocity estimation module 350.Wherein:
Long-pending and module 330, for two frame signals to adjacent, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number.
Concrete, first corresponding data segment is carried out to complex multiplication, the more all products that obtain are added, obtain a plural form and a+jb, i.e. target plural number.
Concrete, the phase place of target plural number
Concrete, the computing formula of the average translational speed of blood flow is:
Wherein, υ is blood flow rate, and c is velocity of ultrasonic sound, and f is ultrasound emission frequency, and θ is the angle between ultrasonic beam and blood flow direction,
for phase place, T is the interval of two frame signals.
The above-mentioned Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal, the ultrasonic echo radiofrequency signal of whole frame is once converted to analytic signal, improved greatly computational speed, do not need to carry out signal decomposition and low-pass filtering, both simplified calculating, also eliminate the negative effect of filtering to result, reduced amount of calculation, greatly shortened computation time.
As shown in Figure 4, be the structured flowchart of the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal in an embodiment.Be somebody's turn to do the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal, except comprising modular converter 310, divide module 320, amassing and module 330, phase calculation module 340 and velocity estimation module 350, also comprise piecemeal module 360 and two-dimension speed distributed image module 370.
This piecemeal module 360 is for being divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal.Concrete, ultrasonic echo radiofrequency signal is divided into N data matrix by side direction collection position, each data matrix size is row * col, represents to comprise row frame data (time orientation), every frame has col element (depth direction).
This modular converter 310 is also for being converted to analytic signal by the ultrasonic echo radiofrequency signal of the whole frame of each data matrix.This modular converter 310 adopts the first kernel function being realized by graphic process unit to process, the line number that the block number of this first kernel function is data matrix, the columns that the thread number of this first kernel function is data matrix.
This division module 320, also for the analytic signal of whole frame being carried out to segmentation according to preset window length on depth direction, obtains segmentation window data section.
This long-pending and module 330 is also for two frame signals to adjacent on time orientation, and segmentation window data section corresponding on depth direction is carried out once, without the amassing and computing of skew, obtaining target plural number.
This two-dimension speed distributed image module 370, for according to calculating in each data matrix of a plurality of data matrixes the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
In one embodiment, this second kernel function long-pending and that module 330, phase calculation module 340 and 350 employings of velocity estimation module are realized by graphic process unit is calculated; The line number that the block number of this second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of this segmentation window number by this data matrix and window width poor divided by step-length, then adds 1 and obtain.
Adopt a plurality of block numbers and thread to count parallel processing, improved treatment effeciency.
One of ordinary skill in the art will appreciate that all or part of flow process realizing in above-described embodiment method, to come the hardware that instruction is relevant to complete by computer program, described program can be stored in a computer read/write memory medium, this program, when carrying out, can comprise as the flow process of the embodiment of above-mentioned each side method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-Only Memory, ROM) or random store-memory body (Random Access Memory, RAM) etc.
The above embodiment has only expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but can not therefore be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (10)
1. the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal, comprising:
Switch process, is converted to analytic signal by the ultrasonic echo radiofrequency signal of whole frame;
Partiting step, carries out segmentation by the analytic signal of whole frame according to preset window length, obtains segmentation window data section;
Long-pending and step, to two adjacent frame signals, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number;
Phase calculation step, calculates the phase place of described target plural number;
Velocity estimation step, utilizes described phase calculation to obtain the average translational speed of blood flow in two frame signal intervals.
2. the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal according to claim 1, is characterized in that, before described switch process, also comprises:
Piecemeal step, is divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal;
Described switch process comprises:
The ultrasonic echo radiofrequency signal of the whole frame of each data matrix is converted to analytic signal;
After described velocity estimation step, also comprise:
Two-dimension speed distributed image step, according to calculating in a plurality of data matrixes in each data matrix the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
3. the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal according to claim 2, is characterized in that, described switch process comprises:
Adopt Fourier transformation and inverse transformation to obtain analytic signal the ultrasonic echo radiofrequency signal of whole frame.
4. the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal according to claim 2, it is characterized in that, described switch process adopts the first kernel function being realized by graphic process unit to process, the line number that the block number of described the first kernel function is data matrix, the columns that the thread number of described the first kernel function is data matrix.
