High intensity focused ultrasound treatment model determination system and storage medium

Abstract

The application discloses a high-energy focused ultrasound treatment model determination system and a storage medium. The system comprises a processor configured to execute the following method, which comprises: acquiring a three-dimensional ultrasound image of a target object, a planned target volume in the three-dimensional ultrasound image, and at least two energy calibration points in a set edge layer of the planned target volume, the at least two energy calibration points being uniformly distributed in the set edge layer; determining a calibration energy value corresponding to each energy calibration point in the planned target volume; determining each treatment point in the planned target volume based on the calibration energy value of each energy calibration point and a set treatment point distribution rule, and generating a treatment model by using the calibration energy value of high-energy focused ultrasound corresponding to each treatment point. By improving the accuracy of the energy calibration value of different position points in the planned target volume, the accuracy of the ultrasound energy value of high-energy focused ultrasound applied to each position point in the ultrasound ablation operation is improved.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and in particular to a high-energy focused ultrasound therapy model determination system and storage medium. Background Technology

[0002] In existing non-invasive ultrasound ablation procedures, the ultrasound energy value of high-energy focused ultrasound corresponding to the target area is usually determined in advance, and then the ultrasound energy value is used to perform ultrasound ablation on the tissue.

[0003] This non-invasive ultrasound ablation method has good therapeutic effects, but the complex and varied tissue structures within the human body cause high-energy focused ultrasound to attenuate during its propagation path, making it difficult to guarantee the therapeutic effect. Furthermore, the energy required to produce cavitation effects varies among different tissues, and excessively high energy can increase the thermal effect on the target tissue and hinder cavitation. All of these factors further increase the difficulty of selecting appropriate high-energy focused ultrasound treatment energy.

[0004] Therefore, accurately designing the ultrasound energy of the high-energy focused ultrasound (HIFU) treatment model is crucial for the successful ablation of HIFU. It is therefore necessary to provide a HIFU treatment model with high ultrasound energy accuracy to improve the clinical efficacy of HIFU ablation. Summary of the Invention

[0005] This invention provides a high-energy focused ultrasound therapy model determination system and storage medium to address the low accuracy of ultrasound energy values ​​in existing non-invasive ultrasound ablation surgeries.

[0006] According to one aspect of the present invention, a high-energy focused ultrasound (HIFU) therapy model determination system is provided, comprising a processor configured to perform a HIFU therapy model determination method, including:

[0007] Acquire a three-dimensional ultrasound image of the target object, a planned target area in the three-dimensional ultrasound image, and at least two energy calibration points in a set edge layer of the planned target area, wherein the at least two energy calibration points are uniformly distributed in the set edge layer;

[0008] The calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area is determined. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point.

[0009] Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, each treatment point in the planned target area and the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point are determined to generate a treatment model.

[0010] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to perform the following method, including:

[0011] Acquire a three-dimensional ultrasound image of the target object, a planned target area in the three-dimensional ultrasound image, and at least two energy calibration points in a set edge layer of the planned target area, wherein the at least two energy calibration points are uniformly distributed in the set edge layer;

[0012] The calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area is determined. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point.

[0013] Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, each treatment point in the planned target area and the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point are determined to generate a treatment model.

[0014] The technical solution of the high-energy focused ultrasound (HIFU) therapy model determination system provided in this invention involves setting energy calibration points at the designated edge layer of the planned target area, determining the energy calibration value of each energy calibration point, and then determining the energy calibration value of each treatment point in the planned target area based on the energy calibration values ​​of the energy calibration points at the designated edge layer of the planned target area. By improving the accuracy of the energy calibration values ​​at different locations in the planned target area, the accuracy of the HIFU therapy model is improved, and the accuracy of the ultrasound energy value of the HIFU applied to each location point during ultrasound ablation surgery is improved, thereby enhancing the therapeutic effect of ultrasound ablation surgery.

