CN110051352A - A kind of conductivity imaging system based on magnetosonic electricity principle - Google Patents

Abstract

A conductivity imaging system based on the principle of magneto-acoustic electricity, the imaging platform of which transmits the collected magneto-acoustic and electric signals to an image reconstruction module. The imaging platform includes a sound field driving excitation module, a magnetic field excitation module and a detection module; the sound field driving excitation module generates a sound field excitation source; the magnetic field excitation module is an open magnet, placed near the living body, and the generated non-uniform static magnetic field acts on the living body Under the action of non-uniform static magnetic field and sound field, the living body generates motion source current, and the detection module collects motion source current and converts it into magneto-acoustic-electric voltage signal. The invention utilizes electrodes to detect magneto-acoustic electrical signals, obtains the conductivity distribution image of the imaging body through the image reconstruction module, and realizes the detection of the conductivity distribution in the target area of biological tissue.

Description

A conductivity imaging system based on the principle of magneto-acoustic electricity

technical field

The invention relates to an open-type magneto-acoustic electric conductivity imaging system.

Background technique

It is of great significance to realize the early diagnosis of the disease. On the one hand, it can reduce the suffering of patients during the treatment process, as well as the high medical expenses, and more importantly, it can improve the survival rate. Imaging methods with electrical parameters as imaging target parameters can realize early diagnosis of diseases. Magneto-acoustic-electric imaging takes electrical parameters as imaging target parameters, and a medical imaging method with good application prospects has the advantages of high contrast and high resolution.

In 1998, Han wen et al. proposed Hall effect imaging, and under the excitation of 4.0T magnetic resonance magnetic field static magnetic field, the experimental signal of bacon meat was detected by electrodes, but the configuration of the experimental system was not mentioned too much. In 2003, Hanwen discussed the imaging system in detail in the patent US6520911B1. During the configuration of the system, a uniform static magnetic field was used as the magnetic field excitation source for magneto-acoustic-electric imaging. In 2007, Y. Xu, S Haider and others proposed a magneto-acoustic imaging based on the reciprocity theorem on the basis of the Hall effect, and obtained the distribution map of the reciprocal current density by experimental methods. Density is simulated, but no reconstruction method for conductivity is given. For the uniform static magnetic field as the magnetic field excitation source for magneto-acoustic-electric imaging, many scholars have done research on the conductivity reconstruction algorithm. In 2014, Ammari H, Grasland-Mongrain P. from the University of Lyon, France, and others reported on magneto-acoustic-electric imaging. The theoretical analysis and simulation study under different signal-to-noise ratio conditions (Ammari H et al., 2014). In the same year, Guo Liang from the Institute of Electrical Engineering, Chinese Academy of Sciences used the time-transmission method, compressed sensing and quasi-Newton iterative algorithms to reconstruct the conductivity of the electrode-detected magneto-acoustic-electric imaging through simulation analysis (Guo L et al., 2014). Kunyansky L reported the reconstruction algorithm of conductivity boundary in 2017, designed a 3D scanning platform, detected the magneto-acoustic electrical signal of beef tissue using electrodes, and reconstructed the interface information of beef tissue, which was not obtained by experimental signal reconstruction. Image of conductivity. The experimental platforms reported above are either excited by a uniform static magnetic field, or the target is a small phantom structure, so it is reasonable to assume that the static magnetic field is uniform.

To sum up, there are no reports of actual medical systems yet. For practical medical systems, there are two solutions to realize the static magnetic field, (1) using a uniform static magnetic field as the magnetic field excitation; (2) using a non-uniform static magnetic field as the magnetic field excitation source. For scheme (1), the realization of uniform static magnetic field can learn from the design concept of static magnetic field in magnetic resonance imaging, and use permanent magnets, electromagnets or superconducting magnets to realize the reconstruction of electrical conductivity. The realization of the static magnetic field will greatly increase the cost of the static magnetic field generating device, and further greatly increase the cost of the clinical application equipment of magneto-acoustic electro-imaging. Moreover, the closed environment reduces the imaging area and is not suitable for claustrophobic patients. For the solution (2), a completely uniform static magnetic field generating device is not required, which greatly reduces the cost of the medical system. However, the reconstruction algorithm currently studied is not applicable.

The existing magneto-acoustic-electric imaging platform is difficult to convert into a medical imaging system, and has the following shortcomings: (1) the current theoretical model is aimed at a uniform static magnetic field, and the realization of a completely uniform static magnetic field greatly increases the cost of the equipment; (2) non- The uniform static magnetic field as the excitation source of the magnetic field can reduce the cost of the equipment, but there is no corresponding reconstruction algorithm at present.

SUMMARY OF THE INVENTION

The purpose of the present invention is to overcome the shortcomings of the prior art and propose a conductivity imaging system based on the principle of magneto-acoustic electricity.

