CN103479397B - Method for extracting color ultrasound parametric blood flow signal based on relaxation algorithm - Google Patents

Abstract

The invention relates to a method for extracting a color ultrasound parametric blood flow signal based on a relaxation algorithm, and aims to solve the problem of poor accuracy of blood flow signal extraction since the energy ratio of a noise signal and a blood flow signal included in an ultrasonic echo signal is possibly as high as 40dB due to higher scattering intensity of soft tissues than red blood cells. The method comprises the following steps: acquiring a blood flow signal by using a color ultrasound detector, and transmitting to a signal receiving end; establishing an affine model for the received ultrasonic echo signal by using the signal receiving end, and estimating an affine model parameter by adopting the relaxation algorithm to obtain the frequency and amplitude of the blood flow signal. The method is suitable for the technical field of ultrasound color blood flow imaging, and is applied to the researches of various cardiovascular diseases.

Description

Based on the colorful ultrasonic parametrization blood flow signal extracting method of relaxed algorithm

Technical field

The present invention relates to ultrasonic color blood flow imaging technical field.

Background technology

As a kind of non-intervention type blood flow imaging method, ultrasonic color blood flow imaging is widely used in various Cardiovascular Disease Study.Because the slow noise signal produced of moving of blood vessel wall and its surrounding soft tissue can cause larger impact to blood flow precision to be shown.If the difficulty of the evaluation accuracy that the risk that blood flow information accurately can not be provided will to increase mistaken diagnosis and patient's long term medical detect.In actual applications, the precise decreasing having following two reasons that blood flow velocity is estimated:

One, because the scattering strength of soft tissue is much larger than erythrocyte, the clutter therefore comprised in ultrasound echo signal and the energy Ratios of blood flow signal may up to 40dB; This is because noise filter often can not fully filtering clutter or mistakenly filtering part blood flow signal, thus cause blood flow estimation difference.Especially, even if clutter can be suppressed fully at filtering stage, filtered residual white noise in the signal still can cause error to the average of the Doppler frequency of blood flow signal and variance evaluation;

Its two, under the requirement of real-time of ultra sonic imaging, the umber of pulse of the Doppler signal of reception is limited, often only continues 8-16 burst length.

Summary of the invention

The present invention is in order to solve because the scattering strength of soft tissue is much larger than erythrocyte, therefore the clutter comprised in ultrasound echo signal and the energy Ratios of blood flow signal may up to 40dB, the problem of the poor accuracy causing blood flow signal to extract, thus propose the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm.

Colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm is: adopt colorful ultrasonic detector to gather blood flow signal, Received signal strength end sets up affine model to the ultrasound echo signal received, adopt relaxed algorithm to estimate affine model parameter, obtain blood flow signal frequency and amplitude.

Received signal strength end to the detailed process that the ultrasound echo signal received sets up affine model is:

Using the ultrasound echo signal x of reception as affine model:

x≈Pα （1）

Wherein, α is oscillator intensity vector,

P is eigenmatrix:

P=[p(f ₁) p(f ₂) …p(f _k)… p(f _K)] （2），

The expression formula of ultrasound echo signal x:

x=[x(1) x(2) …x(n) …x(N)] ^T （3）

Wherein, k is the number of main constituent, k=1,2 ..., K, k and K are positive integer; X (1) represents first sampled value, and x (2) represents second sampled value, and x (n) represents the n-th sampled value, and x (N) represents N number of sampled value, n=1,2 ..., N, n and N are natural number; p (f _k) represent the frequency vector of a kth main constituent.

Adopt relaxed algorithm to estimate affine model parameter, the detailed process obtaining blood flow signal frequency and amplitude is:

Steps A, the frequency estimating first main constituent and amplitude, after this main constituent being deducted from input signal, estimate frequency and the amplitude of second main constituent, perform step B;

Step B, upgrade frequency and the amplitude of first main constituent conversely according to the frequency of second main constituent and amplitude;

Step C, judge whether the frequency of two main constituents is stablized, if perform step D, perform steps A if not;

Step D, stablize according to the frequency of two main constituents after the frequency of two Principal Component Estimation the 3rd main constituent and amplitude, upgrade frequency and the amplitude of second main constituent according to the frequency of first main constituent and the frequency of amplitude and the 3rd main constituent and amplitude, or upgrade frequency and the amplitude of first main constituent according to the frequency of second main constituent and the frequency of amplitude and the 3rd main constituent and amplitude;

Step e, signal is carried out in first main constituent, second main constituent and the 3rd main constituent merge the energy obtaining combined signal, judge whether the difference of the energy of this combined signal and the energy of input signal is more than or equal to and be greater than 1-δ, δ=10 ^-2, if so, then select the Doppler frequency as blood flow signal that three main constituent frequencies are maximum, perform steps A if not.

