CN103267800A - Ultrasound fast imaging and dynamic size distribution estimation method of cavitation microbubbles with high signal-to-noise ratio - Google Patents

Abstract

The invention provides a cavitation micro-bubble high signal-to-noise ratio ultrasonic rapidly imaging and dynamic dimension distribution estimating method, comprising: (1) building a cavitation micro bubble wavelet under a static state starting condition; (2) acquiring information of backscatter Intensity change along time in a solution and in a source energy irradiation volume by a full-digitization ultrasonic two dimension planar-array energy transducer and by a plane wave emission and reception manner, and carrying out micro bubble wavelet transformation on it to raise cavitation micro bubble imaging signal-to-noise ratio; (3) acquiring a radius of micro bubble with a maximum number in a cavitation micro bubble group; (4) dividing a cavitation micro bubble area into sub-areas with a same size, to obtain brightness corresponding to the micro bubble with the maximum number in each sub-area, thereby obtaining dimension distribution of the whole cavitation micro bubble group; and (5) obtaining volume distribution of cavitation micro bubble dimensions under a flow state. The method of the invention carries out cavitation micro bubble wavelet transformation, obtains signal-to-noise ratio enhanced cavitation micro bubble images, and simultaneously, completely dynamic estimation on the cavitation micro bubble dimensions.

Description

The ultrasonic fast imaging of cavitation microvesicle high s/n ratio and dynamic dimension distribution estimation method

Technical field

The invention belongs to the detection of acoustic technical field, particularly a kind of ultrasonic fast imaging of cavitation microvesicle high s/n ratio and dynamic dimension distribution estimation method.

Background technology

Cavitation refers to the cavitation nucleus in the liquid, and the vibration that shows under some energy (as ultrasonic, microwave, laser etc.) effect, expansion, contraction are so that a series of dynamic processes such as implosions.Cavitation corrosion, noise, vibration and luminescence phenomenon that the liquid hollow bubble can produce when crumbling and fall.Cavitation corrosion effect meeting reduces mechanical efficiency, and in biomedicine, phonochemistry etc. are used, also can bring into play the advantage of cavitation.

The size of cavitation microvesicle is regarded as one of important parameter of weighing the cavitation reaction field.Therefore, the size of research cavitation microvesicle has very significant values in the cavitation fundamental research.It is determined that yet the chaos of cavitation processes has caused cavitation microvesicle size to be difficult to.The existing Chinese scholars that studies show that has been studied the method for estimation of cavitation microvesicle size mostly by methods such as optical means and sonoluminescences, but these method hardware operations require than higher, and can not carry out dynamic measurement, fundamentally limited the dynamic measurement of cavitation microvesicle group's Size Distribution.

Summary of the invention

In order to overcome the defective of above-mentioned prior art, the object of the present invention is to provide a kind of ultrasonic fast imaging of cavitation microvesicle high s/n ratio and dynamic dimension distribution estimation method, after liquid generation cavitation produces the cavitation microvesicle, different initial radiums according to the default cavitation microvesicle group who produces, make up cavitation microvesicle wavelet, thereby improve cavitation microbubbles scatter echo strength, dynamically realize the estimation of microvesicle group size.

In order to achieve the above object, technical scheme of the present invention is:

The ultrasonic fast imaging of cavitation microvesicle high s/n ratio and dynamic dimension distribution estimation method may further comprise the steps:

Step 1, cavitation microvesicle wavelet make up:

When the synergy of source energy or these energy acts in certain solution with certain intensity certain hour and near the cavitation microvesicle group who produces its concentration of energy zone is free vibration and does not have coating, according to following steps structure cavitation microvesicle wavelet:

(1) receives detection transducer acoustic field pressure waveform with nautical receiving set;

(2) the RPNNP model of the not coating microvesicle of employing free vibration, the preset model parameter changes static initial radium, finds the solution the differential equation;

(3) result who finds the solution the differential equation is the radius-time curve of microvesicle, and it is carried out differential again, obtains prediction echo-time curve;

(4) prediction echo-time curve is carried out the filtering normalized, obtain cavitation microvesicle wavelet;

That described source energy comprises is ultrasonic, microwave, laser;

Step 2, based on the cavitation microvesicle high s/n ratio imaging of cavitation microvesicle wavelet transform:

Extract the rf data on each the bar sweep trace after wave beam synthesizes, cavitation microvesicle backscattering echoed signal just, choose cavitation microvesicle wavelet and yardstick, it is carried out continuous wavelet transform, obtain the wavelet conversion coefficient of two dimension, the wavelet coefficient of choosing the yardstick at maximal value place in the wavelet conversion coefficient is signal as an alternative, and finally shows the image that signal to noise ratio (S/N ratio) strengthens;

Step 3, based on the maximum cavitation microvesicle of the number number percent of many sizes cavitation microvesicle wavelet transform radius method of estimation:

By the static initial radium of default different cavitation microvesicles, obtain the prediction echo waveform under the different initial radium conditions, as cavitation microvesicle wavelet the time dependent cavitation microvesicle backscatter signals of gathering is carried out cavitation microvesicle wavelet transform with it, obtain the backscatter intensity information that the signal to noise ratio (S/N ratio) of corresponding different static initial radiums strengthens, and then acquisition signal to noise ratio (S/N ratio)-static initial radium curve, the radius that from this moment of this curve acquisition cavitation microvesicle group, has for the maximum microvesicle of cavitation microvesicle backscatter signals contribution, cavitation microvesicle under this radius mainly comes from two aspects for the contribution of backscattering echoed signal, one is its number, another one is the scattering cross-sectional area of this cavitation microvesicle, when cavitation microvesicle group's Size Distribution is narrow and when departing from the natural frequency that detects transducer, scattering cross-sectional area difference can be ignored, at this time has only the influence of microvesicle number, under this condition, think this radius that constantly the maximum cavitation microvesicle of number has among the cavitation microvesicle group;