The conductivity imaging system based on the magneto-acoustic-electric principle of the present invention includes an imaging platform and an image reconstruction module. The imaging platform is connected with the image reconstruction module, and the collected magneto-acoustic electrical signals are transmitted to the image reconstruction module through the transmission line.

The imaging platform includes a sound field driving excitation module, a magnetic field excitation module and a detection module. The sound field drive excitation module generates the sound field excitation source, that is, the ultrasonic wave. The ultrasonic wave attenuates very quickly in the air. In order to better propagate in the living body, it is necessary to couple the water bladder. The coupled water bladder and the sound field drive excitation module are in complete contact to reduce the Attenuation of sound waves. The non-uniform static magnetic field generated by the magnetic field excitation module acts on the living body, and the living body will generate a motional source current under the action of the non-uniform static magnetic field and sound field. The detection module collects the motional source current and converts it into a magneto-acoustic-electrical voltage signal.

The sound field drive excitation module is composed of an ultrasonic drive excitation source, an ultrasonic array and a coupled water bladder. One end of the ultrasonic array is connected to the ultrasonic driving excitation, and the other end of the ultrasonic array is in contact with the coupling water bladder. The ultrasonic drive excitation source excites the ultrasonic array to generate ultrasonic waves. The coupling water bag is filled with water, and the coupling water bag is filled in the space between the ultrasonic array and the organism, so that the ultrasonic waves generated by the ultrasonic array can be transmitted into the organism.

The magnetic field excitation module is an open magnet placed near the living body.

The detection module consists of electrodes, filter circuits, amplifier circuits and signal acquisition devices. The electrode is in contact with the living body to detect the voltage signal on the surface of the living body, the filtering and amplifying circuit realizes the filtering and amplification of the detection signal, and finally the signal collecting device realizes the signal collecting. One end of the electrode is connected to the living body, the other end of the electrode is connected to the input end of the filter circuit, the output end of the filter circuit is connected to the input end of the amplifying circuit, and the output end of the amplifying circuit is connected to the input end of the signal acquisition device. The output end of the device is connected with the image reconstruction module.

The image reconstruction module reconstructs the conductivity distribution according to the magneto-acoustic-electrical voltage signal of the organism output by the signal acquisition device.

The working process of the conductivity imaging system based on the magneto-acoustic-electric principle of the present invention is as follows:

The ultrasonic driving excitation source of the sound field driving excitation module generates a pulse excitation signal, which acts on the ultrasonic array, and the ultrasonic array is coupled with the living body through the coupling water bladder. The ultrasonic array emits ultrasonic waves to generate ultrasonic vibration in the biological tissue, causing local particle vibration of the biological tissue. The magnetic field excitation module generates a non-uniform static magnetic field in the vibration area of the biological tissue, and the ions vibrating in the biological tissue are subjected to the Lorentz force under the action of the non-uniform static magnetic field to generate charge separation, and then a local electric field is formed in the biological body, generating current distribution. The electrode attached to the living body measures the electrical signal, and after filtering and amplification by the filter circuit and amplifying circuit of the detection module, the voltage signal is output to the image reconstruction module by the signal acquisition device. The image reconstruction module utilizes the magneto-acoustic-electrical voltage signal of the organism and the known non-uniform magnetostatic distribution information, and uses an image reconstruction algorithm to reconstruct the electrical conductivity distribution.

The image reconstruction module uses two conductivity reconstruction algorithms to reconstruct the conductivity distribution. The reconstruction algorithm is a direct algebraic iterative conductivity reconstruction algorithm, and the reconstruction algorithm is an equivalent uniform field algebraic iterative conductivity reconstruction algorithm.

Algorithm 1, the direct algebraic iterative conductivity reconstruction algorithm, includes the following three steps:

1. Use the reciprocity theorem to establish the corresponding relationship between the actual measurement process and the physical quantities of the reciprocal process

(1) The actual measurement process is: under the action of the ultrasonic wave generated by the ultrasonic drive excitation module and the non-uniform static magnetic field generated by the magnetic field excitation module, the vibration velocity of the particle is v, and the non-uniform static magnetic field is B ₀ (r). The magnetic field is generated by the open magnets of the magnetic field excitation module, and the distribution of the strength of the non-uniform static magnetic field B ₀ (r) is known.

(2) The reciprocal process is: turn off the sound field drive excitation module, make the magnetic field excitation module not work, and pass a direct current of 1 ampere to the electrodes in the detection module, and the current density generated by this current in the living body is J _r (r ).

