A sound field simulation method, apparatus, device, medium and product

Abstract

This disclosure relates to a sound field simulation method, apparatus, device, medium, and product. The method includes: acquiring first structural data of a first virtual structure and array element excitation data of an ultrasonic transducer; performing forward simulation based on the first structural data and the array element excitation data using a first simulation mode to obtain first excitation data on the first virtual structure; using the first virtual structure as a first emission source, performing forward simulation based on the first structural data and the first excitation data using a second simulation mode to obtain sound field distribution data of an intracranial target point; wherein, the first virtual structure is located in the sound propagation domain between the ultrasonic transducer and the intracranial target point, and the simulation efficiency of the first simulation mode and the second simulation mode differs. This disclosure solves the problem of significant lag in sound field simulation and can adapt to medical application scenarios with high timeliness requirements.

Description

Technical Field

[0001] This disclosure relates to the field of medical ultrasound technology, and in particular to a sound field simulation method, apparatus, equipment, medium and product. Background Technology

[0002] Transcranial focused ultrasound (TCU) is a novel technique that non-invasively focuses ultrasound energy through the scalp and skull onto a specific target area within the cranium. Its non-invasive, precise, and controllable advantages have made it a research hotspot in the field of targeted intervention. To achieve precise application, it is often necessary to simulate and analyze the acoustic field effects generated by the ultrasound beam at the intracranial target point beforehand.

[0003] The acoustic propagation domain from the ultrasound transducer to the intracranial target involves multiple media interfaces. The significant differences in their acoustic properties increase the computational complexity of sound field simulation. At the same time, the insufficient computing power caused by the limited hardware deployment conditions in medical scenarios results in a significant lag in the simulation of sound field effects, which seriously restricts the practical application of transcranial focused ultrasound technology in scenarios with high timeliness requirements. Summary of the Invention

[0004] This disclosure relates to a sound field simulation method, apparatus, equipment, medium, and product to solve the problem of significant lag in sound field simulation and improve its adaptability to medical application scenarios with high timeliness requirements.

[0005] One aspect of this disclosure relates to a sound field simulation method, the method comprising:

[0006] Acquire the first structural data of the first virtual structure and the array element excitation data of the ultrasonic transducer;

[0007] By performing forward simulation based on the first structural data and the array element excitation data in the first simulation mode, the first excitation data on the first virtual structure is obtained.

[0008] Using the first virtual structure as the first emission source, a forward simulation is performed based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target point.

[0009] The first virtual structure is located in the acoustic propagation domain between the ultrasound transducer and the intracranial target, and the simulation efficiency of the first simulation mode is different from that of the second simulation mode.

[0010] Another aspect of this disclosure relates to a sound field simulation device, the device comprising:

[0011] The array element excitation data acquisition module is used to acquire the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer.

[0012] The first excitation data determination module is used to perform forward simulation based on the first structure data and the array element excitation data in a first simulation mode to obtain the first excitation data on the first virtual structure.

[0013] The sound field distribution data determination module is used to take the first virtual structure as the first emission source and perform forward simulation based on the first structure data and the first excitation data through the second simulation mode to obtain the sound field distribution data of the intracranial target point;

[0014] The first virtual structure is located in the acoustic propagation domain between the ultrasound transducer and the intracranial target, and the simulation efficiency of the first simulation mode is different from that of the second simulation mode.

[0015] Another aspect of this disclosure relates to an electronic device comprising:

[0016] At least one processor;

[0017] A memory that is communicatively connected to the at least one processor;

[0018] The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the sound field simulation method according to any embodiment of this disclosure.

[0019] Another aspect of this disclosure relates to a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the sound field simulation method described in any embodiment of this disclosure.

[0020] Another aspect of this disclosure relates to a computer program product, including a computer program that, when executed by a processor, implements the sound field simulation method described in any embodiment of this disclosure.

[0021] The technical solution of this disclosure deploys a virtual structure on the acoustic propagation domain between the ultrasound transducer and the intracranial target, decoupling the entire acoustic propagation domain into two independent acoustic propagation subdomains. A simulation mode with simulation efficiency adaptable to the acoustic characteristics of the acoustic propagation subdomain is used to simulate the acoustic propagation law of the sound wave in this subdomain. The sound field distribution data of the intracranial target is obtained by forward deduction through the two simulation modes. This avoids the situation where the simulation mode with single simulation efficiency is prone to obvious simulation lag, solves the problem of poor focusing quality of transcranial focused ultrasound technology, improves the operating efficiency of the transcranial focusing process, and can adapt to medical application scenarios with high timeliness requirements.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating a sound field simulation method provided in one embodiment of this disclosure;

[0025] Figure 2 A flowchart illustrating another sound field simulation method provided in one embodiment of this disclosure;

[0026] Figure 3 This is a schematic diagram of a two-layer decoupling of the acoustic propagation domain provided in one embodiment of the present disclosure;

[0027] Figure 4 A flowchart illustrating another sound field simulation method provided in one embodiment of this disclosure;

[0028] Figure 5 A schematic diagram of the structure of a sound field simulation device provided in one embodiment of this disclosure;

[0029] Figure 6 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present disclosure. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0031] It should be noted that the terms "first," "second," "third," "fourth," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Figure 1 This is a flowchart illustrating a sound field simulation method according to an embodiment of this disclosure. This embodiment is applicable to simulating the sound field effect generated by an ultrasound transducer at an intracranial target point. The method can be executed by a sound field simulation device, which can be implemented in hardware and / or software and can be configured in a terminal device. Figure 1 As shown, the method includes:

[0033] S110: Obtain the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer.

[0034] The first virtual structure is not an actual physical structure, but rather an abstract set of virtual elements configured based on the propagation path, simulation accuracy requirements, and simulation efficiency requirements of transcranial focused ultrasound. Specifically, the first virtual structure can be a virtual plane or a virtual volume. The first structure data represents the structural feature dimension and spatial deployment dimension of the first virtual structure. For example, the first structure data includes, but is not limited to, the geometric shape, geometric size, grid configuration features, deployment position in the sound propagation domain, and grid filling elements of the first virtual structure. The grid configuration features include, but are not limited to, the number, arrangement, and density of virtual grids.

[0035] Taking the first virtual structure as a virtual plane as an example, its geometry can be a fixed plane, a spherical / cylindrical surface, a curved surface conforming to the surface of the skull, or a closed curved surface. Among these, the fixed plane structure is simple and facilitates the interpolation calculation and data processing of sound signals. The spherical / cylindrical surface better matches the radiation geometry of sound waves, thus better matching the spherical propagation law of sound waves. The curved surface conforming to the surface of the skull or a closed curved surface can more completely preserve the wavefront information of sound waves and effectively reduce the loss of wavefront information.