Adopt above method, can obtain the maximum corresponding radius of microvesicle of number among each moment cavitation microvesicle group on the time series, also can think cavitation microvesicle group's radius because dissipate along with the radius of time change;

Step 4, estimate based on the whole audience microvesicle Size Distribution of the maximum cavitation microvesicle of number number percent in subregion radius:

Cavitation zone is divided into the zonule of several sizes such as grade, according to the method in the step 3, obtains the radius of the microvesicle that number is maximum in each subregion, for each cavitation microvesicle,P wherein_iBe the incident sound pressure of irradiation on single microvesicle, p_sBe single microvesicle backscattering acoustic pressure, z is this microvesicle and the distance that detects transducer face, and σ is the scattering cross-sectional area, and the number of the cavitation microvesicle in each subregion is fewer, and overall backscattering echo then can be expressed as

σ_kCorresponding to the corresponding scattering cross-sectional area of the cavitation microvesicle of different radii, for different cavitation microvesicles, its surperficial incident sound pressure is consistent, the Size Distribution scope of the cavitation microvesicle in the little subregion is narrower and small, can think what single size distributed, in this case, the cavitation microvesicle backscattering echoed signal of each subregion the inside can be expressed as:

Number and the scattering cross-sectional area of the cavitation microvesicle of the main and single size of the scatter echo intensity of the cavitation microvesicle of each subregion the inside have relation as can be seen, introduce the resonance shift coefficient again, equal to predict the inverse of echo strength-radius curve on the numerical value, at this moment, cavitation microbubbles scatter echo strength just only has relation with the number of cavitation microvesicle; The cavitation microvesicle number-radius curve of all little subregions is weighted the data of the microvesicle of all subregions after the demonstration, obtains the dynamic estimation of cavitation microvesicle group's Size Distribution;

Cavitation microvesicle size face distributes and body distribution estimation under step 5, the flow state:

1) for the dynamic estimation of the cavitation microvesicle of flow duct, the source energy when producing the cavitation microvesicle and afterwards, the cavitation microvesicle is along with surrounding liquid takes place to flow, adopt the method for step 3-step 4, can obtain the radius of the maximum microvesicle of number among a certain moment cavitation microvesicle group and the Size Distribution situation of the microvesicle among the whole cavitation microvesicle group;

2) because each corresponding tangent plane of cavitation microvesicle group constantly, the face that namely can obtain the cavitation microvesicle distributes, and can obtain continuous tangent plane information under flow state, just can obtain the body distribution all tangent plane information is finished after.

The present invention proposes a kind of new cavitation microvesicle group's Acoustic detection mode, and dynamic dimension distributes and carries out estimation approach when improving its imaging signal to noise ratio (S/N ratio) again.By being structured on waveform and the spectral characteristic all as far as possible the female small echo near cavitation microvesicle backscatter signals, the cavitation microvesicle group's that plane wave transmission and reception pattern monitor source energy is produced in solution backscatter intensity conversion in time, carry out cavitation microvesicle wavelet transform, obtain the cavitation microvesicle image that signal to noise ratio (S/N ratio) strengthens, finish the dynamic estimation to cavitation microvesicle size simultaneously.

Description of drawings

Fig. 1 is the system chart that obtains cavitation microvesicle group backscatter intensity in the system of the present invention.

Fig. 2 is the sequential control figure that obtains cavitation microvesicle group backscatter intensity of system of the present invention.

Fig. 3 be to cavitation microvesicle on the single scan line dorsad signal carry out the process flow diagram of cavitation microvesicle wavelet transform.

Fig. 4 is cavitation microvesicle wavelet transform and the process flow diagram that shows image.

Fig. 5 is the process flow diagram that the microvesicle of number number percent maximum among a certain moment cavitation microvesicle group is carried out size estimation stream.

Fig. 6 is the process flow diagram that a certain moment cavitation microvesicle group Size Distribution is estimated.

Embodiment

Below in conjunction with the drawings and specific embodiments the present invention is further described in detail.

The ultrasonic fast imaging of cavitation microvesicle high s/n ratio and dynamic dimension distribution estimation method may further comprise the steps:

Step 1, cavitation microvesicle wavelet make up:

When the synergy of source energy or these energy acts in certain solution with certain intensity certain hour and near the cavitation microvesicle group who produces its concentration of energy zone is free vibration and does not have coating, according to following steps structure cavitation microvesicle wavelet:

(1) receives detection transducer acoustic field pressure waveform with nautical receiving set;

(2) the RPNNP model of the not coating microvesicle of employing free vibration, the preset model parameter changes static initial radium, finds the solution the differential equation;

(3) result who finds the solution the differential equation is the radius-time curve of microvesicle, and it is carried out differential again, can obtain to predict echo-time curve;

(4) prediction echo-time curve is carried out the filtering normalized, obtain cavitation microvesicle wavelet.

That described source energy comprises is ultrasonic, microwave, laser.

