A rapid magnetoacoustic-electro-tomography method without mechanical rotation and scanning measurement

Abstract

This invention provides a rapid magnetoacoustic-electroelectric tomography (MAET) method that eliminates the need for mechanical rotation and scanning. Addressing the problems of slow speed, poor stability, and low imaging accuracy in existing MAET rotational scanning measurements, this invention proposes a magnetoacoustic-electroelectric measurement theory suitable for ring-shaped acoustic source excitation and electrode detection based on acoustic radiation and magnetoacoustic-electroelectric coupling mechanisms. A MAET imaging method based on cyclic excitation by multiple ring-shaped acoustic sources and synchronous measurement by multiple electrodes is developed. Based on the influence of the number and position of the ring-shaped acoustic sources and electrodes on imaging quality, the minimum configuration requirements for the MAET system are obtained, and an optimized configuration scheme for rapid MAET imaging is proposed. This invention utilizes phased-array scanning measurement with no transducer required, and eliminates the need for mechanical rotation of the object. Electronic control enables cyclic excitation of the acoustic sources and synchronous measurement by multiple electrodes, improving imaging speed and stability. This invention is easily integrated with commercial ultrasound CT systems to achieve cross-scale multimodal imaging combining ultrasound and electrical impedance tomography.

Description

Technical Field

[0001] This invention relates to the fields of medical ultrasound and electrical impedance imaging, and more specifically to magnetoacoustic-electrochemical tomography techniques and methods based on the measurement of tissue electrical impedance differences. Technical Background

[0002] Cancer is a serious threat to human health. Commonly used methods such as X-rays, ultrasound, and MRI can detect and characterize changes in tissue morphology and physical parameters, but they still suffer from problems such as ionizing radiation, low spatial resolution, and insufficient real-time performance. Studies have shown that relative changes in tissue conductivity are significantly greater than changes in tissue morphology and structure, several times greater than changes in acoustic impedance, and are considered a highly sensitive parameter for the early diagnosis of tissue lesions. For the detection of biological tissue electrical impedance, techniques such as electrical impedance imaging, magnetic induction imaging, and magnetic resonance electrical impedance imaging have been developed, but their practical application is still limited by high current injection, tissue shielding effects, pathological image reconstruction, slow imaging speed, and poor spatial resolution. In recent years, based on the coupling characteristics of magnetoacoustic-electricity (MAE) and their imaging complementarity, a Hall effect-based magnetoacoustic-electric tomography (MAET) technique has been proposed. This technique utilizes the interaction between ultrasonic vibration and magnetic field at the conductive tissue boundary during sound propagation to generate an induced current. The MAE signal detected by electrodes located outside the tissue contains information on the location of the tissue boundary and changes in conductivity, enabling the reconstruction of the tissue conductivity distribution during sound propagation. MAET does not require current injection, and sound propagation is not affected by tissue insulation. It combines the advantages of EIT's high contrast and ultrasound imaging technology's high resolution, showing significant research value and application potential in the field of biomedical imaging.

[0003] Traditional B-mode MAE imaging utilizes a planar or focused transducer to linearly scan the object, receiving the MAE signal via a vertically placed electrode plate. To improve axial resolution, imaging depth, and signal-to-noise ratio, short pulses or coded pulses are used for excitation to detect and image the conductivity boundaries of layered models. Previous studies generally employed a large-aperture transducer with a strongly directional or focused acoustic beam for scanning measurements, achieving good imaging results for layered tissues perpendicular to the acoustic beam. However, the MAE signal attenuates significantly with increasing angle between the incident acoustic beam and the tissue boundary, thus failing to achieve accurate imaging of objects of arbitrary shapes. Further research introduced rotational scanning measurements to compensate for the MAE signal attenuation caused by the tissue boundary angle, achieving MAET. Studies show that using plane waves instead of linear scanning can improve imaging speed; however, since the beam cannot cover the entire model, a small rotation angle is required to ensure imaging quality. Furthermore, plane wave synthesis based on line source phased array increases system complexity and cost. In our previous research, considering the radiation directivity of the actual transducer and the tilt angle of the tissue conductivity boundary, we derived a general principle of MAET applicable to objects of arbitrary shapes. Theoretical and experimental results proved the determining factors of MAE signal attenuation and B-mode image distortion. We demonstrated that small rotation angles and linear scanning steps are necessary to improve MAET image therapy, but this would severely reduce measurement speed and imaging stability.

[0004] Significant progress has been made in MAET research in recent years, but there are still many areas for improvement in measurement methods and system control. Due to the directional limitations of conventional planar piston transducers, the beam cannot completely cover the object under test, requiring lengthy linear scans to achieve B-mode imaging. The complex mechanical rotation and linear scanning of MAET systems reduce measurement speed and stability, leading to decreased imaging accuracy. While phased-array transducers using linear array transducers can eliminate the linear scanning process, they require complex and expensive phased-array systems. Traditional MAET electrodes are generally placed parallel to the sound beam, primarily receiving the MAE signal generated by the induced current perpendicular to the electrode, thus losing information about the parallel direction and reducing the integrity of the MAE signal, resulting in poor imaging contrast at tilted tissue boundaries. Traditional MAET systems require two sets of mechanical mechanisms for transducer linear scanning and object rotation, making it difficult to achieve efficient, rapid, and high-quality imaging. Therefore, there is an urgent need to develop a measurement method that eliminates mechanical rotation and scanning to achieve high-quality, rapid MAET. Summary of the Invention

[0005] To improve the measurement speed and imaging quality of MAET (Magnetic Acoustic Emission Detection), this invention proposes a rapid MAET imaging method that eliminates the need for mechanical rotation and scanning measurements, achieving rapid imaging based on cyclic excitation by a ring-shaped omnidirectional acoustic source and simultaneous measurement by multiple electrodes. First, based on point source radiation and magnetoacoustic-electric coupling mechanisms, a MAET system model is established for ring-shaped M-source excitation and N-electrode detection. A general theoretical formula for MAET, applicable to excitation by an acoustic source at any position on the ring and measurement by any electrode, is derived. Furthermore, a MAET imaging algorithm based on inverse Radon transform and the sum of MAE signal amplitudes is developed. Results demonstrate that the amplitude of the MAE signal detected by the electrodes is determined by the conductivity gradient and direction of the tissue boundary, as well as the angle between the acoustic source and the electrode. Differences in the positions of the ring-shaped acoustic source and electrodes can lead to boundary deformation and uneven intensity distribution in the MAET image. Increasing the number of ring-shaped acoustic sources and electrodes can effectively improve the accuracy, integrity, and smoothness of the boundary distribution. Then, a measurement method based on simultaneous detection by four orthogonal electrodes on a ring is proposed. Orthogonal component measurement improves the information integrity of the MAE signal, thereby enhancing the quality of the MAET image. Furthermore, the radius fluctuation coefficient and intensity relative error of the MAET image boundary were defined for ring boundary imaging quality analysis and measurement system optimization. It was demonstrated that the minimum configuration of the MAET system is 30 sound sources and 4 orthogonal electrodes, which exhibits good noise immunity and robustness. Considering the practical application requirements of uniform distribution of ring sound sources and orthogonal electrode placement, an optimized scheme for a fast MAET system based on 32 sound sources and 4 orthogonal electrodes was proposed. Finally, a MAET experimental system was constructed using 32 sound sources and 4 orthogonal electrodes to perform MAET imaging on an eccentric cylindrical gel tissue model, accurately reconstructing a smooth ring boundary image consistent with the model size.