[0036] The geometry of the virtual plane is only illustrated here and is not limited thereto. It can be configured according to actual needs.

[0037] In this embodiment, the first virtual structure is located on the acoustic propagation domain between the ultrasound transducer and the intracranial target, and is used to decouple the acoustic propagation domain into two acoustic propagation subdomains with different acoustic characteristics. The acoustic characteristics can be reflected by the medium characteristics of the acoustic propagation subdomains. For example, the medium type affects the acoustic impedance, attenuation coefficient and sound velocity, the medium quantity affects the sound field superposition effect and attenuation number, and the medium size affects the sound wave diffraction, scattering intensity and propagation path length. The different medium characteristics will cause the acoustic propagation law of the sound wave through the two acoustic propagation subdomains to show significant differences.

[0038] Specifically, the first virtual structure provides a virtual intermediate layer for the forward sound propagation process, carrying out the sound wave emission function and realizing the segmented transmission and conversion of sound waves. The first virtual structure is consistent with the actual emission characteristics of the ultrasonic transducer, enabling precise response to the control of excitation data. In an optional embodiment, the grid filling elements of the first virtual structure are virtual transmitters.

[0039] The ultrasonic transducer in this embodiment is a phased array transducer, which consists of multiple independently controllable ultrasonic array elements. Different array element combinations can be formed by adjusting the number and arrangement of array elements participating in the focusing task, to adapt to the focusing requirements of different skull shapes, different target positions and different focal zone shapes. For example, the arrangement can be linear, annular and convex, etc.

[0040] The element excitation data characterizes the excitation information of pre-selected ultrasound elements in the ultrasound transducer, used to form a focused sound field at the intracranial target point. Specifically, the element excitation data includes the element excitation signal corresponding to the pre-selected ultrasound element in the ultrasound transducer. The element excitation signal characterizes the excitation information applied to the ultrasound element to generate sound wave radiation, and includes amplitude and phase information.

[0041] S120. Perform forward simulation using the first simulation mode based on the first structural data and the array element excitation data to obtain the first excitation data on the first virtual structure.

[0042] Specifically, the first simulation mode simulates the complete process of sound waves originating from an ultrasonic transducer, passing through one or more media, and finally reaching the first virtual structure. For example, based on the spatial deployment data in the first structure data, the first simulation mode determines the acoustic propagation subdomain near the ultrasonic transducer. Combining this with the physical structure data and array element excitation data in the first structure data, it calculates the attenuation degree, phase shift, and propagation distortions such as reflection and refraction of the sound waves by the medium interface in this acoustic propagation subdomain, ultimately outputting first excitation data that matches the first virtual structure.

[0043] S130. Using the first virtual structure as the first emission source, perform forward simulation based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target.

[0044] The first emission source refers to the virtual radiation source that replaces the ultrasonic transducer. It is a physical or virtual structure that serves as a new starting point for sound wave emission. Its core function is to provide virtual sound waves, which provide a benchmark for subsequent sound wave propagation, signal reception, and data derivation.

[0045] Since the first virtual structure decouples the acoustic propagation domain into two acoustic propagation subdomains with different acoustic characteristics, a second simulation mode with different simulation efficiency than the first simulation mode is used to perform a forward simulation of the other acoustic propagation subdomain that is far away from the ultrasonic transducer. This is to adapt to the acoustic characteristics of this acoustic propagation subdomain that are different from the other acoustic propagation subdomain, thus overcoming many technical defects of the single and highly efficient simulation mode, such as insufficient simulation accuracy, sensitivity to parameter uncertainty, and unreasonable allocation of computing resources.

[0046] Specifically, higher simulation efficiency often leads to lower simulation accuracy. However, simulation accuracy is also affected by non-algorithm factors such as hardware performance, data quality, and boundary conditions. Therefore, it is possible that simulation efficiency may be high but simulation accuracy may not be low. This embodiment does not strictly limit the correlation of simulation accuracy among all simulation modes.

[0047] Specifically, the second simulation mode simulates the complete process of sound waves originating from the first virtual structure, passing through one or more media, and finally reaching the intracranial target. For example, based on the spatial deployment data in the first structural data, the second simulation mode determines the acoustic propagation subdomain far from the ultrasound transducer. Based on the first excitation data, it calculates the attenuation degree, phase shift, reflection and refraction effects of the medium interface on the sound waves in this acoustic propagation subdomain, and the superposition effect at the intracranial target, outputting the sound field distribution data of the intracranial target.

[0048] The sound field distribution data refers to the spatial distribution information of key acoustic physical quantities such as sound pressure, sound intensity, and phase formed by sound waves at intracranial target points, which can be used to assess focusing quality and intervention safety.

[0049] For example, the sound field distribution data includes, but is not limited to, focusing characteristic parameters, energy characteristic parameters, and safety characteristic parameters. The focusing characteristic parameters are used to determine whether the ultrasound energy is accurately focused on the intracranial target point. These parameters may include the focusing position of the ultrasound beam at the intracranial target point, the size of the focal spot, and the size of the -6dB region. The -6dB region refers to the spatial range enclosed by the ultrasound sound field where the sound pressure amplitude drops to half of the peak sound pressure (corresponding to a relative sound intensity level of -6dB). The size of the -6dB region can be the volume or length of the -6dB region. The energy characteristic parameters may include the sound energy distribution at the intracranial target point and the sound energy distribution of the surrounding normal tissues. For example, the sound energy distribution includes peak sound pressure and peak sound intensity. The safety assessment parameters may include the mechanical index, the spatial peak time-averaged sound intensity, and the spatial peak pulse-averaged sound intensity after de-rating. These parameters can provide a quantitative basis for the safety of transcranial focused ultrasound technology.

[0050] This section only provides an example of sound field distribution data and does not limit its application; specific settings can be customized according to actual needs.

[0051] The technical solution of this embodiment deploys a virtual structure on the acoustic propagation domain between the ultrasound transducer and the intracranial target, decoupling the entire acoustic propagation domain into two independent acoustic propagation subdomains. A simulation mode with simulation efficiency adaptable to the acoustic characteristics of the acoustic propagation subdomain is used to simulate the acoustic propagation law of the sound wave in this subdomain. The sound field distribution data of the intracranial target is obtained by forward deduction through the two simulation modes, avoiding the obvious simulation lag that is easy to occur in the simulation mode with single simulation efficiency. This solves the problem of poor focusing quality of transcranial focused ultrasound technology, improves the operating efficiency of the transcranial focusing process, and can adapt to medical application scenarios with high timeliness requirements.