The vibration characteristics of single microvesicle under the sound field excitation obtained broad research, has strict theory model that the dynamics of microvesicle is described.According to model of vibration and the hypothesis of various microvesicles, can obtain simulating the nonlinear ordinary differential equation of the gas-film-liquid system of single ultrasonic contrast microvesicle, find the solution these ordinary differential equations, just can predict the vibration of microvesicle, thereby estimate the echo of microvesicle.This means that we can know the echoing characteristics of microvesicle under the sound field excitation in advance by theoretical model, and and then the suitable cavitation microvesicle wavelet of structure.Up to now, there is the theoretical model based on the RPNNP equation of various ways to describe the vibration behavior of microvesicle under the sound field excitation.

The present invention adopts the RPNNP model of the no coating air micro-bubbles of free vibration, is R for static radius_oSingle free bubble, be in volume ratio microvesicle volume far away in the big liquid medium, fluid density is ρ, the density of gas in the microvesicle, the surface tension of gas and liquid contact surface is σ, the vapour pressure in the bubble is P_VAnd the vapour pressure in the microvesicle is constant all the time in vibration processes, and the coefficient of viscosity of liquid is η, and the static pressure of liquid is P_oThe residing excitation sound field of microvesicle pressure is P (t), the vibrated process keeps spherical and formless change always, distribution of gas is even in the bubble, gas content is constant, and be ideal gas, think that microvesicle can infinitely compress, radius in the vibration processes of bubble is less than wave length of sound (R＜λ), disregard the body viscous effect of microvesicle, liquid is incompressible or compressibility is very little, and the speed of microvesicle wall in vibration processes is far smaller than sound's velocity in liquid, and the radius in microvesicle vibration this moment is that the second differential equation of time is

$R\stackrel{\·\·}{R}+\frac{3{\stackrel{\·}{R}}^2}{2}=\frac{1}{\mathrm{\ρ}}\{(P_o+\frac{2\mathrm{\σ}}{R_o}-P_V){\left(\frac{R_o}{R}\right)}^{3\mathrm{\γ}}+P_V-\frac{2\mathrm{\σ}}{R}-P_o-P\left(t\right)-\frac{4\mathrm{\η}\stackrel{\·}{R}}{R}\}$

Separate this differential equation, can obtain microvesicle vibration radius curve and radial vibration speed and acceleration over time.When the distance between receiving transducer and the microvesicle is r, can obtain microvesicle backscattering echo:

$P={\mathrm{\ρr}}^{-1}(R^2\stackrel{\·\·}{R}+{\stackrel{\·}{R}}^2)$

When outside sound field incentive condition was known, by different microvesicle parameter and signal parameter are set, we can obtain the microbubble echoes signal under the corresponding conditions.But when the phenomenon of caving in of microvesicle can't be ignored, this method needed careful consideration.In theory, numerical solution RPNNP equation the computing limit can not occur, does not detect the microvesicle phenomenon of caving in advance, makes prediction waveform and experimental result grave fault to cause the small wave converting method inefficacy.Therefore, for fear of the phenomenon of caving in, in experiment, must carefully select to add the pressure of sound field, refer to remain on below the stressed threshold value of microvesicle.In fact, the stability of microvesicle corresponding reducing of microvesicle diameter and sharply reducing.In the middle of actual use, because the diffusion of the static state of microvesicle and sound-driving diffusion, the cavitation microvesicle survival time is very short, greater than a hundreds of microsecond is arranged.Consider based on this point, more will note the control of acoustic pressure in transmission.

Obtain suitable cavitation microvesicle wavelet, on the theory, best bet is exactly directly to catch the echoed signal of single microvesicle in sound field.But in fact, consider the operability of direct measurement, we can obtain suitable cavitation microvesicle wavelet by method of emulation.The parameter condition of cavitation microvesicle and the characteristic of excitation sound field known in preceding summary.Specifically comprise the static initial radium of microvesicle, drive acoustic pressure, transponder pulse centre frequency, transponder pulse number, initial phase etc.And in the present invention, because we adopt is that system's B ultrasonic is finished, the exomonental information of device is fixed, and therefore only needs to consider the static radius of microvesicle and drives acoustic pressure.When this incentive condition of driving acoustic pressure does not quantize not obtain, need experiment obtain to encourage the acoustic pressure waveform.Use nautical receiving set to detect the waveform of external drive sound field.

Step 2, based on the cavitation microvesicle high s/n ratio imaging of cavitation microvesicle wavelet transform:

Extract the rf data on each the bar sweep trace after wave beam synthesizes, cavitation microvesicle backscattering echoed signal just, choose cavitation microvesicle wavelet and yardstick, it is carried out continuous wavelet transform, obtain the wavelet conversion coefficient of two dimension, the wavelet coefficient of choosing the yardstick at maximal value place in the wavelet conversion coefficient is signal as an alternative, and finally shows the image that signal to noise ratio (S/N ratio) strengthens;

When obtaining single microbubble echoes signal, next step constructs cavitation microvesicle wavelet exactly.Carry out normalized after earlier this echo acoustic pressure waveform being preserved.Secondly, because directly the echo sound pressure signal of Huo Deing generally speaking sampling rate than higher, if make cavitation microvesicle wavelet, needs reduction sampling rate.At last, choosing suitable echo length then is the needed cavitation microvesicle of imaging wavelet.In theory, for no microvesicle condition harmony field condition, cavitation microvesicle wavelet difference.Clearly, cavitation microvesicle wavelet does not satisfy the admissibility condition, and this names a person for a particular job and explains in ensuing single sweep imaging technique is handled.

