CN106997045B - Ultrasonic imaging method based on ultrasonic system point spread function measurement and compressed sensing - Google Patents

Ultrasonic imaging method based on ultrasonic system point spread function measurement and compressed sensing Download PDF

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CN106997045B
CN106997045B CN201710128830.6A CN201710128830A CN106997045B CN 106997045 B CN106997045 B CN 106997045B CN 201710128830 A CN201710128830 A CN 201710128830A CN 106997045 B CN106997045 B CN 106997045B
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王丛知
杨新新
刘佳妹
肖杨
郑海荣
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Shenzhen Institute of Advanced Technology of CAS
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Abstract

The invention relates to the field of ultrasonic imaging, in particular to an ultrasonic imaging method based on ultrasonic system point spread function measurement and compressed sensing. The purpose of the invention is: the ultrasonic imaging with high frame frequency and high imaging quality is ensured, and meanwhile, the imaging can be realized by a hardware computing platform with a low level. The ultrasonic imaging method provided by the invention comprises the following steps: obtaining a point spread function of the ultrasound imaging system; establishing a relation matrix M according to the point spread function; establishing an equation system reflecting the relationship between the ultrasonic echo radio-frequency signal s and the scattering intensity distribution I of the scattering particles on the pixel points of the ultrasonic image: s ═ MI; it is characterized in that a threshold value is set, and all elements in the relation matrix M which are lower than the threshold value are set to be 0. The invention can be applied to the fields which need high frame frequency and high resolution imaging and have lower hardware computing platform level, such as medical imaging and the like, and has higher practical value.

Description

Ultrasonic imaging method based on ultrasonic system point spread function measurement and compressed sensing
Technical Field
The invention relates to the field of ultrasonic imaging, in particular to an ultrasonic imaging method based on point spread function measurement and compressed sensing of an ultrasonic imaging system.
Background
In the traditional ultrasonic imaging working principle, taking a linear array type ultrasonic transducer as an example, the linear array transducer is provided with N array elements which can independently transmit/receive and correspond to N ultrasonic transmitting channels and signal receiving channels, and ultrasonic signals of different channels simultaneously reach a focusing position by utilizing the delayed transmission of a plurality of channels during ultrasonic transmission to form transmitting focusing; when receiving echoes, the received signals are delayed similarly, and the signals received from different channels returned by the same reflector are added together to form a receiving focus. Thus, one scan line can be formed by one transmission and one reception. Generally, ultrasound imaging uses electronic scanning to perform M times of focused transmission/reception to obtain M scan lines, and then converts these scans into a complete two-dimensional image. Therefore, the frame rate of conventional ultrasound imaging is low, typically between tens of frames to tens of frames. For the application fields that imaging targets are in need of high frame frequency due to high-hardness tissue elastography, aorta high-speed blood flow imaging, cardiac imaging, tracking of ultrasonic contrast agent state change and the like, the frame frequency of traditional ultrasonic imaging is far from meeting the requirements.
The ultrasonic plane wave imaging technology comprises ultrasonic plane wave emission and a corresponding ultrasonic echo beam forming technology, and is a hot research direction for improving the ultrasonic imaging frame frequency in recent years internationally. The technology can improve the traditional ultrasonic imaging frame frequency (generally from dozens of frames to dozens of frames) by hundreds of times, and the frame frequency reaches 10000-20000 frames. The method generally uses all array elements of a linear array transducer for transmitting, adopts the same voltage pulse without relative time delay between the array elements, and simultaneously excites all the array elements of the linear array transducer to generate ultrasonic plane waves which are transmitted forwards along the direction vertical to the surface of the transducer; when an echo signal is received, a two-dimensional image is formed by adopting DAS (Delay and Sum) beam forming technology based on the position of an image pixel point. Thus, only one transmission/reception is needed to complete one-time two-dimensional imaging, and the imaging frame frequency is greatly improved. However, since ultrasound energy is uniformly distributed throughout the two-dimensional imaging plane when using plane wave imaging techniques, echoes reflected from different scatterers may be mixed together and received by the individual channels, making it difficult to distinguish. Therefore, the image obtained by the conventional beamforming method may have significant artifact interference.