[0006] This invention utilizes the cyclic excitation of a ring-shaped omnidirectional sound source and the synchronous measurement of orthogonal electrodes to achieve rapid MAET imaging. A single acoustic radiation from the omnidirectional transducer can completely cover the entire measured field, eliminating the need for linear scanning of the transducer or phased-array scanning of the sound source. Cyclic excitation of the ring-shaped sound source and synchronous measurement of the four electrodes can be achieved through electronic control switching. Rapid measurement can be completed without the mechanical rotation and scanning required in traditional MAET, effectively improving imaging speed and stability, and obtaining high-precision MAET imaging. This invention simplifies the structure of the MAET system, making it easy to integrate with commercial ultrasound CT technology, enabling multimodal and cross-scale imaging of deep human tissues, and providing a new rapid imaging technology for MAET imaging.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows: a rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement, comprising the following steps:

[0008] S1. Establish a MAET measurement system based on a ring-shaped omnidirectional sound source array and an electrode array to realize the cyclic excitation of the sound field and the synchronous measurement of the MAE signal.

[0009] S2. Establish a MAE theoretical model based on the excitation of a sound source at any position in a ring and the reception of electrodes, derive the general theoretical formula of the MAE signal, and obtain the determining factors of the amplitude and time of the MAE signal.

[0010] S3. By introducing the cyclic excitation of a ring sound source and the multi-electrode synchronous measurement technology, a high-precision MAET imaging method based on the inverse Radon transform and the sum of amplitudes (sum of squared amplitudes) of MAE signals is proposed.

[0011] S4. Establish a cylindrical tissue model, conduct MAE signal simulations under different numbers of sound sources and electrodes, complete MAET image reconstruction, and analyze the factors affecting image quality.

[0012] S5. Based on the analysis of the influence of sound source and number of electrodes on the radius fluctuation and intensity relative error of the reconstructed MAET image ring boundary, the minimum configuration requirements of the MAET system are proposed, and further optimization schemes for the fast MAET system are obtained.

[0013] Specifically, step S1 is as follows:

[0014] M uniformly distributed omnidirectional transducers are set at the boundary of a ring-shaped field with radius R0 to cyclically emit sound waves. N sheet-like or needle-like electrodes are set to detect the MAE signal generated by the conductivity boundary of the tested object's tissue. The tested object, with arbitrary shape and conductivity distribution, is placed in a conductive coupling liquid. The entire field has good acoustic coupling and electrical transmission characteristics. A pair of parallel permanent magnets generate a static magnetic field that passes perpendicularly through the tested field. The pulsed sound waves radiated by the transducers propagate as spherical waves, and the sound field covers the entire tested circular field. The vibration of conductive tissue particles caused by sound propagation interacts with the magnetic field to generate an induced current. After propagation through the conductive medium, the current is received by the electrodes, resulting in N MAE signals containing the conductivity gradient and position information of the tissue boundary. By electronically controlling the cyclic excitation of the M transducers and the synchronous measurement of the N electrodes, the rapid measurement of M×N MAE waveforms and MAET image reconstruction are achieved.

[0015] The M sound sources used must be approximately omnidirectional transducers with a spherical sound radiation half-angle greater than 60°, and the radiated sound field must completely cover the object under test. The surface of the omnidirectional transducer and the coupling liquid must be completely insulated to reduce interference between the sound field and the electric field. The electrodes need to be placed in a coupling liquid with conductivity to ensure the reliability of current transmission. The boundary and bottom of the annular test field should be covered with sound-absorbing material to eliminate the effects of sound reflection and sound scattering. Silver or copper sheet or needle-shaped high conductivity electrodes should be selected to improve the electric field detection capability. The electrodes should be placed between two adjacent transducers at the boundary of the annular field to reduce the influence of the annular distributed electrodes on the radiated sound field.

[0016] Specifically, step S2 is as follows:

[0017] The m-th sound source Tm, placed in a circle, emits an omnidirectional sound wave, which propagates to any position r in the field and produces a sound pressure of... Where Q = 4πa 2 u0 is the intensity of the spherical sound source, u0 is the surface velocity of the sound source, a is the radius of the sound source, k = ω / c is the wave number, ω is the angular frequency, ρ and c are the density and speed of sound of the propagation medium, respectively, R Tm =|rr Tm | represents the location of the sound source r Tm The distance to r, t = R Tm / c represents the propagation time, and the sound pressure generates particle vibration velocity. Its direction is e v , It is the gradient operator, static magnetic field B and v(r) Tm The interaction between r and induced current density J(r) generates an induced current density. Tm ,r)=σ(r)v(r Tm ,r)×B, its direction is e J The nth electrode En on the circumference detects a current density component J generated by the mth sound source at point r. En (r Tm ,r)=J(r Tm ,r)cosθ, its direction is e E θ is e E and e J The included angle, θ = π / 2 - χ, where χ is e E and -e v The angle between the electrodes, considering the equivalent resistance R when the induced current is generated at the electrode En receiving r. En And the electrode receiving coefficient α, while considering By e v and the conductivity normal direction e n The included angle γ determines the MAE voltage received by electrode En from sound source Tm across the entire field Ω:

[0018]

[0019] The system's equivalent resistance R En It can be approximately proportional to the propagation distance R En =R s |r En -r|, where R s If the resistance per unit length of the conductive medium is denoted as , then the MAE voltage signal is:

[0020]

[0021] Where ξ=-2αBa2 u0R s It is a constant determined by the system structure and parameters.

[0022] Using an ideal unit pulse signal δ(t) as the excitation sound source, the MAE voltage correction is:

[0023]

[0024] Where V δ (r En ,r Tm ,t) is determined by the position r of the sound source. Tm and electrode receiving position r En And the conductivity distribution is determined by the convolution of the excitation signal S(t) and the transducer's impulse response R(t). The convolution operator is used to obtain the general formula for the MAE waveform generated by the m-th sound source at the n-th electrode throughout the entire field:

[0025]

[0026] The results show that the radiated sound field can only generate MAE signal pulses at the tissue conductivity boundary, and the propagation time from the sound source to the tissue boundary is t = |rr Tm | / c determines the magnitude, while the magnitude is determined by and location information A joint decision.

[0027] Specifically, step S3 is as follows:

[0028] By introducing a ring-shaped sound source for cyclic excitation and electrode synchronous measurement technology, a MAET imaging method based on inverse Radon transform and MAE signal amplitude sum (sum of squared amplitudes) is proposed.

[0029] First, the MAE signal waveform W(r) received by the m-th sound source excitation and the n-th electrode is... En ,r Tm After performing a Hilbert transform on t, the absolute value is taken to obtain the envelope H(r) of the MAE signal. En ,r Tm ,t); Applying the inverse Radon transform based on the diffraction sound source to the MAE signal envelope, H(r En ,r Tm The amplitudes at all times are back-projected into the field |rr) Tm On the arc of |=ct, reconstruct the MAE image g(r) based on the excitation of the sound source Tm and the reception of the electrode En. En ,r Tm ,r)=H(r En ,r Tm ,t)δ(|rrTm |-ct).

[0030] Then, based on synchronous measurements with N electrodes, N MAE images g(r) under the excitation condition of the sound source Tm are reconstructed. En ,r Tm The signal attenuation at different electrode positions is compensated by calculating the sum of amplitudes and the sum of squared amplitudes of the MAE signals, respectively, to obtain MAE images based on sound source Tm excitation and synchronous measurement of N electrodes. and

[0031] Finally, by introducing cyclic excitation from a ring-shaped M-source and synchronous measurement with N electrodes, and using the acquired M×N MAE waveforms, M MAE images g(r) under different sound source excitations are reconstructed. Tm The MAET image is reconstructed using rotation matrices and image interpolation (r).