5. the Doppler blood flow velocity estimating and measuring method based on ultrasonic echo radiofrequency signal according to claim 2, is characterized in that, described the second kernel function long-pending and that step, phase calculation step and the employing of velocity estimation step are realized by graphic process unit is calculated; The line number that the block number of described the second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of described segmentation window number by described data matrix and window width poor divided by step-length, then adds 1 and obtain.
6. the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal, is characterized in that, comprising:
Modular converter, for being converted to analytic signal by the ultrasonic echo radiofrequency signal of whole frame;
Divide module, for the analytic signal of whole frame is carried out to segmentation according to preset window length, obtain segmentation window data section;
Long-pending and module, for two frame signals to adjacent, carries out corresponding segments window data section once, without the amassing and computing of skew, to obtain target plural number;
Phase calculation module, for calculating the phase place of described target plural number;
Velocity estimation module, for utilizing described phase calculation to obtain the average translational speed of two frame signal interval blood flows.
7. the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal according to claim 6, is characterized in that, described system also comprises piecemeal module and two-dimension speed distributed image module,
Described piecemeal module is for being divided into a plurality of data matrixes by ultrasonic echo radiofrequency signal;
Described modular converter is also for being converted to analytic signal by the ultrasonic echo radiofrequency signal of the whole frame of each data matrix;
Described two-dimension speed distributed image module, for according to calculating in each data matrix of a plurality of data matrixes the average translational speed of blood flow in adjacent two frame data intervals, forms the two-dimension speed distributed image of blood flow.
8. the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal according to claim 7, is characterized in that, described modular converter is also for adopting Fourier transformation and inverse transformation to obtain analytic signal the ultrasonic echo radiofrequency signal of whole frame.
9. the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal according to claim 7, it is characterized in that, described modular converter adopts the first kernel function being realized by graphic process unit to process, the line number that the block number of described the first kernel function is data matrix, the columns that the thread number of described the first kernel function is data matrix.
10. the Doppler blood flow velocity estimating system based on ultrasonic echo radiofrequency signal according to claim 7, is characterized in that, described the second kernel function long-pending and that module, phase calculation module and the employing of velocity estimation module are realized by graphic process unit is calculated; The line number that the block number of described the second kernel function is data matrix subtracts 1, and the thread number of each block is segmentation window number, and the columns of described segmentation window number by described data matrix and window width poor divided by step-length, then adds 1 and obtain.
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| CN106955098A (en) * | 2017-05-05 | 2017-07-18 | 飞依诺科技(苏州)有限公司 | A kind of vascular flow rate computational methods and device |
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Family Cites Families (5)
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| CN100518660C (en) * | 2004-03-24 | 2009-07-29 | 株式会社东芝 | Ultrasound diagnostic apparatus |
| JP4846335B2 (en) * | 2004-10-20 | 2011-12-28 | 株式会社東芝 | Ultrasonic Doppler diagnostic device |
| US20090131791A1 (en) * | 2005-08-22 | 2009-05-21 | Koninklijke Philips Electronics N.V. | Ultrasonic Diagnostic Imaging System With Spectral and Audio Tissue Doppler |
| CN102421372B (en) * | 2009-05-13 | 2014-10-29 | 皇家飞利浦电子股份有限公司 | Ultrasonic blood flow doppler audio with pitch shifting |
| JP5972561B2 (en) * | 2011-12-08 | 2016-08-17 | 東芝メディカルシステムズ株式会社 | Ultrasonic diagnostic apparatus, image processing apparatus, and image processing program |
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| CN107530051A (en) * | 2015-03-02 | 2018-01-02 | B-K医疗公司 | Use vector speed ultrasound（US）Noninvasive estimation to intravascular pressure change |
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| CN105919625B (en) * | 2016-05-26 | 2019-01-01 | 飞依诺科技(苏州)有限公司 | Pulse Doppler wall filtering processing method and processing system |
| CN106955098A (en) * | 2017-05-05 | 2017-07-18 | 飞依诺科技(苏州)有限公司 | A kind of vascular flow rate computational methods and device |
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| CN104188687A (en) | 2014-12-10 |
| CN104188687B (en) | 2016-08-24 |
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