CN103784164B - The preprocess method of ultrasonic signal and system - Google Patents
The preprocess method of ultrasonic signal and system Download PDFInfo
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Abstract
The preprocess method of ultrasonic signal provided by the invention and system, said method comprising the steps of: receive N bar echo-signal, from echo-signal described in the N bar received, randomly draw echo-signal described in M bar process, to calculate system function, wherein, M is less than N; Carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N; Based on the system function calculated and P bar echo-signal, carry out deconvolution process; Obtain target image.The preprocess method of this ultrasonic signal and system, before acquisition target image, adopt echo-signal described in deconvolution process, remove the noise in described echo-signal, and at utmost retain original described echo-signal, the final target image contrast obtained significantly is strengthened, and then improves the resolution of target image, make the tissue texture of the target image of acquisition also more careful, clear simultaneously.
Description
Technical field
The invention belongs to ultrasonic diagnostic imaging field, relate to a kind of preprocess method and system of ultrasonic signal.
Background technology
What require self living standard along with the develop rapidly of microelectric technique, computer technology and the mankind improves constantly, and the medical ultrasound diagnosis imaging technique as clinical diagnosis becomes one of Medical Technology field with fastest developing speed.
Wherein, be widely used with the medical supersonic instrument obtaining target image by receiving, processing echo-signal, contemporary medical supersonic instrument, no matter be linear scan or sector scanning, the echo-signal received by ultrasonic transducer all comprises three partial informations usually: Part I part is the useful information (also referred to as tissue texture) of tested tissue structure; Part II is the obfuscation information to tissue texture because the reasons such as system imaging limited resolution cause; In addition the random phase superposition because hyperacoustic scattering produces is also had, and the random noise that instrument oneself factor, environmental unit factor etc. produce.
Ultra sonic imaging gained image is the convolution of Part I information and Part II information, adds Part III information.The result of convolution makes the image resolution ratio of measured signal decline; Measured object reads shape and distorts; Noise makes contrast decline; Meanwhile, the system function of ultrasonic image-forming system is hidden in the signal seized, and is difficult to be separated, and this is the inherent limitation of any one signal detection system.
Current ultrasonic device, generally can carry out processing in reception control, signal to the signal that scanning obtains, ultra sonic imaging completes to obtain target image, processes afterwards to the target image obtained again, be referred to as " post processing ", i.e. processed offline (Off Line); Concrete, after ultra sonic imaging completes, respective system function is all estimated to every subgoal image, and do not consider whether several target images are generated by same system.Therefore, the system function of every subgoal image is different, and this situation is called that system function is relevant with tested tissue, and this has run counter to " system uniqueness " this basic norm of measurement; Meanwhile, adopt this processing method to obtain in the process of target image, acquisition speed and efficiency are all very low.
Summary of the invention
In order to solve the problem, the invention provides a kind of target image system organization texture making to get preprocess method that is more careful, ultrasonic signal clearly and system.
Accordingly, the preprocess method of a kind of ultrasonic signal of the present invention, said method comprising the steps of:
S1, reception N bar echo-signal, randomly draw echo-signal described in M bar and process from echo-signal described in the N bar received, and adopt two spectrum identification process to process, and to calculate system function, wherein, M is less than N;
S2, carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N;
S3, based on the system function calculated and P bar echo-signal, carry out the long-pending process of Fourier-small echo regular deconvolution, remove the noise in described echo-signal;
S4, acquisition target image.
As a further improvement on the present invention, " removing the noise in described echo-signal " step comprises: adopt echo-signal described in Fourier-Tikhonov shrink process, to weaken the noise in described echo-signal.
As a further improvement on the present invention, " removing the noise in described echo-signal " step also comprises: adopt echo-signal described in small echo hard-threshold shrink process, again decompose described echo-signal, remove noise to described echo-signal secondary.
As a further improvement on the present invention, step also comprises " to remove the noise in described echo-signal ": adopt echo-signal described in Wavelet Domain Wiener Filtering process.