After cavitation microvesicle wavelet structure is finished, just can handle cavitation microbubbles scatter echo.Respectively the rf data that obtains being carried out synthetic every the sweep trace afterwards of wave number handles.Accompanying drawing 3 has shown the small echo treatment technology at single scan line.At first, determine cavitation microvesicle wavelet after, choose suitable yardstick.Rf data to every sweep trace carries out the small echo correlation analysis, obtains the small echo related coefficient.Then, all wavelet coefficients of choosing small echo related coefficient maximal value place yardstick replace original radio frequency signal.At last, carry out imaging.By imaging technique as can be seen, original radiofrequency signal is characterized by the small echo related coefficient, carries out subsequent treatment then.That is to say us only to carry out the decomposition of signal and do not carry out the reconstruct of signal.Like this, even cavitation microvesicle wavelet does not satisfy the admissibility condition, still can carry out imaging processing.Because the resulting small echo related coefficient of conversion has represented the energy of original signal to a certain extent.

Step 3, estimate based on the maximum cavitation microvesicle of the number number percent of many sizes cavitation microvesicle wavelet transform radius:

By the static initial radium of default different cavitation microvesicles, obtain the prediction echo waveform under the different initial radium conditions, as cavitation microvesicle wavelet the time dependent cavitation microvesicle backscatter signals of gathering is carried out cavitation microvesicle wavelet transform with it, can obtain the backscatter intensity information that the signal to noise ratio (S/N ratio) of corresponding different static initial radiums strengthens, and then can obtain signal to noise ratio (S/N ratio)-static initial radium curve, from this curve, can obtain the radius that this constantly has for the maximum microvesicle of cavitation microvesicle backscatter signals contribution the cavitation microvesicle group, cavitation microvesicle under this radius mainly comes from two aspects for the contribution of backscattering echoed signal, one is its number, another one is to be exactly the scattering cross-sectional area of this cavitation microvesicle, when cavitation microvesicle group's Size Distribution is narrow and when departing from the natural frequency that detects transducer, scattering cross-sectional area difference can be ignored, at this time has only the influence of microvesicle number, under this condition, we can think this radius that constantly the maximum cavitation microvesicle of number has among the cavitation microvesicle group, adopt above method, can obtain the maximum corresponding radius of microvesicle of number among each moment cavitation microvesicle group on the time series, also can think cavitation microvesicle group's radius because dissipate along with the radius of time change;

Step 4, estimate based on the whole audience microvesicle Size Distribution of the maximum cavitation microvesicle of number number percent in subregion radius:

Cavitation zone reasonably is divided into the zonule of several sizes such as grade, according to the method in the step 3, obtains the radius of the microvesicle that number is maximum in each subregion, for each cavitation microvesicle,

P wherein_iBe the incident sound pressure of irradiation on single microvesicle, p_sBe single microvesicle backscattering acoustic pressure, z is this microvesicle and the distance that detects transducer face, and σ is the scattering cross-sectional area, and the number of the cavitation microvesicle in each subregion is fewer, and overall backscattering echo then can be expressed as

σ_kCorresponding to the corresponding scattering cross-sectional area of the cavitation microvesicle of different radii, for different cavitation microvesicles, its surperficial incident sound pressure is consistent, the Size Distribution scope of the cavitation microvesicle in the little subregion is narrower and small, can think what single size distributed, in this case, the cavitation microvesicle backscattering echoed signal of each subregion the inside can be expressed as:

Number and the scattering cross-sectional area of the cavitation microvesicle of the main and single size of the scatter echo intensity of the cavitation microvesicle of each subregion the inside have relation as can be seen, introduce the resonance shift coefficient again, equal to predict the inverse of echo strength-radius curve on the numerical value, at this moment, cavitation microbubbles scatter echo strength just only has relation with the number of cavitation microvesicle.The cavitation microvesicle number-radius curve of all little subregions is weighted the data of the microvesicle of all subregions after the demonstration, obtains the dynamic estimation of cavitation microvesicle group's Size Distribution;

Cavitation microvesicle size face distributes and the body distribution estimation method under step 5, the flow state:

(1) for the dynamic estimation of the cavitation microvesicle in flow duct such as the blood vessel, the source energy when producing the cavitation microvesicle and afterwards, the cavitation microvesicle is along with surrounding liquid takes place to flow, adopt the method for step 3-step 4, can obtain the radius of the maximum microvesicle of number among a certain moment cavitation microvesicle group and the Size Distribution situation of the microvesicle among the whole cavitation microvesicle group;

(2) because each corresponding tangent plane of cavitation microvesicle group constantly, the face that namely can obtain the cavitation microvesicle distributes, and can obtain continuous tangent plane information under flow state, just can obtain the body distribution all tangent plane information is finished after.