[0052] Figure 2 This is a flowchart of another sound field simulation method provided in one embodiment of the present disclosure. This embodiment further refines the above embodiment's "performing forward simulation based on the first structural data and the array element excitation data using a first simulation mode to obtain the first excitation data on the first virtual structure." In this embodiment, the step of performing forward simulation based on the first structural data and the array element excitation data using a first simulation mode to obtain the first excitation data on the first virtual structure includes: acquiring a first simulation mode matching the first propagation subdomain; performing forward simulation based on the first structural data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure; wherein, the simulation efficiency of the first simulation mode for the intracranial propagation subdomain is lower than that of the first simulation mode for the extracranial propagation subdomain. Figure 2 As shown, the method includes:

[0053] S210. Obtain the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer.

[0054] In this embodiment, the first virtual structure is located on the side of the first propagation subdomain closer to the skull structure. The first propagation subdomain is either an extracranial propagation subdomain or an intracranial propagation subdomain. The extracranial propagation subdomain is the acoustic propagation subdomain between the ultrasound transducer and the skull structure, and the intracranial propagation subdomain represents the acoustic propagation subdomain between the skull structure and the intracranial target.

[0055] The skull is the bony framework of the human head, mainly composed of multiple skull bones such as the frontal bone, parietal bone, temporal bone, and occipital bone. Its acoustic properties differ significantly from those of air and human soft tissue, and it has a strong and complex influence on the propagation of sound waves, including scattering, absorption, and refraction.

[0056] Specifically, both the extracranial and intracranial propagation subdomains are acoustic propagation subdomains that do not include the skull structure. The extracranial propagation subdomain is mainly composed of air, and its acoustic characteristics are relatively uniform and stable. The attenuation and distortion of sound waves within the extracranial propagation subdomain are relatively small, making simulation easier. The intracranial propagation subdomain is mainly composed of intracranial tissues such as brain parenchyma, cerebrospinal fluid, and cerebral blood vessels. The acoustic characteristics within each medium are relatively uniform, which will have a slight impact on sound wave propagation.

[0057] S220. Obtain the first simulation mode that matches the first propagation subdomain.

[0058] Taking the ultrasound transducer as a reference point, when the first propagation subdomain is an intracranial propagation subdomain, the acoustic propagation subdomain near the ultrasound transducer is an acoustic propagation subdomain containing the skull structure, and the acoustic propagation subdomain far from the ultrasound transducer is the first propagation subdomain. When the first propagation subdomain is an extracranial propagation subdomain, the acoustic propagation subdomain near the ultrasound transducer is the first propagation subdomain, and the acoustic propagation subdomain far from the ultrasound transducer is an acoustic propagation subdomain containing the skull structure.

[0059] In response to the flexible customization attributes of the first propagation subdomain, this embodiment configures first simulation modes with different simulation efficiencies for customized scenarios where the first propagation subdomain is either an extracranial or intracranial propagation subdomain. Specifically, the simulation efficiency of the first simulation mode for the intracranial propagation subdomain is lower than that of the first simulation mode for the extracranial propagation subdomain.

[0060] In embodiments where the first propagation subdomain is an extracranial propagation subdomain, the acoustic propagation subdomain near the ultrasound transducer is the first propagation subdomain. Its acoustic characteristics are simple, and a high-efficiency simulation mode is configured as the first simulation mode to adapt to the simple acoustic characteristics in this acoustic subdomain and ensure the simulation efficiency of the first excitation data.

[0061] For example, the high-efficiency simulation mode employs simulation methods including, but not limited to, the angular spectrum method, the Rayleigh integral method, the pre-calculated acoustic window table method, or the simplified ray method. The core principle of the angular spectrum method is to convert the propagation of sound waves in the spatial domain to the frequency domain for calculation. By simplifying the propagation equation through Fourier transform, the computational load can be significantly reduced, and the propagation response in the sound propagation subdomain can be quickly output. The core principle of the Rayleigh integral method is to calculate the superposition effect of sound pressure generated by radiated sound waves at sampling points through integration, quickly completing the simulation task. The core principle of the pre-calculated acoustic window table method is to pre-calculate the excitation data of multiple array elements and the excitation data on the first virtual structure under various acoustic parameters using a high-precision simulation mode, constructing a standardized acoustic window table. In the actual sound field simulation, there is no need to perform fitting calculations of sound wave propagation behavior; the first excitation data matching the array element excitation data is found from the acoustic window table. The core principle of the simplified ray method is to simplify sound wave propagation to ray propagation, ignoring secondary effects such as sound wave scattering and diffraction, and only calculating the propagation path, propagation time, and attenuation of the ray. Millisecond-level simulation calculations can be achieved with a small number of ray samples.

[0062] In the embodiment where the first propagation subdomain is an intracranial propagation subdomain, the acoustic propagation subdomain near the ultrasound transducer includes the skull structure. This acoustic propagation subdomain has complex acoustic characteristics. A low-efficiency mode is configured as the first simulation mode to adapt to the complex acoustic characteristics of this acoustic propagation subdomain, especially the acoustic characteristics of the skull structure, to ensure the accuracy of the first excitation data, achieve reasonable allocation of computing resources, and improve the stability of the sound field simulation process without affecting the overall simulation efficiency.

[0063] For example, the simulation methods used in inefficient simulation modes include, but are not limited to, pseudospectral time-domain methods, finite difference time-domain methods, finite element methods, or boundary element methods. Among them, the core principle of the pseudospectral time-domain method is to solve the sound wave equation using the Fourier pseudospectral method. It uses low-efficiency interpolation to approximate the sound propagation subdomain and the finite difference method to iterate in the time domain, which can accurately simulate the propagation distortion of the sound wave in the sound propagation subdomain. The core principle of the finite difference time-domain method is to discretize the sound propagation subdomain into a three-dimensional mesh, approximate the sound wave equation through the difference equation, and calculate the sound pressure and particle velocity at each mesh point step by step, which can accurately capture the propagation characteristics of the sound wave in a small region. The core principle of the finite element method is to discretize the sound propagation subdomain into a finite number of elements and solve the sound wave equation through the variational principle. It can perform fine mesh subdivision of the sound propagation subdomain and accurately calculate the sound pressure, phase distribution, and focusing range and intensity of the sound field at the target point. The core principle of the boundary element method is to transform the sound wave propagation equation into a boundary integral equation. It only discretizes the boundary of the sound propagation subdomain and does not need to mesh the entire sound propagation subdomain. It can shorten the simulation time while ensuring simulation accuracy.

[0064] For example, to address the issues of high computational load and long simulation time in inefficient simulation modes, it can be combined with graphics processor acceleration technology to allocate highly parallel computational tasks such as grid computing and differential iteration to the graphics processor core. By utilizing the parallel computing capabilities of the graphics processor, the simulation time of inefficient simulation modes can be further shortened, achieving a balance between simulation accuracy and simulation efficiency.

[0065] It is understood that the above embodiments are merely illustrative examples of the simulation methods used in the high-efficiency simulation mode and the low-efficiency simulation mode, and are not intended to limit them.

