Method for generating ultrasonic cavitation and tissue fragmentation robot system

Abstract

The invention relates to a method for generating ultrasonic cavitation and a tissue fragmentation robot system, and the method comprises the steps: carrying out the multi-modal image matching, and obtaining a fusion display image; marking an interested target area and a sensitive medium; extracting acoustic parameters of the multilayer medium, and calculating amplitude compensation values and phase compensation values of a plurality of array element driving signals; according to the tissue type, region division is carried out, and at least one of an inherent threshold value, impact scattering and a boiling cavitation region is included; cavitation focuses are arranged; different sound pressure and pulse parameters are set for the inherent threshold value, the impact scattering area and the boiling cavitation area; and generating ultrasonic cavitation at the position of one cavitation focus, and moving the ultrasonic transduction device to generate ultrasonic cavitation on the other cavitation focus until the ultrasonic cavitation of all the cavitation focuses is completed. Compared with the prior art, the method realizes diversification of ultrasonic emission modes, and has the advantages of high pulse emission precision, remarkable tissue fragmentation effect, small side effect, high cost effectiveness and high registration precision.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic cavitation technology, and in particular to a method for generating ultrasonic cavitation and a tissue fragmentation robotic system. Background Technology

[0002] Ultrasonic cavitation technology, as an emerging medical treatment method, achieves precise treatment of diseased tissues by generating and controlling cavitation effects, showing great application potential in medical fields such as tumor ablation, thrombolysis, and drug delivery. The core of this technology lies in using high-intensity focused ultrasound to generate cavitation bubbles in the target area, and destroying diseased tissue through the mechanical and thermal effects generated by the oscillation, expansion, and collapse of the bubbles.

[0003] Current ultrasonic cavitation technology still faces many technical shortcomings and limitations, specifically: (1) Existing treatment modes are relatively simple and difficult to adapt to different tissue types and treatment needs. Achieving diversified cavitation treatment usually requires different medical equipment, which makes the treatment cost high and the equipment utilization rate low. (2) Existing image fusion methods cannot meet the real-time standard in surgery. Moreover, the tissue fragmentation robot system is a new technology for treating lesions in the body (such as liver lesions). It innovatively integrates the first modal image acquisition device and the robotic arm to perform real-time fusion with another modal image obtained from the outside. There is no existing technology based on the robotic arm and the fusion technology of two modal images. Manual registration leads to low image registration accuracy, cumbersome user interaction process, and complex operation steps, which is difficult to meet the fast-paced treatment requirements of clinical practice. (3) In terms of focus layout optimization, existing technologies lack a high-density uniform focus arrangement method and cannot achieve optimal filling in the spherical or ellipsoidal space, resulting in insufficient treatment coverage. (4) In clinical applications, high-intensity short-pulse focused ultrasound technology is usually guided by ultrasound imaging. However, due to the limitations of ultrasound imaging sensitivity and quantitative ability, it is not sensitive to weak or early cavitation. In clinical treatment, cavitation monitoring can only be subjectively judged, and it is impossible to achieve accurate monitoring and effective control of steady-state cavitation. This seriously restricts the widespread application of high-intensity focused ultrasound technology in clinical treatment and the further improvement of treatment effect. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method for generating ultrasonic cavitation, achieving the technical effects of diversified focused ultrasound modes and high image registration accuracy.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a method for generating ultrasonic cavitation, comprising:

[0007] Acquire the first modality image and the second modality image;

[0008] The first modal image is matched with the second modal image to obtain a fused display image;

[0009] Identify and label regions of interest and sensitive media on the fused display image;

[0010] The acoustic parameters of the multilayer medium are extracted from the fused display image, and the amplitude compensation value and phase compensation value of several array element driving signals are calculated.

[0011] Within the target region of interest, the region is divided according to the tissue type, including at least one of the intrinsic threshold cavitation region, shock scattering cavitation region, and boiling cavitation region;

[0012] Arrange cavitation focal points according to the region classification type;

[0013] Different sound pressure and pulse parameters were set for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region, respectively.

[0014] Based on the location of a certain cavitation focus, sound pressure, and pulse parameters, pulses are emitted to the target region of interest to generate ultrasonic cavitation. The ultrasonic transducer is moved to emit pulses to the target region of interest at the location of another cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation, until ultrasonic cavitation of all cavitation focuses is completed.

[0015] Preferably, the above-described method for generating ultrasonic cavitation further includes:

[0016] Real-time steady-state cavitation monitoring using high-intensity short-pulse focused ultrasound in a region where cavitation occurs at a cavitation focus;

[0017] If steady-state cavitation occurs at a certain cavitation focus, the cavitation location of the cavitation region is determined, and steady-state ultrasonic cavitation of the cavitation focus is completed. The ultrasonic transducer then moves to the location of the next cavitation focus until steady-state ultrasonic cavitation of all cavitation focuses is completed.

[0018] Preferably, the above-described method for generating ultrasonic cavitation, which involves real-time steady-state cavitation monitoring of a region where cavitation occurs at a cavitation focal point using high-intensity short-pulse focused ultrasound, includes:

[0019] If no steady-state cavitation characteristic parameters are generated within time T, or if the proportion of the steady-state cavitation characteristic parameters being met within N periods is less than 80%, it is considered that steady-state cavitation has not been generated. The initialization system parameters are readjusted, and the above steps are repeated until steady-state cavitation is generated.

[0020] Preferably, in the above-described method for generating ultrasonic cavitation, if steady-state cavitation occurs at a certain cavitation focus, the method for spatially locating the cavitation location of the cavitation region includes:

[0021] The characteristic parameters of steady-state cavitation generated by a certain cavitation focus include sub-narrowband harmonics;

[0022] Collect sub-narrowband harmonics and sub-narrowband harmonic peak values;

[0023] Remove interference signals outside the fundamental frequency bandwidth of the envelope curve;

[0024] Perform Fourier transform on the harmonic and subharmonic signals after removing interference;

[0025] Calculate the time difference between the arrival times of the two steady-state cavitation sub-narrowband harmonic signals in the target region in sequence.

[0026] The distance difference between the cavitation point and the receiver = speed of sound × time difference;

[0027] Based on the distance difference, the three-dimensional coordinates of the cavitation point are obtained.

[0028] Preferably, the method for generating ultrasonic cavitation described above, which involves matching a first modal image with a second modal image to obtain a fused display image, includes:

[0029] Determine the coordinate system relationship between the first modal image and the second modal image, including the transformation between the two-dimensional image coordinate system, the three-dimensional coordinate system of the tool center point, the three-dimensional coordinate system of the robot arm base, and the three-dimensional modeling coordinate system;

[0030] Based on the coordinate system transformation relationship, the first modal image and the second modal image are rigidly or non-rigidly registered and fused to generate a fused display image of the reference object.

[0031] Preferably, the above-described method for generating ultrasonic cavitation, which identifies and marks the target region of interest and the sensitive medium on the fused display image, includes:

[0032] Image processing algorithms are used to identify regions of interest and / or mark sensitive tissue regions in fused display images.

[0033] Preferably, the above-described method for generating ultrasonic cavitation, which extracts acoustic parameters of the multilayer medium from the fused display image and calculates the amplitude compensation value and phase compensation value of the driving signal of several array elements, includes: filtering the fused display image; and extracting the acoustic transmission thickness information of each array element in the multilayer medium. and the ultrasonic velocity C in each layer of medium i ; Obtain the acoustic path length of each array element within each medium layer. and total propagation time in multi-layer media ;according to Obtain the amplitude compensation coefficient of the driving signal of the nth element after attenuation in all media. ;according to and Calculate the amplitude compensation value and phase compensation value of the driving signal of several array elements, and compensate the amplitude and delay time of the driving signal of the corresponding array element according to the corresponding amplitude compensation value and phase compensation value of each array element.

[0034] Preferably, in the above-described method for generating ultrasonic cavitation, the acoustic path length of each element within each layer of the medium is obtained. and total propagation time in multi-layer media The method includes: assuming the focused ultrasound transducer has n array elements, and the coordinates of each element are (X... n ,Y n Z n The natural focal point coordinates are (0,0,0), and the focal length is L; when passing through the first layer of medium,

[0035]

[0036] When passing through multiple media, the angle of refraction is calculated for each layer.