Under the excitation of the non-uniform static magnetic field B ₀ (r) generated by the magnetic field excitation module, the magneto-acoustic-electrical voltage distribution u(r,t) and the vibration velocity potential can be obtained based on the reciprocity theorem The relationship between the reciprocal process current density J _r (r) and the non-uniform static magnetic field B ₀ (r) generated by the magnetic field excitation module:

In formula (1), t represents the propagation time of ultrasonic waves, Ω represents the area where the organism is located, r represents the field point, that is, the point in the area Ω where the organism is located, represents the vibrational velocity potential, ρ ₀ is the density of the organism, J _r (r) is the current density of the organism in the reciprocal process, B ₀ (r) is the non-uniform static magnetic field distribution generated by the magnetic field excitation module, ▽· is the dispersion degree operator.

2. According to the magneto-acoustic-electrical voltage u(r,t) measured in the actual measurement process, the relationship between the reciprocal process current density J _r (r) and the static magnetic field B ₀ (r) is reconstructed according to formula (1)▽ ·(J _r (r)×B ₀ (r))

Vibration velocity potential in formula (1) The Green's function that satisfies is

According to the symmetry of formula (1) and Green's function, it can be known that the magneto-acoustic-electrical voltage u(r, t) satisfies:

In formula (2), r' is the source point, which represents the point in the area where the ultrasound array is located.

Using formula (2), the relationship between the current density J _r (r) of the reciprocal process and the non-uniform static magnetic field B ₀ (r) generated by the open magnet can be obtained. At the same time, since ρ ₀ is a constant, it is obtained:

In formula (3), c ₀ represents the speed at which the sound field drives the excitation module to generate ultrasonic waves, t _rd =2T ₀ -t+|r-r'|/c ₀ represents the time of reversal field, t represents the propagation time of ultrasonic waves, T ₀ Represents the moment of reversal u(r,t), r' represents the point in the area where the ultrasound array is located, r represents the point in the area Ω where the organism is located, S represents the surface of the area Ω where the organism is located, and n is the area where the organism is located Ω Unit normal vector at the boundary, u'(r',t _rd ) represents the first derivative of u(r',t _rd ), u"(r',t _rd ) represents u(r',t _rd )two order derivative.

The reconstruction of the variable H(r)=▽·(J _r (r)×B ₀ (r)) can be realized by using equation (3).

3. Reconstruct the conductivity distribution according to the variable H(r)

After realizing the distribution of the variable H(r)=▽·(J _r (r)×B ₀ (r)) using formula (3), the variable H(r) on each fault plane z ₀ of the biological tissue is can be expressed as which is:

The brackets (x, y, z ₀ ) of each variable represent the coordinates of the corresponding variable on each fault plane z ₀ inside the organism.

J _r (x,y,z ₀ ) is the current density of the reciprocal process on the z ₀ fault plane. Using Ohm's law, the current density J _r (x,y,z ₀ ) can be expressed as the gradient of the reciprocal process potential and The product between the conductivities, i.e.:

J _r (x,y,z)＝-σ(x,y,z)▽u _r (x,y,z)

So f(x,y,z ₀ ) can be expressed as:

where _ur (x, y, z ₀ ) is the distribution of the potential of the reciprocal process on the z ₀ fault plane, and σ(x, y, z ₀ ) is the distribution of the electrical conductivity of the organism on the z ₀ fault plane.

The distribution of the potential of the reciprocal process on the z ₀ fault plane satisfies the following relationship:

where I is the direct current of 1 ampere injected in the reciprocal process, r _A and r _B represent the position of the electrode pair in the detection module, Γ represents the surface of the region Ω where the target is located, and n represents the unit vector of the outer normal direction of the surface Γ .

on each fault plane z ₀ The value of is expressed as f(x, y, z ₀ ), and the method steps for reconstructing the conductivity σ from f(x, y, z ₀ ) are as follows:

1) Divide the organism into a series of sub-blocks, consider that the conductivity inside these sub-blocks is uniform, and give the initial value of the conductivity distribution matrix [σ] of the organism. Usually, the initial value of the conductivity is selected as 0.1S/m , the given error accuracy ε;

2) Calculate the electric scalar potential _ur (x, y, z ₀ ) of the reciprocal process according to formula (5);

3) Use formula (4) to reconstruct the conductivity distribution of the fault plane with z=z ₀ ;

4) Using the electrical conductivity distribution of each fault obtained in step 3), the electrical conductivity distribution of each sub-block is obtained by linear difference, thus obtaining the electrical conductivity distribution σ ^k of the entire three-dimensional area of the organism in the k-th iteration.

5) Calculate the relative error between the biological conductivity distribution σ ^k obtained in the k-th iteration and the k+1-th biological conductivity distribution σ ^k+1 , and compare whether the relative error satisfies the given error accuracy ε , if the given error accuracy ε is satisfied, stop the iteration. Otherwise, take the conductivity distribution σ ^k of the organism obtained for the kth time as the initial conductivity distribution, go to step 2), and the above process iterates successively until the relative error of the conductivity distribution of the organism obtained by two adjacent calculations satisfies precision requirements.