Accompanying drawing 1 has shown the device that obtains cavitation microvesicle group's backscatter intensity among the present invention.When the synergy of certain provenance energy (as ultrasonic, microwave, laser etc.) or these energy acts in certain solution and after producing cavitation microvesicle group near its concentration of energy zone with certain intensity certain hour, fail immediately, the inertia of back power and the influence that the cavitation microvesicle is subjected to buoyancy because the source energy disappears, this microvesicle group is that space-time is fast-changing.Meanwhile at once by the detection transducer on the ultrasonic platform of synchronization call total digitalization, comprise single array element transducer or one dimensional linear array transducer or two-dimensional array transducer, make it obtain in the solution near the microvesicle group's of volume generation the time dependent information of the backscatter intensity burnt territory of source transducer according to plane wave emission receive mode.Therefore the present invention not only adopts the one dimensional linear array that extensively comes into operation on single array element transducer or the current diagnosis Ultrasound Instrument, more comprised the two-dimensional array transducer, the advantage of the more conventional one-dimensional array transducer of this transducer is to obtain the interior cavitation microvesicle group information of spatial volume, rather than a certain cross section is the cavitation microvesicle information in the conventional one-dimensional array transducer imaging plane.The setting of two-dimensional array transducer is in the plane wave transmission and reception pattern, it is non-focusing broad beam transmission and reception pattern, can after once emission receives, obtain the information of cavitation microvesicle group in the whole monitored volume, need not as in the super imaging of traditional B by obtaining object information in the whole guarded region by line sweep, and the latter reaches many irradiation simultaneously to whole microvesicle group's monitoring right and wrong.Simultaneously, such system and device also is to be applicable to that the fluid pump drives current downflow medium cavitation microvesicle group's the obtaining of backscattering echoed signal.

Accompanying drawing 2 has shown the sequential control of obtaining cavitation microvesicle group backscatter intensity among the present invention.At first, the two-dimensional array of diagnostic ultrasound instrument is gathered the background reference signal in the solution of crossing without the source energy irradiation earlier.Secondly, the source energy carries out radiation with the certain energy of certain hour to solution, produces the cavitation microvesicle in the concentration of energy zone.At last, the two-dimensional array transducer of diagnostic ultrasound instrument begins cavitation microvesicle group is carried out integral monitoring after the source energy fails at once.The monitoring of diasonograph spatially comprises the microvesicle group of whole spatial variations, contains cavitation microvesicle group's whole evanishment in time, namely from the source energy fail to the microvesicle group solution, dissipate finish till.

Accompanying drawing 4 has shown the process flow diagram of whole cavitation signal cavitation microvesicle wavelet transform.For the signal on each bar scan synthesis line, adopt the process flow diagram shown in the accompanying drawing 3 to finish.This technology comprises four modules.It at first is the rf data acquisition module.Next is cavitation microvesicle wavelet constructing module.As previously mentioned, comprise three kinds of situations: directly catch single bubble echoed signal, experiment records external drive acoustic pressure waveform and emulation obtains single bubble echoed signal, and parameter and emulation that external drive acoustic pressure waveform is set obtain single bubble echoed signal.Be signal processing module again.Be display module as a result at last.Display module refers to that mainly image shows as a result.It is exactly the subsequent treatment of radiofrequency signal in fact that image shows.Mainly comprise coordinate transform and gradation conversion.Obtain cavitation microvesicle wavelet transform image afterwards at last.

Accompanying drawing 5 has shown the process flow diagram of the size that the maximum microvesicle of number has among the synchronization cavitation microvesicle group, and this distribution is on the space also to be temporal.In fact, many Size Distribution during the cavitation microvesicle.We can obtain the cavitation microvesicle wavelet under the different static initial radiums, and the cavitation microbubbles scatter echo of synchronization is handled, and obtain the image under the correspondingly-sized.By the calculating to signal noise ratio (snr) of image, obtain signal to noise ratio (S/N ratio)-static initial radium curve.Therefrom as can be seen this constantly in to the size of the maximum microvesicle of cavitation microvesicle group backscattering echoed signal contribution.Mainly with two relating to parameters, one is the number of microvesicle, and another one is the degree of microvesicle deviation resonance in detecting transducer acoustic field.For the arrowband distribute and the cavitation microvesicle group of deviation resonance for, the degree of its microvesicle deviation resonance in detecting transducer acoustic field is negligible, can obtain the size that number is maximum among the cavitation microvesicle group microvesicle has like this.With above algorithm application to the time sequence, then can obtain size in the cavitation microvesicle evanishment variation.

Accompanying drawing 6 has shown the process flow diagram of synchronization cavitation microvesicle group Size Distribution.Cavitation microvesicle zone is divided into the subregion that several equate, the fine degree of division can reach hypothesis in this subregion, and the number of microvesicle is few, and the distribution range of microvesicle is narrow, can think what single size distributed.By the portrayal to the signal to noise ratio (S/N ratio)-static initial radium curve of each subregion, extract the size for the maximum microvesicle of cavitation microvesicle backscattering echoed signal contribution in this subregion.Cavitation microvesicle in each subregion is that single size distributes, and can revise the degree of the cavitation microvesicle deviation resonance of each subregion, becomes the resonance coefficient of deviation.After by the resonant frequency coefficient brightness of each subregion being proofreaied and correct, the number of microvesicle in this subregion can be obtained, the size of the corresponding number of respective radius in each subregion can be obtained.The data of the microvesicle of all subregions are weighted after the demonstration, obtain the dynamic estimation of cavitation microvesicle group's Size Distribution.Above algorithm application to the time sequence, then can be obtained the variation of Size Distribution in the cavitation microvesicle evanishment.