[0037]

[0038] The acoustic path length within each layer of medium is calculated based on the included angle.

[0039]

[0040] Based on the sound path length and sound speed, the total propagation time of each array element in the multilayer medium is calculated.

[0041]

[0042] Among them, the Each array element is in the first layer of medium, the first Layered medium, first The angles between the acoustic beam direction of the layered medium and the normal to the medium interface are respectively , , C i This represents the ultrasonic velocity of focused ultrasound within the i-th layer of the medium. This represents the acoustic transmission path length of the nth array element within the i-th layer of medium; It means that the nth array element is in the nth position. The thickness of the acoustic transmission medium within the layer medium, This represents the total propagation time of the nth array element in the multilayer medium.

[0043] Preferably, the above-described method for generating ultrasonic cavitation, Phase value with For a period, when the absolute value exceeds At this time, a modulo operation needs to be performed, that is, subtracting... To ensure the phase value is within Within the range.

[0044] Preferably, the above-described method for generating ultrasonic cavitation is based on... Obtain the amplitude compensation coefficient of the driving signal of the nth element after attenuation in all media. The methods include:

[0045]

[0046] in, Indicates the first The attenuation coefficient of the layer medium is a known constant. This represents the reference amplitude value before attenuation. It represents the amplitude compensation coefficient after the driving signal of the nth element is attenuated in the entire medium.

[0047] Preferably, the above-described method for generating ultrasonic cavitation includes identifying and marking the target region of interest and sensitive medium on the fused display image using an image processing algorithm.

[0048] Preferably, the above-described method for generating ultrasonic cavitation includes the following steps for arranging cavitation focal points within a target region of interest: setting initial parameters for the region of interest; identifying the outer edge of interest and performing gridding along the X, Y, and Z axes; generating target candidate points layer by layer; verifying the target candidate points according to the initial parameters, and marking the target candidate points as target points if the verification is successful; sampling and evaluating the current coverage rate; if the coverage rate is lower than the initial parameters, randomly sampling in the uncovered area and attempting to place new focal points until the coverage rate is greater than or equal to the initial parameters, thus completing the arrangement of cavitation focal points.

[0049] Preferably, in the above-described method for generating ultrasonic cavitation, the initial parameters include: the size of the outer ellipsoid. Dimensions of the inner ellipsoid Allowable overlap ratio Interlayer spacing factor Density factor Target coverage .

[0050] Preferably, the above-described method for generating ultrasonic cavitation, which identifies the outer edge of interest and performs meshing layering along the X, Y, and Z axes, includes: smoothing the outer edge of the region of interest to generate a sphere or ellipsoid; and obtaining the layering position in the Z direction according to the following formula:

[0051] in: This represents the interlayer spacing factor, which is 0.2 ≤ A constant ≤ 1.0 This represents the length of the semi-axis of the inner ellipsoid in the Z direction. Let represent the semi-axis length of the external ellipsoid in the Z direction, l represent the l-th layer of the spatial structure, and be an integer greater than or equal to 0. This represents the interlayer spacing in the Z direction between adjacent mesh layers. This indicates the layer position of the l-th layer in the Z direction.

[0052] Preferably, the above-described method for generating ultrasonic cavitation, comprising the method of generating target candidate points layer by layer, includes:

[0053] The cross-section of the l-th layer is an ellipse. Therefore, the semi-axis lengths of the elliptical cross-section of the l-th layer in the x and y directions are respectively... and :

[0054]

[0055] Arranged according to grid ;

[0056] in, , These represent the distances between adjacent target candidate points in the x and y directions, respectively, on the same grid layer. The density factor of the elliptical cross section is 0.2 ≤ A constant ≤ 1.0;

[0057] The cross-sectional coordinates of the target candidate point on the l-th layer mesh are ( , The formula is:

[0058] in, This represents the variable at the j-th point along the y-direction;

[0059] Interlayer offset enables cell stacking:

[0060] in, , These represent the offsets of the target candidate points in the x and y directions on the l-th layer mesh, respectively.

[0061] Preferably, the above-described method for generating ultrasonic cavitation, which verifies target candidate points based on initial parameters, and marks the target candidate points as target points if the verification is successful, includes the following:

[0062] Filter the target candidate points and remove those that extend beyond the outer edge;

[0063] Obtain the normalized distance d between two target candidate points;

[0064] if Candidate points are marked as target points, where, The allowed overlap ratio is a constant of 0 ≤ β ≤ 1, and (x1, y1, z1) and (x2, y2, z2) represent the coordinates of the first and second target candidate points, respectively.

[0065] Preferably, the above-described method for generating ultrasonic cavitation, which involves sampling and evaluating the current coverage rate, and if the coverage rate is lower than the initial parameter, randomly sampling in the uncovered area and attempting to place new focal points until the coverage rate is greater than or equal to the initial parameter, thus completing the arrangement of cavitation focal points, includes:

[0066] The coverage rate is filtered using the following formula:

[0067]

[0068] in, Indicates the number of target points sampled. This represents random target points uniformly distributed within the outer ellipsoid. This indicates an indicator function, which is 1 if the point is at least inside an inner ellipsoid, and 0 otherwise.

[0069] The formula for generating target sampling points is as follows:

[0070]

[0071]

[0072]

[0073] in, satisfy ;

[0074] After achieving the required coverage, the target points within each layer are sorted by polar coordinates:

[0075] Calculate polar coordinates , ;

[0076] By radius Grouped, with a group spacing of ;

[0077] Group by angle Sort in ascending order;

[0078] Output all target point elliptical models in a spiral sorting manner from the inside out, thus completing the cavitation focus arrangement.

[0079] Preferably, the above-described method for generating ultrasonic cavitation, which involves dividing the target region of interest into regions based on tissue type, including at least one of an intrinsic threshold cavitation region, an impact scattering cavitation region, and a boiling cavitation region, includes the following method:

[0080] Determine the target organization type within the region of interest;

[0081] If the target tissue is the brain, or is near blood vessels, bile ducts, or nerves, it is classified as an intrinsic threshold cavitation region.

[0082] If the target tissue is a tumor in a solid organ, it is classified as a shock scattering cavitation region.

[0083] If the target tissue is fibrous, it is classified into a boiling cavitation region;

[0084] If the target tissue involves boundaries, blood vessels, or the gallbladder, these areas are classified as intrinsic threshold regions, while other areas are classified as impact scattering cavitation regions.

[0085] Preferably, in the above-described method for generating ultrasonic cavitation, the sound pressure and pulse parameters of the inherent threshold cavitation region include: ultrasonic frequency of 0.5MHz to 5MHz, negative sound pressure greater than 30MPa, pulse duration of 1 to 3 cycles, duty cycle less than 1%, negative sound pressure exceeding the inherent cavitation threshold of the target tissue, generating cavitation clouds at locations exceeding the negative pressure, thereby damaging the cell structure of the target tissue; and / or

[0086] The acoustic pressure and pulse parameters in the shock scattering cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 20~30MPa, positive acoustic pressure greater than 100MPa, pulse duration 3~20 cycles, and duty cycle less than 1%. If the negative acoustic pressure does not exceed the inherent cavitation threshold of the target tissue, the initial pulse generates initial bubbles, and the second pulse generates cavitation nuclei near the bubbles, disrupting the cell structure of the target tissue; and / or

[0087] The acoustic pressure and pulse parameters of the boiling cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 10~20MPa, positive acoustic pressure greater than 60MPa, pulse duration 1ms~20ms, and duty cycle 1%~2%. An initial pulse sequence is implemented to rapidly accumulate energy, heating the target tissue and generating boiling steam bubbles. Subsequent sequences accelerate bubble expansion and collapse, disrupting the target tissue's cellular structure.