[0032]

[0033] Theoretical results demonstrate that increasing the number of ring sound sources M and the number of electrodes N, and increasing their uniform distribution density in the range of 0-2π, can effectively reduce the influence of the sound source and electrode positions on θ and γ, thereby improving the accuracy and integrity of MAET images.

[0034] Specifically, step S4 is as follows:

[0035] A cylindrical tissue model was established, and MAE signal simulations were carried out under different numbers of sound sources and electrodes. MAET image reconstruction was completed, and the influencing factors of imaging quality were analyzed.

[0036] A 16-source and 16-electrode MAET system was established. An eccentric cylindrical tissue model was placed inside the measurement field. By cyclically exciting the 16 sources and synchronously measuring the 16 electrodes, 16×16 MAE signal waveforms were obtained, and the MAET image was reconstructed. The results showed the reconstructed circular model boundary. However, due to the limited number of cyclic excitations of the transducer, the circular boundary exhibited obvious unevenness and discontinuity, as well as significant artifacts, demonstrating that the number of sources has a significant impact on MAET.

[0037] Specifically, step S5 is as follows:

[0038] Based on the analysis of the influence of sound source and number of electrodes on the radius fluctuation and intensity relative error of MAET ring boundary, the minimum configuration requirements of MAET system are proposed, and further optimization scheme of fast MAET system is obtained.

[0039] A circular tissue model was established to simulate MAE signals received synchronously by 16 electrodes under different M conditions, and MAET images were reconstructed. The results show that when the number of sound sources is small, the annular boundary of the MAET image fluctuates significantly, forming a petal distribution of approximately polygonal shapes with sharp angles, exhibiting fluctuations in amplitude and shape, accompanied by obvious arc-shaped artifacts. As M increases, the number of sides of the polygon increases, but the intensity of the petals weakens, the smoothness of the boundary increases, and the contrast and sharpness are correspondingly improved, thus enhancing the image quality. The radius fluctuation coefficient of the annular boundary is defined. Where R -3 (i) is the radius at the i-th measured angle. The average radius of the Q-time circular measurements shows that the fluctuation coefficient ε decreases as M increases. When M ≥ 30, the radius fluctuation coefficient is less than 0.02 mm. Therefore, taking ε = 0.02 as the acceptable standard for image quality, the minimum number of sound sources required for the MAET system is M = 30.

[0040] Under the condition of a maximum number of sound sources M=30, a 64-electrode MAET system was constructed. An eccentric circumferential structure model was set up, and N electrodes uniformly distributed along the circumference were selected to form different synchronous measurement groups to carry out different initial electrode n. s MAE signal simulation and imaging were performed under N=1, 2, 4, 8, 16, 32, and 64 conditions. The results show that when N=1 and 2, the shape and position of the model boundary can be basically reconstructed, but there are significant intensity differences in the annular boundary. Its continuity and intensity consistency are greatly affected by the position of the measuring electrodes. When N=4, the MAET images measured by orthogonal four electrodes are almost identical, and the continuity and consistency of the annular boundary are significantly improved. The relative error of the annular boundary intensity between the MAET image and the model is defined. Where Q is the number of ring sampling points, g p (i) represents the intensity of the i-th sampling point on the ring boundary of the MAET image, given different N and n values. s MAET imaging was performed under these conditions to obtain average values. The relationship between N and N shows that as N increases from 1 to 4, The value rapidly decreased from 0.19 to 0.027 and stabilized after N≥4, demonstrating that when N<4, the reconstructed MAET image quality was poor and significantly affected by the electrode positions. When N≥4, the MAET image accurately reflected the boundary distribution of the model, and the imaging quality was not affected by the positions of the four orthogonal electrodes. Therefore, with N≥4, the reconstructed MAET image... To achieve acceptable image quality, the minimum number of electrodes for the MAET system is determined to be N = 4.

[0041] In summary, the minimum configuration for the proposed MAET system, which eliminates the need for mechanical rotation and scanning, requires M ≥ 30 and N ≥ 4. Furthermore, considering the requirement for a uniform annular distribution of transducers and electrodes, and to ensure that the electrodes do not affect the sound field, the MAET system configuration needs to be based on 2... k To set M and N (k is an integer greater than 4), the sound sources and electrodes are alternately distributed on the circumference, and N is an integer multiple of 4. While ensuring imaging quality, the imaging speed is increased as much as possible, resulting in an optimized configuration of 32 sound sources and 4 orthogonally distributed electrodes for the fast MAET system (M=32 and N=4).

[0042] As an improvement to the present invention, the method further includes the following steps:

[0043] An experimental system with a ring-shaped 32-electrode source and orthogonal 4 electrodes was established. MAE measurements and MAET imaging were performed on an eccentric cylindrical model to prove the correctness of the imaging method and the feasibility of the optimization scheme. The specific implementation process is as follows:

[0044] The MAET system includes a computer, a function generator, a power amplifier, a 32-channel analog signal switcher, a 4-channel analog signal switcher, a low-noise preamplifier, a low-pass filter amplifier, an oscilloscope, a cylindrical container, neodymium iron boron magnets, 32 omnidirectional transducers, and four sheet electrodes. The 32 omnidirectional transducers are sequentially connected to the 32-channel analog signal switcher, the power amplifier, and the function generator. The function generator outputs a pulsed sine wave signal, which is amplified by the power amplifier and then drives the transducer to emit sound waves after being switched through the 32 analog signals. The sound waves propagate in the cylindrical container and generate MAE signals under the influence of the magnetic field. These signals are synchronously detected by the orthogonally placed four electrodes, selected by the four analog signal switchers, amplified by the low-noise preamplifier and the low-pass filter amplifier, acquired by the oscilloscope, and stored in the computer.

[0045] Using the measured 32×4 MAE signal waveform, the annular boundary distribution of the cylindrical model was reconstructed using the aforementioned imaging method, demonstrating the feasibility of the fast MAET method. Furthermore, by selecting sound sources and electrodes at intervals and changing the number of sound sources and electrodes used for imaging, 16×4 and 8×4, and 32×2 and 32×4 signals were obtained.

[0046] Under several experimental conditions below the minimum configuration, such as ×1, MAET images were reconstructed. The results showed that the imaging quality under these conditions was significantly reduced, further proving that the minimum requirements for the MAET system configuration proposed in this invention are M≥30 and N≥4, and the optimized configuration of the fast MAET system is M=32 and N=4.

[0047] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the aforementioned rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement.

[0048] A computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the aforementioned rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement.

[0049] The fast MAET imaging method proposed in this invention, employing the above technical solutions, has the following advantages:

[0050] This invention utilizes the cyclic excitation of a ring-distributed omnidirectional sound source and the synchronous measurement of orthogonal electrodes to achieve rapid MAET imaging. A single acoustic radiation from the omnidirectional transducer can completely cover the entire measured field, eliminating the need for linear scanning of the transducer or phased scanning of the array sound source. Electronic control switching enables the cyclic excitation of the ring sound source and the synchronous measurement of the four orthogonal electrodes, achieving rapid measurement without the mechanical rotation and scanning required in traditional MAET, effectively improving imaging speed and stability, and obtaining high-precision MAET images. This invention simplifies the structure of the MAET system and is easily integrated with commercial ultrasound CT technology, enabling multimodal and cross-scale imaging through ultrasound and electrical impedance fusion, providing a new rapid imaging technology for MAET imaging. Attached Figure Description

[0051] Figure 1 A schematic diagram of the MAET principle based on a ring-shaped omnidirectional transducer array;

[0052] Figure 2 (a) Schematic diagram of MAET imaging of a ring-shaped 16 sound source and 16 electrodes based on an eccentric cylindrical tissue model; (b) Reconstructed image of cyclic excitation of the 16 sound source and synchronous measurement of the 16 electrodes.