Accordingly, the pretreatment system of a kind of ultrasonic signal of the present invention, described system comprises:
Communication unit, for receiving N bar echo-signal;
Processing unit, processes for randomly drawing echo-signal described in M bar from echo-signal described in the N bar received, and adopts two spectrum identification process to process, and to calculate system function, wherein, M is less than N;
Carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N;
Based on the system function calculated and P bar echo-signal, the long-pending process of Fourier-small echo regular deconvolution, removes the noise in described echo-signal;
Obtain target image.
As a further improvement on the present invention, described processing unit also for adopting echo-signal described in Fourier-Tikhonov shrink process, to weaken the noise in described echo-signal; Adopt echo-signal described in small echo hard-threshold shrink process, again decompose described echo-signal, noise is removed to described echo-signal secondary; Adopt echo-signal described in Wavelet Domain Wiener Filtering process.
Compared with prior art, the preprocess method of ultrasonic signal of the present invention and system, before acquisition target image, adopt echo-signal described in deconvolution process, remove the noise in described echo-signal, and at utmost retain original described echo-signal, the final target image contrast obtained significantly is strengthened, and then improve the resolution of target image, make the tissue texture of the target image of acquisition also more careful, clear simultaneously.
Accompanying drawing explanation
Fig. 1 is the flow chart of the processing method of the ultrasonic signal provided in prior art;
Fig. 2 is the flow chart of the processing method of the ultrasonic signal provided in embodiment of the present invention;
Fig. 3 is the flow chart of the preprocess method of the ultrasonic signal provided in embodiment of the present invention;
Fig. 4 is the module diagram of the pretreatment system of the ultrasonic signal that embodiment of the present invention provides.
Detailed description of the invention
Describe the present invention below with reference to embodiment shown in the drawings.But embodiment does not limit the present invention, the structure that those of ordinary skill in the art makes according to these embodiments, method or conversion functionally are all included in protection scope of the present invention.
As shown in Figure 1, the processing method of ultrasonic signal in prior art, the method mainly comprises the following steps:
M1, launch scanning linear scan destination organization, to sample to original image by Ultrasound Instrument;
M2, receive described echo-signal;
M3, complete ultra sonic imaging according to described echo-signal, obtain target image;
M4, finally to described destination organization estimating system function, to do further process to described target image.
What above process adopted is post-processing technology, namely processes further on the basis obtaining target image, to make the final target image obtained more outstanding; But owing to adopting said method, during the different target image of medical supersonic instrument scanning, each system function obtained is different.Run counter to " system uniqueness " this basic norm of measurement, and then result in image processing process low speed, poor efficiency.
As shown in Figure 2, the processing method of ultrasonic signal of the present invention, the method mainly comprises the following steps:
P1, launch scanning linear scan destination organization, to sample to original image by Ultrasound Instrument;
P2, receive all echo-signals;
P3, pretreatment is carried out to described echo-signal;
P4, complete ultra sonic imaging according to described echo-signal, obtain target image;
The difference part of the ultrasonic signal processing method of ultrasonic signal processing method of the present invention and prior art is: before completing ultra sonic imaging according to described echo-signal, described method also comprises, pretreatment is carried out to described ultrasonic signal, complete ultra sonic imaging according to through pretreated described echo-signal more afterwards, obtain target image.The target image now obtained is the target image that finally will obtain.And no longer adopt post-processing technology to process to described target image.
As shown in Figure 3, Fig. 3 is the flow chart of the preprocess method of the ultrasonic signal provided in embodiment of the present invention; Be the concrete introduction of step P3 in Fig. 2, concrete, the preprocess method of a kind of ultrasonic signal of the present invention, said method comprising the steps of:
S1, reception N bar echo-signal, from echo-signal described in the N bar received, randomly draw echo-signal described in M bar process, to calculate system function, wherein, M is less than N;
S2, carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N;
S3, based on the system function calculated and P bar echo-signal, carry out deconvolution process;
S4, acquisition target image.
Accordingly, in an embodiment of the present invention, because described system function is unknown, therefore before carrying out described deconvolution process, first carry out system identification, i.e. blind deconvolution (blind deconvolution).