[0088] Secondly, a tissue fragmentation robotic system includes:

[0089] The main control unit, used for electrical connection or information interaction with the ultrasonic transducer and robotic arm, includes an image processing module, an acoustic processing module, and a cavitation processing module. The image processing module acquires real-time first-mode and second-mode images, matches the first-mode and second-mode images to obtain a fused display image, and identifies and marks the target region of interest and sensitive medium on the fused display image. The acoustic processing module, connected to the image processing module, extracts acoustic parameters of the multilayer medium based on the fused display image and calculates amplitude and phase compensation values ​​for several array element driving signals. The cavitation processing module, also connected to the acoustic processing module, divides the target region of interest into regions based on tissue type, including at least one of an inherent threshold cavitation region, an impact scattering cavitation region, and a boiling cavitation region; arranges cavitation focal points according to the region division type; and sets different sound pressure and pulse parameters for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region, respectively.

[0090] The robotic arm device is connected to the ultrasonic transducer and the main control device. It is used to move the ultrasonic transducer according to the location of the cavitation focus, sound pressure and pulse parameters fed back by the main control device, plan the travel route, and bring the ultrasonic transducer into contact with the degassed water in the coupling device and align it with the location of the cavitation focus.

[0091] An ultrasonic transducer includes several ultrasonic transducers and a first modal image acquisition probe. The first modal image acquisition probe is used to acquire first modal images in real time. The ultrasonic transducer emits pulses to the target region of interest based on the location of a certain cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation. The ultrasonic transducer is moved to emit pulses to the target region of interest based on the location of another cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation, until ultrasonic cavitation of all cavitation focuses is completed.

[0092] The display device is connected to the main control device and is used to enable user interaction;

[0093] The coupling device is equipped with degassed water inside, and its bottom is in contact with the detection medium.

[0094] Preferably, the tissue fragmentation robot system described above further includes a multi-channel power amplifier, which is connected to the main control device and the ultrasonic transducer, respectively.

[0095] Thirdly, a computer-readable storage medium having a program stored thereon, which, when executed, implements the above-described method.

[0096] Compared with the prior art, the present invention has the following beneficial effects:

[0097] This invention provides a method for generating ultrasonic cavitation and a tissue fragmentation robot system. By supporting the switching between three working modes—intrinsic threshold cavitation, shock scattering cavitation, and boiling cavitation—the system can adapt to the needs of different tissue types. Compared with traditional single-mode equipment, this system has significantly improved adaptability to various tissues. Through an adaptive filling algorithm based on spheres / ellipsoids, a high-density uniform arrangement of focal points within the ellipsoid space is achieved, increasing the filling efficiency by more than 30% compared to traditional methods. By employing a multi-layer medium acoustic compensation method to calculate phase delay and sound pressure amplitude attenuation compensation, the problem of low cavitation accuracy caused by sound beam refraction and ultrasonic amplitude attenuation is effectively solved.

[0098] This invention achieves precise spatiotemporal registration and unification of multimodal information. By systematically establishing and obtaining a complete coordinate transformation chain from the "first modal image" to the "second modal image," encompassing multiple intermediate links (two-dimensional image coordinate system, tool center point coordinate system, robotic arm base coordinate system, and three-dimensional modeling coordinate system), it ensures micron- and millimeter-level precise alignment of image data from different sources and dimensions in spatial location. It fundamentally solves the core problem of navigation benchmark inaccuracy caused by inconsistent coordinate systems and large registration errors in multimodal image fusion, providing more accurate path planning and spatial registration.

[0099] This invention employs a real-time steady-state cavitation monitoring and localization method using high-intensity short-pulse focused ultrasound. The method involves setting initial system parameters, performing multiple cavitation acquisitions to obtain multiple frames of cavitation data, preprocessing the data to extract steady-state cavitation characteristic parameters, and considering that no steady-state cavitation has occurred if no steady-state cavitation characteristic parameters are generated within time T or if the proportion of parameters meeting the requirements within N periods is less than 80%. This invention can automatically and continuously assess whether the expected steady-state cavitation effect has occurred, significantly reducing the high dependence on operator experience in traditional methods and improving the objectivity and consistency of the detection process. Attached Figure Description

[0100] Figure 1 This is a flowchart of the method for generating ultrasonic cavitation according to the present invention;

[0101] Figure 2 The image is a fused display image of the present invention;

[0102] Figure 3 This is a schematic diagram of the intrinsic threshold cavitation region of the present invention;

[0103] Figure 4 This is a schematic diagram of the impact scattering cavitation region of the present invention;

[0104] Figure 5 This is a schematic diagram of the boiling cavitation region of the present invention;

[0105] Figure 6 This is a flowchart illustrating the generation of steady-state ultrasonic cavitation and cavitation localization according to the present invention;

[0106] Figure 7 A schematic diagram of the structure of the tissue fragmentation robot system;

[0107] Figure label:

[0108] The system includes a main control unit 100, a robotic arm unit 200, an ultrasonic transducer unit 300, a first modal image acquisition probe 310, a coupling device 400, a multi-channel power amplifier 500, a display device 600, a degassed water device 700, and a first modal image acquisition device 800. Detailed Implementation

[0109] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0110] Example 1:

[0111] like Figure 1 As shown, the present invention provides a method for generating ultrasonic cavitation. This method acquires and fuses multiple image data to accurately locate the target area and uses different cavitation parameters according to different tissue types to achieve precise emission of ultrasonic cavitation pulses.

[0112] S100, acquire the first modality image and the second modality image;

[0113] Combining images from different imaging principles, such as ultrasound, CT, and MR (e.g., ultrasound + CT or ultrasound + MR), can fully leverage the complementary advantages of each modality. Ultrasound images offer strong real-time performance and are radiation-free, facilitating dynamic monitoring and guidance during surgery; CT images provide high contrast and excellent spatial resolution for hard tissues such as bones, offering clear anatomical structures; and MR images provide extremely high soft tissue resolution, offering rich functional and metabolic information. This multimodal combination strategy ensures from the data source that subsequent fused images contain both real-time dynamic information (from ultrasound) and high-resolution static anatomical details or functional information (from CT / MR), laying a solid foundation for comprehensive and accurate navigation. This embodiment uses a real-time two-dimensional ultrasound image as the first modality and a CT image as the second modality as an example, but is not limited to this embodiment.

[0114] S200, Match the first modality image with the second modality image to obtain, as shown below. Figure 2 The image shown is a fused display.

[0115] Determine the coordinate system relationship from the first modal image to the second modal image, including the transformation between the two-dimensional image coordinate system, the tool center point three-dimensional coordinate system, the robotic arm base three-dimensional coordinate system, and the three-dimensional modeling coordinate system, including:

[0116] The first modal image acquisition probe 310, through the action of the robotic arm, performs multi-angle real-time image scanning on at least one reference object placed in the target area, and obtains multiple real-time first modal images containing the reference object.

[0117] Record the real-time spatial pose of the first modal image acquisition probe 310 in the coordinate system of the robot arm base and the parameters of the first modal image during the acquisition of each first modal image;

[0118] The two-dimensional pixel coordinates of the reference object in multiple real-time first modal images are mapped one by one to the three-dimensional coordinate system of the tool center point of the first modal image acquisition device;

[0119] By combining the real-time spatial pose of the first modal image acquisition device, the set of three-dimensional spatial coordinates of the reference object in the coordinate system of the robot arm base is calculated;

[0120] Transform the coordinates of the reference object located in the robot arm coordinate system to the same 3D modeling coordinate system as the second modal image;

[0121] Based on the three-dimensional image set of the second modal image of the reference object, the parameters of the second modal image are extracted and the three-dimensional volume data of the second modal image of the reference object are reconstructed to obtain the three-dimensional spatial coordinates of the reference object in the coordinate system of the second modal image.

[0122] Based on the coordinate system transformation relationship, the first modal image and the second modal image are rigidly or non-rigidly registered and fused to generate a reference object, such as... Figure 2 The image shown is a fused display.

[0123] This method integrates the real-time nature of ultrasound and the high-resolution three-dimensional anatomical information of CT / MRI, enabling doctors to observe the positional relationship between the treatment probe and the target in real time against a clear anatomical background, overcoming the limitations of a single image modality. By establishing a complete coordinate transformation chain between the first modality image, the robotic arm, and the second modality image, it ensures the precise alignment between the virtual image space and the physical therapy space, laying the mathematical foundation for the robotic arm's automatic navigation.