[0053] Figure 3 (a) Electrical impedance distribution of the cross section of the columnar model, MAET images under the conditions of N=16 and M=10, 15, 20, 30 and 40; (c) Circumferential radius R in the range of 0°-90°. -3 Distribution, (d) Relationship between radius fluctuation coefficient ε and number of sound sources M;

[0054] Figure 4 M = 30, N = (a) 1, (b) 2 and (c) 4, three types of n s MAET reconstructed images based on MAE amplitude under different conditions, (d) relative intensity error (RE) of MAET image ring boundary and model boundary under different N conditions, varying with the initial electrode number n sThe distribution of (e) average relative error The relationship between n and M: (f)M=30 and N=4, for three different n values. s MAET reconstructed image based on the sum of squared magnitudes of MAE under the given conditions;

[0055] Figure 5 MAET measurement system block diagram;

[0056] Figure 6 (a) Cross-sectional conductivity distribution of the eccentric cylindrical model, measurement of the MAE signal (b) waveform and (c) envelope. MAET images reconstructed under conditions of M=32, N=(d1)1,(d2)2 and(d3)4, and MAET images reconstructed under conditions of N=4, M=(e1)16,(e2)8 and(e3)4. Detailed Implementation

[0057] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0058] Example: See Figures 1-6 A rapid MAET imaging method that does not require mechanical rotation and scanning, the method comprising the following steps:

[0059] S1. Establish a MAET measurement system based on a ring-shaped omnidirectional sound source array and an electrode array to realize the cyclic excitation of the sound field and the synchronous measurement of the MAE signal.

[0060] S2. Establish a MAE theoretical model based on the excitation of a sound source at any position in a ring and the reception of electrodes, derive the general theoretical formula of the MAE signal, and obtain the determining factors of the amplitude and time of the MAE signal.

[0061] S3. By introducing the cyclic excitation of a ring sound source and the multi-electrode synchronous measurement technology, a high-precision MAET imaging method based on the inverse Radon transform and the sum of amplitudes (sum of squared amplitudes) of MAE signals is proposed.

[0062] S4. Establish a cylindrical tissue model, conduct MAE signal simulation under different numbers of sound sources and electrodes, complete MAET image reconstruction, and analyze the factors affecting imaging quality.

[0063] S5. Based on the analysis of the influence of sound source and number of electrodes on the radius fluctuation and intensity relative error of the reconstructed MAET image ring boundary, the minimum configuration requirements of the MAET system are proposed, and further optimization schemes for the fast MAET system are obtained.

[0064] S6. Establish a 32-sound-source and 4-electrode experimental system, perform MAE measurement and MAET imaging on the eccentric cylindrical model, and prove the correctness of the imaging method and the feasibility of the optimization scheme.

[0065] Specifically as follows:

[0066] First, in step S1, a MAET measurement system based on a ring-shaped omnidirectional sound source array and an electrode array is established to realize the cyclic excitation of the sound field and the synchronous measurement of the MAE signal, as detailed below:

[0067] A MAET system is established where the measured field covers the size of the measured object. M uniformly distributed omnidirectional transducers are placed at the boundary of the annular field to cyclically emit sound waves. N sheet-like or needle-like electrodes are used to detect the MAE signal generated by the conductivity boundary of the measured object's tissue. For example... Figure 1 As shown, an arbitrarily shaped conductive material with a conductivity distribution σ(r) is placed in a coupled liquid filled with a conductivity of σ0, exhibiting excellent acoustic coupling and electrical transport characteristics throughout the entire field. A pair of parallel permanent magnets generate a static magnetic field B = Be along the x-direction. x , where e x Let represent the unit vector in the x-direction. M omnidirectional sound sources and N electrodes are uniformly distributed on a circle of radius R0, where the position coordinates of the m-th sound source Tm and the n-th electrode En are r... Tm and r En The sound source surface and coupling liquid are completely insulated to reduce interference between the sound and electric fields, while the influence of the ring-shaped electrodes on the transducer's radiated sound field is ignored. The pulsed sound waves radiated by the transducer propagate in a spherical form, covering the entire circular field under test. The vibration of conductive tissue particles induced by sound propagation interacts with the magnetic field to generate an induced current, which is received by the circumferentially placed electrodes after propagation through the conductive medium, resulting in N MAE signals containing the conductivity gradient and position information of the tissue boundary. By electronically controlling the cyclic excitation of M transducers and controlling the synchronous measurement of N electrodes, M×N MAE signal waveforms are acquired to reconstruct the MAE image.

[0068] Then, in step S2, a theoretical model of MAE based on excitation by a sound source at an arbitrary position in a ring and reception by electrodes is established, the general theoretical formula of the MAE signal is derived, and the determining factors of the amplitude and time of the MAE signal are obtained, as follows:

[0069] like Figure 1 As shown, with r Tm The omnidirectional sound wave emitted by the m-th sound source Tm centered at the center propagates to any position r in the field, and its sound pressure is... Where Q = 4πa 2 u0 is the intensity of the spherical sound source, u0 is the surface velocity of the sound source, a is the radius of the sound source, k = ω / c is the wave number, ω is the angular frequency, ρ and c are the density and speed of sound of the propagation medium, respectively, R Tm =|rr Tm |for the sound source rTm The distance to r, t = R Tm / c represents the propagation time. The sound pressure at point r is p(r). Tm r) generates particle vibration velocity Its direction is e v =(rr Tm ) / |rr Tm |, It is the gradient operator. The vibration velocity v(r) at points B and r in the static magnetic field. Tm The induced current density J(r) generated in the yz plane by the interaction of r) Tm ,r)=σ(r)v(r Tm ,r)×B, whose unit vector e J Perpendicular to e v .

[0070] r on the circumference En The current density detected by the nth electrode En at position r, generated by the mth sound source at position r, is J. En (r Tm ,r)=J(r Tm ,r)cosθ, its unit vector e E =(r En -r) / |r En -r|, where θ is e E and e J The angle between the electrodes. The amplitude of the MAE signal generated at electrode En receiving r is determined by the equivalent resistance R along the current propagation path. En The receiving coefficient α, determined by the electrode characteristics, is therefore the MAE voltage received by electrode En from the sound source Tm across the entire field Ω.

[0071]

[0072] Where t=|rr Tm | / c is the propagation time of sound radiation, θ=π / 2-χ, χ is e E and -e v The included angle. Considering It is the conductivity gradient along the direction of sound propagation, and its magnitude is given by e. v and the conductivity normal direction e n The included angle γ is determined, therefore we get:

[0073]

[0074] Since the N electrode positions are distributed around a circle, from r to r En Propagation distance |r En -r| is different, its equivalent resistance R En It can be approximately proportional to the propagation distance R En=R s |r En -r|, where R s If the resistance per unit length of the conductive medium is denoted as , then the MAE voltage signal is:

[0075]

[0076] Where ξ=-2αBa 2 u0R s It is a constant determined by the system structure and parameters. Using an ideal unit pulse signal δ(t) as the excitation source to generate the MAE signal, the MAE voltage received by the electrode is corrected as follows:

[0077]

[0078] V δ (r En ,r Tm ,t) is the position r of the sound source emission. Tm and electrode receiving position r En And the spatial transfer function of the system determined by the conductivity distribution. Under the actual excitation signal S(t), the transducer output pulse acoustic wave cluster is Where R(t) is the impulse response of the transducer under excitation δ(t), This is the convolution operator. Therefore, the MAE signal waveform received by the nth electrode from the mth sound source across the entire field is:

[0079]

[0080] Theoretical formulas show that radiated sound fields can only generate MAE signal pulses at the tissue conductivity boundary, and the propagation time from the sound source to the tissue boundary is t = |rr|. Tm | / c determines the magnitude, while the magnitude is determined by and location information A joint decision.