[0066] S230. Perform forward simulation using the first simulation mode based on the first structural data and the array element excitation data to obtain the first excitation data on the first virtual structure.

[0067] In an optional embodiment, the first simulation mode is used to perform forward simulation based on the first structural data and the array element excitation data to obtain the first excitation data on the first virtual structure, including: when the first propagation subdomain is an intracranial propagation subdomain, obtaining a skull acoustic model registered with the intracranial target; and performing forward simulation based on the skull acoustic model, the first structural data, and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure.

[0068] The skull acoustic model represents the acoustic parameters of the skull structure. In one optional embodiment, the skull acoustic model is extracted from a head acoustic model registered with intracranial targets, or it is reconstructed based on skull imaging data.

[0069] Among them, the head acoustic model is used to comprehensively and accurately characterize the acoustic properties of various tissues in the human head. For example, head tissues include, but are not limited to, the skull structure, brain parenchyma, cerebrospinal fluid and cerebral blood vessels, as well as all other tissues related to sound propagation. Acoustic properties include, but are not limited to, sound velocity, density and attenuation coefficient.

[0070] In an optional embodiment, obtaining the head acoustic model registered with the intracranial target includes: obtaining head image data corresponding to the intracranial target; preprocessing the head image data; segmenting the preprocessed head image data to obtain head mask data, wherein the head mask data includes at least tissue mask data corresponding to the skull structure and intracranial soft tissue respectively; mapping the pixel grayscale values ​​in each tissue mask data to acoustic parameter values ​​to obtain tissue acoustic data; and determining the head acoustic model registered with the intracranial target based on each tissue acoustic data.

[0071] For example, head imaging data can be image data acquired by medical imaging equipment such as MRI, computed tomography, digital subtraction angiography, or positron emission tomography. Preprocessing includes, but is not limited to, noise reduction and resampling. Segmentation methods include, but are not limited to, threshold segmentation, region growing, or deep learning networks. The mapping methods corresponding to different tissue acoustic data can be linear mapping, piecewise linear mapping, or actual measurement mapping. Linear mapping or piecewise linear mapping can be achieved by obtaining pixel acoustic mapping data through sample statistics. Pixel acoustic mapping data represents the mapping function or mapping range between pixel gray values ​​and acoustic parameter values.

[0072] For example, spatial smoothing or boundary correction processing is performed on the acoustic data of each tissue to obtain multiple tissue acoustic models, and the tissue acoustic models are integrated to obtain a head acoustic model registered with intracranial targets.

[0073] In this embodiment, the first simulation mode is a low-efficiency simulation mode. Based on the physical laws of sound wave propagation through the skull structure characterized by the skull acoustic model, it deduces the process of sound wave propagating from the ultrasonic transducer to the first virtual structure in the skull. After calculating the scattering, attenuation and other characteristics of the skull structure interface, it accurately solves and outputs the first excitation data that matches the spatial characteristics and excitation characteristics of the first virtual structure.

[0074] In another optional embodiment, the step of performing forward simulation based on the first structural data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure includes: when the first propagation subdomain is an extracranial propagation subdomain, acquiring spatial deployment data from the first structural data; and performing forward simulation based on the spatial deployment data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure.

[0075] In this embodiment, the spatial deployment data represents the spatial mapping information between the virtual grid in the first virtual structure and the ultrasonic array elements in the ultrasonic transducer, and the first simulation mode is a high-efficiency simulation mode.

[0076] For example, spatial deployment data can be obtained by projecting the center of the ultrasonic array element in the ultrasonic transducer onto the first virtual structure, or by projecting the effective radiation surface of the ultrasonic array element onto the first virtual structure. If the number of array elements is different from the number of grids or there are no matching virtual grids after projection, then the multiple virtual grids closest to the projection position of the ultrasonic array element are all used as virtual grids matching the ultrasonic array element.

[0077] Specifically, for each pre-selected ultrasonic array element, one or more virtual grids that match the ultrasonic array element are searched from the spatial deployment data. When there is only one matching virtual grid, the array element excitation signal of the ultrasonic array element is used as the first excitation signal corresponding to the virtual grid. When there are multiple matching virtual grids, the array element excitation signal of the ultrasonic array element is downsampled or subjected to least squares inverse processing to obtain the first excitation signals corresponding to the multiple virtual grids respectively.

[0078] S240. Using the first virtual structure as the first emission source, perform forward simulation based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target.

[0079] In one optional embodiment, a forward simulation is performed using a second simulation mode based on the first structural data and the first excitation data to obtain the sound field distribution data of the intracranial target. This includes: when the first propagation subdomain is an extracranial propagation subdomain, obtaining a head acoustic model registered with the intracranial target; and performing a forward simulation using the second simulation mode based on the head acoustic model, the first structural data, and the first excitation data to obtain the sound field distribution data of the intracranial target.

[0080] In this embodiment, the second simulation mode is a low-efficiency simulation mode. Based on the physical laws of sound wave propagation through the entire head as represented by the head acoustic model, it deduces the process of sound wave propagating from the first virtual structure to the intracranial target. After calculating the scattering, attenuation and other characteristics of the skull structure interface and soft tissue interface, it outputs the sound field distribution data of the intracranial target.

[0081] In another optional embodiment, a forward simulation is performed based on the first structural data and the first excitation data using a second simulation mode to obtain the sound field distribution data of the intracranial target. This includes: when the first propagation subdomain is an intracranial propagation subdomain, obtaining a soft tissue acoustic model registered with the intracranial target; and performing a forward simulation based on the soft tissue acoustic model, the first structural data, and the first excitation data using the second simulation model to obtain the sound field distribution data of the intracranial target.

[0082] In this embodiment, the second simulation mode is a high-efficiency simulation mode, which is based on the physical laws of sound wave propagation through soft tissue represented by the soft tissue acoustic model. It deduces the propagation process of sound wave from the first virtual structure in the skull to the intracranial target point. After calculating the scattering, attenuation and other characteristics of the soft tissue interface, it outputs the sound field distribution data of the intracranial target point.

[0083] The skull, as a natural barrier for sound propagation inside and outside the skull, has the characteristics of strong scattering, strong attenuation, and significant heterogeneity in sound velocity. It is also the main influencing factor of sound field distortion and energy loss during transcranial sound propagation. Therefore, the acoustic propagation laws of the sound propagation subdomain containing the skull structure and the sound propagation subdomain not containing the skull structure show significant differences.