To solve this problem, a multi-angle coherent stack imaging method is proposed. The method transmits ultrasonic plane waves from 2N +1(N is a positive integer) angles (one angle is a commonly used angle vertical to the surface of an ultrasonic transducer, and other 2N angles are distributed around the vertical angle in a symmetrical mode, such as-2 degrees, -1 degree, 0 degree, 1 degree and 2 degrees), and obtains 2N +1 two-dimensional images by adopting the DAS beam forming technology based on the positions of image pixel points, and the images are overlapped, so that coherence enhancement is realized among the ultrasonic plane waves transmitted from multiple angles, and the focusing-like effect is generated, thereby realizing the enhancement of image resolution and contrast. The larger the value of N, the more significant the effect of improving resolution and contrast. With this technique, a new technique of high spatial-temporal resolution, which can image dynamic changes of the whole brain microvasculature in response to brain activity in real time, ultrasonic brain function imaging (fuss), has been realized. The frame frequency imaging effect of up to kilohertz order is the key to research the dynamic blood flow change condition. In addition, the technology is also applied to the leading-edge research directions of biomedical ultrasonics, such as real-time three-dimensional ultrasonic imaging, high-speed Doppler blood flow field velocity distribution imaging, two-dimensional real-time elastography, cardiac and aorta strain imaging and the like, and has very wide application prospects. However, the multi-angle coherent superposition imaging method is equivalent to reducing the frame rate again, for example, a 10000 frames per second frame rate can be realized by adopting a common ultrasonic plane wave imaging method, but in order to improve the resolution and contrast of an image, the multi-angle coherent superposition imaging method is adopted instead, an image is synthesized by transmitting/receiving results of 51 angles, and the frame rate is reduced to be lower than 200 frames per second. Therefore, the application range of the multi-angle coherent overlay imaging method is severely restricted.
In summary, how to improve the resolution and contrast of the image as much as possible while ensuring that the frame frequency is not decreased becomes an important problem to be solved in the ultrasonic plane wave imaging.
In recent years, papers on ultrasonic plane wave imaging methods based on compressed sensing are published at home and abroad. These methods are divided into two steps:
(1) each pixel point of the image is regarded as a grid node in a two-dimensional plane, and if a scatterer exists at each grid node to cause scattering of incident ultrasound and form an echo, it can be considered that the ultrasonic image to be formed actually reflects the distribution of the scattering intensity of the scatterer on the grid node in the two-dimensional plane. Firstly, a mathematical model reflecting the relationship between the ultrasonic echo radio-frequency signal s and the scattering intensity distribution I of the scatterers on the grid nodes needs to be established, and an equation set in the following form is formed:
s=MI
where matrix M is a relationship matrix. Due to the existence of noise in the ultrasonic echo radio frequency signal during actual imaging, solving the equation set is usually an uncertain problem, and a unique solution cannot be obtained.
(2) When I is sparse (sparse), that is, the number of non-zero elements therein is much smaller than the number of zero elements, the above equation system can be solved by a compressed sensing method:
Figure BDA0001239343820000031
where beta reflects how many noise components are allowed to be present.
For ultrasonic imaging, in the step (1), how to establish a mathematical model capable of reflecting the relation between s and I as truly as possible according to the physical principle followed by the mathematical model, and accordingly, establish a matrix M convenient for completing subsequent iterative computation is the key for determining the ultrasonic imaging quality and the practicability of the imaging method. In the step (2), a plurality of mature numerical iteration methods are available for the specific calculation method for solving the equation set, and the method does not belong to the important point set forth by the invention.
For the mathematical model reflecting the relationship between the ultrasonic echo radio frequency signal and the scattering intensity distribution of scatterers on the grid nodes in the step (1), the following three types have been published: a more complex model based on the compressibility distribution of the medium to be imaged (Martin f. schiffner and Georg Schmitz, et al, boghur university, germany); secondly, a relatively simple model (Shantou university Shen, etc.) based on frequency domain signal delay.