The invention has the advantages that the vibration characteristics of cavitation microvesicle the Ultrasonic Detection transducer acoustic field that under analyzing certain provenance energy, produces, by Acquisition Detection transducer acoustic field waveform, utilize the RPNNP model of vibration of not coating microvesicle in sound field of free vibration, make up cavitation microvesicle wavelet.Utilize cavitation microvesicle wavelet, carry out cavitation microvesicle wavelet transform for the scan-line data that obtains after wave number is synthesized with plane wave emission receive mode, obtain to strengthen the ultrasonic fast imaging of signal to noise ratio (S/N ratio).By changing the static initial radium in the model of vibration, obtain the cavitation microvesicle wavelet under the different static initial radium conditions, after the cavitation microvesicle backscatter signals of synchronization carried out cavitation microvesicle wavelet transform, obtain the ultrasonoscopy of the signal to noise ratio (S/N ratio) enhancing of corresponding different static initial radiums, and then can obtain signal to noise ratio (S/N ratio)-static initial radium curve.Maximal value in the curve is exactly this radius that constantly microvesicle of number number percent maximum has among the cavitation microvesicle group.Adopt as above method, with cavitation microvesicle group subregion, can obtain the radius that the microvesicle of the number number percent maximum in each subregion has, because the vibration characteristics of cavitation microvesicle is related with the degree of its skew resonant frequency, based on this, we can obtain the corresponding brightness of revised subregion cavitation microvesicle, travel through all subregions, then can obtain brightness-radius curve, just cavitation microvesicle group's Size Distribution situation.With above method be applied to different constantly along with the time changes cavitation microvesicle backscatter signals, then can obtain the cavitation microvesicle group's in arbitrary moment Size Distribution situation.At last, the method is applied to cavitation microvesicle under the flow state, can obtains then that its face distributes and the body distribution.

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1.空化微泡高信噪比超声快速成像及动态尺寸分布估计方法，其特征在于，包括以下步骤：1. The method for rapid ultrasound imaging and dynamic size distribution estimation of cavitation microbubbles with high signal-to-noise ratio, comprising the following steps:步骤一、空化微泡子波构建：Step 1. Construction of cavitation microbubble wavelet:当源能量或这些能量的联合作用以一定强度一定时间作用于某溶液中并且在其能量集中区域附近产生的空化微泡群是自由振动而且没有包膜的，按照如下步骤构造空化微泡子波：When the source energy or the combination of these energies acts on a solution with a certain intensity and a certain time, and the cavitation microbubbles generated near the energy concentration area are free to vibrate and have no envelope, the cavitation microbubbles are constructed according to the following steps Wave:（1）以水听器接收检测换能器声场压力波形；(1) Receive and detect the sound field pressure waveform of the transducer with a hydrophone;（2）采用自由振动的未包膜微泡的RPNNP模型，预设模型参数，改变静态初始半径，求解微分方程；(2) Using the RPNNP model of free vibrating unencapsulated microbubbles, preset model parameters, change the static initial radius, and solve the differential equation;（3）求解微分方程的结果是微泡的半径-时间曲线，对其进行再微分，可以获得预测回波-时间曲线；(3) The result of solving the differential equation is the radius-time curve of the microbubble, which can be differentiated again to obtain the predicted echo-time curve;（4）对预测回波-时间曲线进行滤波归一化处理，得到空化微泡子波；(4) Filter and normalize the predicted echo-time curve to obtain the cavitation microbubble wavelet;所述源能量包括超声、微波、激光；The source energy includes ultrasound, microwave, laser;步骤二、基于空化微泡子波变换的空化微泡高信噪比成像：Step 2. High signal-to-noise ratio imaging of cavitation microbubbles based on cavitation microbubble wavelet transform:提取波束合成后的每一条扫描线上的射频数据，也就是空化微泡背向散射回波信号，选取空化微泡子波以及尺度，对其进行连续小波变换，获得二维的小波变换系数，选取小波变换系数中最大值所在的尺度的小波系数作为替换信号，并最终显示信噪比增强的图像；Extract the radio frequency data on each scanning line after beamforming, that is, the cavitation microbubble backscatter echo signal, select the cavitation microbubble wavelet and scale, and perform continuous wavelet transformation on it to obtain two-dimensional wavelet transformation coefficients , select the wavelet coefficient of the scale where the maximum value of the wavelet transform coefficients is located as the replacement signal, and finally display the image with enhanced signal-to-noise ratio;步骤三、基于多尺寸空化微泡子波变换的个数百分比最大空化微泡半径估计：Step 3. Estimation of the maximum cavitation microbubble radius based on the number percentage of multi-size cavitation microbubble wavelet transform:通过预设不同的空化微泡静态初始半径，来获得不同初始半径条件下的预测回波波形，以其作为空化微泡子波对采集的随时间变化的空化微泡背向散射信号进行空化微泡子波变换，获得对应着不同静态初始半径的信噪比增强的背向散射强度信息，进而获得信噪比-静态初始半径曲线，从这条曲线上获得这一时刻中空化微泡群中对于空化微泡背向散射信号贡献最大的微泡所具有的半径，这个半径下的空化微泡对于背向散射回波信号的贡献主要来自于两个方面，一个是其数目，另外一个是就是该空化微泡的散射横截面积，当空化微泡群的尺寸分布比较窄时且偏离检测换能器的固有频率时，散射横截面积差异可以忽略，这时候只有微泡数目的影响，在这种条件下，认为这一时刻空化微泡群中数目最多的空化微泡所具有的半径；By presetting different static initial radii of cavitation microbubbles, the predicted echo waveforms under the conditions of different initial radii are obtained, which are used as cavitation microbubble sub-waves to analyze the cavitation microbubble backscattering signals that vary with time. The cavitation microbubble wavelet transform obtains the backscattering intensity information corresponding to the signal-to-noise ratio enhancement of different static initial radii, and then obtains the signal-to-noise ratio-static initial radius curve, and from this curve, the cavitation microbubble at this moment is obtained. The radius of the microbubble that contributes the most to the cavitation microbubble backscatter signal in the group. The contribution of the cavitation microbubble to the backscatter echo signal under this radius mainly comes from two aspects, one is its number, The other is the scattering cross-sectional area of the cavitation microbubbles. When the size distribution of the cavitation microbubbles is relatively narrow and deviates from the natural frequency of the detection transducer, the difference in the scattering cross-sectional area can be ignored. At this time, only the microbubbles The influence of the number, under this condition, consider the radius of the cavitation microbubble with the largest number in the cavitation microbubble group at this moment;步骤四、基于分区内个数百分比最大空化微泡半径的全场微泡尺寸分布估计：Step 4. Estimate the size distribution of microbubbles in the whole field based on the maximum cavitation microbubble radius in the partition:将空化区域划分为若干个等大小的小区域，根据步骤三中的方法，获得每个分区中数目最多的微泡的半径，对于每一个空化微泡而言，其中p_i是辐照在单个微泡上的入射声压，p_s是单个微泡背向散射声压，z是该微泡与检测换能器表面的距离，σ是散射横截面积，每个分区中的空化微泡的数目比较少，总体背向散射回波则可以表示为