The frequency of estimation first main constituent described in steps A and amplitude, after this main constituent being deducted from input signal, estimate that the frequency of second main constituent and the detailed process of amplitude are:

Step one, initialization ultrasound echo signal x, this ultrasound echo signal comprises K main constituent, if K=1, by ultrasound echo signal x in formula (9) and (10), obtains the estimated value of the 1st characteristic component frequency with the estimated value of the amplitude of the 1st characteristic component perform step 2;

$\begin{array}{cc}{\hat{f}}_1=\arg & {\min }_f{\left|\right|[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x\left|\right|}^2\\ =\arg & {\min }_f{\left|p{\left(f\right)}^{H}x\right|}^2\end{array}---\left(9\right)$

${\widehat{\mathrm{\α}}}_1=\frac{p{\left(f\right)}^{H}x}{N}{|}_{f={\hat{f}}_1}---\left(10\right)$

Wherein, f is variable, and the span of this variable is [-fs/2, fs/2], and fs is sample frequency, and superscript H represents the conjugate transpose of vector;

Step 2, make K ₀=K ₀+ 1, according to the estimated value of the 1st the characteristic component frequency that step one obtains with the estimated value of the amplitude of the 1st characteristic component x is obtained according to formula (11) ₁,

$x_1=x-\underset{k=2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(11\right),$

Formula (12) and (13) is adopted to obtain the estimated value of the 2nd characteristic component frequency with the estimated value of the amplitude of the 2nd characteristic component according to estimated value with formula (14) is adopted to calculate x ₂,

$\begin{array}{cc}{\hat{f}}_2=\arg & \mathrm{mi}{n}_f{\left|\right|[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x_2\left|\right|}^2\\ =\arg & {\min }_f{\left|p{\left(f\right)}^H{x}_2\right|}^2\end{array}---\left(12\right)$

${\widehat{\mathrm{\α}}}_2=\frac{p{\left(f\right)}^H{x}_2}{N}{|}_{f={\hat{f}}_2}---\left(13\right)$

$x_2=x-\underset{k=1,k\≠2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(14\right).$

The detailed process of frequency and amplitude that the frequency according to second main constituent described in step B and amplitude upgrade first main constituent is conversely: according to the x obtained ₂obtained by formula (9) and (10) with

The detailed process whether frequency judging two main constituents described in step C is stable is: by estimated value with estimated value do difference, judge whether the absolute value of the difference obtained is less than or equal to 10 ^-3if the frequency being less than or equal to expression two main constituents is stablized, if the frequency being greater than expression two main constituents is unstable.

The present invention is different from the blood flow signal extracting method of imparametrization, and parameterized method does not need to design noise filter, but directly from ultrasound echo signal, extracts the Doppler frequency of blood flow signal.The present invention sets up a kind of affine model to input signal, and utilize relaxed algorithm estimation model parameter, improve estimation average and the estimate variance of the Doppler frequency of blood flow signal, thus reach the object of accuracy that improve blood flow signal and extract, compare popular parametric method (Multiple Signal Classification) clutter and blood flow signal energy Ratios under 40dB precision maximum lift 40%.

Accompanying drawing explanation

Fig. 1 is the method flow diagram that relaxed algorithm estimates affine model parameter;

Fig. 2 is that relaxed algorithm and parametric method are for estimating the comparative graph of the Doppler frequency of blood flow signal when C/S is 40dB; C represents clutter clutter; S represents blood flow signal Signal,

Fig. 3 is that relaxed algorithm and parametric method are for estimating the comparative graph of the Doppler frequency of blood flow signal when C/S is 20dB;

Fig. 4 is relaxed algorithm and the parametric method comparative graph of variance when C/S is 40dB for estimated result;

Fig. 5 is relaxed algorithm and the parametric method comparative graph of variance when C/S is 20dB for estimated result.

Detailed description of the invention

The colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention one, present embodiment is: adopt colorful ultrasonic detector to gather blood flow signal, Received signal strength end sets up affine model to the ultrasound echo signal received, adopt relaxed algorithm to estimate affine model parameter, obtain blood flow signal frequency and amplitude.