The final form of the model (i) is:
Figure BDA0001239343820000032
wherein G is an NelNk× N matrix, NelIs the number of channels, N, of the echo signal received by the ultrasonic transducer arraykDividing broadband ultrasonic echo signals into NkA discrete wave number kl,1≤l≤Nk,N=NxNzIs the total number of pixels (or number of grid nodes), N, of the imagex、NzThe number of rows and columns of image pixels in the x-direction (width direction) and z-direction (depth direction), respectively. Each element in the matrix G is defined as:
Figure BDA0001239343820000033
wherein m represents the m-th array element on the transducer, and m is more than or equal to 1 and less than or equal to NelI represents the ith pixel on the image, i is more than or equal to 1 and less than or equal to N,
Figure BDA0001239343820000034
sound pressure, r, representing incident ultrasoundel,mRepresenting the spatial position, r, of the m-th array element on the ultrasonic transduceriIndicating the position of the ith pixel on the image, gl(rel,m-ri) Is the green's function of open space, defined as:
Figure BDA0001239343820000041
where j represents the imaginary part, where,
Figure BDA0001239343820000042
is a second type of Hankel function of zero order. p is a radical ofscRepresenting ultrasonic echo radio frequency signals, gammaκRepresenting the distribution of compressibility of the medium to be imaged (compressibility of the medium is the main factor determining its acoustic scattering intensity).
The final form of model (c) is:
X(ω)=A(ω)·S(ω)
because the processing is based on frequency domain signals, in practice, the value of omega-2 pi f is taken0Wherein f is0The center transmit frequency of the ultrasound transducer used. X is an ultrasonic echo radio frequency signal after short-time Fourier transform, and S is the scattering intensity of a scatterer to be imaged, which corresponds to f on a frequency domain0A is a relationship of K × L consisting of time delay dataA matrix, defined as:
[A(ω)k]i=exp[jωτki)]
k is the number of channels for receiving echo signals by the ultrasonic transducer array, L is the total pixel number (or the number of grid nodes) of the image, K is more than or equal to 1 and less than or equal to K, i is more than or equal to 1 and less than or equal to L, and rhoiRepresenting a pixel point (or grid node) on the image,
Figure BDA0001239343820000043
representing the time delay for an echo signal emanating from a certain pixel point to reach a certain ultrasound transducer array channel,
Figure BDA0001239343820000044
representing the spatial location of a certain ultrasound transducer array channel,
Figure BDA0001239343820000045
representing a certain pixel piThe spatial position of (a). It should be noted that X is a frequency domain signal obtained by cutting out a small segment from all the ultrasonic echo radio frequency signals and performing short-time fourier transform, and therefore if all the ultrasonic echo radio frequency signals are divided into Q segments, all imaging needs to be completed, and the subsequent solving process needs to be repeated Q times.
After the two models are established, the equation set is solved by a compressed sensing method, and then the gamma can be solvedκ(model ①) or S (model ②), and then the vector is transformed into a matrix corresponding to the number of pixels of the image, so that the image which is expected to be obtained can be displayed.
The two mathematical models reflecting the relationship between the ultrasonic echo radio-frequency signal and the scattering intensity distribution of the scatterers on the grid nodes have limitations respectively.
The model ① is established based on proven accurate mathematical model of sound propagation and scattering, and has the advantages of truly reflecting various physical phenomena of sound in medium, but has the obvious disadvantages of being too complex
Figure BDA0001239343820000051
The size of the method is too large, a large amount of memory is required to be occupied, and meanwhile, the calculation amount of the subsequent solving process is huge. Taking the imaging experimental data in the paper as an example, when N isx=400,Nz=600,Nel=128,NkAt 1000, the matrix G occupies up to 458GB of memory. Therefore, in order to realize the algorithm, the method of recalculating the numerical values of the elements of the G is only needed to be adopted each time the G is called, so that the calculation amount is greatly increased. Moreover, in practice, the above parameter values cannot meet the requirements of normal medical ultrasonic imaging at all, and if the imaging depth exceeds 5cm, NzThe value of (A) is usually over 3000, so the memory occupation is further increased by 5 times, and the method is not a task which can be born by a common computer.