Concrete, described step S1 specifically comprises: receive N bar echo-signal, from echo-signal described in the N bar received, randomly draw echo-signal described in M bar, and adopts two spectrum identification process to process, and to calculate system function, wherein, M is less than N.Adopt the described system function that this kind of method calculates, can environmentally temperature, the impact of the extraneous factors such as humidity change, calculates suitable described system function in real time.
Select the method for high order equilibrium, for gaussian signal, all Higher Order Cumulants are all zero, can eliminate the interference of white Gaussian noise and coloured noise in non-Gaussian filtering, improve signal to noise ratio; In non-minimum phase system, higher-order spectrum method can the phase property of stick signal.
Concrete, adopt two spectrum identification process to calculate system function, its implementation is as follows:
The Third-order cumulants of zero average signal y (n) is defined as:
In formula,
it is zero average signal
third-order cumulants, be a constant;
represent assembly average.
Afterwards, (3) (1) (2) step in following formula is successively used to estimate system function;
Further, two spectrum of falling does transform to above formula, after getting natural logrithm, then does inverse transformation, obtain:
The cepstrum of note h (n) is:
In formula,
represent two-dimension fourier transform.
By above-mentioned two spectra system identification algorithm that falls, utilize MatLab higher-order spectrum calculation procedure, the described echo-signal received is processed, choose optimum described system function by estimation.
Accordingly, step S2 carries out linear interpolation calculating to echo-signal described in the N bar received, and so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N.
Adopt the algorithm of linear interpolation that N bar echo-signal is increased to P bar echo-signal, be general knowledge known in this field, be not described in detail at this.
Accordingly, step S3, based on the system function calculated and P bar echo-signal, carry out deconvolution process; S4, acquisition target image.
Concrete, described deconvolution is treated to the long-pending process of Fourier-small echo regular deconvolution, removes the noise in described echo-signal simultaneously.Fourier-small echo regular deconvolution integration method has very strong robustness, has high resistance and make performance, significantly can improve the resolution degradation phenomenon caused by convolution, strengthens picture contrast, reduces noise.
Accordingly, echo-signal described in Fourier-Tikhonov shrink process is adopted, to weaken the noise in described echo-signal.
The concrete methods of realizing adopting Fourier-Tikhonov to shrink is as follows:
The mathematical model of ultra sonic imaging is:
In formula: y (n) represents the described echo-signal observed; X (n) represents the signal of tested tissue, is a Gauss, zero average, stable signal; H (n) is and asks in step S1, represents the described system function of Ultrasound Instrument, be a length is M, determine, the FIR filter system of cause and effect;
represent additive gaussian noise; * convolution is represented.
Do discrete Fourier transform to above formula to obtain:
Inverse operator is adopted to obtain the estimated value of X:
If
, deconvolution becomes morbid state.
In order to solve the problem of ill deconvolution, the impact of the method attenuating noise shunk with Fourier, will
be multiplied by a contraction
Obtain:
Above step inverse operator and Fourier shrink and carry out simultaneously, are called Fourier's regular deconvolution area method.
Wherein, the constriction coefficient that Fourier's regular deconvolution is long-pending is:
for regular terms, the regular terms that different Fourier's regular deconvolutions amasss technology is different.
If σ
2for noise variance, α is regular parameter (α >0), and the regular terms of Tikhonov deconvolution is
the i.e. meansigma methods of y;
If get regular parameter
, then the noisy unbiased esti-mator of signal can be obtained;
If get regular parameter
, then can restraint speckle completely, but also lose the information of former described echo-signal kth item simultaneously.
Choose optimum regular parameter, the mean square deviation of signal and the former described echo-signal finally estimated will be made
minimum, because former described echo-signal is unknown, so MSE cannot directly obtain.
The present invention carrys out approximate MSE with based on the cost function observed:
The minimum α of above formula value is made namely to be optimum regular parameter α.
In the ultrasonic system of reality, noise variance is unknown; Select classical Donoho to ask the method for noise variance herein, namely on the most fine dimension of wavelet decomposition, the intermediate value of signal wavelet coefficient is divided by 0.6745;
If the signal after making Fourier-Tikhonov shrink is
, wherein,
fourier transformation.