[0084] The technical solution of this embodiment sets the skull structure as the decoupling benchmark for the entire acoustic propagation domain, dividing it into two independent acoustic propagation subdomains with significantly different acoustic propagation laws. The acoustic propagation subdomain does not include the skull structure, and because its acoustic characteristics are relatively simple, it is matched with a simulation mode with higher simulation efficiency to quickly restore the acoustic propagation law of this subdomain. For the acoustic propagation subdomain that includes the skull structure, because its acoustic characteristics are complex, it is matched with a simulation model with lower simulation efficiency to accurately restore the acoustic propagation law of strong scattering and strong attenuation of the skull structure. Under the premise of meeting the timeliness requirements of the overall simulation efficiency, the stability of the sound field simulation process is improved. This combination of domain-based and efficiency-based simulation paradigm enables transcranial focused ultrasound technology to complete intracranial targeted intervention tasks more flexibly and accurately.

[0085] Based on the above embodiments, optionally, a second virtual structure is deployed on the side of the skull structure closer to the second propagation subdomain in the sound propagation domain. This second propagation subdomain is different from the first propagation subdomain. Specifically, the second propagation subdomain can be an intracranial or extracranial propagation subdomain. When the first propagation subdomain is intracranial, the second propagation subdomain is extracranial; when the first propagation subdomain is extracranial, the second propagation subdomain is intracranial.

[0086] In this embodiment, the first virtual structure and the second virtual structure are distributed on both sides of the skull structure, decoupling the entire sound propagation domain into three sound propagation subdomains, namely the extracranial propagation subdomain, the skull propagation subdomain, and the intracranial propagation subdomain, wherein the skull propagation subdomain includes the skull structure. Figure 3 This is a schematic diagram of a two-layer decoupling of the acoustic propagation domain provided in one embodiment of the present disclosure. Figure 3 The diagram illustrates a two-layer decoupled architecture where the first propagation subdomain is an intracranial propagation subdomain and the second propagation subdomain is an extracranial propagation subdomain.

[0087] In an optional embodiment, the first propagation subdomain is an intracranial propagation subdomain, and the second propagation subdomain is an extracranial propagation subdomain. This embodiment addresses the above... Figure 2 The method for determining the first excitation data provided by the embodiment where the first propagation subdomain is an intracranial propagation subdomain, as shown in S230, is further refined.

[0088] Specifically, the step of performing forward simulation based on the skull acoustic model, the first structural data, and the array element excitation data in the first simulation mode to obtain the first excitation data on the first virtual structure includes: acquiring the second structural data of the second virtual structure; performing forward simulation based on the second structural data and the array element excitation data in the third simulation mode to obtain the second excitation data on the second virtual structure; and using the second virtual structure as a second emission source, performing forward simulation based on the skull acoustic model, the first structural data, and the second excitation data in the first simulation mode to obtain the first excitation data on the first virtual structure.

[0089] Specifically, the sound waves originating from the ultrasonic transducer pass through the extracranial propagation subdomain and the skull propagation subdomain in sequence before reaching the first virtual structure. In this embodiment, the second virtual structure further decouples the acoustic propagation subdomain containing the skull structure in the single-layer decoupling architecture into the extracranial propagation subdomain and the skull propagation subdomain. Since the acoustic characteristics of the extracranial propagation subdomain and the skull propagation subdomain are very different, this embodiment adds a third simulation mode compared to the single first simulation mode in the single-layer decoupling architecture. This third simulation mode is used to perform forward simulation of the extracranial propagation subdomain, while the first simulation mode only performs forward simulation of the skull propagation subdomain.

[0090] In this embodiment, the simulation efficiency of both the second simulation mode and the third simulation mode is higher than that of the first simulation mode. For example, the third simulation mode can be the same as the second simulation mode, or it can be a different, more efficient simulation mode. This embodiment does not strictly limit the correlation between the third simulation mode and the second simulation mode in terms of simulation efficiency.

[0091] The method for determining the second incentive data is the same as described above. Figure 2 The method for determining the first excitation data provided in the embodiment where the first propagation subdomain is an extracranial propagation subdomain, as shown in S230, is similar and will not be repeated in this embodiment.

[0092] Specifically, the first simulation mode is a low-efficiency simulation mode. Based on the physical laws of sound wave propagation through the skull structure represented by the skull acoustic model, it deduces the process of sound wave propagating from the second virtual structure outside the skull through the skull structure to the first virtual structure inside the skull. After calculating the scattering, attenuation and other characteristics of the skull structure interface, it accurately solves and outputs the first excitation data that matches the spatial characteristics and excitation characteristics of the first virtual structure.

[0093] like Figure 3As shown, the dashed arrows indicate the direction of sound wave propagation. The sound wave originates from the ultrasonic transducer, passes through the high-efficiency simulation mode of the extracranial propagation subdomain, and obtains the second excitation data on the second virtual structure outside the skull. After passing through the second virtual structure, the sound wave passes through the low-efficiency simulation mode of the skull propagation subdomain and obtains the first excitation data on the first virtual structure inside the skull. After passing through the first virtual structure, the sound wave passes through the high-efficiency simulation mode of the intracranial propagation subdomain and obtains the sound field distribution data of the intracranial target point.

[0094] In another optional embodiment, the first propagation subdomain is an extracranial propagation subdomain, and the second propagation subdomain is an intracranial propagation subdomain. The method for determining the first excitation data in this embodiment is the same as described above. Figure 2 The method for determining the first excitation data provided in the embodiment where the first propagation subdomain is an extracranial propagation subdomain, as shown in S230, is the same or similar, and will not be repeated in this embodiment.

[0095] This embodiment refers to the above. Figure 2 The method for determining the sound field distribution data provided by the embodiment where the first propagation subdomain is the extracranial propagation subdomain, as shown in S240, is further refined.

[0096] Specifically, the step of performing forward simulation based on the first structural data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target includes: acquiring the second structural data of the second virtual structure; acquiring the skull acoustic model and soft tissue acoustic model registered with the intracranial target; performing forward simulation based on the skull acoustic model, the first structural data, and the first excitation data in the second simulation mode to obtain the second excitation data on the second virtual structure; using the second virtual structure as the second emission source, performing forward simulation based on the soft tissue acoustic model, the second structural data, and the second excitation data in the fourth simulation mode to obtain the sound field distribution data of the intracranial target.

[0097] Specifically, the sound waves originating from the first virtual structure pass through the skull propagation subdomain and the intracranial propagation subdomain in sequence before reaching the intracranial target. In this embodiment, the second virtual structure further decouples the acoustic propagation subdomain containing the skull structure in the single-layer decoupled architecture into the intracranial propagation subdomain and the skull propagation subdomain. Since the acoustic characteristics of the intracranial propagation subdomain and the skull propagation subdomain are very different, this embodiment adds a fourth simulation mode compared to the single first simulation mode in the single-layer decoupled architecture. This fourth simulation mode is used to perform forward simulation of the intracranial propagation subdomain, while the second simulation mode only performs forward simulation of the skull propagation subdomain.