[0081] Furthermore, in step S3, a ring-source cyclic excitation and electrode synchronous measurement technique is introduced to propose a MAET imaging method based on inverse Radon transform and the sum of squared amplitudes (MAE signals), as detailed below:

[0082] First, perform a Hilbert transform on the MAE signal waveforms excited by the m-th sound source and received by the n-th electrode, and then take the absolute value to obtain the MAE signal amplitude envelope H(r). En ,r Tm ,t)=ABS(Hilbert[W(r En ,r Tm ,t)]), which satisfies |rr Tm|=ct. Then, the inverse Radon transform based on the diffraction sound source is introduced, and H(r) is transformed into H(r). En ,r Tm The amplitudes at all times are back-projected into the field |rr) Tm On the arc of |=ct, reconstruct the MAE image g(r) based on the radiation from the sound source Tm and the reception from the electrode En. En ,r Tm ,r)=H(r En ,r Tm ,t)δ(|rr Tm |-ct). Furthermore, the amplitude (sum of squares) of the MAE signal is simultaneously measured using N-electrodes to compensate for signal attenuation at different angles, resulting in MAE images based on sound source Tm excitation and simultaneous N-electrode measurements:

[0083] or

[0084] Finally, a circular M-source cyclic excitation and N-electrode synchronous measurement were introduced to acquire M×N MAE waveforms. M MAE images under different sound source excitations were reconstructed, taking into account the angle between the sound sources. Reconstructing MAET images using rotation matrices and image interpolation:

[0085]

[0086] Theoretical evidence shows that increasing the number of ring sound sources M and the number of electrodes N, and increasing their uniform distribution density in the 0-2π range, can reduce the influence of the sound source and electrode positions on θ and γ, thereby improving the accuracy and integrity of MAET images.

[0087] Further, in step S4, a cylindrical tissue model is established, MAE signal simulation is carried out under different sound sources and electrode numbers, MAET image reconstruction is completed, and the influencing factors of imaging quality are analyzed, as follows:

[0088] Establish a MAET system with M=16 and N=16, and an excitation signal frequency f=2MHz. Its yz cross-sectional distribution is as follows. Figure 2As shown in (a), the center of the circular field is located at the origin. Sixteen omnidirectional transducers and sixteen sheet electrodes are placed alternately, neglecting edge reflections of the sound waves and the influence of the electrodes on the radiated sound field. An eccentric cylindrical model with a radius of 10 mm is placed inside the measurement field, with its center at (10,10) mm. The conductivity of the model and the surrounding medium are set to 1 and 0.03 S / m, respectively, and the sound velocity is set to 1540 m / s. The sixteen transducers are cyclically excited, and the sixteen electrodes are simultaneously measured, acquiring 16×16 received MAE signal waveforms. Through cyclic excitation of 16 sound sources and simultaneous measurement of 16 electrodes, 16×16 MAE signal waveforms are obtained. A rotation matrix is ​​introduced to reconstruct the waveforms as shown below. Figure 2 (b) shows the MAET image. The reconstruction results show a clear circular model boundary, but due to the limited number of cyclic excitations of the transducer, the circular boundary exhibits an uneven and discontinuous distribution, along with obvious artifacts.

[0089] Based on the analysis of the influence of the sound source and electrodes on the radius fluctuation and relative intensity error of the MAET ring boundary, the minimum configuration requirements for the MAET system are proposed, and further, an optimized scheme for the fast MAET system is obtained, as follows:

[0090] To determine the impact of the number of sound sources N on MAET imaging quality, a model was established as follows: Figure 3 (a) shows a circular tissue model with a radius of 10 mm, its conductivity set to σ = 1 S / m, and its center located at (0,0) mm, placed in a conductive liquid with σ0 = 0.03 S / m. The MAE signals synchronously received by the 16 electrodes were simulated under different M = 10, 15, 20, 30, and 40 conditions, as shown below. Figure 3 MAET images are shown in (b1)-3(b5). The results show that MAET can reconstruct the ring-shaped distribution of the tissue model under several M conditions, with the sound pressure peak located on a ring with a radius of 10 mm. When M=10, the boundary fluctuations are obvious, forming an approximately decagonal petal distribution with sharp angles, showing both amplitude and shape fluctuations, accompanied by obvious arc-shaped artifacts. However, as M increases, the number of sides of the polygon increases, but the intensity of the petals weakens, the smoothness of the boundaries increases, and its contrast and sharpness also improve accordingly. When M=30, as... Figure 3 (b4) shows that the model boundary forms an approximately standard ring distribution, and the imaging quality is basically acceptable, but the outward petal-shaped radiation at the 30-degree angle is still visible. When M is increased to 40, the shape and size of the ring boundary remain basically unchanged, but the intensity of the 40-petal distribution is significantly reduced, the intensity of the ring distribution of the model boundary is increased, the contrast is enhanced, and the imaging quality is significantly improved.

[0091] extract Figure 3 (b1)-3(b5) The outer radius (R) at which the peak intensity at the annular boundary decays by -3dB on the ring boundary-3 The distribution is obtained as follows: Figure 2 (c) shows the annular intensity distribution within the 0°-90° range. The results indicate radius fluctuation, and the fluctuation range decreases as M increases. To quantitatively evaluate the coherence and smoothness of the model boundary in the MAET image, the radius fluctuation coefficient is defined as:

[0092]

[0093] Where R -3 (i) is the radius at the i-th measured angle. The average radius of the Q-time circular measurements. Figure 3 (d) Showing the relationship between the radius fluctuation coefficient ε and M, when M increases from 10 to 40, the fluctuation coefficient decreases from 0.64 to 0.019 mm, proving that the fluctuation coefficient ε decreases as M increases. Therefore, with ε = 0.02 mm as the standard, the number of sound sources in the MAET system must be M ≥ 30 under acceptable imaging quality conditions.

[0094] A MAET system with 64 electrodes was constructed using at least 30 sound sources. The sound sources and electrodes were uniformly placed in a ring at the boundary of the field. An eccentrically centered circular model with a radius of 10 mm and a conductivity σ = 1 S / m was placed in a conductive liquid with a conductivity σ0 = 0.03 S / m. N electrodes uniformly distributed along the circumference were selected to form different synchronous measurement groups, achieving electrode numbers N = 1, 2, 4, 8, 16, 32, and 64 for each measurement group, with the initial electrode number being n. s Given N = 1, 2, and 4, choose different n... s The electrode combination was used to simulate MAE signals and reconstruct MAET images of an eccentric circular model. The results are as follows: Figure 4 As shown in (a)-4(c). Figure 4 (a) shows that a single electrode measurement can largely reconstruct the shape and position of the model boundary, but significant intensity differences exist in the annular boundary, demonstrating that the continuity and intensity consistency of the MAET-reconstructed model boundary are greatly affected by the position of the measuring electrode. Increasing N=2, Figure 4 (b) The circumferentially symmetrical dual-electrode measurement can compensate for signal attenuation to some extent, improve the continuity of the ring boundary, and reduce intensity differences. However, intensity differences still exist in the ring boundary distribution, and their positions vary with the electrode positions. When N=4, Figure 4 (c) shows that the orthogonal four-electrode measurement results are almost identical, and the continuity and consistency of the ring boundary are significantly improved. This proves that orthogonal four-electrode measurement can effectively improve the information integrity of the measured MAE signal, improve the accuracy of the MAET model boundary, and the imaging results are not affected by the position of the orthogonal electrodes, thus exhibiting good performance stability.