[0124] The S300 uses image processing algorithms to identify and fused display regions of interest and marked sensitive tissue regions on images. It can clearly mark sensitive media such as blood vessels, nerves, and bile ducts, and can actively avoid them during planning, greatly reducing the risk of accidental damage and ensuring the accuracy and safety of target recognition.

[0125] S400 extracts the acoustic parameters of the multilayer medium based on the fused display image and calculates the amplitude compensation and phase compensation values ​​of several array element driving signals, including:

[0126] First, the fused display image is filtered to extract the acoustic transmission thickness information of each array element in the multi-layer medium. and the ultrasonic velocity C in each layer of medium i ;

[0127] Secondly, obtain the acoustic path length of each array element within each layer of the medium. and total propagation time in multi-layer media The methods include:

[0128] Assume a focused ultrasound transducer has n array elements, and the coordinates of each element are (X, X). n ,Y n Z n The natural focal point coordinates are (0,0,0), and the focal length is L; when passing through the first layer of medium,

[0129]

[0130] When passing through multiple media, the angle of refraction is calculated layer by layer according to Snell's Law;

[0131]

[0132] The acoustic path length within each layer of medium is calculated based on the included angle.

[0133]

[0134] Based on the sound path length and sound speed, the total propagation time of each array element in the multilayer medium is calculated.

[0135]

[0136] Among them, the Each array element is in the first layer of medium, the first Layered medium, first The angles between the acoustic beam direction of the layered medium and the normal to the medium interface are respectively , , C i This represents the ultrasonic velocity of focused ultrasound within the i-th layer of the medium. This represents the acoustic transmission path length of the nth array element within the i-th layer of medium; It means that the nth array element is in the nth position. The thickness of the acoustic transmission medium within the layer medium, This represents the total propagation time of the nth element in the multilayer medium. This method considers the complex physical processes of ultrasound waves passing through multilayer media (such as skin, fat, muscle, and tumors) with different sound velocities, thicknesses, and attenuation characteristics, and performs personalized corrections on the amplitude (to compensate for attenuation) and delay time (to compensate for sound velocity differences) of the driving signal for each transducer element.

[0137] Furthermore, Phase value with For a period, when the absolute value exceeds At this time, a modulo operation needs to be performed, that is, subtracting... To ensure the phase value is within Within the range.

[0138] Secondly, according to Obtain the amplitude compensation coefficient of the driving signal of the nth element after attenuation in all media. The methods include:

[0139]

[0140] in, Indicates the first The attenuation coefficient of the layer medium is a known constant. This represents the reference amplitude value before attenuation. It represents the amplitude compensation coefficient after the driving signal of the nth element is attenuated in the entire medium.

[0141] according to and It compensates for the amplitude and delay time of the driving signal of each array element, effectively corrects the problems of focus drift, deformation and energy dispersion caused by uneven tissue sound velocity, and significantly improves the sharpness and energy density of the focus; when achieving the same treatment effect, the required sound power is lower, the mechanical damage to the surrounding normal tissue is less, and the cavitation effect is ensured to occur at the predetermined position, avoiding cavitation damage in unexpected areas.

[0142] S 500, within the target region of interest, divides the region according to tissue type, including at least one of the following: intrinsic threshold cavitation region, shock scattering cavitation region, and boiling cavitation region, including:

[0143] If the target tissue is the brain, or is near blood vessels, bile ducts, or nerves, it is classified as an intrinsic threshold cavitation region; if the target tissue is a tumor of a solid organ, it is classified as an impact scattering cavitation region; if the target tissue is fibrous tissue, it is classified as a boiling cavitation region; if the target tissue involves boundaries, blood vessels, or the gallbladder, the boundaries, blood vessels, and gallbladder are classified as intrinsic threshold regions, while other parts are classified as impact scattering cavitation regions.

[0144] S600, based on the area classification type, arranges the cavitation focus; including:

[0145] First, initial parameters are set for the region of interest; these parameters include: outer ellipsoid size (Rx, Ry, Rz), inner ellipsoid size (a, b, c), allowable overlap ratio β, and interlayer spacing factor α. z Density factor α d Target coverage C target .

[0146] Secondly, identify the outer edges of interest and perform meshing and layering along the X, Y, and Z axes, specifically:

[0147] The outer edge of the region of interest is smoothed to generate a sphere or ellipsoid; the layer position in the Z direction is obtained according to the following formula:

[0148]

[0149]

[0150] in: This represents the interlayer spacing factor, which is 0.2 ≤ A constant ≤ 1.0 This represents the length of the semi-axis of the inner ellipsoid in the Z direction. Let represent the semi-axis length of the external ellipsoid in the Z direction, l represent the l-th layer of the spatial structure, and be an integer greater than or equal to 0. This represents the interlayer spacing in the Z direction between adjacent mesh layers. This indicates the layer position of the l-th layer in the Z direction.

[0151] Next, target candidate points are generated layer by layer, specifically as follows:

[0152] The cross-section of the l-th layer is an ellipse. Therefore, the semi-axis lengths of the elliptical cross-section of the l-th layer in the x and y directions are respectively... and :

[0153]

[0154]

[0155] Arranged according to a grid:

[0156]

[0157] in, , These represent the distances between adjacent target candidate points in the x and y directions, respectively, on the same grid layer. The density factor of the elliptical cross section is 0.2 ≤ A constant ≤ 1.0;

[0158] The cross-sectional coordinates of the target candidate point on the i-th layer of the grid are ( , The formula is:

[0159]

[0160]

[0161]

[0162] in, This represents the variable at the j-th point along the y-direction;

[0163] Interlayer offset enables cell stacking:

[0164]

[0165]

[0166] in, , These represent the offsets of the target candidate points in the x and y directions on the l-th layer mesh, respectively.

[0167] Another approach is to determine the parity of each mesh layer and set the x-direction offset based on the parity. This differentiated x and y-direction offset setting can introduce position adjustments in even-numbered layers. The alternating setting of the y-direction offset complements the x-direction offset, ensuring precise vertical adjustment in odd-numbered layers.

[0168] Finally, the calculated offset is applied to the target candidate points at the corresponding level. Through this differential offset setting method based on odd and even levels, the target candidate points at adjacent levels exhibit an alternating offset distribution pattern in the x and y directions. Setting different offsets in the x and y directions ensures both overlap and sufficient arrangement within the region, while also ensuring that the overlapping area is not too large, thereby improving the accuracy and security of target detection and localization.

[0169] Next, the target candidate points are validated based on the initial parameters. If the validation is successful, the target candidate points are marked as target points. Specifically:

[0170] Filter the target candidate points and remove those that extend beyond the outer edge;

[0171] Obtain the normalized distance d between two target candidate points;

[0172]

[0173] if Candidate points are marked as target points, where, The allowed overlap ratio is a constant of 0 ≤ β ≤ 1, and (x1, y1, z1) and (x2, y2, z2) represent the coordinates of the first and second target candidate points, respectively.

[0174] Finally, the current coverage is evaluated by sampling; if the coverage is lower than the initial parameter, random sampling is performed in the uncovered area and new focal points are attempted until the coverage is greater than or equal to the initial parameter, thus completing the cavitation focal point arrangement, specifically:

[0175] The coverage rate is filtered using the following formula:

[0176] in, Indicates the number of target points sampled. This represents random target points uniformly distributed within the outer ellipsoid. This indicates an indicator function, which is 1 if the point is at least inside an inner ellipsoid, and 0 otherwise.

[0177] The formula for generating target sampling points is as follows:

[0178]

[0179]

[0180]

[0181] in, satisfy ;

[0182] After achieving the required coverage, the target points within each layer are sorted by polar coordinates:

[0183] Calculate polar coordinates: , ;

[0184] By radius Grouped, with a group spacing of ;

[0185] Group by angle Sort in ascending order;

[0186] Output all target point elliptical models in a spiral sorting manner from the inside out, thus completing the cavitation focus arrangement.

[0187] The target ellipse models for the intrinsic threshold cavitation region, the shock scattering cavitation region, and the boiling cavitation region can be different. Preferably, the minor axis and major axis of the target ellipse model when modeling the intrinsic threshold cavitation region are smaller than the minor axis and major axis of the target ellipse model for the shock scattering cavitation region and the boiling cavitation region.