[0098] In this embodiment, the simulation efficiency of both the first simulation mode and the fourth simulation mode is higher than that of the second simulation mode. For example, the fourth simulation mode can be the same as the first simulation mode, or it can be a different, more efficient simulation mode. This embodiment does not strictly limit the correlation between the fourth simulation mode and the first simulation mode in terms of simulation efficiency.

[0099] Specifically, the second simulation mode is a low-efficiency simulation mode. Based on the physical laws of sound wave propagation through the skull structure represented by the skull acoustic model, it deduces the process of sound wave propagating from the first virtual structure outside the skull through the skull structure to the second virtual structure inside the skull. After calculating the scattering, attenuation and other characteristics of the skull structure interface, the second excitation data on the second virtual structure is obtained.

[0100] In the two-layer decoupling architecture, the methods for determining the sound field distribution data in the above embodiments are all the same as those described above. Figure 2 The method for determining the sound field distribution data provided in S240 in the embodiment where the first propagation subdomain is the intracranial propagation subdomain is the same or similar, and will not be repeated in this embodiment.

[0101] This embodiment constructs a two-layer decoupling architecture for the sound propagation domain by adding a second virtual structure. The entire sound propagation domain is divided into three independent sound propagation subdomains: the extracranial propagation subdomain, the skull propagation subdomain, and the intracranial propagation subdomain. The skull structure is separately divided into an independent sound propagation subdomain, which further reduces the strong coupling effect between different acoustic media in the sound propagation domain, improves the stability and efficiency of the sound field simulation process, and further ensures the adaptability of transcranial focused ultrasound technology to medical application scenarios with high timeliness requirements.

[0102] Figure 4 This is a flowchart illustrating another sound field simulation method provided in one embodiment of the present disclosure. This embodiment further refines the sound field simulation method in the above embodiment. Figure 4 As shown, the method includes:

[0103] S310, Obtain the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer.

[0104] S320. Perform forward simulation based on the first structure data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure.

[0105] S330. Using the first virtual structure as the first emission source, perform forward simulation based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target.

[0106] S310-S330 in this embodiment are the same as or similar to any of the above embodiments of this disclosure, and will not be described again here.

[0107] In an embodiment of the single-layer decoupled architecture, the first virtual structure is a virtual cache structure used to store the first stimulus data.

[0108] In an embodiment of the two-layer decoupled architecture, the first virtual structure and / or the second virtual structure are virtual cache structures, the first virtual structure is used to store the first stimulus data, and the second virtual structure is used to store the second stimulus data.

[0109] Specifically, the virtual structure located in the intracranial propagation subdomain is a virtual cache structure used to store the stimulus data that matches it. Optionally, the virtual structure located in the extracranial propagation subdomain is also a virtual cache structure used to store the stimulus data that matches it.

[0110] The advantage of configuring two virtual structures for storage is that it enables independent storage of simulation data for different sound propagation subdomains. This ensures the continuity and integrity of data transmission in multi-level simulation modes and avoids simulation errors caused by cross-interference of simulation data under different simulation performance levels.

[0111] In the above embodiments, the storage function of the virtual structure can also eliminate the need to repeatedly execute the full-process simulation solution in multiple sound field simulations. Only the sound propagation subdomain closest to the intracranial target needs to be simulated, which in particular meets the real-time response requirements of interactive scenarios for multiple sound field simulations.

[0112] Based on the above embodiments, specifically, the grid filling elements of the first virtual structure and / or the second virtual structure are virtual storage media.

[0113] S340, in response to the sound field update operation, acquire target offset data.

[0114] Specifically, sound field update operations refer to various operations that trigger the update of sound field distribution data for intracranial target points. For example, sound field update operations include at least one of the following: target point change operations, head acoustic model posture adjustment operations in a preset coordinate system, and ultrasound transducer pose shift operations. Target point change operations may include intracranial target point position adjustment operations, size adjustment operations, target point addition operations or target point reduction operations in multi-target scenarios, etc. The preset coordinate system refers to a unified spatial coordinate system set according to the image coordinate system, transducer coordinate system, and intervention object coordinate system. Posture adjustment operations may include head pitch, rotation, translation, etc., and pose shift operations indicate a change in the spatial positioning of the ultrasound transducer.

[0115] This section only provides an example of the sound field update operation and is not limited to the example scenarios given above.

[0116] In this embodiment, the target offset data represents the pose offset information of the intracranial target relative to the ultrasound transducer. For example, reference pose data of the intracranial target and the ultrasound transducer are acquired, representing their relative pose information. The current spatial orientation of the ultrasound transducer and the current target pose of the intracranial target are acquired. Real-time pose data is calculated based on the current spatial orientation and the current target pose. The real-time pose data is compared with the reference pose data to obtain the target offset data. The relative pose parameters include relative offset distance and / or relative offset angle.

[0117] S350. If the target offset data meets the preset offset range, read the excitation data from the virtual structure closest to the intracranial target, and obtain the third excitation data by calibrating the excitation data according to the target offset data.

[0118] The preset offset range represents the maximum adaptability of the sound field distribution data to the target offset data. If the target offset data meets the preset offset range, it means that the acoustic propagation law of the intracranial propagation subdomain can be compensated for by the acoustic distortion caused by the pose offset, and the sound field can be refocused. If the target offset data exceeds the preset offset range, it means that the acoustic distortion caused by the pose offset has seriously damaged the sound field focusing characteristics, and the focusing requirements cannot be met again by compensation. The sound field simulation process needs to be repeated.

[0119] In a single-layer decoupled architecture, the virtual structure closest to the intracranial target is only the first virtual structure. In a two-layer decoupled architecture, the virtual structure closest to the intracranial target is either the first virtual structure or the second virtual structure. When the virtual structure is the first virtual structure, the stimulus data is the first stimulus data. When the virtual structure is the second virtual structure, the stimulus data is the second stimulus data.

[0120] Based on the above embodiments, the method may optionally further include: re-executing S310 if the target offset data does not meet the preset offset range.

[0121] S360. Update the third excitation data into the virtual structure, and perform forward simulation based on the third excitation data using the second simulation mode to obtain the updated sound field distribution data.

[0122] Specifically, the third excitation data is overwritten with the excitation data stored in the virtual structure, and a forward simulation is performed again based on the third excitation data in the second simulation mode to re-determine the process of sound waves propagating from the first or second emission source to the deflected intracranial target point, and the updated sound field distribution data is output.

[0123] The technical solution of this embodiment, in response to the sound field update operation, calibrates and updates the excitation data stored in the virtual structure closest to the intracranial target based on the target offset data when the target offset data meets the preset offset range. Based on the obtained third excitation data, it re-performs the forward simulation of the intracranial propagation subdomain, thereby achieving the purpose of synchronously updating the sound field distribution data. This enables rapid updating of the sound field under target offset conditions, meets the real-time response requirements in high-frequency sound field update scenarios, improves the flexibility and adaptability of transcranial focused ultrasound technology in practical interactive applications, ensures the stability and accuracy of sound field focusing, and further guarantees the safety and reliability of transcranial focused ultrasound technology.