[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a structural block diagram of a high-energy focused ultrasound therapy model determination system provided in an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of a method for determining a high-energy focused ultrasound therapy model according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of a planned target area including energy calibration points according to an embodiment of the present invention;

[0020] Figure 4A This is a structural block diagram of another high-energy focused ultrasound therapy model determination system provided in an embodiment of the present invention;

[0021] Figure 4B This is a structural block diagram of an ultrasonic device provided according to an embodiment of the present invention;

[0022] Figure 5 This is a flowchart of another method for determining a high-energy focused ultrasound therapy model according to an embodiment of the present invention;

[0023] Figure 6 This is a flowchart of a method for determining a planned target area according to an embodiment of the present invention;

[0024] Figure 7 This is a flowchart illustrating the method for determining the energy calibration value of an energy calibration point according to an embodiment of the present invention.

[0025] Figure 8 This is a schematic diagram illustrating tissue whitening during high-energy focused ultrasound as provided in the embodiments of the present invention;

[0026] Figure 9 This is a flowchart of the method for determining the target wide-area noise value according to an embodiment of the present invention;

[0027] Figure 10 It is a spectrum diagram of the target radio frequency data provided in the embodiments of the present invention;

[0028] Figure 11A This is a schematic diagram of the wide-area noise curve provided in the embodiments of the present invention;

[0029] Figure 11B This is another schematic diagram of a wide-area noise curve provided in the embodiments of the present invention;

[0030] Figure 11C This is a schematic diagram of another wide-area noise curve provided in the embodiments of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the term "object" in the specification, claims, and accompanying drawings of this invention is used to distinguish similar objects and is not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention 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 a 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.

[0033] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0034] As disclosed herein, the term "High-Intensity Focused Ultrasound" is a non-invasive surgical ablation technique. This technique focuses high-energy ultrasound waves to a focal point, utilizing the cavitation or thermal effects generated by the ultrasound waves to break up and ablate or denature the tissue.

[0035] As disclosed in this article, the term "non-inertial cavitation" refers to the phenomenon where, when high-energy focused ultrasound ablates similar tissues (such as the same tissue within the same organ of the same patient) at different energies, tiny bubbles within the tissue aggregate under high-frequency vibrations, eventually expanding and exploding. Non-inertial cavitation causes tissue cells to decompose and liquefy, ultimately forming cavities at the site of non-inertial cavitation. Boiling histotripsy, a non-invasive tissue ablation technique, utilizes non-inertial cavitation to remove target tissue.

[0036] like Figure 1 As shown, the high-energy focused ultrasound (HIFU) therapy model determination system 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. 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 HIFU therapy model determination system 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.

[0037] Multiple components in the high-energy focused ultrasound (HIFU) therapy model determination system 10 are connected to I / O interface 15, including: input unit 16, such as a keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as a disk, optical disk, etc.; and communication unit 19, such as a network card, modem, wireless transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0038] 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, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 can perform the high-energy focused ultrasound therapy model determination method described below.

[0039] Figure 2 This is a flowchart of a high-energy focused ultrasound (HIFU) therapy model determination method provided in an embodiment of the present invention. This embodiment is applicable to determining the calibration energy value of HIFU corresponding to each treatment point in the planned target area. This method can be executed by a HIFU therapy model determination device, which can be implemented in hardware and / or software and can be configured in a processor. Figure 2 As shown, the method includes:

[0040] S11. Acquire a three-dimensional ultrasound image of the target object and a planned target area in the three-dimensional ultrasound image, and at least two energy calibration points in the set edge layer of the planned target area, wherein the at least two energy calibration points are evenly distributed in the set edge layer.

[0041] The planned target area refers to the region where high-energy focused ultrasound is planned to be delivered during clinical treatment.

[0042] In one embodiment, the planned target area is a three-dimensional image region with a regular shape that includes the target area, such as a sphere or ellipsoid, the specific shape of which can be determined according to the shape of the target area.