[0095] To quantitatively evaluate the image quality of the reconstructed MAET, the relative error (RE) of the ring boundary intensity distribution between the MAET image and the model is defined as:

[0096]

[0097] Where Q is the number of ring sampling points, g p (i) represents the intensity of the i-th sampling point on the annular boundary of the MAET image, with a corresponding measurement angle of 360°i / Q. Under the conditions of N = 1, 2, 4, 8, 16, and 32, changing n... s =1,2,3,…,63 and 64 to adjust the position of the electrodes in each synchronous measurement group, simulate the MAE signal and complete the MAET image reconstruction, to obtain, as Figure 4 (d) shows the relative error of the ring-shaped intensity distribution at the model boundary as n s The distribution of RE values ​​shows an N-period fluctuation, with the amplitude decreasing as N increases. When N = 1 and 2, the reconstructed MAET image quality is poor, with larger RE values ​​and greater fluctuation ranges for the ring boundary intensity distribution, indicating that the measurement electrode position has a significant impact on image quality. When N ≥ 4, the RE value rapidly decreases to 0.027, exhibiting minimal fluctuation, demonstrating that a uniformly distributed ring of 4 electrodes can obtain complete MAE information, effectively improving the quality of the MAET image, and that the electrode position has a relatively small impact on image quality. Figure 5 (d) Same N, different n s Calculation of the arithmetic mean of the RE distribution under the given conditions Get as Figure 3 (e) shows The relationship with N. The results show that as N increases from 1 to 4, The value rapidly decreased from 0.19 to 0.027 and stabilized after N≥4, demonstrating that when N<4, the reconstructed MAET image quality is poor due to the limited number of electrodes, which cannot acquire component information of the MAE signal in all directions, and is significantly affected by the electrode positions. However, when N≥4, the MAET image accurately reflects the boundary distribution of the model, and the imaging quality is unaffected by the positions of the four orthogonal electrodes. Therefore, with... To ensure acceptable imaging quality, the minimum number of electrodes for the MAET system is N = 4.

[0098] With N=4, choose different n s The electrode combination was used to simulate the MAE signal of the eccentric circle model, and the MAET image was reconstructed using the MAE amplitude sum of squares algorithm, such as... Figure 4The results shown in (f1)-4(f3) demonstrate that the amplitude sum-of-squares algorithm based on orthogonal four-electrode detection of MAE can accurately reconstruct the ring boundary of the model, with almost identical ring peak intensities. Furthermore, changing n... s The relative error RE for reconstructing the ring boundary using orthogonal four electrodes was calculated to be 0.027, which is almost independent of n. s It changes and fluctuates. The results show that the algorithm based on the sum of squared amplitudes of the MAE signal has a clearer physical meaning and is a MAET imaging algorithm with better image reconstruction effect.

[0099] In summary, the minimum configuration for the proposed MAET system, which eliminates the need for mechanical rotation and scanning, requires M ≥ 30 and N ≥ 4. Furthermore, considering the requirement for a uniform annular distribution of the transducer and electrodes, and ensuring that the electrodes do not affect the sound field, the optimized configuration of the MAET system needs to be based on 2... k M and N (k is an integer greater than 4) are set so that the sound sources and electrodes are alternately distributed on the circumference, and N is an integer multiple of 4. Therefore, the optimal configuration of the MAET system, which maximizes imaging speed while ensuring imaging quality and meeting the needs of practical applications, is 32 sound sources and four orthogonally distributed electrodes (M=32 and N=4).

[0100] Finally, in step S6, a 32-sound-source and 4-electrode experimental system is established. MAE measurement and MAET imaging are performed on the eccentric cylindrical model to prove the correctness of the imaging method and the feasibility of the optimization scheme, as detailed below:

[0101] like Figure 5 As shown, the MAET system includes a computer A, a function signal generator B, a power amplifier C, a 32-channel analog signal switcher D, a 4-channel analog signal switcher E, a low-noise preamplifier F, a low-pass filter amplifier G, an oscilloscope H, a cylindrical container, neodymium iron boron magnets, 32 omnidirectional transducers, and 4 sheet electrodes. The 32 transducers are sequentially connected to the 32-channel analog signal switcher, the power amplifier, and the function signal generator. The function signal generator outputs a pulsed sine wave signal, which is amplified by the power amplifier and then drives the transducer to emit sound waves after being switched through the 32 analog signals. The sound waves propagate in the cylindrical container, generating MAE signals under the influence of the magnetic field. These signals are detected by the orthogonally placed four electrodes, selected by the 4-channel analog signal switcher, amplified by the low-noise preamplifier and the low-pass filter amplifier, acquired by the oscilloscope, and stored in the computer.

[0102] Using the measured 32×4 MAE signal waveform, the annular boundary distribution of the cylindrical model was reconstructed using the proposed imaging method, demonstrating the feasibility of the fast MAET method. Furthermore, by selecting sound sources and electrodes at intervals and changing the number of sound sources and electrodes used for imaging, several experimental conditions lower than the optimal minimum configuration were obtained, including 16×4, 8×4, 32×2, and 32×1. The quality of the reconstructed MAET images significantly decreased in all these cases, proving that the minimum requirements for the proposed MAET system configuration are M≥30 and N≥4. This also demonstrates that the optimal configuration for the fast MAET system is M=32 and N=4.

[0103] Example 2:

[0104] Based on the above theoretical and simulation research conclusions, this example utilizes a ring-shaped, uniformly distributed 32 transducers and orthogonally placed 4 electrodes to construct a system as follows: Figure 5 The experimental system shown is used for MAET imaging experiments and has the following characteristics:

[0105] (1) Using a planar piston transducer with radius a = 3.5 mm and frequency f = 2 MHz, a hemispherical convex lens with radius a is designed and made of acrylic resin. It is coaxially mounted on the transducer surface to construct an omnidirectional transducer. The output sound wave of the planar transducer is modulated to form an approximately omnidirectional radiating sound field.

[0106] (2) Thirty-two omnidirectional transducers were uniformly installed on the central plane of the boundary of a cylindrical container with a diameter of 120 mm and a height of 60 mm. The acoustic axis of the radiated sound waves propagated along the radial direction. Sound-absorbing materials were placed on the inner side and bottom of the cylinder to reduce sound reflection. The entire system was placed in the central area of ​​a pair of neodymium iron boron magnets (100 mm * 100 mm * 50 mm), which generated an approximately uniformly distributed magnetic field of about 0.3 T, completely covering the gel model under test. A cylindrical gel model with a diameter of 30 mm and a conductivity of 1 S / m was placed eccentrically inside the container. The outside was filled with a liquid with a conductivity of 0.3 S / m to ensure the propagation of sound waves and current. The transducer and lens surfaces were completely insulated from the conductive liquid to reduce interference from the sound field and electric field.