[0124] The following are embodiments of the sound field simulation device provided in this disclosure. This device and the sound field simulation method in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the sound field simulation device, please refer to the content of the sound field simulation method in the above embodiments.

[0125] Figure 5 This is a schematic diagram of the structure of a sound field simulation device provided in one embodiment of the present disclosure. Figure 5 As shown, the device includes: an array element excitation data acquisition module 410, a first excitation data determination module 420, and a sound field distribution data determination module 430.

[0126] Among them, the array element excitation data acquisition module 410 is used to acquire the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer.

[0127] The first excitation data determination module 420 is used to perform forward simulation based on the first structure data and the array element excitation data in a first simulation mode to obtain the first excitation data on the first virtual structure.

[0128] The sound field distribution data determination module 430 is used to take the first virtual structure as the first emission source and perform forward simulation based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target point.

[0129] The first virtual structure is located in the acoustic propagation domain between the ultrasound transducer and the intracranial target, and the simulation efficiency of the first simulation mode is different from that of the second simulation mode.

[0130] The technical solution of this embodiment deploys a virtual structure on the acoustic propagation domain between the ultrasound transducer and the intracranial target, decoupling the entire acoustic propagation domain into two independent acoustic propagation subdomains. A simulation mode with simulation efficiency adaptable to the acoustic characteristics of the acoustic propagation subdomain is used to simulate the acoustic propagation law of the sound wave in this subdomain. The sound field distribution data of the intracranial target is obtained by forward deduction through the two simulation modes, avoiding the obvious simulation lag that is easy to occur in the simulation mode with single simulation efficiency. This solves the problem of poor focusing quality of transcranial focused ultrasound technology, improves the operating efficiency of the transcranial focusing process, and can adapt to medical application scenarios with high timeliness requirements.

[0131] In an optional embodiment, the first virtual structure is located on the side of the first propagation subdomain closer to the skull structure. The first propagation subdomain is an extracranial propagation subdomain or an intracranial propagation subdomain. The extracranial propagation subdomain is the acoustic propagation subdomain between the ultrasound transducer and the skull structure, and the intracranial propagation subdomain represents the acoustic propagation subdomain between the skull structure and the intracranial target.

[0132] In an optional embodiment, the first stimulus data determination module 420 includes:

[0133] The first simulation mode acquisition unit is used to acquire a first simulation mode that matches the first propagation subdomain.

[0134] The first excitation data determination unit is used to perform forward simulation based on the first structure data and the array element excitation data in the first simulation mode to obtain the first excitation data on the first virtual structure.

[0135] The simulation efficiency of the first simulation mode of the intracranial propagation subdomain is lower than that of the first simulation mode of the extracranial propagation subdomain.

[0136] In an optional embodiment, the first excitation data determining unit includes:

[0137] The skull acoustic model acquisition subunit is used to acquire a skull acoustic model registered with the intracranial target when the first propagation subdomain is an intracranial propagation subdomain.

[0138] The first excitation data determination sub-unit is used to perform forward simulation based on the skull acoustic model, the first structural data, and the array element excitation data through the first simulation mode to obtain the first excitation data on the first virtual structure.

[0139] In an optional embodiment, the first excitation data determining unit includes:

[0140] The second excitation data determination subunit is used to obtain spatial deployment data in the first structure data when the first propagation subdomain is an extracranial propagation subdomain. The spatial deployment data represents the spatial mapping information between the virtual grid in the first virtual structure and the ultrasonic array element in the ultrasonic transducer.

[0141] By performing forward simulation based on the spatial deployment data and the array element excitation data using the first simulation mode, the first excitation data on the first virtual structure is obtained.

[0142] In an optional embodiment, the first excitation data determines the subunit, specifically for:

[0143] Acquire the second structural data of the second virtual structure, which is located on the side of the second propagation subdomain closer to the skull structure, and the second propagation subdomain is different from the first propagation subdomain;

[0144] By performing forward simulation based on the second structural data and the array element excitation data in the third simulation mode, the second excitation data on the second virtual structure is obtained.

[0145] Using the second virtual structure as the second emission source, a forward simulation is performed in the first simulation mode based on the skull acoustic model, the first structural data and the second excitation data to obtain the first excitation data on the first virtual structure.

[0146] The simulation efficiency of the second simulation mode and the third simulation mode is higher than that of the first simulation mode.

[0147] In an optional embodiment, the sound field distribution data determination module 430 is specifically used for:

[0148] In the case that the first propagation subdomain is an extracranial propagation subdomain, the second structure data of the second virtual structure is obtained. The second virtual structure is located on the side of the second propagation subdomain that is close to the skull structure. The second propagation subdomain is different from the first propagation subdomain.

[0149] Acoustic models of the skull and soft tissues registered with the intracranial target were obtained.

[0150] The second simulation mode is used to perform forward simulation based on the skull acoustic model, the first structural data and the first excitation data to obtain the second excitation data on the second virtual structure.

[0151] Using the second virtual structure as the second emission source, a forward simulation is performed in the fourth simulation mode based on the soft tissue acoustic model, the second structure data, and the second excitation data to obtain the sound field distribution data of the intracranial target point.

[0152] The simulation efficiency of the first simulation mode and the fourth simulation mode is higher than that of the second simulation mode.

[0153] In an optional embodiment, the first virtual structure and / or the second virtual structure are virtual cache structures, wherein the first virtual structure is used to store first stimulus data and the second virtual structure is used to store second stimulus data.

[0154] In an optional embodiment, the device further includes:

[0155] A sound field distribution data updating device is used to acquire target point offset data in response to a sound field updating operation, wherein the target point offset data characterizes the pose offset information of the intracranial target point relative to the ultrasound transducer.

[0156] If the target offset data meets the preset offset range, the excitation data is read from the virtual structure closest to the intracranial target, and the excitation data is calibrated according to the target offset data to obtain the third excitation data;

[0157] The third excitation data is updated into the virtual structure, and a forward simulation is performed based on the third excitation data using the second simulation mode to obtain the updated sound field distribution data.

[0158] Wherein, when the virtual structure is the first virtual structure, the incentive data is the first incentive data; when the virtual structure is the second virtual structure, the incentive data is the second incentive data.

[0159] The sound field simulation device provided in this disclosure can execute the sound field simulation method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0160] Figure 6 This is a schematic diagram of an electronic device provided according to one embodiment of the present disclosure. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0161] like Figure 6As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor 11. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0162] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information or data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0163] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the sound field simulation method provided in the above embodiments.