[0043] In one embodiment, a three-dimensional ultrasound image of the target object is acquired; a planned target area is generated in the three-dimensional ultrasound image in response to a user's delineation of the planned target area in the three-dimensional ultrasound image; and at least two energy calibration points are generated at a predetermined edge layer of the planned target area in response to an energy calibration point generation command. Specifically, after acquiring the three-dimensional ultrasound image of the target object, the three-dimensional ultrasound image is displayed through a first visual interactive interface. The user can manually or automatically delineate the planned target area in the three-dimensional ultrasound image and then submit the planned target area through the confirmation option in the first visual interactive interface. Upon detecting the submission operation, the processor generates a three-dimensional ultrasound image including the planned target area. Then, the user sends an energy calibration point generation command to the processor by selecting the energy calibration point generation option in a second visual interactive interface. The processor generates the at least two energy calibration points at a predetermined edge layer of the planned target area according to the energy calibration point generation command. The first and second visual interactive interfaces can also be set to the same visual interactive interface. In this embodiment, the three-dimensional ultrasound image can be determined based on three-dimensional ultrasound data acquired by a three-dimensional ultrasound probe, or it can be determined based on two-dimensional ultrasound data acquired by a two-dimensional ultrasound probe, and then based on a predetermined image reconstruction method, such as a two-dimensional stacking algorithm, to determine the three-dimensional ultrasound image corresponding to the two-dimensional ultrasound data.

[0044] In one embodiment, the edge layer includes tissue surrounding the target area but excludes the target area itself.

[0045] Obtain the pre-configured layer thickness of the target area, and determine the target area's edge layer based on the spatial distribution information of the target area and this layer thickness. Where the layer thickness is greater than or equal to 0, if the layer thickness is 0, the edge layer is defined as the outer surface of the target area.

[0046] In one embodiment, the two energy calibration points may be evenly distributed at the intersection of any coordinate axis and a defined edge layer.

[0047] In one embodiment, the number of energy calibration points is an integer multiple of 3, such as 3 or 6. These 3 or 6 energy calibration points are evenly distributed at the intersection of the three coordinate axes and the set edge layer to improve the accuracy of the calibration energy values ​​of other locations within the planned target area determined based on the calibration energy values ​​of the energy calibration points, thereby improving the accuracy of the treatment model and the treatment effect when the treatment model is implemented.

[0048] In one embodiment, the number of energy calibration points is an integer multiple of 2, such as 2, 4, 6, or 8. All energy calibration points are evenly distributed at the designated edge layer of the planned target area and are coaxial in pairs, wherein each axis passes through the center of the planned target area.

[0049] S12. Determine the calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point.

[0050] In one embodiment, for any energy calibration point, an initial energy calibration value for high-energy focused ultrasound is determined, and the sum of this initial energy calibration value and a set energy deviation is used as the energy calibration value for that energy calibration point. This embodiment ensures the accuracy of the calibration energy values ​​at each location of the planned target area determined based on the calibration energy values ​​of the energy calibration points, thereby ensuring the accuracy of the treatment model.

[0051] S13. Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, determine each treatment point in the planned target area, as well as the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point, to generate a treatment model.

[0052] The treatment point is used to determine the location where high-intensity focused ultrasound (HIFU) is applied during ultrasound ablation surgery. Specifically, the application location of HIFU in the three-dimensional ultrasound image is determined based on the spatial coordinates of the treatment point in the localization image and the mapping relationship between the localization image and the three-dimensional ultrasound image.

[0053] Once the planned target area and the set treatment point distribution rules are determined, the spatial coordinates of each treatment point in the planned target area can be determined according to the set treatment point distribution rules. The set treatment point distribution rules include the distance values ​​between adjacent treatment points in three-dimensional space.

[0054] In one embodiment, the energy calibration value for each treatment point in the planned target area is determined based on linear interpolation and the calibration energy value at each energy calibration point. For example, Figure 3 As shown, the planned target area is ellipsoidal in shape, with six energy calibration points. The endpoints of the three coordinate axes of this ellipsoidal planned target area are set as energy calibration points. After the calibration energy values ​​of these six energy calibration points are determined, the calibration energy values ​​of each treatment point in the plane defined by the larger plane endpoints (P1, P2, P5, and P6) are determined based on a four-point planar interpolation method. Then, the calibration energy values ​​of each treatment point in the planned target area are determined based on linear interpolation of the remaining two energy calibration points (P3 and P4). The details are as follows:

[0055]

[0056]

[0057] Where P3 has coordinates (x3, y3, z3), P4 has coordinates (x4, y4, z4), and P1, P2, P5, and P6 represent their respective calibration energy values. `bilinear()` performs bilinear interpolation on the corresponding energy calibration values.