[0188] This application automatically performs 3D meshing and layering based on the shape of the target area, applicable to reference objects of different shapes and sizes (e.g., lesions, including liver lesions), demonstrating strong versatility. Through an inter-layer offset algorithm, the focal points of adjacent layers are arranged in a honeycomb-like staggered pattern, and combined with normalized distance verification, ensuring coverage continuity while precisely controlling the overlap ratio β between focal points. This avoids "treatment blind spots" caused by incomplete coverage and prevents energy waste and heat accumulation caused by excessive overlap. Through polar coordinate sorting and spiral output, a smooth and orderly focal point movement path is generated from the distal to the proximal end, from the outside to the inside, or from the inside to the outside, reducing unnecessary idle movement of the robotic arm and improving treatment continuity and overall efficiency. A random sampling method is used to objectively evaluate the coverage rate of the focal point arrangement on the target area, ensuring that the preset target is achieved, making the cavitation planning results quantifiable and verifiable.

[0189] S700 sets different sound pressure and pulse parameters for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region, including:

[0190] like Figure 3As shown, the sound pressure and pulse parameters of the inherent threshold cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative sound pressure greater than 30MPa, pulse duration 1~3 cycles, duty cycle less than 1%, negative sound pressure exceeding the inherent cavitation threshold of the target tissue, generating cavitation clouds at the position exceeding the negative pressure, and destroying the cell structure of the target tissue.

[0191] like Figure 4 As shown, the acoustic pressure and pulse parameters of the impact scattering cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 20~30MPa, positive acoustic pressure greater than 100MPa, pulse duration 3~20 cycles, and duty cycle less than 1%. When the negative acoustic pressure does not exceed the inherent cavitation threshold of the target tissue, the initial pulse generates initial bubbles, and the second pulse generates cavitation nuclei near the bubbles, destroying the cell structure of the target tissue.

[0192] like Figure 5 As shown, the acoustic pressure and pulse parameters of the boiling cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 10~20MPa, positive acoustic pressure greater than 60MPa, pulse duration 1ms~20ms, and duty cycle 1%~2%. An initial pulse sequence is implemented to rapidly accumulate energy, heating the target tissue and generating boiling steam bubbles. Subsequent sequences accelerate bubble expansion and collapse, disrupting the target tissue's cellular structure.

[0193] This application divides the target area into an intrinsic threshold cavitation zone (sensitive tissue), an impact scattering cavitation zone (solid tumor), and a boiling cavitation zone (fibrous tissue), which is consistent with clinical pathology and has a suitable mechanism; (1) For sensitive areas: the "intrinsic threshold" method with extremely high negative pressure and ultra-short pulse is used to complete the fragmentation instantaneously. The action time is extremely short and the thermal diffusion effect is negligible, thus maximizing the protection of adjacent blood vessels and nerves; (2) For solid tumors: the "impact scattering" method is used to generate mechanical shear force by repeatedly expanding and contracting the cavitation bubble cloud. It can achieve subcellular level fragmentation without significant heat generation, which is particularly suitable for tumors with rich blood supply and has higher safety; (3) For fibrous tissue: the "boiling cavitation" method is used to reduce the cavitation threshold by moderate heating and generate strong destruction by expanding and collapsing the steam bubbles, which has a better decomposition effect on tough fibrous tissue; (4) It breaks through the limitation of a single parameter and realizes dynamic switching of working modes in different sub-regions, which is more precise.

[0194] S800 emits pulses to the target region of interest based on the location of a certain cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation. It moves the ultrasonic transducer to emit pulses to the target region of interest based on the location of another cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation, until ultrasonic cavitation of all cavitation focuses is completed.

[0195] This method achieves precise, safe, and efficient ultrasound cavitation treatment through multimodal image fusion, acoustic distortion compensation, intelligent focus arrangement, and regional parameter settings, providing personalized solutions for cavitation of different types of tissues.

[0196] Example 2:

[0197] like Figure 6 As shown, based on Example 1, it further includes: S900, performing high-intensity short-pulse focused ultrasound real-time steady-state cavitation monitoring on the region where cavitation occurs at a certain cavitation focus; if steady-state cavitation occurs at a certain cavitation focus, the cavitation location of the cavitation region is located, the steady-state ultrasound cavitation of the cavitation focus is completed, and the ultrasound transducer moves to the location of the next cavitation focus until the steady-state ultrasound cavitation of all cavitation focuses is completed.

[0198] Furthermore, the method for real-time steady-state cavitation monitoring of a region where cavitation occurs at a certain cavitation focus using high-intensity short-pulse focused ultrasound includes: if no steady-state cavitation characteristic parameters are generated within time T or the proportion of parameters meeting the steady-state cavitation characteristic parameters within N cycles is less than 80%, it is considered that no steady-state cavitation has occurred. The initialization system parameters are then readjusted, and the above steps are repeated until steady-state cavitation occurs.

[0199] Furthermore, if steady-state cavitation occurs at a certain cavitation focus, the method for locating the cavitation position in the cavitation region includes:

[0200] First, the sub-narrowband harmonics and their peak values, which are assumed to be generated by steady-state cavitation, are collected. The methods for obtaining the sub-harmonic signals include: based on the original signal model... , find the sub-harmonic signal in, Let A(t) represent the original signal, and let N represent the subharmonic signal. i (t) represents the random noise during the i-th acquisition; the method for obtaining the steady-state cavitation threshold by solving the formula of the multiple averaging algorithm includes:

[0201]

[0202] in, This represents the weighted average, where M represents the number of signal acquisitions. Let A(t) represent the original cavitation signal value, and let N represent the subharmonic signal value. i (t) represents the random noise signal value during the i-th acquisition;

[0203] Due to noise N i (t) is random, sometimes positive and sometimes negative; according to the law of large numbers, when the number of superpositions M is large enough, the random noise will cancel each other out, and the expected value of its average value will approach zero.

[0204] ,

[0205] therefore, As the subharmonic cavitation threshold, i.e., the steady-state cavitation characteristic parameter;

[0206] Then, interference signals outside the fundamental frequency bandwidth of the envelope curve are removed;

[0207] Then, Fourier transform is performed on the harmonic and subharmonic signals after removing the interference.

[0208] Then, the time difference between the arrival times of the two steady-state cavitation sub-narrowband harmonic signals in the target region is calculated sequentially.

[0209] Then, the distance difference from the cavitation point to the receiver = speed of sound × time difference;

[0210] Finally, the three-dimensional coordinates of the cavitation point are obtained based on the distance difference.

[0211] The presence of subharmonic signals within time T serves as a marker of steady-state cavitation. However, it is still necessary to continuously monitor the proportion of parameters satisfying steady-state cavitation characteristics over N cycles. The steady-state cavitation threshold is obtained by solving the formula of the multiple averaging algorithm and is used as the steady-state cavitation characteristic parameter. This application monitors steady-state cavitation characteristic signals such as subharmonics to determine in real time whether the desired steady-state cavitation effect has been generated under the current parameters, rather than blindly treating based solely on preset parameters. When cavitation is not effectively generated, the parameters (such as sound pressure and frequency) are adjusted, requiring the ultrasonic transducer to re-emit pulses to the target region of interest, ensuring that each transmission is effective and improving the overall reliability and success rate of the cavitation effect.

[0212] Compared with existing technologies, by employing multiple averaging algorithms and Fourier transform algorithms, the sensitivity to weak or early cavitation is significantly improved, overcoming the shortcomings of traditional B-mode ultrasound imaging technology in its insensitivity to weak cavitation. This enables effective monitoring and accurate judgment of steady-state cavitation, solving the problem of subjective judgment in clinical treatment cavitation monitoring. Utilizing the statistical properties that deterministic signals can be superimposed and enhanced, and random noise can cancel each other out, the signal-to-noise ratio of cavitation detection is effectively improved, enhancing the accurate identification and analysis of weak cavitation signals and improving the accuracy and reliability of cavitation monitoring. By acquiring cavitation signals in real time, treatment parameters and plans can be adjusted in real time according to changes in cavitation intensity, improving the efficiency of cavitation treatment and achieving effective control of steady-state cavitation, ensuring the safety and effectiveness of steady-state cavitation. The use of time difference technology enables two-dimensional spatial distribution monitoring of cavitation signals, providing spatiotemporal characteristic information of cavitation phenomena and providing comprehensive and accurate real-time feedback for treatment parameter optimization and treatment progress. Combined with the Fourier transform algorithm, the spectral leakage problem caused by frequency offset is avoided, improving the accuracy of spectral analysis and contributing to improved detection sensitivity and accuracy of cavitation signals.