After shrinking described echo-signal by Fourier Tikhonov, the noise contribution be exaggerated is cut down greatly, but simultaneously also have lost a part of signal component, and due to the existence on border, signal exists distortion.In order to improve the quality of signal, need at wavelet field decomposed signal carry out denoising to signal again.
Accordingly, adopt echo-signal described in small echo hard-threshold shrink process, again decompose described echo-signal, noise is removed to described echo-signal secondary.
The concrete methods of realizing adopting small echo hard-threshold to shrink is as follows:
After adopting echo-signal described in Fourier-Tikhonov contraction, small echo hard-threshold shrink process, recycling Wavelet Domain Wiener Filtering obtains final estimated value
Compared with prior art, the preprocess method of ultrasonic signal of the present invention, before acquisition target image, during in order to overcome same Ultrasound Instrument scanning different target image, the system function of each acquisition is different, adopts two spectrum identification process to calculate system function; Afterwards, adopt the described echo-signal of the long-pending process of Fourier-small echo regular deconvolution, remove the noise in described echo-signal, and at utmost retain original described echo-signal, the final target image contrast obtained significantly is strengthened, and then improves the resolution of target image, simultaneously, make the tissue texture of the target image of acquisition also more careful, clear.
As shown in Figure 4, Fig. 4 is the module diagram of the pretreatment system of ultrasonic signal in an embodiment of the present invention.
Accordingly, described system comprises: communication unit 100, for receiving N bar echo-signal; Processing unit 200, process for randomly drawing echo-signal described in M bar from echo-signal described in the N bar received, to calculate system function, wherein, M is less than N; Carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N; Based on the system function calculated and P bar echo-signal, carry out deconvolution process; Obtain target image.
Accordingly, want to process to obtain target image to ultrasonic signal, first need to receive echo-signal by communication unit 100, by processing unit 200, described echo-signal is processed again afterwards, to obtain described target image.
Accordingly, in an embodiment of the present invention, because described system function is unknown, therefore before carrying out described deconvolution process, first carry out identification by processing unit 200 pairs of systems, i.e. blind deconvolution (blind deconvolution).
Accordingly, described processing unit 200, for receiving N bar echo-signal, randomly draws echo-signal described in M bar from echo-signal described in the N bar received, and adopts two spectrum identification process to process, and to calculate system function, wherein, M is less than N.Adopt the described system function that this kind of method calculates, can environmentally temperature, the impact of the extraneous factors such as humidity change, calculates suitable described system function in real time.
Described processing unit 200 selects the method for high order equilibrium, and for gaussian signal, all Higher Order Cumulants are all zero, can eliminate the interference of white Gaussian noise and coloured noise in non-Gaussian filtering, improves signal to noise ratio; In non-minimum phase system, higher-order spectrum method can the phase property of stick signal.
Concrete, described processing unit 200 adopts two spectrum identification process to calculate system function, and its implementation is as follows:
The Third-order cumulants of zero average signal y (n) is defined as:
In formula,
being the Third-order cumulants of zero average signal x (n), is a constant; E{} represents assembly average.
Afterwards, (3) (1) (2) step in following formula is successively used to estimate system function;
Further, two spectrum of falling does transform to above formula, after getting natural logrithm, then does inverse transformation, obtain:
In formula, F [] represents two-dimension fourier transform.
By above-mentioned two spectra system identification algorithm that falls, utilize MatLab higher-order spectrum calculation procedure, the described echo-signal received is processed, choose optimum described system function by estimation.
Accordingly, described processing unit 200 is also for carrying out linear interpolation calculating to echo-signal described in the N bar received, and so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N.
Described processing unit 200 adopts the algorithm of linear interpolation that N bar echo-signal is increased to P bar echo-signal, is general knowledge known in this field, is not described in detail at this.
Accordingly, described processing unit 200 also for based on the system function calculated and P bar echo-signal, carries out deconvolution process; Obtain target image.
Concrete, described processing unit 200 adopts the described echo-signal of the long-pending process of Fourier-small echo regular deconvolution, removes the noise in described echo-signal simultaneously.Fourier-small echo regular deconvolution integration method has very strong robustness, has high resistance and make performance, significantly can improve the resolution degradation phenomenon caused by convolution, strengthens picture contrast, reduces noise.