[0058] Optionally, such as Figure 4A As shown, the system also includes an ultrasound device 20, which includes a first transducer for outputting high-energy focused ultrasound and a second transducer for acquiring ultrasound images. The first and second transducers are configured to operate independently. The ultrasound images are either three-dimensional ultrasound images for determining the planned target area or real-time ultrasound images for monitoring. An output device (not shown) is used to display the ultrasound images. The processor 11 is also used to send a treatment model to the corresponding ultrasound device 20 when a treatment model acquisition command is detected. The ultrasound device 20 is configured to acquire a treatment model through a treatment model acquisition command, and to control the first transducer to output high-energy focused ultrasound for a set duration to the corresponding position of the target object according to the treatment model, control the second transducer to acquire a real-time ultrasound image of the target object, and send the real-time ultrasound image to the output device. The user monitors the implementation process of the treatment model through the real-time ultrasound image output by the output device.

[0059] Specifically, after detecting that a treatment model has been determined, the processor marks it as completed. When performing ultrasound ablation surgery on a patient, the ultrasound device inputs the target object's (patient's) identification information, such as patient identity information, into the model selection interface. If the treatment model corresponding to this identification information is in a completed state, the treatment model can be selected, and the processor, in response to this selection operation, outputs the treatment model to the ultrasound device. The user inputs the treatment model execution command into the ultrasound device, and the ultrasound device's controller (set in...) Figure 4B The host unit (not shown) can control the first transducer mounted on the robotic arm 40 to output high-energy focused ultrasound for a set duration to the corresponding position of the target object (patient) 30 according to the treatment model, and control the second transducer to output ultrasound signals for imaging to the target object to generate real-time ultrasound images. The user can monitor the ablation effect of high-energy focused ultrasound in real time through the real-time ultrasound images output by the output device.

[0060] In one embodiment, the first transducer is configured to include a ring transducer array with a second transducer disposed in the center of the ring transducer array, such that the first and second transducers do not interfere with each other in transmission and can operate independently. That is, while the first transducer is controlled to output high-energy focused ultrasound, the second transducer can be controlled to output ultrasound signals for ultrasound imaging, so that the user can monitor the progress of ultrasound ablation in real time through the real-time ultrasound images.

[0061] In one embodiment, the energy calibration point is used only to determine the treatment point. In this case, the ultrasound device controls the first transducer of the ultrasound device to output high-energy focused ultrasound for a set duration to the corresponding position of the target object according to the target parameters of each treatment point in the treatment model.

[0062] The technical solution of the high-energy focused ultrasound (HIFU) therapy model determination system provided in this invention involves setting energy calibration points at the designated edge layer of the planned target area, determining the energy calibration value of each energy calibration point, and then determining the energy calibration value of each treatment point in the planned target area based on the energy calibration values ​​of the energy calibration points at the designated edge layer of the planned target area. By improving the accuracy of the energy calibration values ​​at different locations in the planned target area, the accuracy of the HIFU therapy model is improved, and the accuracy of the ultrasound energy value of the HIFU applied to each location point during ultrasound ablation surgery is improved, thereby improving the therapeutic effect of ultrasound ablation surgery.

[0063] Figure 5 This is a flowchart illustrating another method for determining a high-energy focused ultrasound therapy model according to an embodiment of the present invention. This embodiment refines the acquisition of three-dimensional ultrasound images based on the aforementioned embodiments, including:

[0064] S211. Obtain the positioning image of the target object and the planned target area in the positioning image.

[0065] Among them, the localization image is a three-dimensional clinical image that can present the structure, location and state of each tissue of the target object, such as CT (Computed Tomography) localization image, MR (Nuclear Magnetic Resonance Imaging) localization image or ultrasound localization image.

[0066] In one embodiment, the user delineates a target region or clinical target region in the localization image. The target region is a lesion area or a clinical target region that includes a lesion area. The clinical target region may be generated by extending outward from the lesion area. The tissue surrounding the target region refers to the tissue that surrounds the target region. If the target region is surrounded by only one type of tissue, the user determines the planned target region that includes the target region in the localization image.

[0067] S212. Generate at least two energy calibration points in the designated edge layer of the planned target area.