[0107] (3) Under the control of the computer, the function signal generator (33220A, Agilent Technologies, USA) outputs a single-cycle sine pulse signal (V). pp=1V, f=2MHz, PRF=100Hz), amplified by a power amplifier (53dB, E&I 2200L, Electronics and Innovation Ltd, USA), and then selected and switched by a 32-channel switch, can individually or cyclically drive 32 transducers to generate an omnidirectional pulse sound field. Four electrodes are orthogonally placed inside the cylindrical sound-absorbing material to receive the MAE signal generated by the gel model. After being amplified by a low-noise preamplifier (46dB, NF SA-230F5, NF Corporation, Japan) and a self-made bandpass amplifier (45dB, cutoff frequency 1.5-2.5MHz), the signal is selected and switched by a 4-channel switch and then acquired by a digital oscilloscope (DSO9064A, Agilent Technologies, USA) and stored in a computer for subsequent signal processing and MAET image reconstruction.

[0108] (4) The experiment used 32 sound sources for cyclic excitation and orthogonal 4-electrode synchronous measurement to acquire 32×4 measured MAE signal waveforms. The conductivity distribution of the experimental model cross-section is shown in the figure. Figure 6 As shown in (a), the speed of sound in the measured circular field is uniformly approximated as 1550 m / s. Figure 6 (b) and (c) show the MAE signal waveform and its envelope measured by a certain electrode. Figure 6 (b) shows two distinct MAE voltage clusters, A and B, corresponding to Figure 6 In (c), the two envelope peaks A and B correspond to the two boundaries of the gel model, respectively, and their measurement times are approximately 25.2 and 43.7 μs. The length corresponding to the time interval of 18.5 μs perfectly matches the cylinder diameter of 30 mm. As the sound waves propagate in the cylindrical model and the surrounding liquid, the acoustic reflection between the model boundaries generates a small-amplitude MAE voltage, thus forming many relatively small-amplitude wave clusters between wave clusters A and B.

[0109] (5) Using the 32×4 MAE signals collected, under the condition of M=32, and with system configurations of N=1, 2 and 4 respectively, reconstruct as follows: Figure 6 The MAET images (d1)-6(d3) normalized to their respective maximum intensity values ​​show that when M=32, all three N-reconstructed MAET images can accurately reconstruct the shape and position of the model boundary. When N=1, Figure 6 In (d1), the MAET image shows poor continuity and consistency of the ring boundary, with obvious edge spikes and artifacts of varying intensities; when N=2, Figure 6 (d2) The continuity and consistency of the ring boundary are improved, and the intensity of the central artifact is reduced; when N=4, Figure 6(d3) shows a clear eccentric ring with good continuity and uniformity at its boundary, while the artifacts inside are significantly suppressed, forming an approximately uniform distribution.

[0110] (6) With a fixed number of electrodes N=4, different excitation transducers are selected from the measured 32×4 MAE signal waveforms according to the interval, forming system configurations of M=16, 8, and 4, as shown below. Figure 6 The MAET images shown in (e1)-6(e3) illustrate this. The results show that the MAET image with M=32 exhibits the best boundary reconstruction performance. As M decreases, the continuity of the ring-shaped boundary decreases, resulting in an M-sided distribution with distinct sharp angles. When M decreases to 8 and 4, the boundary appears as octagons and quadrilaterals, respectively, failing to form a ring-shaped distribution, thus hindering the reconstruction of the model's conductivity boundary. These results demonstrate that the number of transducers M determines the shape of the boundary; a larger M results in higher integrity and accuracy of the reconstructed model boundary shape. Conversely, the number of electrodes N determines the consistency and continuity of the boundary intensity; a larger N results in higher continuity and consistency of the reconstructed model boundary intensity distribution, and fewer artifacts.

[0111] (7) Experimental results demonstrate the feasibility of the proposed fast MAET imaging method that does not require mechanical rotation and scanning measurement. They also demonstrate that the minimum configuration of the MAET system is M≥30 and N≥4, while the optimized scheme of the fast MAET system is 32 sound sources and orthogonal 4 electrodes.

[0112] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0113] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement, characterized in that, Includes the following steps: S1. Establish a MAET measurement system based on a ring-shaped omnidirectional sound source array and an electrode array to realize the cyclic excitation of the sound field and the synchronous measurement of the MAE signal. S2. Establish a MAE theoretical model based on the excitation of a sound source at any position in a ring and the reception of electrodes, derive the general theoretical formula of the MAE signal, and obtain the determining factors of the amplitude and time of the MAE signal. S3. By introducing the cyclic excitation of a ring sound source and the multi-electrode synchronous measurement technology, a high-precision MAET imaging method based on inverse Radon transform and MAE signal amplitude summation is proposed. S4. Establish a cylindrical tissue model, conduct MAE signal simulations under different numbers of sound sources and electrodes, complete MAET image reconstruction, and analyze the factors affecting image quality. S5. Based on the analysis of the influence of sound source and number of electrodes on the radius fluctuation and intensity relative error of the reconstructed MAET image ring boundary, the minimum configuration requirements of the MAET system are proposed, and further optimization schemes for the fast MAET system are obtained.

2. The rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement according to claim 1, characterized in that, In step S1, a MAET measurement system based on a ring-shaped omnidirectional sound source array and an electrode array is established to realize the cyclic excitation of the sound field and the synchronous measurement of the MAE signal, as detailed below: M uniformly distributed omnidirectional transducers are set at the boundary of a ring-shaped field with radius R0 to cyclically emit sound waves. N sheet-like or needle-like electrodes are set to detect the MAE signal generated by the conductivity boundary of the tested object's tissue. The tested object, of arbitrary shape with conductivity distribution, is placed in a conductive coupling liquid. The entire field exhibits acoustic coupling and electrical transmission characteristics. A pair of parallel permanent magnets generate a uniformly distributed static magnetic field, which acts perpendicularly on the tested field. The pulsed sound waves radiated by the transducers propagate as spherical waves, and the sound field covers the entire tested circular field. The vibration of conductive tissue particles caused by sound propagation interacts with the magnetic field to generate an induced current. After propagation through the conductive medium, the current is received by the electrodes, resulting in N MAE signals containing the conductivity gradient and position information of the tissue boundary. By electronically controlling the cyclic excitation of the M transducers and the synchronous measurement of the N electrodes, rapid measurement of M×N MAE waveforms and MAET image reconstruction are achieved. The M sound sources used must be approximately omnidirectional transducers with a spherical sound radiation half-angle greater than 60°, and the radiated sound field must completely cover the object under test; the surface of the omnidirectional transducer and the coupling liquid must be completely insulated to reduce interference between the sound field and the electric field; the electrodes need to be placed in a coupling liquid with conductivity to ensure the reliability of current transmission. The boundary and bottom of the annular test field should be covered with sound-absorbing material to eliminate the effects of sound reflection and sound scattering. To improve the electric field detection capability, silver or copper sheet or needle-shaped high conductivity electrodes should be selected. The electrodes should be placed between two adjacent transducers at the boundary of the ring field to reduce the influence of the ring-shaped distributed electrodes on the radiated sound field.