Accordingly, described processing unit 200 adopts echo-signal described in Fourier-Tikhonov shrink process, to weaken the noise in described echo-signal.
The concrete methods of realizing that described processing unit 200 adopts Fourier-Tikhonov to shrink is as follows:
The mathematical model of ultra sonic imaging is:
In formula: y (n) represents the described echo-signal observed; X (n) represents the signal of tested tissue, is a Gauss, zero average, stable signal; H (n) is and asks in step S1, represents the described system function of Ultrasound Instrument, be a length is M, determine, the FIR filter system of cause and effect; γ (n) represents additive gaussian noise; * convolution is represented.
Do discrete Fourier transform to above formula to obtain:
Inverse operator is adopted to obtain the estimated value of X:
Inverse operator is adopted to obtain the estimated value of X:
If
, deconvolution becomes morbid state.
In order to solve the problem of ill deconvolution, the impact of the method attenuating noise shunk with Fourier, will
be multiplied by a constriction coefficient
Obtain:
Above step inverse operator and Fourier shrink and carry out simultaneously, are called Fourier's regular deconvolution area method.
Wherein, the constriction coefficient that Fourier's regular deconvolution is long-pending is:
for regular terms, the regular terms that different Fourier's regular deconvolutions amasss technology is different.
If σ
2for noise variance, α is regular parameter (α >0), and the regular terms of Tikhonov deconvolution is
the i.e. meansigma methods of y;
If get regular parameter
, then the noisy unbiased esti-mator of signal can be obtained;
If get regular parameter
, then can restraint speckle completely, but also lose the information of former described echo-signal kth item simultaneously.
Choose optimum regular parameter, the mean square deviation of signal and the described echo original signal finally estimated will be made
minimum, because former described echo-signal is unknown, so MSE cannot directly obtain.
The present invention carrys out approximate MSE with based on the cost function observed:
The minimum α of above formula value is made namely to be optimum regular parameter α.
In the ultrasonic system of reality, noise variance is unknown; Select classical Donoho to ask the method for noise variance herein, namely on the most fine dimension of wavelet decomposition, the intermediate value of signal wavelet coefficient is divided by 0.6745;
If the signal after making Fourier-Tikhonov shrink is
then
, wherein,
fourier transformation.
After described processing unit 200 shrinks described echo-signal by Fourier Tikhonov, the noise contribution be exaggerated is cut down greatly, but simultaneously also have lost a part of signal component, and due to the existence on border, signal exists distortion.In order to improve the quality of signal, need at wavelet field decomposed signal carry out denoising to signal again.
Accordingly, described processing unit 200 adopts echo-signal described in small echo hard-threshold shrink process, again decomposes described echo-signal, removes noise to described echo-signal secondary.
The concrete methods of realizing that described processing unit 200 adopts small echo hard-threshold to shrink is as follows:
After described processing unit 200 adopts echo-signal described in Fourier-Tikhonov contraction, small echo hard-threshold shrink process, recycling Wavelet Domain Wiener Filtering obtains final estimated value
;
Compared with prior art, the preprocess method of ultrasonic signal of the present invention and system, before acquisition target image, during in order to overcome same Ultrasound Instrument scanning different target image, each system function obtained is different; Adopt two spectrum identification process to calculate system function; Afterwards, adopt the described echo-signal of the long-pending process of Fourier-small echo regular deconvolution, remove the noise in described echo-signal, and at utmost retain former described beginning echo-signal, the final target image contrast obtained significantly is strengthened, and then improves the resolution of target image, simultaneously, make the tissue texture of the target image of acquisition also more careful, clear.
For convenience of description, various module is divided into describe respectively with function when describing above device.Certainly, the function of each module can be realized in same or multiple software and/or hardware when implementing the application.
As seen through the above description of the embodiments, those skilled in the art can be well understood to the mode that the application can add required general hardware platform by software and realizes.Based on such understanding, the technical scheme of the application can embody with the form of software product the part that prior art contributes in essence in other words, this computer software product can be kept to be preserved in medium, as ROM/RAM, magnetic disc, CD etc., comprising some instructions in order to make a computer equipment (can be personal computer, Information Push Server, or the network equipment etc.) perform the method described in some part of each embodiment of the application or embodiment.