[0068] The planned target area is defined by determining the edge layer. After the edge layer is determined, at least two energy calibration points are determined in the edge layer. The two energy calibration points are evenly distributed in the edge layer.

[0069] The specific distribution of the at least two energy calibration points is described in the aforementioned embodiment.

[0070] S213. Acquire a three-dimensional ultrasound image of the target object, and perform image registration between the positioning image and the three-dimensional ultrasound image to determine the planned target area and the location of the at least two energy calibration points in the three-dimensional ultrasound image. The three-dimensional ultrasound image includes the tissue region corresponding to the planned target area.

[0071] Image registration maps the planned target area and energy calibration point in the localization image to the three-dimensional ultrasound image, allowing the creation of the planned target area and the generation of energy calibration points to be separated from the subsequent energy calibration in time and space, thus improving the flexibility of high-energy focused ablation.

[0072] S22. Determine the calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point.

[0073] S23. Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, determine each treatment point in the planned target area, as well as the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point, to generate a treatment model.

[0074] This invention maps the planned target area and energy calibration point in the positioning image to a three-dimensional ultrasound image through image registration, so that target area creation, energy calibration point generation and energy calibration and ultrasound ablation can be separated in time, improving the flexibility of ultrasound ablation surgery.

[0075] Figure 6 This is a flowchart of a high-energy focused ultrasound (HIFU) treatment model determination method provided in an embodiment of the present invention. This embodiment adds a method for determining the treatment model when the number of tissue types surrounding the target area is greater than or equal to two, based on the previous embodiments. Figure 6 As shown, the method includes:

[0076] S3101. Obtain the positioning image of the target object and the target area in the positioning image.

[0077] S3102. When the tissue type of the tissue surrounding the target area is detected to be uniform, the planned target area including the target area is determined in the positioning image.

[0078] S3103. When the number of detected tissue types is greater than or equal to 2, tissue segmentation is performed on the target region in the localization image to obtain tissue segmentation results. The tissue segmentation results include at least two sub-tissue regions, and the tissue types of each sub-tissue region are single and different.

[0079] If the number of tissue types surrounding the target area is greater than or equal to 2, it means that the target area is surrounded by at least two types of tissue.

[0080] When the target area is surrounded by at least two types of tissues, the target region including the target area is determined in the localization image. Then, tissue segmentation is performed on the target region to obtain the tissue segmentation result. Based on the tissue segmentation result, the distribution range of each tissue type can be determined, that is, the distribution range of each sub-tissue region.

[0081] S3104. Based on the tissue segmentation results, the target area is segmented to obtain the target area segmentation results. The target area includes the target area, and the target area segmentation results include at least two sub-target areas. Each sub-target area corresponds to a unique sub-tissue area.

[0082] After the tissue segmentation results are determined, the target region is segmented according to the tissue segmentation results to obtain a target region segmentation result including at least two sub-target regions. The segmentation principle of the target region is that each sub-target region corresponds to only one sub-tissue region, and one sub-tissue region also corresponds to only one sub-target region.

[0083] S3105. In the target area, a comprehensive planning target area including the target target area is determined. The comprehensive planning target area includes at least two planning target areas, wherein each planning target area is set to include a corresponding sub-target target area and part or all of the sub-organization area corresponding to the sub-target target area.

[0084] In this embodiment, the surrounding tissue for each tissue type corresponds to a planned target area.

[0085] In one embodiment, the rules for determining the planned target area may differ for different tissue types. For example, the first planned target area is obtained by expanding the first sub-target area outward by a first thickness in a first set direction, and the second planned target area is obtained by expanding the second sub-target area outward by a second thickness in a second set direction. The method for determining the first set direction is to take the direction of the surrounding tissue of the first sub-target area relative to the center of the first sub-target area as the first set direction, and take the direction of the surrounding tissue of the second sub-target area relative to the center of the second sub-target area as the second set direction.

[0086] It should be noted that the above steps are only one optional embodiment. In one embodiment, after the target area and tissue segmentation results are determined, the planned target area can be determined first based on each sub-target area and the surrounding tissue corresponding to each sub-target area in the target area segmentation results, and then the planned target areas are combined to obtain the comprehensive planned target area.