The model ② only considers the time delay of the ultrasonic echo radio frequency signal and only considers the central transmitting frequency f of the ultrasonic0Without considering other frequency components of the signal, the size of the relationship matrix a (ω) used therein is greatly reduced. However, the model still has the following problems. Firstly, all elements of the matrix a (ω) are nonzero, and X is a frequency domain signal obtained by performing short-time fourier transform on a small section of ultrasound echo radio-frequency signals obtained by cutting out the small section of ultrasound echo radio-frequency signals, and if all the ultrasound echo radio-frequency signals are divided into Q sections, all imaging needs to be completed, and a subsequent solving process needs to be repeated Q times, so that the calculation amount is still large when subsequent matrix multiplication is performed. Secondly, to facilitate the time delay calculation of the signal, all operations of the model are performed in the frequency domain. This requires first converting the time domain ultrasound echo rf signal to the frequency domain by a short time fourier transform. This procedure not only increases the amount of computation, but also introduces computation errors due to limited signal length, which in turn affects the final imaging quality.
In view of the above, there is a need to develop a new method to overcome the above-mentioned drawbacks.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to simplify a relation matrix as much as possible and reduce the memory storage space and the calculated amount during operation compared with a model (i); with respect to model 2, the use of fourier transforms and frequency domain calculations is avoided.
In order to achieve the above purpose, the present invention provides an ultrasonic imaging method based on point spread function measurement and compressive sensing of an ultrasonic imaging system, so as to achieve imaging with the method only requiring a low-level hardware computing platform while ensuring high frame frequency and high imaging quality, and facilitate the realization of industrial transformation of the present invention.
The invention provides an ultrasonic imaging method based on point spread function measurement and compressed sensing of an ultrasonic imaging system, which comprises the following steps: obtaining a point spread function of the ultrasound imaging system; establishing a relation matrix M according to the point spread function; and establishing an equation set reflecting the relationship between the ultrasonic echo radio-frequency signal s and the scattering intensity distribution I of the scattering particles on the pixel points of the ultrasonic image: s ═ MI; it is characterized in that a threshold value is set, and all elements in the relation matrix M which are lower than the threshold value are set to be 0.
In some embodiments, the point spread function of the ultrasound imaging system at spatial positions corresponding to all pixel points on an ultrasound image in a certain ultrasound emission mode is obtained through an experimental measurement.
In some embodiments, the manner of experimental measurement may include the steps of: (i) placing a scatterer with a small enough size at a spatial position corresponding to a certain pixel point on the ultrasonic image, and simultaneously not having any interference of the scatterer at other positions; (ii) the ultrasonic imaging system transmits an ultrasonic signal in a certain mode, and an ultrasonic echo signal is formed after the ultrasonic signal is reflected by the scatterer and is received by the ultrasonic imaging system, wherein the received ultrasonic echo signal is a point spread function of the system at the spatial position in the certain ultrasonic transmission mode; (iii) and (ii) executing the steps (i) and (ii) on all the pixel points on the ultrasonic image to obtain the point spread function of the ultrasonic imaging system at the spatial positions corresponding to all the pixel points on the ultrasonic image in a certain ultrasonic emission mode.
In some embodiments, the experimentally measured obtaining of the point spread function of the ultrasound imaging system at a spatial position corresponding to all pixel points on an ultrasound image in a certain ultrasound emission mode may include, but is not limited to, a measurement with a nylon wire in a water tank.
In some embodiments, the method may further comprise the steps of: and solving the equation set s-MI by a mature compressed sensing algorithm to obtain a vector I, converting the vector I into a matrix corresponding to the number of image pixels, and then adjusting the dynamic range, performing digital scanning conversion and the like to obtain the expected ultrasonic image.
In some embodiments, the mature compressed sensing algorithm includes, but is not limited to, matching pursuit (matching pursuit method), Bregman algorithm, operator/variable partitioning, FPC (Fixed-point continuity) algorithm, L1-magic algorithm, newton's descent method, and the like.