The reconstruction of building ▽·(J _r (r)×B ₀ (r)) can be achieved by using formulas (1) and (2), and the above steps 1) to 5) can be used to reconstruct the bioconductivity image. The conductivity reconstruction algorithm is called the direct algebraic iterative conductivity reconstruction algorithm.

Algorithm 2, the equivalent uniform field algebraic iterative conductivity reconstruction algorithm is as follows:

The equivalent uniform field algebraic iterative conductivity reconstruction algorithm is based on the relationship between the magneto-acoustic-electric voltage signal and the non-uniform static magnetic field B ₀ (r), and the non-uniform static magnetic field B ₀ (r) is used as the magneto-acoustic-electric voltage of the magnetic field excitation source The principle that the signal is equivalent to a magneto-acoustic-electrical voltage signal excited by a uniform static magnetic field is as follows: formulas (6)-(14).

Given a three-dimensional model, under the excitation of a non-uniform static magnetic field B ₀ (r), the current I(t) corresponding to the equivalent current source in the organism and the vibration velocity v of the ultrasonic wave generated by the sound field-driven excitation module in the organism are between The relationship is:

I(t)=∫ _s σv×B ₀ (r)·dS (6)

where S represents the surface element of the surface through which the equivalent current source flows.

According to the acoustic principle, the ultrasonic dynamic impulse M and the vibration velocity v need to satisfy:

where ρ ₀ is the density of the organism, and ▽ is the gradient operator.

Substituting equation (7) into equation (6), we can get:

where n represents the unit vector of the normal direction of the face element of the surface through which the equivalent current source flows.

Further using Stokes formula and vector identities, Equation (8) is simplified to:

Among them, l represents the line of the outer edge of the surface element, and the positive direction of l and the outer normal direction of S conform to the right-hand theorem, and the normal direction of S is n.

When considering practical applications, the frequency range of the energy emitted by the ultrasonic array contains very few DC frequencies, which means that the net momentum of the wave packet generated by the ultrasonic array is zero, so the first term on the right side of the equation (9) is zero.

At the same time, in the actual detection, the electrode can only detect a part of the current of the organism, so the current collected by the signal acquisition device is only a part of the current I(t). The acoustic and electrical voltage U(t) can be expressed as:

Equation (11) is the relationship between the detected magneto-acoustic-electrical voltage U(t), the non-uniform static magnetic field B ₀ (r), the electrical conductivity σ and the density ρ ₀ .

In practical application, ▽×B ₀ (r) is a very small quantity, so the second term on the right side of the equation (11) is a small quantity, ignoring this small quantity, so formula (11) can be simplified as:

In formula (12), when the direction of the unit vector n of the normal direction of the surface element of the surface through which the equivalent current source flows is equal to When the directions are the same, formula (12) can be expressed as:

in Taking the e _x direction component of this variable, formula (13) can be expressed as:

where B _oy and B _oz are the magnetic field distribution θ of B ₀ (r) along the y and z directions, respectively and B ₀ (r).

Equation (14) is the theoretical relationship that the magneto-acoustic-electrical voltage signal is equivalent to the magneto-acoustic-electrical voltage signal under the excitation of a uniform static magnetic field under the excitation of a non-uniform static magnetic field. Magneto-acoustic electrical signals are amplified or reduced times.

Algorithm 2, equivalent uniform field algebraic iterative conductivity reconstruction algorithm, the process is:

Firstly, the magneto-acoustic-electrical voltage signal u _in (r, t) collected under non-uniform static magnetic field excitation is adjusted to the equivalent magneto-acoustic-electrical voltage signal u _ho (r, t) collected under uniform field excitation using equation (14). ;

Then replace all non-uniform static magnetic fields B ₀ (r) in formulas (1)-(5) with uniform static magnetic fields B ₀ ;

Finally, the reconstruction of the conductivity is realized by using the algorithm-step 1)-5) of the direct algebraic iterative conductivity reconstruction algorithm.

In the equivalent uniform field algebraic iterative conductivity reconstruction algorithm, the magneto-acoustic-electrical voltage signal u _in (r,t) collected under the excitation of a non-uniform static magnetic field is adjusted to the magneto-acoustic-electrical voltage signal u _ho collected under the excitation of a uniform static magnetic field After (r, t), not only the direct algebraic iterative conductivity reconstruction algorithm can be used to reconstruct the conductivity, but also other conductivity reconstruction algorithms under the excitation of a uniform static magnetic field can be used to obtain the conductivity image.