[0087] During the energy calibration process, the energy calibration method described in the previous embodiment is used to perform energy calibration on each planned target area to obtain the treatment model corresponding to each planned target area. After determining the treatment model corresponding to each planned target area, all treatment models are merged to obtain a comprehensive treatment model.

[0088] This embodiment is adapted to determine the comprehensive planning target area for a target area surrounded by at least two types of surrounding tissue, and to determine the calibration energy value of each treatment point in each planning target area included in the comprehensive planning target area. This helps to improve the accuracy of the treatment model for complex lesions, thereby improving the treatment effect of complex lesions.

[0089] Figure 7 This is a flowchart illustrating a method for determining the energy calibration value of an energy calibration point according to an embodiment of the present invention. This embodiment refines the "determining the calibration energy of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area" in the aforementioned embodiments, and belongs to the same inventive concept as the aforementioned embodiments. Figure 7 As shown, the method includes:

[0090] S4301. For any given energy calibration point, determine whether the set of set ultrasound energy values ​​contains an ultrasound energy value that can cause non-inertial cavitation effect in the tissue corresponding to the energy calibration point.

[0091] The set of ultrasonic energy values ​​can be a matrix that includes at least two ultrasonic energy values, or it can be an expression that includes the minimum ultrasonic energy value, the maximum ultrasonic energy value, and the step size interval.

[0092] If any ultrasound energy value is set to correspond to high-energy focused ultrasound, the tissue corresponding to the applied energy calibration point will appear white in the real-time ultrasound image (see [reference]). Figure 8 If the wide-area noise value generated during the application of high-energy focused ultrasound is a target wide-area noise value that meets the set noise conditions, then it is determined that the set of set ultrasound energy values ​​contains an ultrasound energy value that can cause the tissue corresponding to the energy calibration point to have a non-inertial cavitation effect.

[0093] In other words, if the high-energy focused ultrasound corresponding to any ultrasound energy value in the set of set ultrasound energy values ​​cannot make the tissue corresponding to the energy calibration point white, and / or the corresponding wide-area noise value is not the target wide-area noise value that meets the set noise conditions, then it is determined that there is no ultrasound energy value in the set of set ultrasound energy values ​​that can make the tissue corresponding to the energy calibration point undergo non-inertial cavitation effect.

[0094] S4302. If so, then determine the calibration energy value of the energy calibration point based on the ultrasonic energy value.

[0095] If the set of ultrasonic energy values ​​contains an ultrasonic energy value that can cause non-inertial cavitation effect in the tissue corresponding to the energy calibration point, then the calibration energy value of the energy calibration point is determined based on this ultrasonic energy value. Specifically, the sum of the ultrasonic energy value and the set offset value is used as the calibration energy value of the energy calibration point. The set offset value is positive, and its introduction ensures that the calibration energy value at each location within the planned target area can cause non-inertial cavitation effect in the corresponding tissue.

[0096] S4303. If not, delete the energy calibration point and generate a replacement energy calibration point in the set edge layer within the set neighborhood of the energy calibration point; if the set of ultrasonic energy values ​​has an ultrasonic energy value that can cause non-inertial cavitation effect in the tissue corresponding to the replacement energy calibration point, use the replacement energy calibration point as the energy calibration point.

[0097] Specifically, at least two alternative energy calibration points are generated in the set edge layer within the set neighborhood of the energy calibration point; in response to the user's calibration point selection operation, a target alternative energy calibration point is determined from the at least two alternative energy calibration points, and the target alternative energy calibration point is used as the replacement energy calibration point for the deleted energy calibration point, i.e., the new energy calibration point.

[0098] Specifically, the radius of the defined neighborhood range is greater than or equal to the focal size of the high-energy focused ultrasound (HIFU) field. For example, when the focal size is 2 mm, the distance between the invalid energy calibration point and each of its alternative energy calibration points is greater than or equal to 2 mm. In one embodiment, the radius of the defined neighborhood range is greater than or equal to three times the focal size of the HIFU field.