The colorful ultrasonic parametrization blood flow signal extracting method hypothesis input signal that present embodiment adopts is a mathematical model with unknown parameter, and these unknown parameters (such as frequency, intensity) are that the input signal received by reality by certain algorithm is obtained.The parameter that the Doppler frequency of final blood flow signal is estimated by these by suitable selection and obtaining.The advantage of parameterized method is: it not only can filtering clutter effectively, and can get rid of the interference of white noise, thus reduces the variance of Frequency Estimation, and the larger effect of variance is poorer.Therefore colorful ultrasonic parametrization blood flow signal extracting method for estimation blood flow velocity theoretical and in fact all there is advantage.

Colorful ultrasonic parametrization blood flow signal extracting method mainly based on following 2 considerations.The first, the model of signal is set up; The second, the parameter estimation of model.For the modeling of signal, a kind of mode is classical Zero pole distribution.Such as, autoregression model (Autoregressive, AR) is a kind of method being calculated the Doppler frequency of each main constituent by the full limit of analytic signal.In AR method, ultrasonic echo data is expressed the linear combination of the sampling of signal past and white noise for this reason.Weight parameter in model is then solved by Burg method or Yule-walker method.The high-strength characteristic of clutter do not considered by AR model, so when clutter energy is very surging, comparatively big error appears in the estimation of blood flow signal.Another widely used modeling pattern is characteristic component model, such as multiple signal classification method (Multiple signal classification, MUSIC).The method of MUSIC originates in the feature decomposition to input signal, and calculates model parameter by analysis of spectrum or extraction of root.Need the covariance of signal calculated in MUSIC, when the hits of input signal is less, computational accuracy is not high

The present invention sets up a kind of affine model to input signal, and utilizes relaxed algorithm estimation model parameter, and object is estimation average and the estimate variance of the Doppler frequency improving blood flow signal.

The difference of the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention two, present embodiment and detailed description of the invention one is, Received signal strength end to the detailed process that the ultrasound echo signal received sets up affine model is:

Using the ultrasound echo signal x of reception as affine model:

x≈Pα （1）

Wherein,

P is eigenmatrix:

P=[p(f ₁) p(f ₂) …p(f _k)… p(f _K)] （2），

The expression formula of ultrasound echo signal x:

x=[x(1) x(2) …x(n) …x(N)] ^T （3）

Wherein, k is the number of main constituent, k=1,2 ..., K, k and K are positive integer; X (1) represents first sampled value, and x (2) represents second sampled value, and x (n) represents the n-th sampled value, x (N) represents N number of sampled value, n=1,2 ... N, N represent signal length, n and N is natural number; P (f _k) represent the frequency vector of a kth main constituent.

P (f _k) expression formula be:

$p\left(f_k\right)={\left[\begin{array}{cccc}1& e^{j2\mathrm{\π}{f}_k}{e}^{j2\mathrm{\π}2f_k}& \·\·\·& e^{j2\mathrm{\π}(N-1)f_k}\end{array}\right]}^T---\left(4\right)$

The expression formula of oscillator intensity vector α is:

α=[α ₁ α ₂…α _k… α _K] （5）

Based on the affine model set up, the computational problem of the Doppler frequency of blood flow signal just transforms in order to a Parameter Estimation Problem.Namely exist european norm under, K parameter group parameter { f _k, α _k, k=1 ..., the estimated result of K} can be solved by following Optimized model, as

${\{{\hat{f}}_k,{\widehat{\mathrm{\α}}}_k\}}_{k=1}^K=\arg {\min }_{{\{f_k,{\mathrm{\α}}_k\}}_{k=1}^k}{\left|\right|x-\mathrm{P\α}\left|\right|}^2---\left(6\right)$

Wherein, || || representative european norm.

During the optimization problem described in solution formula (5), first do not consider the frequency of main constituent and concentrate consideration amplitude vecotr α.When namely supposing that P is known, obtain the least square solution of amplitude vecotr α,

$\widehat{\mathrm{\α}}={\left(P^{H}P\right)}^{-1}{P}^{H}x---\left(7\right)$

Then, utilization obtains amplitude vecotr α by following object function calculated rate vector f=[f ₁f ₂f _k] ^tas

${\left\{f_k\right\}}_{k=1}^K=\arg {\min }_{{\left\{f_k\right\}}_{k=1}^K}{\left|\right|(I-P{\left(P^{H}P\right)}^{-1}{P}^H)x\left|\right|}^2---\left(8\right)$

Wherein I is unit matrix.