Description of drawings

1 is a schematic diagram of the composition of the conductivity imaging system of the present invention;

2 is a schematic structural diagram of an embodiment of the conductivity imaging system of the present invention;

Fig. 3 The positional relationship between the organism and the coupled water bladder and the ultrasound array;

In the figure, A1 ultrasonic drive excitation source, A2 ultrasonic array, A3 coupled water bladder, A4 magnetic field excitation module, A5 organism, A6 electrode, A7 amplifier circuit, A8 filter circuit, A9 signal acquisition device, A10 image reconstruction module, A11 single ultrasound Probe, A12 magnetic field generated by magnetic field excitation module, A13 particle vibration velocity.

Fig. 4 is a flow chart of reconstruction algorithm;

Figure 5 is a flowchart of the second reconstruction algorithm.

Detailed ways

The present invention is further described below with reference to the accompanying drawings and specific embodiments.

The conductivity imaging system based on the magneto-acoustic-electric principle of the present invention includes an imaging platform and an image reconstruction module. The imaging platform is connected to the image reconstruction module A10, and the collected magneto-acoustic electrical signals of the imaging platform are transmitted to the reconstruction algorithm module A10.

As shown in FIG. 1 and FIG. 2 , the imaging platform includes a sound field driving excitation module, a magnetic field excitation module A4 and a detection module. The sound field excitation source module generates ultrasonic waves. The magnetic field excitation module A4 generates a magnetic field to stimulate A12 to act on the living body, and the living body generates a motion source current under the action of the magnetic field and the sound field. The detection module detects the current signal, and the image reconstruction module A10 reconstructs the conductivity distribution according to the voltage signal.

The sound field drive excitation module is composed of an ultrasonic drive excitation source A1, an ultrasonic array A2 and a coupled water bladder A3. One end of the ultrasonic array A2 is connected to the ultrasonic driving excitation source A1, and the other end of the ultrasonic array A2 is in contact with the coupling water bladder A3. The coupling water bladder A3 is filled between the ultrasonic array A2 and the living body A5, and is in contact with the ultrasonic array A2 and the living body A5. Good, as shown in FIG. 3 , the ultrasonic waves generated by the excitation of the ultrasonic array A2 by the ultrasonic-driven excitation source A1 can be propagated into the living body A5 .

The non-uniform static magnetic field A12 generated by the magnetic field excitation module A4 is generated by an open magnet.

The detection module consists of an electrode A6, a filter circuit A8, an amplifying circuit A7 and a signal acquisition device A9. The electrode A6 is in contact with the living body A5 to detect the voltage signal on the surface of the living body. The detected voltage signal is filtered and amplified by the filter circuit A8 and the amplifier circuit A7, and collected by the signal acquisition device A9. One end of the electrode A6 is connected to the living body A5, the other end of the electrode A6 is connected to the input end of the filter circuit A8, the output end of the filter circuit A8 is connected to the input end of the amplifying circuit A7, and the output end of the amplifying circuit A7 is connected to the signal acquisition. The input end of the device A9 and the output end of the signal acquisition device A9 are connected to the image reconstruction module A10.

The image reconstruction module A10 reconstructs the conductivity distribution according to the voltage signal of the living body A5 output by the signal acquisition device A9.

The working process of the conductivity imaging system based on the magneto-acoustic-electric principle of the present invention is as follows:

The ultrasonic driving excitation source A1 of the sound field driving excitation module generates a pulse excitation signal, which acts on the ultrasonic array A2, and the ultrasonic array A2 is coupled with the living body A5 through the coupling water bladder A3. The ultrasonic array A2 emits ultrasonic waves to generate ultrasonic vibrations in the tissue of the living body A5, causing local particle vibration of the living body tissue. The magnetic field excitation module A4 generates a non-uniform static magnetic field A12 in the tissue vibration area of the living body A5, and the ions vibrating in the living body A5 are subjected to the Lorentz force under the action of the non-uniform static magnetic field A12 to generate charge separation, and then in the living body A5. A local electric field is formed in it, resulting in a current distribution. The electrical signal is measured by the electrode A6 attached to the living body A5, filtered and amplified by the filter circuit A8 and the amplifier circuit A7 of the detection module, and the voltage signal is output by the signal acquisition device A9 to the image reconstruction module A10. The image reconstruction module A10 utilizes the voltage signal of the organism A5 and the known distribution information of the non-uniform magnetostatic A12, and uses an image reconstruction algorithm to reconstruct the conductivity distribution. The image reconstruction module A10 uses two conductivity reconstruction algorithms to reconstruct the conductivity distribution. The first reconstruction algorithm is a direct algebraic iterative conductivity reconstruction algorithm, and the second reconstruction algorithm is an equivalent uniform field algebraic iterative conductivity reconstruction algorithm.