Device embodiments described above is only schematic, the wherein said module illustrated as separating component can or may not be physically separates, parts as module display can be or may not be physical module, namely can be positioned at a place, or also can be distributed on multiple mixed-media network modules mixed-media.Some or all of module wherein can be selected according to the actual needs to realize the object of present embodiment scheme.Those of ordinary skill in the art, when not paying creative work, are namely appreciated that and implement.
The application can be used in numerous general or special purpose computing system environment or configuration.Such as: personal computer, Information Push Server computer, handheld device or portable set, laptop device, multi-processing module system, system, set top box, programmable consumer-elcetronics devices, network PC, minicomputer, mainframe computer, the distributed computing environment comprising above any system or equipment etc. based on micro treatment module.
The application can describe in the general context of computer executable instructions, such as program module.Usually, program module comprises the routine, program, object, assembly, data structure etc. that perform particular task or realize particular abstract data type.Also can put into practice the application in a distributed computing environment, in these distributed computing environment, be executed the task by the remote processing devices be connected by communication network.In a distributed computing environment, program module can be arranged in the local and remote computer preservation medium comprising preservation equipment.
Be to be understood that, although this description is described according to embodiment, but not each embodiment only comprises an independently technical scheme, this narrating mode of description is only for clarity sake, those skilled in the art should by description integrally, technical scheme in each embodiment also through appropriately combined, can form other embodiments that it will be appreciated by those skilled in the art that.
A series of detailed description listed is above only illustrating for feasibility embodiment of the present invention; they are also not used to limit the scope of the invention, all do not depart from the skill of the present invention equivalent implementations done of spirit or change all should be included within protection scope of the present invention.
Claims (6)
1. a preprocess method for ultrasonic signal, is characterized in that, said method comprising the steps of:
S1, reception N bar echo-signal, randomly draw echo-signal described in M bar and process from echo-signal described in the N bar received, and adopt two spectrum identification process to process, and to calculate system function, wherein, M is less than N;
S2, carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N;
S3, based on the system function calculated and P bar echo-signal, carry out the long-pending process of Fourier-small echo regular deconvolution, remove the noise in described echo-signal;
S4, acquisition target image.
2. the preprocess method of ultrasonic signal according to claim 1, is characterized in that, " removing the noise in described echo-signal " step comprises:
Adopt echo-signal described in Fourier-Tikhonov shrink process, to weaken the noise in described echo-signal.
3. the preprocess method of ultrasonic signal according to claim 2, is characterized in that, " removing the noise in described echo-signal " step also comprises:
Adopt echo-signal described in small echo hard-threshold shrink process, again decompose described echo-signal, noise is removed to described echo-signal secondary.
4. the preprocess method of ultrasonic signal according to claim 3, is characterized in that, " removing the noise in described echo-signal " step also comprises:
Adopt echo-signal described in Wavelet Domain Wiener Filtering process.
5. a pretreatment system for ultrasonic signal, is characterized in that, described system comprises:
Communication unit, for receiving N bar echo-signal;
Processing unit, processes for randomly drawing echo-signal described in M bar from echo-signal described in the N bar received, and adopts two spectrum identification process to process, and to calculate system function, wherein, M is less than N;
Carry out linear interpolation calculating to echo-signal described in the N bar received, so that N bar echo-signal is increased to P bar echo-signal, wherein, P is greater than N;
Based on the system function calculated and P bar echo-signal, carry out the long-pending process of Fourier-small echo regular deconvolution, remove the noise in described echo-signal;
Obtain target image.
6. the pretreatment system of ultrasonic signal according to claim 5, is characterized in that, described processing unit also for adopting echo-signal described in Fourier-Tikhonov shrink process, to weaken the noise in described echo-signal; Adopt echo-signal described in small echo hard-threshold shrink process, again decompose described echo-signal, noise is removed to described echo-signal secondary; Adopt echo-signal described in Wavelet Domain Wiener Filtering process.
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