Detailed description of the invention three, composition graphs 1 illustrate present embodiment, the difference of present embodiment and the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention one is, adopt relaxed algorithm to estimate affine model parameter, the detailed process obtaining blood flow signal frequency and amplitude is:

Steps A, the frequency estimating first main constituent and amplitude, after this main constituent being deducted from input signal, estimate frequency and the amplitude of second main constituent, perform step B;

Step B, upgrade frequency and the amplitude of first main constituent conversely according to the frequency of second main constituent and amplitude;

Step C, judge whether the frequency of two main constituents is stablized, if perform step D, perform steps A if not;

Step D, stablize according to the frequency of two main constituents after the frequency of two Principal Component Estimation the 3rd main constituent and amplitude, upgrade frequency and the amplitude of second main constituent according to the frequency of first main constituent and the frequency of amplitude and the 3rd main constituent and amplitude, or upgrade frequency and the amplitude of first main constituent according to the frequency of second main constituent and the frequency of amplitude and the 3rd main constituent and amplitude;

Step e, signal is carried out in first main constituent, second main constituent and the 3rd main constituent merge the energy obtaining combined signal, judge whether the difference of the energy of this combined signal and the energy of input signal is more than or equal to and be greater than 1-δ, δ=10 ^-2, if so, then select the Doppler frequency as blood flow signal that three main constituent frequencies are maximum, perform steps A if not.

The difference of the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention four, present embodiment and detailed description of the invention three is, the frequency of estimation first main constituent described in steps A and amplitude, after this main constituent being deducted from input signal, estimate that the frequency of second main constituent and the detailed process of amplitude are:

Step one, initialization ultrasound echo signal x, this ultrasound echo signal comprises K main constituent, if K=1, by ultrasound echo signal x in formula (9) and (10), obtains the estimated value of the 1st characteristic component frequency with the estimated value of the amplitude of the 1st characteristic component perform step 2;

$\begin{array}{cc}{\hat{f}}_1=\arg & {\min }_f{\left|\right|[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x\left|\right|}^2\\ =\arg & {\min }_f{\left|p{\left(f\right)}^{H}x\right|}^2\end{array}---\left(9\right)$

${\widehat{\mathrm{\α}}}_1=\frac{p{\left(f\right)}^{H}x}{N}{|}_{f={\hat{f}}_1}---\left(10\right)$

Wherein, f is variable, and the span of this variable is [-fs/2, fs/2], and fs is sample frequency, and superscript H represents the conjugate transpose of vector; for cyclic spectrum function | p (f) ^hx| ²the abscissa value that in all peak values of/N, peak-peak is corresponding; And can by cyclic spectrum function p (f) ^hin all peak values of x/N, the highest peak value calculates.

Step 2, make K ₀=K ₀+ 1, according to the estimated value of the 1st the characteristic component frequency that step one obtains with the estimated value of the amplitude of the 1st characteristic component x is obtained according to formula (11) ₁,

$x_1=x-\underset{k=2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(11\right),$

Formula (12) and (13) is adopted to obtain the estimated value of the 2nd characteristic component frequency with the estimated value of the amplitude of the 2nd characteristic component according to estimated value with formula (14) is adopted to calculate x ₂,

$\begin{array}{cc}{\hat{f}}_2=\arg & \mathrm{mi}{n}_f{\left|\right|[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x_2\left|\right|}^2\\ =\arg & {\min }_f{\left|p{\left(f\right)}^H{x}_2\right|}^2\end{array}---\left(12\right)$

${\widehat{\mathrm{\α}}}_2=\frac{p{\left(f\right)}^H{x}_2}{N}{|}_{f={\hat{f}}_2}---\left(13\right)$

$x_2=x-\underset{k=1,k\≠2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(14\right).$

Known in the present embodiment

The difference of the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention five, present embodiment and detailed description of the invention three is, the detailed process of frequency and amplitude that the frequency according to second main constituent described in step B and amplitude upgrade first main constituent is conversely: according to the x obtained ₂obtained by formula (9) and (10) with

The difference of the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm described in detailed description of the invention six, present embodiment and detailed description of the invention three is, the detailed process whether frequency judging two main constituents described in step C is stable is: by estimated value with estimated value do difference, judge whether the absolute value of the difference obtained is less than or equal to 10 ^-3if the frequency being less than or equal to expression two main constituents is stablized, if the frequency being greater than expression two main constituents is unstable.