[0213] Example 3:

[0214] like Figure 7 As shown, this embodiment provides a tissue fragmentation robot system, which includes a main control device 100, a robotic arm device 200, an ultrasonic transducer device 300, a coupling device 400, and a display device 600. The display device 600 is connected to the main control device 100 and is used to realize user interaction.

[0215] The main control unit 100, as the core control unit of the entire system, is responsible for electrical connection and information exchange with the ultrasonic transducer 300 and the robotic arm device 200. The main control unit 100 has a built-in high-performance processor and control algorithm, which can analyze the characteristics of the detection medium in real time and formulate the optimal cavitation treatment scheme. The main control device 100 identifies and classifies different types of media through a preset program, and automatically adjusts the ultrasonic parameters and the motion trajectory of the robotic arm device 200 according to the characteristics of the media. It includes an image processing module, an acoustic processing module, and a cavitation processing module. The image processing module acquires a real-time first modal image and a second modal image, matching the first and second modal images to obtain a fused display image. The acoustic processing module, connected to the image processing module, extracts the acoustic parameters of the multilayer media based on the fused display image and calculates the amplitude and phase compensation values ​​of several array element driving signals. The cavitation processing module, also connected to the acoustic processing module, divides the target area of ​​interest into regions based on tissue type, including at least one of an inherent threshold cavitation region, an impact scattering cavitation region, and a boiling cavitation region. It then arranges cavitation focal points according to the region division type and sets different sound pressure and pulse parameters for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region.

[0216] The robotic arm 200 is connected to the ultrasonic transducer 300 to form a precise positioning system. It moves the ultrasonic transducer 300 based on the location of the cavitation focus, sound pressure, and pulse parameters fed back from the main control device 100, planning its path to bring the ultrasonic transducer 300 into contact with the degassed water in the coupling device 400 and align it with the location of the cavitation focus. The robotic arm 300 includes multiple joint actuators and position sensors, enabling precise position control in three-dimensional space. After the main control device 100 completes the planning, the robotic arm 200 moves according to the predetermined path, guiding the ultrasonic transducer 300 to the designated position, ensuring full contact with the degassed water in the coupling device 400. The high-precision servo system of the robotic arm 200 ensures that the ultrasonic transducer 300 can accurately align with the cavitation focus, achieving a positioning accuracy down to the sub-millimeter level.

[0217] The ultrasonic transducer 300 is the core actuator of the system, responsible for emitting ultrasonic pulses with specific parameters toward the cavitation focal point. This device employs a piezoelectric ceramic transducer array, capable of generating high-intensity focused ultrasonic waves. It includes several ultrasonic transducers and a first-mode image acquisition probe 310, which acquires real-time first-mode images. The ultrasonic transducers emit pulses toward the target region of interest based on the location of a cavitation focal point, sound pressure, and pulse parameters, generating ultrasonic cavitation. Moving the ultrasonic transducer, it emits pulses toward the target region of interest at another cavitation focal point with the same sound pressure and pulse parameters, generating ultrasonic cavitation, until all cavitation focal points are cavitated.

[0218] Serial Number Organization (pig) Tissue cavitation threshold / PRF100HZ (peak negative pressure MPa) Tissue cavitation threshold / PRF100HZ (peak negative pressure MPa) 1 lung 1.578±0.89 13.42±1.08 2 Fat 17.13±1.41 13.26±1.85 3 kidney 17.84±1.48 14.56±0.95 4 liver 19.97±0.77 17.75±1.07 5 heart 20.03±0.36 17.06±1.28 6 muscle 21.01±0.48 19.12±0.57 7 skin 25.10±0.69 23.21±1.01 8 Tongue 26.54±0.88 24.27±0.44 9 tendon 26.41±0.52 24.47±0.49

[0219] The table above shows the initial thresholds for cavitation when treating pig tissues at pulse repetition frequencies (PRF) of 100 Hz and 1000 Hz, indicating that the cavitation threshold for each tissue is known. (1) Inherent threshold cavitation region: The system sets a relatively high pulse power and a short duration, directly exceeding the tissue cavitation threshold to achieve tissue fragmentation; it is not suitable for sensitive and demanding tissues, and can easily cause danger if the pulse is misaligned; (2) Impact scattering cavitation region: The system uses a high-intensity pulse power slightly lower than the inherent threshold and a duration slightly longer than the inherent threshold cavitation time. It uses short, high-density repetitive pulses and low-duty-cycle sound waves to periodically generate high-density, high-energy cavitation bubble clouds inside the tissue. The repeated expansion of the bubble clouds Zhang and contraction mechanically decompose the tissue into subcellular levels, and use subsequent bubble clouds to superimpose the previous bubble clouds to achieve energy superposition. That is, the tissue fragmentation of the medium is achieved through the shock wave effect of cavitation bubbles. Compared with the high risk of inherent cavitation threshold, it is less damaging to the tissue and is safer and more reliable. It can be used for sensitive and high-risk tissues. (3) Boiling cavitation region: The system applies a low-intensity pulse power for a long time. The cavitation threshold is reduced by heating the tissue (the cavitation threshold decreases as the temperature increases). That is, the tissue fragmentation of the medium is achieved through cavitation boiling phenomenon. Heating may have heat conduction, which may cause tissue damage. Moreover, the single point time is long, which leads to poor efficiency. It can be used for tissues with high heat resistance and insensitivity to time, such as fat.

[0220] The coupling device 400, serving as a container for the acoustic propagation medium, is filled with specially treated degassed water. This degassed water has an extremely low dissolved gas content, reducing scattering and attenuation during ultrasound propagation. The bottom of the coupling device 400 is in direct contact with the tissue medium to be treated, forming a good acoustic coupling interface. The walls of the coupling device 400 are made of an acoustically transparent material, ensuring that ultrasound waves can propagate to the target area without loss. The internal degassed water ensures good acoustic propagation characteristics. The bottom of the coupling device 400 uses a transparent acoustic module, forming a continuous acoustic propagation path, allowing ultrasound waves to be effectively transmitted from the degassed water to the detection medium.

[0221] Furthermore, this device also includes a multi-channel power amplifier 500, which is electrically connected to both the main control unit 100 and the ultrasonic transducer 300. The multi-channel power amplifier 500 includes multiple independent amplification channels, each corresponding to a transducer unit in the ultrasonic transducer array. The main control unit 100 generates multiple control signals via a digital signal processor. These signals are independently amplified by the multi-channel power amplifier 500 and then drive their respective transducer units. The multi-channel power amplifier 500 employs a high-efficiency Class-D amplifier architecture, featuring fast response and precise power control characteristics. Each amplification channel is equipped with an independent power monitoring and feedback control circuit, enabling real-time monitoring and dynamic adjustment of the output power.

[0222] The system operates as follows: First, the main control device 100 scans and analyzes the target tissue, identifies the target area to be processed, and classifies it into different cavitation region types. Then, the main control device 100 sends motion commands to the robotic arm device 200, which carries the ultrasonic transducer 300 to a predetermined position. Once positioning is complete, the main control device 100 generates corresponding drive signals and transmits them to the multi-channel power amplifier 500. The multi-channel power amplifier 500 independently amplifies these signals, providing precise drive power to each transducer unit of the ultrasonic transducer 300. Driven by the multi-channel power amplifier 500, the ultrasonic transducer 300 emits ultrasonic pulses of corresponding intensity into different cavitation regions, achieving layered fragmentation of the target tissue through controllable cavitation effects.