In some embodiments, when I is not sparse, I may be subjected to a sparse transformation Ψ, where θ is a coefficient of I in the sparse transformation domain, and θ is sparse, which may be solved according to a solution formula for compressive sensing
Figure BDA0001239343820000071
To solve for I, where β indicates how many noise components are allowed to be present.
In some embodiments, the sparse transform Ψ may include, but is not limited to, a Discrete Cosine Transform (DCT), various wavelet transforms, and the like.
In some embodiments, the ultrasound imaging system may employ an ultrasound plane wave transmit mode.
In some embodiments, the ultrasound imaging system may employ an ultrasound convex wave emission mode.
In some embodiments, the ultrasound imaging system may employ an ultrasound concave wave transmit mode.
In some embodiments, the ultrasound imaging system may employ a transmit mode that is excited by an arbitrary irregular waveform signal.
The invention ensures the ultrasonic imaging with high frame frequency and high imaging quality, and simultaneously realizes the imaging only by a hardware computing platform with a lower level, thereby having great practical value.
These and other advantages of the present invention will be appreciated by those skilled in the art upon review of the entire specification and claims.
Drawings
Fig. 1 shows the results of a simulation experiment using a method according to an embodiment of the invention for imaging a cavity contrast phantom.
Fig. 2 shows the results of a simulation experiment using a conventional time delay overlay (DAS) to image an aerial contrast phantom.
Detailed Description
The following describes an embodiment of the present invention with reference to the drawings. In the following description of the embodiments of the present invention, some specific features are described in order to better understand the present invention, but it is apparent that not all of the features are necessary to implement the present invention to those skilled in the art. The embodiments of the present invention described below are merely exemplary embodiments of the present invention, which should not be construed as limiting the present invention. In addition, some well-known techniques have not been described in order to avoid obscuring the present invention.
The method of the present invention is implemented using an ultrasound imaging system. In one embodiment, an ultrasound transducer array is first excited using computer-controlled ultrasound transmit circuitry of an ultrasound imaging system to transmit ultrasound signals. When the channels (each channel corresponding to an array element) of the ultrasound transducer array are excited simultaneously, the emitted ultrasound signals are a set of plane wave signals, i.e. the wave fronts are considered to be perpendicular to the ultrasound emission direction, and the time of arrival of the wave fronts at a certain depth in the imaging plane is consistent. The ultrasonic signal propagates in the medium and is scattered to form an ultrasonic echo signal. The ultrasonic echo signals are received by the ultrasonic transducer array and then sampled by the ultrasonic receiving circuit to form ultrasonic echo radio frequency signals. The ultrasonic echo radio frequency signals are sent back to the computer, and the ultrasonic plane wave imaging based on the compressed sensing is realized in the computer.
In this embodiment, the known ultrasound transducer array comprises K array elements, wherein the K-th array element has the coordinate (x)k,0). The number of pixels of the ultrasound image to be formed (i.e., the number of mesh nodes that divide the imaging plane) is N ═ Nx×NzIn which N isx、NzThe number of rows and columns of image pixels in the x-direction (width direction) and z-direction (depth direction), respectively. The coordinate of scatterer n at a certain grid node is (x)n,zn). The sampling frequency of the ultrasonic echo radio frequency signal is fsAnd if the number of sampling points of each channel is D, the total number of the ultrasonic radio frequency echo data acquired by one-time ultrasonic plane wave transmission/reception is D × K.
Firstly, a point spread function of the used ultrasonic imaging system in a certain ultrasonic emission mode is obtained through an experimental measurement mode. The experiments were generally performed in a water bath. In one embodiment, a scatterer with a sufficiently small size (for example, a thin nylon wire is vertically tensioned in a direction perpendicular to an imaging plane) is placed at a spatial position corresponding to a certain pixel point on an image, and no interference of the scatterer exists at other positions, the system transmits an ultrasonic signal of a certain mode, and after the ultrasonic signal is reflected by the scatterer, an ultrasonic echo signal received by the system, namely a point spread function of the system at the spatial position in the certain ultrasonic transmission mode, can be regarded as a matrix with a size of D × K, and can be further converted into a vector m with a length of D × K.