Concrete example:

Utilize Doppler to cover the simulate signal of synthesis, wherein clutter composition has the characteristic of rather low-frequency, but the energy of signal is better than blood flow signal and thermal noise far away.Blood flow signal has the characteristic of relative high frequency, although the energy of signal is starkly lower than clutter composition, but is better than thermal noise.Noise is the low-yield composition of a Whole frequency band, can represent in emulation with white Gaussian noise.

In order to verify the extensive adaptability of proposed method, fixing some parameters in emulation, and allowing it change for interested especially parameter.Table 1 lists the parameter and their numerical value that emulate and use.Table 1 represents experiment parameter.

Table 1

In emulation and in discussing, the ultimate unit of all numerical value relevant with frequency is orientated as impulse ejection frequency (Pulse repetition frequency, PRF) by mark.In emulation, the mid frequency of clutter is 0.1PRF.And blood flow mid frequency changes from 0.05PRF to 0.5PRF, be spaced apart 0.025PRF.For meeting ultra sonic imaging requirement of real-time, its clutter filtration result respectively under 16 pulse periods of all tests.In addition, for eliminating systematic error, to each group simulation parameter, 1024 emulation is carried out.

The present invention and popular two kinds of parameterized blood flow signal methods of estimation: second-order autoregressive model and the second order multiple signal classification based on extraction of root compare, and result is shown in Fig. 2 to Fig. 5.Can find, the present invention shows estimated result accurately under the Doppler of blood flow signal is lower than all situations of 0.45PRF.

This is because first relaxed algorithm estimates signal frequency from input signal, because noise intensity is very large, this signal frequency is approximately clutter mid frequency; Then, the Doppler frequency of blood flow signal is estimated from residual signal, described in algorithm steps A as described.And the blood flow signal parameter estimated is applied to the parameter upgrading clutter composition conversely, as shown in stepb.This process is repeated, until the Doppler frequency of blood flow signal and clutter keeps stable, i.e. between the double estimated value of step C demand, gap is lower than 10 ^-3pRF.That now calculate the clutter of estimation and blood flow signal with signal and input signal energy Ratios, due to the existence of white noise, now proceed to the parameter of estimation the 3rd main constituent, namely return step 2.Step before repetition, until the frequency of three main constituents is stablized, as shown in Step D.Finally, as described in step e, Doppler frequency corresponding to the second largest main constituent of selection intensity parameter is that the Doppler frequency of blood flow signal exports.

From foregoing, accurately estimate that the parameter of clutter will comprise less clutter composition by causing in residual signal, thus improve the Parameter Estimation Precision of blood flow signal.Conversely, estimate that the parameter of blood flow signal will promote clutter Parameter Estimation Precision exactly.These two kinds of advantages are superposed repeatedly until the parameter estimated tends towards stability.Final result shows, the method for parameter estimation of this antithesis of the present invention achieves the accurate estimation of clutter and blood flow signal parameter simultaneously, especially, when the Doppler frequency of blood flow signal and clutter composition mid frequency relatively close to time, estimation effect of the present invention is obviously better than other two kinds parameterized blood flow signal extracting method.

Claims (5)

1., based on the colorful ultrasonic parametrization blood flow signal extracting method of relaxed algorithm, adopt colorful ultrasonic detector to gather blood flow signal, and be emitted to Received signal strength end; Received signal strength end sets up affine model to the ultrasound echo signal received, and adopts relaxed algorithm to estimate affine model parameter, obtains blood flow signal frequency and amplitude;

It is characterized in that: Received signal strength end to the detailed process that the ultrasound echo signal received sets up affine model is:

Using the ultrasound echo signal x of reception as affine model:

x≈Pα (1)

Wherein, α is oscillator intensity vector,

P is eigenmatrix:

P＝[p(f ₁)p(f ₂)…p(f _k)…p(f _K)] (2)，

The expression formula of ultrasound echo signal x:

x＝[x(1)x(2)…x(n)…x(N)] ^T (3)

Wherein, k is the number of main constituent, k=1,2 ..., K, k and K are positive integer; X (1) represents first sampled value, and x (2) represents second sampled value, and x (n) represents the n-th sampled value, and x (N) represents N number of sampled value, n=1,2 ..., N, n and N are natural number; p (f _k) represent the frequency vector of a kth main constituent.