The flow of reconstruction algorithm 1 is shown in Figure 4, and the steps are as follows:

1) Use u(r,t) and formula (2) to reconstruct the distribution of variable H(r);

2) Divide the organism into a series of sub-blocks, consider that the conductivity inside these sub-blocks is uniform, and give the initial value of the distribution matrix [σ] of the conductivity of the organism. Usually, the initial value of the conductivity is 0.1S/ m, the given error accuracy ε;

3) Calculate the electric scalar potential _ur (x, y, z ₀ ) of the reciprocal process according to formula (5);

4) Use formula (4) to reconstruct the conductivity distribution of the fault plane with z=z ₀ ;

5) using the electrical conductivity distribution of each fault obtained in step 3) to obtain the electrical conductivity distribution of each sub-block through the linear difference, thus obtaining the electrical conductivity distribution σ ^k of the entire three-dimensional area of the organism in the k-th iteration;

6) Calculate the relative error between the biological conductivity distribution σ ^k obtained in the k-th iteration and the k+1-th biological conductivity distribution σ ^k+1 , and compare whether the relative error satisfies the given error accuracy ε , if the given error accuracy ε is satisfied, stop the iteration. Otherwise, take the conductivity distribution σ ^k of the organism obtained for the kth time as the initial conductivity distribution, go to step 2), and the above process iterates successively until the relative error of the conductivity distribution of the organism obtained by two adjacent calculations satisfies precision requirements.

The process of reconstruction algorithm 2 is shown in Figure 5, and the steps are as follows:

1) Using equation (14), firstly adjust the magneto-acoustic-electrical voltage signal u in (r, t) collected under the excitation of the non-uniform static magnetic field B ₀ (r) to the magneto-acoustic-electrical voltage signal u _in (r, t) collected under the excitation of the equivalent uniform field B ₀ . voltage signal u _ho (r,t);

2) Then replace all non-uniform static magnetic fields B ₀ (r) in formulas (1)-(5) with uniform static magnetic fields B ₀ ;

3) Finally, use steps 1)-6) of Algorithm 1 to reconstruct the conductivity.

In the equivalent uniform field algebraic iterative conductivity reconstruction algorithm, the magneto-acoustic-electrical voltage signal u _in (r,t) collected under the excitation of the non-uniform static magnetic field B ₀ (r) is adjusted to the one collected under the excitation of the uniform static magnetic field B ₀ After the magneto-acoustic-electrical voltage signal u _ho (r, t), not only can the direct algebraic iterative conductivity reconstruction algorithm be used to reconstruct the conductivity, but also other conductivity reconstruction algorithms under the excitation of a uniform static magnetic field can be used to obtain conductivity images.

Claims (4)