3. The rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement according to claim 1, characterized in that, In step S2, a theoretical model of MAE based on excitation by a sound source at an arbitrary position in a ring and reception by electrodes is established. The general theoretical formula for the MAE signal is derived, and the determining factors of the MAE signal amplitude and time are obtained, as follows: The m-th sound source Tm, placed in a circle, emits an omnidirectional sound wave. The sound pressure produced at any position r in the field is: ,in The intensity of the spherical sound source, Let 'a' be the surface vibration velocity of the sound source, and 'a' be the radius of the sound source. For wave number, Angular frequency, c and ρ are the density of the propagation medium and the speed of sound, respectively. Location of the sound source The distance to r, For propagation time, sound pressure generates particle vibration velocity Its direction is , It is the gradient operator, static magnetic field B and Interaction generates induced current density Its direction is ; The nth electrode En on the circumference detects the current density component generated by the mth sound source at point r. Its direction is , yes and The included angle, , yes and The angle between the electrodes, considering the equivalent resistance of the induced current generated at the receiving point r during propagation. and electrode receiving coefficient At the same time, consider Depend on and the direction of conductivity normal The included angle The decision is made based on the fact that electrode En receives sound from source Tm throughout the entire field. The MAE voltage generated internally: The equivalent resistance of the system Proportional to the distance of transmission ,in If the resistance per unit length of the conductive medium is denoted as , then the MAE voltage signal is: in, It is a constant determined by the system structure and parameters; Using an ideal unit pulse signal As the excitation sound source, the MAE voltage is corrected as follows: in, From the location of the sound source and electrode receiving position And the conductivity distribution is determined by taking into account the excitation signal. and the impulse response of the transducer convolution The convolution operator is used to obtain the general formula for the MAE waveform generated by the m-th sound source at the n-th electrode throughout the entire field: The derived theoretical formula proves that the radiated sound field can only generate MAE signal pulses at the tissue conductivity boundary, and the propagation time from the sound source to the tissue boundary is [missing information]. The decision, and the magnitude of it. and location information A joint decision.

4. The rapid magnetoacoustic-electrochemical tomography method without mechanical rotation and scanning measurement according to claim 1, characterized in that, In step S3, a high-precision MAET imaging method based on inverse Radon transform and MAE signal amplitude sum is proposed by introducing a ring sound source cyclic excitation and electrode synchronous measurement technology, as follows: First, the MAE signal waveforms excited by the m-th sound source and received by the n-th electrode. After performing the Hilbert transform and taking the absolute value, the envelope of the MAE signal is obtained. Applying the inverse Radon transform based on the diffraction sound source to the MAE signal envelope, The amplitudes at all times are back-projected into the field. On the arc, reconstruct the MAE image based on the excitation of the sound source Tm and the reception of the electrode En. , Based on synchronous N-electrode measurements, N MAE images under the excitation condition of the sound source Tm are reconstructed. The signal attenuation caused by the measurement angle at different electrode positions is compensated by calculating the sum of amplitudes and the sum of squares of the amplitudes of the MAE signals, respectively, to obtain MAE images based on sound source Tm excitation and synchronous measurement of N electrodes. and , Finally, by introducing cyclic excitation from a ring-shaped M-source and synchronous measurement with N electrodes, and using the acquired M×N MAE waveforms, M MAE images under different sound source excitations are reconstructed. Reconstructing the MAET image using a rotation matrix: ； It represents the angle between adjacent sound sources.

5. The rapid magnetoacoustic-electrochemical tomography method according to claim 1, characterized in that, In step S4, a cylindrical tissue model is established, and MAE signal simulations are conducted under different sound sources and electrode numbers to complete MAET image reconstruction and analyze the factors affecting imaging quality, as detailed below: A 16-source and 16-electrode MAET system was established. An eccentric cylindrical tissue model was placed inside the measurement field. Sixteen transducers were used for cyclic excitation, and sixteen electrodes were used for synchronous measurement to obtain a 16×16 MAET waveform. The MAET image was reconstructed, and the results showed the boundary of the reconstructed circular model, proving that the number of sound sources has a significant impact on MAET.

6. The rapid magnetoacoustic-electrochemical tomography method according to claim 1, characterized in that, In step S5, based on the analysis of the influence of the number of sound sources M and the number of electrodes N on the radius fluctuation and relative intensity error of the ring boundary of the MAET image, the minimum configuration requirements of the MAET system are proposed, and the optimization scheme of the fast MAET system is further obtained, as follows: A circular tissue model was established to simulate MAE signals synchronously received by 16 electrodes under different numbers of sound sources. The MAET image was reconstructed, and the radius fluctuation coefficient of the annular boundary was defined. ,in It is the radius at the i-th measured angle. The average radius of the Q-time circular measurements proves that the wave coefficient decreases as the number of sound sources increases. At that time, the radius fluctuation coefficient is less than 0.02 mm, therefore... To achieve an acceptable image quality standard, the minimum number of sound sources required for a MAET system configuration is: , Under the condition of minimum number of sound sources M=30, a 64-electrode MAET system was constructed. An eccentric circumferential structure model was set up, and N electrodes uniformly distributed along the circumference were selected to form different synchronous measurement groups. Different starting electrodes n were used for measurement. s MAE signal simulation and imaging under N=1, 2, 4, 8, 16, 32 and 64 conditions, defining the relative error of the ring boundary strength of the MAET image and model. Where Q is the number of ring sampling points, The intensity of the i-th sampling point on the annular boundary of the MAET image, given different N and n values. s MAET imaging was performed under these conditions to obtain average values. The relationship between N and N is used to prove that as N increases from 1 to 4, The value rapidly decreased from 0.19 to 0.027, and then stabilized after N≥4. When N<4, the reconstructed MAET image quality was poor and significantly affected by the electrode positions. When N≥4, the MAET image accurately reflected the boundary distribution of the model, and the imaging quality was not affected by the positions of the four orthogonally distributed electrodes. Therefore, with N≥4, the reconstructed MAET image... =0.027 is the acceptable standard for image quality. Therefore, the minimum number of electrodes for the MAET system is N=4, and they need to be orthogonally placed. In summary, the minimum configuration of the proposed MAET system that does not require mechanical rotation and scanning is M≥30 and N≥4. Further considering the actual requirements of uniform distribution of transducers on the circumference and orthogonal distribution of electrodes, the optimized configuration of the MAET system is M=32 and N=4.

7. The rapid magnetoacoustic-electrochemical tomography method according to claim 1, characterized in that, A circular 32-electrode sound source and orthogonal 4-electrode experimental system were established. MAE measurements and MAET imaging were performed on an eccentric cylindrical model to prove the correctness of the imaging method and the feasibility of the optimization scheme. The MAET system includes a computer, a function generator, a power amplifier, a 32-channel analog signal switcher, a 4-channel analog signal switcher, a low-noise preamplifier, a low-pass filter amplifier, an oscilloscope, a cylindrical container, neodymium iron boron magnets, 32 omnidirectional transducers, and 4 sheet electrodes. The 32 omnidirectional transducers are sequentially connected to the 32-channel analog signal switcher, the power amplifier, and the function generator. The function generator outputs a pulsed sine wave signal, which is amplified by the power amplifier and then drives the transducer to emit sound waves after being switched through the 32 analog signals. The sound waves propagate in the cylindrical container and generate MAE signals under the influence of the magnetic field. These signals are synchronously detected by the orthogonally placed four electrodes, selected by the 4-channel analog signal switcher, amplified by the low-noise preamplifier and the low-pass filter amplifier, acquired by the oscilloscope, and stored in the computer. Using the measured 32×4 MAE signal waveform, the annular boundary distribution of the cylindrical model was reconstructed using the above imaging method, demonstrating the feasibility of the fast MAET method.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a rapid magnetoacoustic tomography method without mechanical rotation and scanning measurement as described in any one of claims 1 to 7.

9. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, the computer instructions implement a rapid magnetoacoustic tomography method as described in any one of claims 1-7, which does not require mechanical rotation and scanning measurements.

Images