[0223] The robotic arm device 200 has multi-degree-of-freedom motion capabilities, enabling precise positioning and attitude adjustment in three-dimensional space, ensuring that the ultrasonic transducer device 300 always maintains the best acoustic coupling state with the target area.

[0224] The introduction of the multi-channel power amplifier 500 significantly improves the system's processing power and control precision. By independently controlling the drive power of each transducer unit, the system can achieve more precise cavitation region control, avoiding the uneven power distribution problems that may occur with traditional single-channel drive methods. At the same time, the multi-channel design also improves the system's reliability; even if one channel fails, the other channels can still operate normally, ensuring the continuous and stable operation of the system.

[0225] The entire system operates based on precise cavitation region control and parameter optimization. The parameter control unit of the main control device 100 first analyzes the characteristics of the target tissue to determine the distribution of the inherent threshold cavitation region, the shock scattering cavitation region, and the boiling cavitation region. Then, the parameter control unit sets corresponding sound pressure and pulse parameters for each region, including key parameters such as sound pressure amplitude, pulse repetition frequency, pulse width, and interval time. The robotic arm device 200 moves the ultrasonic transducer 300 sequentially to each target position according to a preset path plan. The ultrasonic transducer 300 automatically switches to the corresponding operating mode based on the cavitation region type at the current position, outputting matching sound pressure and pulse parameters.

[0226] By employing this regional and differentiated parameter control strategy, the system can achieve optimal target tissue fragmentation in different cavitation regions, while avoiding the problems of low cavitation efficiency or media damage caused by improper parameter settings in traditional methods. This significantly improves the accuracy and efficiency of ultrasonic cavitation target tissue fragmentation.

[0227] In another embodiment, it also includes: a degassed water device 700, which is connected to the coupling device 400 and is used to input degassed water into the coupling device 400; it may also optionally include a first modal image acquisition device 800, which is used to acquire first modal images and is connected to the first modal image acquisition probe 310 on the main control device 100 and the ultrasonic transducer 300, and may be a B-ultrasound probe, etc.

[0228] A computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the method for generating ultrasonic cavitation of Embodiment 1.

[0229] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0230] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0231] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0232] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0233] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0234] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems / devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0235] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for generating ultrasonic cavitation, characterized in that, include: Acquire the first modality image and the second modality image; The first modal image is matched with the second modal image to obtain a fused display image; Identify and mark the target area of ​​interest and sensitive media on the fused display image; Based on the fused display image, the acoustic parameters of the multilayer medium are extracted, and the amplitude compensation value and phase compensation value of several array element driving signals are calculated. Within the target area of ​​interest, the region is divided according to the tissue type, including at least one of the intrinsic threshold cavitation region, shock scattering cavitation region, and boiling cavitation region; Based on the aforementioned region division type, cavitation focus arrangement is performed; Different sound pressure and pulse parameters are set for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region, respectively; Based on the location of one of the cavitation focal points, sound pressure, and pulse parameters, a pulse is emitted to the target region of interest to generate ultrasonic cavitation. The ultrasonic transducer is then moved to emit a pulse to the target region of interest at the location of another cavitation focal point, sound pressure, and pulse parameters to generate ultrasonic cavitation, until ultrasonic cavitation of all cavitation focal points is completed.

2. The method for generating ultrasonic cavitation according to claim 1, characterized in that, Also includes: Real-time steady-state cavitation monitoring using high-intensity short-pulse focused ultrasound in a region where cavitation occurs at a cavitation focus; If a steady-state cavitation occurs at a certain cavitation focus, the cavitation region is located to complete the steady-state ultrasonic cavitation of the cavitation focus. The ultrasonic transducer then moves to the location of the next cavitation focus until the steady-state ultrasonic cavitation of all cavitation focuses is completed.

3. The method for generating ultrasonic cavitation according to claim 1, characterized in that, The method for real-time steady-state cavitation monitoring of a region where cavitation occurs at a cavitation focus using high-intensity short-pulse focused ultrasound includes: If no steady-state cavitation characteristic parameters are generated within time T, or if the proportion of the steady-state cavitation characteristic parameters being met within N periods is less than 80%, it is considered that steady-state cavitation has not been generated. The initialization system parameters are readjusted, and the above steps are repeated until steady-state cavitation is generated.

4. A method for generating ultrasonic cavitation according to claim 2, characterized in that, If a cavitation focus generates steady-state cavitation, the method for spatially locating the cavitation location of the cavitation region includes: The characteristic parameters of steady-state cavitation generated by a certain cavitation focus include sub-narrowband harmonics; Collect the sub-narrowband harmonics and their peak values; Remove interference signals outside the fundamental frequency bandwidth of the envelope curve; Perform Fourier transform on the harmonic and subharmonic signals after removing interference; Calculate the time difference between the arrival times of the two steady-state cavitation sub-narrowband harmonic signals in the target region in sequence. The distance difference between the cavitation point and the receiver = speed of sound × time difference; Based on the distance difference, the three-dimensional coordinates of the cavitation point are obtained.

5. A method for generating ultrasonic cavitation according to claim 1, characterized in that, The method for matching the first modal image with the second modal image to obtain the fused display image includes: Determine the coordinate system relationship between the first modal image and the second modal image, including the transformation between the two-dimensional image coordinate system, the three-dimensional coordinate system of the tool center point, the three-dimensional coordinate system of the robot arm base, and the three-dimensional modeling coordinate system; Based on the coordinate system transformation relationship, the first modal image and the second modal image are rigidly or non-rigidly registered and fused to generate a fused display image of the reference object.

6. A method for generating ultrasonic cavitation according to claim 5, characterized in that, The method for identifying and marking target areas of interest and sensitive media on a fused display image includes: Image processing algorithms are used to identify regions of interest and / or mark sensitive tissue regions on the fused display image.

7. A method for generating ultrasonic cavitation according to claim 1, characterized in that, The method for extracting acoustic parameters of the multilayer medium from the fused display image and calculating the amplitude compensation value and phase compensation value of several array element driving signals includes: Filter the merged display image; Extract the acoustic transmission thickness information of each array element in the multilayer medium. and the ultrasonic velocity C in each layer of medium i ; Obtain the acoustic path length of each array element within each medium layer. and total propagation time in multi-layer media ; according to Obtain the amplitude compensation coefficient of the driving signal of the nth element after attenuation in all media. ; according to and Calculate the amplitude compensation value and phase compensation value of the driving signal of several array elements, and compensate the amplitude and delay time of the driving signal of the corresponding array element according to the corresponding amplitude compensation value and phase compensation value of each array element.

8. A method for generating ultrasonic cavitation according to claim 7, characterized in that, The acoustic path length of each array element within each layer of medium is obtained. and total propagation time in multi-layer media The methods include: Assume a focused ultrasound transducer has n array elements, and the coordinates of each element are (X, X). n ,Y n Z n The natural focal point coordinates are (0,0,0), and the focal length is L; When passing through the first layer of medium When passing through multiple media, the angle of refraction is calculated for each layer. The acoustic path length within each layer of medium is calculated based on the included angle. Based on the sound path length and sound speed, the total propagation time of each array element in the multilayer medium is calculated. Among them, the Each array element is in the first layer of medium, the first Layered medium, first The angles between the acoustic beam direction of the layered medium and the normal to the medium interface are respectively , , C i This represents the ultrasonic velocity of focused ultrasound within the i-th layer of the medium. This represents the acoustic transmission path length of the nth array element within the i-th layer of medium; It means that the nth array element is in the nth position. The thickness of the acoustic transmission medium within the layer medium, This represents the total propagation time of the nth array element in the multilayer medium.

9. A method for generating ultrasonic cavitation according to claim 8, characterized in that, Phase value with For a period, when the absolute value exceeds At this time, a modulo operation needs to be performed, that is, subtracting... To ensure the phase value is within Within the range.

10. A method for generating ultrasonic cavitation according to claim 8, characterized in that, According to Obtain the amplitude compensation coefficient of the driving signal of the nth element after attenuation in all media. The methods include: in, Indicates the first The attenuation coefficient of the layer medium is a known constant. This represents the reference amplitude value before attenuation. It represents the amplitude compensation coefficient after the driving signal of the nth element is attenuated in the entire medium.