Thus, for scatterer n at each grid node, a vector m may be generatednThrough experimental measurement, point spread functions of the system on spatial positions corresponding to all pixel points on an image in a certain ultrasonic emission mode are obtained, namely N scatterers are combined to form a D × K row, and a relation matrix M of N columns is set as I for all grid nodesThe scattering intensity of a scatterer at a point, i.e., I, is a vector of length N. Then there are:
s=MI
in the relationship matrix M at this time, most elements have values close to 0. Therefore, a threshold value can be set, and all elements in M lower than the threshold value are set to be 0, so that M can be stored and used in a sparse expression mode, and the memory storage space occupied by M and the calculation amount are greatly reduced.
And establishing an equation system reflecting the relation between the ultrasonic echo radio-frequency signal s and the scattering intensity distribution I of the scatterers on the grid nodes. And finally, solving the equation set through a mature compressed sensing algorithm to obtain a vector I, converting the vector I into a matrix corresponding to the number of image pixels, and then obtaining the ultrasonic image which is expected to be obtained through steps of adjusting the dynamic range, performing digital scanning conversion and the like. The mature compressed sensing algorithm includes, but is not limited to, matching pursuit (matching pursuit method), Bregman algorithm, operator/variable scattering, FPC (Fixed-point continuity), L1-magic algorithm, newton descent method, etc.
In this embodiment, the ultrasound imaging system employs an ultrasound plane wave emission mode. But in practice the method is not limited to only the ultrasonic plane wave transmission mode. For example, if the ultrasound system employs a convex or concave wave transmit mode, or even a transmit mode excited by an arbitrary irregular waveform signal, imaging can be achieved using the present method.
It should be noted that compressed sensing theory requires that the unknown signal I is sparse. In actual ultrasound imaging, the scatter intensity distribution of scatterers on the mesh nodes may not satisfy this condition by itself. In this case, I is sparsely transformed Ψ, let θ ═ Ψ I, where θ is the coefficient of I in the sparse transform domain. At this time, θ is sparse, and the solution formula using compressed sensing becomes:
Figure BDA0001239343820000091
therefore, the equation set can be solved by a mature compressed sensing algorithm to obtain I. The sparse transform Ψ includes, but is not limited to, a Discrete Cosine Transform (DCT), various wavelet transforms, and the like.
It should also be noted that the method for obtaining the point spread function of the used ultrasound imaging system in a certain ultrasound transmission mode through experimental measurement includes, but is not limited to, the above-mentioned manner of measurement by using nylon wire in the water tank, and other suitable experimental devices and materials can be used for measurement.
The model used in the invention is greatly simplified compared with the model (I). The time domain expression problem of signal time delay calculation is solved, Fourier transform and calculation in a frequency domain are not needed any more, and calculation errors caused by Fourier transform are avoided. In addition, because the relation matrix M established by the model is finally simplified into a matrix capable of sparse expression, compared with the model I, the memory storage space occupied by the relation matrix M and the calculation amount are greatly reduced. Compared with the model ii, since all the ultrasonic echo radio frequency signals need to be divided into Q segments (a certain overlap is needed between two front and back segments of the data to improve the resolution in the depth direction), the length of 4000 multiple data points needs to be divided into at least 100 segments, 100 segments in the first embodiment, 200 segments in the second embodiment, and 400 segments in the third embodiment), each segment of the truncated data is subjected to short-time fourier transform to obtain a frequency domain signal, and the subsequent solution calculation is repeated. Therefore model 2 is much larger in total calculation amount than the model used in the present invention. In addition, model 2 is convenient for time delay calculation of signals, and all operations are performed in a frequency domain. The short-time Fourier transform calculation not only increases the calculation amount, but also introduces calculation errors caused by limited signal length, and further influences the final imaging quality.