[0164] In some embodiments, the sound field simulation method provided in the above embodiments can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the sound field simulation method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the sound field simulation method by any other suitable means (e.g., by means of firmware).

[0165] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of embodiments of this disclosure.

[0166] Various embodiments of the systems and techniques described above herein can be implemented in the following systems or combinations thereof: digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard parts (ASSPs), system-on-chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0167] Computer programs used to implement the sound field simulation method of this disclosure can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0168] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable storage medium. Examples of machine-readable storage media include, based on an electrical connection of at least one wire, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0169] To provide interaction with a user, the systems and techniques described herein can be implemented on a terminal device having: a display device for displaying information to the user (e.g., a cathode-ray tube (CRT) or liquid crystal display (LCD) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the terminal device. Other types of devices can also provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0170] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0171] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and Virtual Private Server (VPS) services, such as high management difficulty and weak business scalability.

[0172] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0173] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A sound field simulation method, characterized in that, include: Acquire the first structural data of the first virtual structure and the array element excitation data of the ultrasonic transducer; By performing forward simulation based on the first structural data and the array element excitation data in the first simulation mode, the first excitation data on the first virtual structure is obtained. Using the first virtual structure as the first emission source, a forward simulation is performed based on the first structure data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target point. The first virtual structure is located in the acoustic propagation domain between the ultrasound transducer and the intracranial target, and the simulation efficiency of the first simulation mode is different from that of the second simulation mode.

2. The method according to claim 1, characterized in that, The first virtual structure is located on the side of the first propagation subdomain closer to the skull structure. The first propagation subdomain is either an extracranial propagation subdomain or an intracranial propagation subdomain. The extracranial propagation subdomain is the acoustic propagation subdomain between the ultrasound transducer and the skull structure, and the intracranial propagation subdomain represents the acoustic propagation subdomain between the skull structure and the intracranial target.

3. The method according to claim 2, characterized in that, The step of performing forward simulation based on the first structural data and the array element excitation data in a first simulation mode to obtain the first excitation data on the first virtual structure includes: Obtain the first simulation pattern that matches the first propagation subdomain; The first simulation mode is used to perform forward simulation based on the first structural data and the array element excitation data to obtain the first excitation data on the first virtual structure. The simulation efficiency of the first simulation mode of the intracranial propagation subdomain is lower than that of the first simulation mode of the extracranial propagation subdomain.

4. The method according to claim 3, characterized in that, The step of performing forward simulation based on the first structural data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure includes: When the first propagation subdomain is an intracranial propagation subdomain, obtain the skull acoustic model registered with the intracranial target. The first simulation mode is used to perform forward simulation based on the skull acoustic model, the first structural data, and the array element excitation data to obtain the first excitation data on the first virtual structure.

5. The method according to claim 3, characterized in that, The step of performing forward simulation based on the first structural data and the array element excitation data using the first simulation mode to obtain the first excitation data on the first virtual structure includes: When the first propagation subdomain is an extracranial propagation subdomain, spatial deployment data in the first structural data is obtained, and the spatial deployment data represents the spatial mapping information between the virtual grid in the first virtual structure and the ultrasonic array element in the ultrasonic transducer. By performing forward simulation based on the spatial deployment data and the array element excitation data using the first simulation mode, the first excitation data on the first virtual structure is obtained.

6. The method according to claim 4, characterized in that, The step of performing forward simulation based on the skull acoustic model, the first structural data, and the array element excitation data in the first simulation mode to obtain the first excitation data on the first virtual structure includes: Acquire the second structural data of the second virtual structure, which is located on the side of the second propagation subdomain closer to the skull structure, and the second propagation subdomain is different from the first propagation subdomain; By performing forward simulation based on the second structural data and the array element excitation data in the third simulation mode, the second excitation data on the second virtual structure is obtained. Using the second virtual structure as the second emission source, a forward simulation is performed in the first simulation mode based on the skull acoustic model, the first structural data and the second excitation data to obtain the first excitation data on the first virtual structure. The simulation efficiency of the second simulation mode and the third simulation mode is higher than that of the first simulation mode.

7. The method according to claim 3, characterized in that, The step of performing forward simulation based on the first structural data and the first excitation data in the second simulation mode to obtain the sound field distribution data of the intracranial target point includes: In the case that the first propagation subdomain is an extracranial propagation subdomain, the second structure data of the second virtual structure is obtained. The second virtual structure is located on the side of the second propagation subdomain that is close to the skull structure. The second propagation subdomain is different from the first propagation subdomain. Acoustic models of the skull and soft tissues registered with the intracranial target were obtained. The second simulation mode is used to perform forward simulation based on the skull acoustic model, the first structural data and the first excitation data to obtain the second excitation data on the second virtual structure. Using the second virtual structure as the second emission source, a forward simulation is performed in the fourth simulation mode based on the soft tissue acoustic model, the second structure data, and the second excitation data to obtain the sound field distribution data of the intracranial target point. The simulation efficiency of the first simulation mode and the fourth simulation mode is higher than that of the second simulation mode.

8. The method according to any one of claims 6 or 7, characterized in that, The first virtual structure and / or the second virtual structure are virtual cache structures, wherein the first virtual structure is used to store the first stimulus data and the second virtual structure is used to store the second stimulus data.

9. The method according to claim 8, characterized in that, The method further includes: In response to the sound field update operation, target offset data is acquired, which characterizes the pose offset information of the intracranial target relative to the ultrasound transducer. If the target offset data meets the preset offset range, the excitation data is read from the virtual structure closest to the intracranial target, and the excitation data is calibrated according to the target offset data to obtain the third excitation data; The third excitation data is updated into the virtual structure, and a forward simulation is performed based on the third excitation data using the second simulation mode to obtain the updated sound field distribution data. Wherein, when the virtual structure is the first virtual structure, the incentive data is the first incentive data; when the virtual structure is the second virtual structure, the incentive data is the second incentive data.

10. A sound field simulation device, characterized in that, include: The array element excitation data acquisition module is used to acquire the first structure data of the first virtual structure and the array element excitation data of the ultrasonic transducer. The first excitation data determination module is used to perform forward simulation based on the first structure data and the array element excitation data in a first simulation mode to obtain the first excitation data on the first virtual structure. The sound field distribution data determination module is used to take the first virtual structure as the first emission source and perform forward simulation based on the first structure data and the first excitation data through the second simulation mode to obtain the sound field distribution data of the intracranial target point; The first virtual structure is located in the acoustic propagation domain between the ultrasound transducer and the intracranial target, and the simulation efficiency of the first simulation mode is different from that of the second simulation mode.

11. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the sound field simulation method according to any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the sound field simulation method according to any one of claims 1-9.

13. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the sound field simulation method according to any one of claims 1-9.

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