2. the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm according to claim 1, is characterized in that: adopt relaxed algorithm to estimate affine model parameter, the detailed process obtaining blood flow signal frequency and amplitude is:

Steps A, the frequency estimating first main constituent and amplitude, after described first main constituent being deducted from input signal, estimate frequency and the amplitude of second main constituent, perform step B;

Step B, upgrade frequency and the amplitude of first main constituent conversely according to the frequency of second main constituent and amplitude;

Step C, judge whether the frequency of two main constituents is stablized, if perform step D, perform steps A if not;

Step D, stablize according to the frequency of two main constituents after the frequency of two Principal Component Estimation the 3rd main constituent and amplitude, upgrade frequency and the amplitude of second main constituent according to the frequency of first main constituent and the frequency of amplitude and the 3rd main constituent and amplitude, or upgrade frequency and the amplitude of first main constituent according to the frequency of second main constituent and the frequency of amplitude and the 3rd main constituent and amplitude;

Step e, signal is carried out in first main constituent, second main constituent and the 3rd main constituent merge the energy obtaining combined signal, judge whether the difference of the energy of this combined signal and the energy of input signal is more than or equal to and be greater than 1-δ, δ=10 ^-2, if so, then select the Doppler frequency as blood flow signal that three main constituent frequencies are maximum, perform steps A if not.

3. the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm according to claim 2, it is characterized in that: the frequency of estimation first main constituent described in steps A and amplitude, after described first main constituent being deducted from input signal, estimate that the frequency of second main constituent and the detailed process of amplitude are:

Step one, initialization ultrasound echo signal x, this ultrasound echo signal comprises K main constituent, if K=1, by ultrasound echo signal x in formula (9) and (10), obtains the estimated value of the 1st characteristic component frequency with the estimated value of the amplitude of the 1st characteristic component perform step 2;

$\begin{array}{c}{\hat{f}}_1=\arg \min \left|\right|_f[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x{\left|\right|}^2\\ =\arg \min |p{\left(f\right)}^{H}x{|}^2_f\end{array}---\left(9\right)$

${\widehat{\mathrm{\α}}}_1=\frac{p{\left(f\right)}^{H}x}{N}{|}_{f={\hat{f}}_1}---\left(10\right)$

Wherein, f is variable, and the span of this variable is [-fs/2, fs/2], and fs is sample frequency, and superscript H represents the conjugate transpose of vector;

Step 2, make K ₀=K ₀+ 1, according to the estimated value of the 1st the characteristic component frequency that step one obtains with the estimated value of the amplitude of the 1st characteristic component x is obtained according to formula (11) ₁,

$x_1=x-\underset{k=2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(11\right),$

Formula (12) and (13) is adopted to obtain the estimated value of the 2nd characteristic component frequency with the estimated value of the amplitude of the 2nd characteristic component according to estimated value with formula (14) is adopted to calculate x ₂,

$\begin{array}{c}{\hat{f}}_2=\arg \min \left|\right|_f[I-\frac{p\left(f\right)p{\left(f\right)}^H}{N}]x_1{\left|\right|}^2\\ =\arg \min |p{\left(f\right)}^H{x}_1{|}^2_f\end{array}---\left(12\right)$

${\widehat{\mathrm{\α}}}_2=\frac{p{\left(f\right)}^H{x}_1}{N}{|}_{f={\hat{f}}_2}---\left(13\right)$

$x_2=x-\underset{k=1,k\≠2}{\overset{K}{\mathrm{\Σ}}}{\widehat{\mathrm{\α}}}_{k}p\left({\hat{f}}_k\right)---\left(14\right).$

4. the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm according to claim 3, is characterized in that: the detailed process of frequency and amplitude that the frequency according to second main constituent described in step B and amplitude upgrade first main constituent is conversely: according to the x obtained ₂obtained by formula (9) and (10) with

5. the colorful ultrasonic parametrization blood flow signal extracting method based on relaxed algorithm according to claim 3, is characterized in that: the detailed process whether frequency judging two main constituents described in step C is stable is: by estimated value with estimated value do difference, judge whether the absolute value of the difference obtained is less than or equal to 10 ^-3if the frequency being less than or equal to expression two main constituents is stablized, if the frequency being greater than expression two main constituents is unstable.