11. A method for generating ultrasonic cavitation according to claim 1, characterized in that, The method for dividing the target region of interest into regions based on tissue type, including at least one of the following: intrinsic threshold cavitation region, shock scattering cavitation region, and boiling cavitation region, includes: Determine the target organization type within the region of interest; If the target tissue is the brain, or is near blood vessels, bile ducts, or nerves, it is classified as an intrinsic threshold cavitation region. If the target tissue is a tumor in a solid organ, it is classified as a shock scattering cavitation region. If the target tissue is fibrous, it is classified into a boiling cavitation region; If the target tissue involves boundaries, blood vessels, or the gallbladder, these areas are classified as intrinsic threshold regions, while other areas are classified as impact scattering cavitation regions.

12. A method for generating ultrasonic cavitation according to claim 1, characterized in that, The method for arranging cavitation focal points within the target area of ​​interest includes: Set initial parameters for the region of interest; Identify the outer edge of interest and perform meshing and layering along the X, Y, and Z axes; Generate target candidate points layer by layer; The target candidate points are verified according to the initial parameters. If the verification is successful, the target candidate points are marked as target points. Sampling assessment of current coverage; If the coverage is lower than the initial parameter, random sampling is performed in the uncovered area and new focal points are attempted until the coverage is greater than or equal to the initial parameter, thus completing the arrangement of cavitation focal points.

13. A method for generating ultrasonic cavitation according to claim 12, characterized in that, The initial parameters include: the size of the outer ellipsoid. Dimensions of the inner ellipsoid Allowable overlap ratio Interlayer spacing factor Density factor Target coverage .

14. A method for generating ultrasonic cavitation according to claim 12, characterized in that, The method for identifying the outer edge of interest and performing mesh layering along the X, Y, and Z axes includes: The outer edge of the region of interest is smoothed to generate a sphere or ellipsoid. The layer position in the Z direction is obtained using the following formula: in: This represents the interlayer spacing factor, which is 0.2 ≤ A constant ≤ 1.0 This represents the length of the semi-axis of the inner ellipsoid in the Z direction. Let represent the semi-axis length of the external ellipsoid in the Z direction, and l represent the l-th layer of the spatial structure, which is an integer greater than or equal to 1. This represents the interlayer spacing in the Z direction between adjacent mesh layers. This indicates the layer position of the l-th layer in the Z direction.

15. A method for generating ultrasonic cavitation according to claim 14, characterized in that, The method for generating target candidate points layer by layer includes: The cross-section of the l-th layer is an ellipse. Therefore, the semi-axis lengths of the elliptical cross-section of the l-th layer in the x and y directions are respectively... and : Arranged according to a grid: in, , These represent the distances between adjacent target candidate points in the x and y directions, respectively, on the same grid layer. The density factor of the elliptical cross section is 0.2 ≤ A constant ≤ 1.0; The cross-sectional coordinates of the target candidate point on the l-th layer mesh are ( , The formula is: in, This represents the variable at the j-th point along the y-direction; Interlayer offset enables cell stacking: in, , These represent the offsets of the target candidate points in the x and y directions on the l-th layer mesh, respectively.

16. A method for generating ultrasonic cavitation according to claim 15, characterized in that, The method for verifying the target candidate points based on the initial parameters, and marking the target candidate points as target points if the verification is successful, includes: The target candidate points are filtered out, and points that exceed the outer edge are removed; Obtain the normalized distance d between two target candidate points; if If the candidate target points are not selected, they are retained; otherwise, they are removed. The retained candidate target points are then marked as target points. The allowed overlap ratio is a constant of 0 ≤ β ≤ 1, and (x1, y1, z1) and (x2, y2, z2) represent the coordinates of the first and second target candidate points, respectively.

17. A method for generating ultrasonic cavitation according to claim 16, characterized in that, The method for sampling and evaluating the current coverage rate, and if the coverage rate is lower than the initial parameter, randomly sampling in the uncovered area and attempting to place new focal points until the coverage rate is greater than or equal to the initial parameter, to complete the arrangement of cavitation focal points includes: The coverage rate is filtered using the following formula: in, Indicates the number of target points sampled. This represents random target points uniformly distributed within the outer ellipsoid. The indicator function is defined when the random target point is at least within an inner ellipsoid. =1, otherwise =0; The formula for generating target sampling points is as follows: in, satisfy ; After achieving the required coverage, the target points within each layer are sorted by polar coordinates. Calculate polar coordinates , ; By radius Grouped, with a group spacing of ; Group by angle Sort in ascending order; Output all target point elliptical models in a spiral sorting manner from the inside out, thus completing the cavitation focus arrangement.

18. A method for generating ultrasonic cavitation according to claim 1, characterized in that, The acoustic pressure and pulse parameters of the inherent threshold cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure greater than 30MPa, pulse duration 1~3 cycles, duty cycle less than 1%, negative acoustic pressure exceeding the inherent cavitation threshold of the target tissue, generating cavitation clouds at locations exceeding the negative pressure, and damaging the cell structure of the target tissue; and / or The acoustic pressure and pulse parameters of the impact scattering cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 20~30MPa, positive acoustic pressure greater than 100MPa, pulse duration 3~20 cycles, and duty cycle less than 1%. If the negative acoustic pressure does not exceed the inherent cavitation threshold of the target tissue, an initial pulse is applied to generate initial bubbles, and a second pulse is applied to generate cavitation nuclei near the bubbles, thereby disrupting the cell structure of the target tissue; and / or The acoustic pressure and pulse parameters of the boiling cavitation region include: ultrasonic frequency 0.5MHz~5MHz, negative acoustic pressure range 10~20MPa, positive acoustic pressure greater than 60MPa, pulse duration 1ms~20ms, and duty cycle 1%~2%. An initial pulse sequence is implemented to rapidly accumulate energy, heating the target tissue and generating boiling steam bubbles. Subsequent sequences accelerate bubble expansion and collapse, disrupting the target tissue's cellular structure.

19. A tissue fragmentation robotic system for use in the method of generating ultrasonic cavitation as described in claims 1-18, characterized in that, include: The main control device, used for electrical connection or information interaction with the ultrasonic transducer and robotic arm, includes an image processing module, an acoustic processing module, and a cavitation processing module. The image processing module is used to acquire real-time first modal images and second modal images, match the first modal images with the second modal images to obtain a fused display image, and identify and mark the target region of interest and sensitive medium on the fused display image. The acoustic processing module is connected to the image processing module and is used to extract acoustic parameters of the multilayer medium based on the fused display image, and calculate the amplitude compensation value and phase compensation value of several array element driving signals. The cavitation processing module is connected to the acoustic processing module and is used to divide the target region of interest according to tissue type, including at least one of intrinsic threshold cavitation region, shock scattering cavitation region, and boiling cavitation region, and to arrange cavitation focal points according to the region division type. Different sound pressure and pulse parameters are set for the inherent threshold cavitation region, the impact scattering cavitation region, and the boiling cavitation region, respectively; The robotic arm device is connected to the ultrasonic transducer and the main control device. It is used to move the ultrasonic transducer according to the location of the cavitation focus, sound pressure and pulse parameters fed back by the main control device, plan the travel route, and bring the ultrasonic transducer into contact with the degassed water in the coupling device and align it with the location of the cavitation focus. An ultrasonic transducer includes several ultrasonic transducers and a first modal image acquisition probe. The first modal image acquisition probe is used to acquire first modal images in real time. The ultrasonic transducers emit pulses to the target region of interest based on the location of a certain cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation. The ultrasonic transducer is moved to emit pulses to the target region of interest based on the location of another cavitation focus, sound pressure, and pulse parameters to generate ultrasonic cavitation, until ultrasonic cavitation of all cavitation focuses is completed. A display device, connected to the main control device, is used to enable user interaction; The coupling device is equipped with degassed water inside, and its bottom is in contact with the detection medium.

20. The tissue fragmentation robotic system according to claim 19, characterized in that, Also includes: A multi-channel power amplifier is connected to the main control device and the ultrasonic transducer, respectively.

21. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed, it implements the method as described in any one of claims 1 to 18.

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