1. a conductivity imaging system based on the principle of magneto-acoustic electricity, is characterized in that, described imaging system comprises imaging platform and image reconstruction module; It is transmitted to the image reconstruction module; the imaging platform includes a sound field driving excitation module, a magnetic field excitation module and a detection module; the sound field driving excitation module generates a sound field excitation source; The uniform static magnetic field acts on the living body, and the living body generates a motional source current under the action of the non-uniform static magnetic field and sound field, and the detection module collects the motional source current and converts it into a magneto-acoustic-electrical voltage signal; The sound field driving excitation module is composed of an ultrasonic driving excitation source, an ultrasonic array and a coupling water bladder; one end of the ultrasonic array is connected to the ultrasonic driving excitation, and the other end of the ultrasonic array is in contact with the coupling water bladder; the ultrasonic driving excitation source excites the ultrasonic array to generate ultrasonic waves ; The coupling water bag is filled with water, and the coupling water bag is filled in the space between the ultrasonic array and the organism, so that the ultrasonic waves generated by the ultrasonic array can be transmitted to the organism; The detection module is composed of an electrode, a filter circuit, an amplifier circuit and a signal acquisition device; the electrode is in contact with the organism to detect the voltage signal on the surface of the organism; one end of the electrode is connected to the organism, and the other end of the electrode is connected to the input end of the filter circuit. The output end of the filter circuit is connected to the input end of the amplifying circuit, the output end of the amplifying circuit is connected to the input end of the signal acquisition device, and the output end of the signal acquisition device is connected to the image reconstruction module; The image reconstruction module reconstructs the conductivity distribution according to the magneto-acoustic-electrical voltage signal of the organism output by the signal acquisition device. 2. The electrical conductivity imaging system based on the principle of magneto-acoustic electricity according to claim 1, wherein the image reconstruction module utilizes the magneto-acoustic-electric voltage signal of the living body and the known non-uniform magnetostatic distribution information, and image reconstruction algorithm is used to reconstruct the conductivity distribution; the image reconstruction module uses two conductivity reconstruction algorithms to reconstruct the conductivity distribution, the reconstruction algorithm one is the direct algebraic iterative conductivity reconstruction algorithm, and the second reconstruction algorithm is Equivalent Uniform Field Algebraic Iterative Conductivity Reconstruction Algorithm. 3. The conductivity imaging system based on the principle of magneto-acoustic-electricity according to claim 2, wherein the algorithm one is a direct algebraic iterative conductivity reconstruction algorithm, comprising the following three steps: (1) Use the reciprocity theorem to establish the corresponding relationship between the actual measurement process and the physical quantity of the reciprocal process; The actual measurement process is as follows: under the action of the ultrasonic wave generated by the ultrasonic drive excitation module and the non-uniform static magnetic field generated by the magnetic field excitation module, the vibration velocity of the particle is v, and the non-uniform static magnetic field is B ₀ (r). The magnetic field is generated by the open magnets of the magnetic field excitation module, and the distribution of the strength of the non-uniform static magnetic field B ₀ (r) is known; Described reciprocity process is: turn off the sound field drive excitation module, make the magnetic field excitation module not work, pass the direct current of 1 ampere to the electrode in the detection module, the current density that this current produces in the living body is J _r (r ); Under the excitation of the non-uniform static magnetic field B ₀ (r) generated by the magnetic field excitation module, the magneto-acoustic-electrical voltage distribution u(r,t) and the vibration velocity potential are obtained based on the reciprocity theorem The relationship between the reciprocal process current density J _r (r) and the non-uniform static magnetic field B ₀ (r) generated by the magnetic field excitation module is: In formula (1), t represents the propagation time of ultrasonic waves, Ω represents the area where the organism is located, r represents the field point, that is, the point in the area Ω where the organism is located, represents the vibrational velocity potential, ρ ₀ is the density of the organism, J _r (r) is the current density of the organism in the reciprocal process, B ₀ (r) is the non-uniform static magnetic field distribution generated by the magnetic field excitation module, is the divergence operator; (2) According to the magneto-acoustic-electrical voltage u(r,t) measured in the actual measurement process, the relationship between the reciprocal process current density J _r (r) and the static magnetic field B ₀ (r) is reconstructed according to formula (1). Vibration velocity potential The Green's function that satisfies is Bring it into formula (1), according to the symmetry of Green's function, it can be known that the magneto-acoustic-electrical voltage u(r, t) satisfies: In formula (2), r' is the source point, which represents the point in the area where the ultrasonic array is located; Using formula (2), the relationship between the current density J _r (r) of the reciprocal process and the non-uniform static magnetic field B ₀ (r) generated by the open magnet is obtained. At the same time, since ρ ₀ is a constant, it is obtained: In formula (3), c ₀ represents the speed at which the sound field drives the excitation module to generate ultrasonic waves, t _rd =2T ₀ -t+|r-r'|/c ₀ represents the time of reversal field, t represents the propagation time of ultrasonic waves, T ₀ Represents the moment of reversal u(r,t), r' represents the point in the area where the ultrasound array is located, r represents the point in the area Ω where the organism is located, S represents the surface of the area Ω where the organism is located, and n is the area where the organism is located Ω Unit normal vector at the outer boundary, u'(r',t _rd ) denotes the first derivative of u(r',t _rd ), u"(r',t _rd ) denotes u(r',t _rd ) Second Derivative; Use formula (3) to realize the variable reconstruction; (3) Reconstructing the conductivity distribution according to the variable H(r); Use formula (3) to realize the variable After reconstruction of the distribution of , the variable H(r) on each fault plane z ₀ of the biological tissue is Expressed as which is: The brackets (x, y, z ₀ ) of each variable represent the coordinates of the corresponding variable on each fault plane z ₀ inside the organism; J _r (x,y,z ₀ ) is the current density of the reciprocal process on the z ₀ fault plane. Using Ohm’s law, the current density J _r (x,y,z ₀ ) is expressed as the gradient of the reciprocal process potential and conductance The product between the rates, that is: So f(x,y,z ₀ ) is expressed as where _ur (x, y, z ₀ ) is the distribution of the potential of the reciprocal process on the z ₀ fault plane, and σ(x, y, z ₀ ) is the distribution of the electrical conductivity of the organism on the z ₀ fault plane; The distribution of the potential of the reciprocal process on the z ₀ fault plane satisfies the following relationship: Among them, I is the direct current of 1 ampere injected in the reciprocal process, r _A and r _B represent the position of the electrode pair in the detection module, Γ represents the surface of the region Ω where the target is located, and n represents the unit vector of the outer normal direction of the surface Γ ; on each fault plane z ₀ The value of is expressed as f(x, y, z ₀ ), and the method steps for reconstructing the conductivity σ from f(x, y, z ₀ ) are as follows: 1) Divide the organism into a series of sub-blocks, consider that the conductivity inside these sub-blocks is uniform, and give the initial value of the conductivity distribution matrix [σ] of the organism. Usually, the initial value of the conductivity is selected as 0.1S/m , the given error accuracy ε; 2) Calculate the electric scalar potential _ur (x, y, z ₀ ) of the reciprocal process according to formula (5); 3) Use formula (4) to reconstruct the conductivity distribution of the fault plane with z=z ₀ ; 4) using the electrical conductivity distribution of each fault obtained in step 3) to obtain the electrical conductivity distribution of each sub-block through the linear difference, thus obtaining the electrical conductivity distribution σ ^k of the entire three-dimensional area of the organism in the k-th iteration; 5) Calculate the relative error between the biological conductivity distribution σ ^k obtained in the k-th iteration and the k+1-th biological conductivity distribution σ ^k+1 , and compare whether the relative error satisfies the given error accuracy ε , if the given error accuracy ε is satisfied, stop the iteration; otherwise, take the conductivity distribution σ ^k of the organism obtained at the kth time as the initial conductivity distribution, go to step 2), and the above process iterates in turn until the adjacent two The relative error of the biological conductivity distribution obtained by the second calculation meets the accuracy requirements; Using formulas (1) and (2) can be achieved and then use the above steps 1) to 5) to realize the reconstruction of the biological conductivity image. 4. The electrical conductivity imaging system based on the principle of magneto-acoustic-electricity according to claim 2, wherein the algorithm two equivalent uniform field algebraic iterative conductivity reconstruction algorithm is based on the magneto-acoustic-electrical voltage signal and the non-uniform static magnetic field The relationship between B ₀ (r) and the non-uniform static magnetic field B ₀ (r) as the magnetic field excitation source is equivalent to the magneto-acoustic-electric voltage signal excited by the uniform static magnetic field. The principle is as follows: formula (6) -(14) shows: Given a three-dimensional model, under the excitation of a non-uniform static magnetic field B ₀ (r), the current I(t) corresponding to the equivalent current source in the organism and the vibration velocity v of the ultrasonic wave generated by the sound field-driven excitation module in the organism are between The relationship is: I(t)=∫ _s σv×B ₀ (r)·dS (6) where S represents the surface element of the surface through which the equivalent current source flows; According to the acoustic principle, the ultrasonic dynamic impulse M and the vibration velocity v need to satisfy: where _ρ0 is the density of the organism, is the gradient operator; Substituting equation (7) into equation (6), we can get: where n represents the unit vector of the normal direction of the surface element of the surface through which the equivalent current source flows; Further using Stokes formula and vector identities, Equation (8) is simplified to: Among them, l represents the line of the outer edge of the surface element, and the positive direction of l and the outer normal direction of S conform to the right-hand theorem, and the normal direction of S is n; When considering practical applications, the frequency range of the energy emitted by the ultrasonic array contains very few DC frequencies, which means that the net momentum of the wave packet generated by the ultrasonic array is zero, so the first term on the right side of the equation (9) is zero; At the same time, in the actual detection, the electrode can only detect a part of the current of the organism, so the current collected by the signal acquisition device is only a part of the current I(t). The acoustic and electrical voltage U(t) is expressed as: Equation (11) is the relationship between the detected magneto-acoustic-electrical voltage U(t), the non-uniform static magnetic field B ₀ (r), the electrical conductivity σ and the density ρ ₀ ; In practical application, is a very small quantity, so the second term on the right side of the equation (11) is a small quantity, ignoring this small quantity, so formula (11) is simplified to: In formula (12), when the direction of the unit vector n of the normal direction of the surface element of the surface through which the equivalent current source flows is equal to When the directions are the same, formula (12) is expressed as: in Taking the e _x direction component of this variable, formula (13) is expressed as: Among them, B _oy and B _oz are the magnetic field distributions of B ₀ (r) along the y and z directions, respectively, and θ represents and the angle between B ₀ (r); Equation (14) is the theoretical relationship that the magneto-acoustic-electrical voltage signal is equivalent to the magneto-acoustic-electrical voltage signal under the excitation of a uniform static magnetic field under the excitation of a non-uniform static magnetic field. Magneto-acoustic electrical signals are amplified or reduced times; The steps of the algorithm 2 equivalent uniform field algebraic iterative conductivity reconstruction algorithm are: Firstly, the magneto-acoustic-electrical voltage signal u _in (r, t) collected under non-uniform static magnetic field excitation is adjusted to the equivalent magneto-acoustic-electrical voltage signal u _ho (r, t) collected under uniform field excitation using equation (14). ; Then replace all non-uniform static magnetic fields B ₀ (r) in formulas (1)-(5) with uniform static magnetic fields B ₀ ; Finally, the reconstruction of the conductivity is realized by using the algorithm-step 1)-5) of the direct algebraic iterative conductivity reconstruction algorithm.