Reference is now made to fig. 1 and 2, which show the results of simulating ultrasound imaging using the ultrasound imaging simulation software Field II. Fig. 1 shows a method according to an embodiment of the invention (where K-128, D-4364, N)x=256,Nz3000) simulation experiment results of imaging a hollow contrast phantom. Fig. 2 shows the results of a simulation experiment using a conventional time delay overlay (DAS) to image an aerial contrast phantom. As can be seen from fig. 1 and 2, the contrast of the image formed by the method of the present invention is significantly better than that of the conventional method.
Therefore, the novel ultrasonic imaging method provided by the invention can realize the rapid ultrasonic imaging with ultrahigh frame frequency on one hand, ensures higher imaging quality on the other hand, can be realized only by a lower-level hardware operation platform, and is convenient for realizing industrial conversion.
While this invention has been described in terms of a preferred embodiment, there are alterations, permutations, and various substitute equivalents, which fall within the scope of this invention. It should also be noted that there are many alternative ways of implementing the methods and systems of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, permutations, and various substitute equivalents as fall within the true spirit and scope of the present invention.

Claims (7)

1. An ultrasonic imaging method based on point spread function measurement and compressed sensing of an ultrasonic imaging system comprises the following steps:
obtaining a point spread function of the ultrasound imaging system;
establishing a relation matrix M according to the point spread function; and
establishing an equation system reflecting the relationship between the ultrasonic echo radio-frequency signal s and the scattering intensity distribution I of the scattering particles on the pixel points of the ultrasonic image: s ═ MI;
it is characterized in that the preparation method is characterized in that,
setting a threshold value, and setting elements in the relation matrix M which are lower than the threshold value to be 0;
the point spread function of the ultrasonic imaging system at the spatial position corresponding to all the pixel points on the ultrasonic image in a certain ultrasonic emission mode is obtained by an experimental measurement mode, and the method comprises the following steps:
(i) placing a scatterer with a small enough size at a spatial position corresponding to a certain pixel point on the ultrasonic image, and simultaneously not having any interference of the scatterer at other positions;
(ii) the ultrasonic imaging system transmits an ultrasonic signal in a certain mode, and an ultrasonic echo signal is formed after the ultrasonic signal is reflected by the scatterer and is received by the ultrasonic imaging system, wherein the received ultrasonic echo signal is a point spread function of the system at the spatial position in the certain ultrasonic transmission mode;
(iii) and (ii) executing the steps (i) and (ii) on all the pixel points on the ultrasonic image to obtain the point spread function of the ultrasonic imaging system at the spatial positions corresponding to all the pixel points on the ultrasonic image in a certain ultrasonic emission mode.
2. The method of claim 1, wherein the experimentally measured obtaining of the point spread function of the ultrasound imaging system at spatial positions corresponding to all pixel points on an ultrasound image in a certain ultrasound emission mode includes but is not limited to: in a water tank with a nylon thread measurement.
3. The method according to claim 1, characterized in that the method further comprises the steps of: and solving the equation set s-MI by a mature compressed sensing algorithm to obtain a vector I, converting the vector I into a matrix corresponding to the number of image pixels, and then adjusting the dynamic range and performing digital scanning conversion to obtain the expected ultrasonic image.
4. The method of claim 3, wherein the mature compressed sensing algorithm comprises: matching pursuit method, Bregman algorithm, operator/variable splitting, FPC algorithm, L1-magic algorithm, Newton descent method.
5. The method according to claim 3 or 4, characterized in that when I is not sparse, I is sparsely transformed Ψ, let θ ═ Ψ I, where θ is the coefficient of I in the sparse transform domain,theta is sparse and is solved according to a compressed sensing solution formula
Figure FDA0002338299860000021
To solve for I, where β indicates how many noise components are allowed to be present.
6. The method according to claim 5, wherein the sparse transform Ψ comprises: discrete Cosine Transform (DCT), various wavelet transforms.
7. The method of claim 1, wherein the ultrasound imaging system employs an ultrasound plane wave transmit mode, an ultrasound convex wave transmit mode, an ultrasound concave wave transmit mode, or a transmit mode excited by any irregular waveform signal.
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