σ_k对应于不同半径的空化微泡所对应的散射横截面积，对于不同的空化微泡，其表面的入射声压是一致的，小分区内的空化微泡的尺寸分布范围比较狭小，可以认为是单一尺寸分布的，在这种情况下，每个分区里面的空化微泡背向散射回波信号可以表示为：

可以看出每个分区里面的空化微泡的散射回波强度主要与单一尺寸的空化微泡的数目和散射横截面积有关系，再引入共振偏移系数，数值上等于预测回波强度-半径曲线的倒数，此时，空化微泡散射回波强度就只与空化微泡的个数有关系；所有小分区的空化微泡数目-半径曲线，将所有分区的微泡的数据进行加权显示之后，获得空化微泡群的尺寸分布的动态估计；The cavitation area is divided into several small areas of equal size, and according to the method in step 3, the radius of the most numerous microbubbles in each partition is obtained. For each cavitation microbubble, where p_i is the incident sound pressure irradiated on a single microbubble, p_s is the backscattered sound pressure of a single microbubble, z is the distance between the microbubble and the surface of the detection transducer, σ is the scattering cross-sectional area, each The number of cavitation microbubbles in each partition is relatively small, and the overall backscattered echo can be expressed as

σ_k corresponds to the scattering cross-sectional area of cavitation microbubbles with different radii. For different cavitation microbubbles, the incident sound pressure on the surface is consistent. Narrow, can be considered as a single size distribution, in this case, the cavitation microbubble backscatter echo signal in each partition can be expressed as:

It can be seen that the scattering echo intensity of cavitation microbubbles in each partition is mainly related to the number of cavitation microbubbles of a single size and the scattering cross-sectional area, and then the resonance offset coefficient is introduced, which is numerically equal to the predicted echo intensity -the reciprocal of the radius curve, at this time, the cavitation microbubble scattering echo intensity is only related to the number of cavitation microbubbles; the number of cavitation microbubbles in all small partitions-radius curves, the microbubbles of all partitions After the data is weighted and displayed, a dynamic estimate of the size distribution of the cavitation microbubble population is obtained;步骤五、流动状态下空化微泡尺寸面分布和体分布估计：Step 5. Estimation of cavitation microbubble size surface distribution and volume distribution under flow state:1）对于流动管道如血管中的空化微泡的动态估计，源能量在产生空化微泡的同时以及之后，空化微泡随着周围液体发生流动，采用步骤三-步骤四的方法，获得某一时刻空化微泡群中的数目最多的微泡的半径以及整个空化微泡群中的微泡的尺寸分布情况；1) For the dynamic estimation of cavitation microbubbles in flow channels such as blood vessels, the cavitation microbubbles flow with the surrounding liquid while the source energy is generating cavitation microbubbles, and the method of step 3-step 4 is adopted, Obtaining the radius of the most numerous microbubbles in the cavitation microbubble population at a certain moment and the size distribution of the microbubbles in the entire cavitation microbubble population;2）因为每一个时刻对应着空化微泡群的一个切面，即获得空化微泡的面分布，在流动状态下可以获得连续的切面信息，将所有的切面信息完成后就获得体分布。2) Because each moment corresponds to a section of the cavitation microbubble group, that is, to obtain the surface distribution of the cavitation microbubbles, continuous section information can be obtained in the flow state, and the volume distribution can be obtained after all the section information is completed.2.根据权利要求1所述的空化微泡高信噪比超声快速成像及动态尺寸分布估计方法，其特征在于，步骤一所述的采用自由振动的未包膜微泡的RPNNP模型，预设模型参数，改变静态初始半径，求解微分方程，具体步骤如下：2. the cavitation microbubble high signal-to-noise ratio ultrasonic fast imaging and dynamic size distribution estimation method according to claim 1, it is characterized in that, the RPNNP model of the non-encapsulated microbubble adopting free vibration described in step 1, predict Set the model parameters, change the static initial radius, and solve the differential equation. The specific steps are as follows:对于静态半径为R_o的单个自由气泡，处于体积比微泡体积远远大的液体介质中，液体密度为ρ，远大于微泡内气体的密度，气体及液体接触面的表面张力为σ，气泡内的蒸汽压为P_V且微泡内的蒸汽压在振动过程中始终不变，液体的粘滞系数为η，液体的静态压力为P_o，微泡所处的激励声场压力为P(t)，气泡振动过程一直保持球形而没有形状的改变，气泡内气体分布均匀，气体含量不变，且为理想气体，认为微泡可以无穷压缩，气泡的振动过程中的半径小于声波波长（R＜λ），不计微泡的体粘滞效应，液体不可压缩或压缩性很小，微泡壁在振动过程中的速度远远小于液体中的声速，此时微泡振动中的半径为时间的二次微分方程为For a single free bubble with a static radius of R_o , in a liquid medium whose volume is much larger than that of the microbubble, the density of the liquid is ρ, which is much greater than the density of the gas in the microbubble, and the surface tension of the gas-liquid contact surface is σ, the bubble The vapor pressure in the microbubble is P_V and the vapor pressure in the microbubble remains unchanged during the vibration process, the viscosity coefficient of the liquid is η, the static pressure of the liquid is P_o , and the excitation sound field pressure of the microbubble is P(t ), the bubble vibration process has been kept spherical without shape change, the gas distribution in the bubble is uniform, the gas content remains unchanged, and it is an ideal gas. λ), excluding the bulk viscous effect of the microbubble, the liquid is incompressible or the compressibility is very small, the velocity of the microbubble wall in the vibration process is much smaller than the sound velocity in the liquid, and the radius of the microbubble vibration is twice the time The sub-differential equation is$\mathrm{<span><span>R</span>R</span>}\stackrel{<span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span>}{\mathrm{<span><span>R</span>R</span>}}<span><span>+</span>+</span>\frac{\mathrm{<span><span>3</span>3</span>}{\stackrel{<span><span>\&CenterDot;</span>\&Center\; Dot;</span>}{\mathrm{<span><span>R</span>R</span>}}}^{\mathrm{<span><span>2</span>2</span>}}}{\mathrm{<span><span>2</span>2</span>}}<span><span>=</span>=</span>\frac{\mathrm{<span><span>1</span>1</span>}}{\mathrm{<span><span>\&rho;</span>\&rho;</span>}}<span><span>\{</span>\{</span><span><span>(</span>(</span>{\mathrm{<span><span>P</span>P</span>}}_{\mathrm{<span><span>o</span>o</span>}}<span><span>+</span>+</span>\frac{\mathrm{<span><span>2</span>2</span>}\mathrm{<span><span>\&sigma;</span>\&sigma;</span>}}{{\mathrm{<span><span>R</span>R</span>}}_{\mathrm{<span><span>o</span>o</span>}}}<span><span>-</span>-</span>{\mathrm{<span><span>P</span>P</span>}}_{\mathrm{<span><span>V</span>V</span>}}<span><span>)</span>)</span>{<span><span>(</span>(</span>\frac{{\mathrm{<span><span>R</span>R</span>}}_{\mathrm{<span><span>o</span>o</span>}}}{\mathrm{<span><span>R</span>R</span>}}<span><span>)</span>)</span>}^{\mathrm{<span><span>3</span>3</span>}\mathrm{<span><span>\&gamma;</span>\&gamma;</span>}}<span><span>+</span>+</span>{\mathrm{<span><span>P</span>P</span>}}_{\mathrm{<span><span>V</span>V</span>}}<span><span>-</span>-</span>\frac{\mathrm{<span><span>2</span>2</span>}\mathrm{<span><span>\&sigma;</span>\&sigma;</span>}}{\mathrm{<span><span>R</span>R</span>}}<span><span>-</span>-</span>{\mathrm{<span><span>P</span>P</span>}}_{\mathrm{<span><span>o</span>o</span>}}<span><span>-</span>-</span>\mathrm{<span><span>P</span>P</span>}<span><span>(</span>(</span>\mathrm{<span><span>t</span>t</span>}<span><span>)</span>)</span><span><span>-</span>-</span>\frac{\mathrm{<span><span>4</span>4</span>}\mathrm{<span><span>\&eta;</span>\&eta;</span>}\stackrel{<span><span>\&CenterDot;</span>\&Center\; Dot;</span>}{\mathrm{<span><span>R</span>R</span>}}}{\mathrm{<span><span>R</span>R</span>}}<span><span>\}</span>\}</span>$解这个微分方程,得到微泡振动半径随时间的变化曲线及其径向振动速度和加速度，当接收换能器与微泡之间的距离为r时,得到微泡背向散射回波:Solve this differential equation to obtain the change curve of the microbubble vibration radius with time and its radial vibration velocity and acceleration. When the distance between the receiving transducer and the microbubble is r, the backscattered echo of the microbubble is obtained:$\mathrm{<span><span>P</span>P</span>}<span><span>=</span>=</span>{\mathrm{<span><span>\&rho;r</span>\&rho;r</span>}}^{<span><span>-</span>-</span>\mathrm{<span><span>1</span>1</span>}}<span><span>(</span>(</span>{\mathrm{<span><span>R</span>R</span>}}^{\mathrm{<span><span>2</span>2</span>}}\stackrel{<span><span>\&CenterDot;</span>\&Center\; Dot;</span><span><span>\&CenterDot;</span>\&CenterDot;</span>}{\mathrm{<span><span>R</span>R</span>}}<span><span>+</span>+</span>{\stackrel{<span><span>\&CenterDot;</span>\&CenterDot;</span>}{\mathrm{<span><span>R</span>R</span>}}}^{\mathrm{<span><span>2</span>2</span>}}<span><span>)</span>)</span>$当外部声场激励条件已知时，通过设置不同的微泡参数和信号参数，得到相应条件下的微泡回波信号。When the excitation conditions of the external sound field are known, the microbubble echo signals under corresponding conditions are obtained by setting different microbubble parameters and signal parameters.

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