[0099] In one embodiment, for an alternative energy calibration point, if there is no ultrasonic energy value in the set of ultrasonic energy values ​​that can cause non-inertial cavitation effect in the tissue corresponding to each alternative energy calibration point, then another alternative energy calibration point among the at least two alternative energy calibration points generated simultaneously is used as the alternative energy calibration point; it is determined whether there is an ultrasonic energy value in the set of ultrasonic energy values ​​that can cause non-inertial cavitation effect in the tissue corresponding to the new alternative energy calibration point. If so, the new alternative energy calibration point is used as the energy calibration point. If not, another alternative energy calibration point among the at least two alternative energy calibration points generated simultaneously is used as the alternative energy calibration point until there is an ultrasonic energy value in the set of ultrasonic energy values ​​that causes non-inertial cavitation effect in the tissue corresponding to the alternative energy calibration point of the deleted energy calibration point.

[0100] This embodiment sets up alternative energy calibration points for energy calibration points where the calibration energy value cannot be determined. The calibration energy value of each treatment point in the planned target area is determined based on the energy calibration value of the alternative energy calibration point and the energy calibration values ​​of other energy calibration points. This can improve the accuracy of determining the calibration energy value of each treatment point, thereby improving the accuracy of the treatment model.

[0101] Figure 9 A flowchart of the target wide-area noise value determination method provided in the embodiments of the present invention is shown below. Figure 9 As shown, the method includes:

[0102] S53011. For any ultrasonic energy value in the set of ultrasonic energy values, apply high-energy focused ultrasound of the ultrasonic energy value to the energy calibration point, and determine the wide-area noise value of the target radio frequency data corresponding to the high-energy focused ultrasound, wherein the target radio frequency data includes the high-energy focused ultrasound.

[0103] For any energy calibration point, for any ultrasonic energy value in the set of ultrasonic energy values, high-energy focused ultrasound of that ultrasonic energy value is applied to the energy calibration point, and during the application of high-energy focused ultrasound, target radio frequency data corresponding to the high-energy focused ultrasound is acquired from the second transducer, and then the wide-area noise value corresponding to the target radio frequency data is determined.

[0104] The wide-area noise value is determined by the following steps:

[0105] Step b1: When high-energy focused ultrasound is detected to be output from the first transducer, the frequency domain data of the radio frequency data output from the second transducer of the probe is acquired to obtain the radio frequency domain data.

[0106] When the first transducer outputs high-energy focused ultrasound, the second transducer captures the monitoring area and generates radio frequency (RF) data. This RF data includes high-energy focused ultrasound and background noise. When the first transducer is not outputting high-energy focused ultrasound, the RF data of the second transducer only includes background noise. Therefore, the RF frequency domain data includes the frequency domain data of high-energy focused ultrasound and the frequency domain data of background noise.

[0107] In one embodiment, after acquiring the radio frequency data, the radio frequency signal of each scan line is converted into a frequency domain signal using a short-time Fourier transform, and the frequency domain signal of each scan line is averaged to obtain radio frequency domain data.

[0108] Step b2: Obtain the background noise frequency domain data.

[0109] Acquire pre-stored background noise frequency domain data. For example, before controlling the first transducer of the ultrasound device to output high-energy focused ultrasound, first acquire the background noise output by the second transducer, determine the frequency domain data of the background noise, and use this frequency domain data as noise frequency domain data. Store this noise frequency domain data in a designated storage location. In one embodiment, "before the first transducer outputs high-energy focused ultrasound" means that before energy calibration is performed on all energy calibration points, the first transducer is controlled to enter the high-energy focused ultrasound working mode, but not outputting high-energy focused ultrasound, and then the background noise output by the second transducer is acquired.

[0110] Step b3: Use the difference between the radio frequency domain data and the noise frequency domain data of the radio frequency data as the target frequency domain data corresponding to the radio frequency data.

[0111] Since the target frequency domain data is obtained by subtracting the noise frequency domain data from the radio frequency domain data, the target frequency domain data can be considered to include only the frequency domain data of high-energy focused ultrasound.

[0112] Step b4: In response to the user's harmonic range selection operation, output the wide-area noise value in the target RF data corresponding to the harmonic range.

[0113] In one embodiment, after the target frequency domain data is determined, harmonic interval identifiers are output in the visual interactive interface so that users can select the wide-area noise value corresponding to the harmonic interval by selecting the harmonic interval.

[0114] In one embodiment, after the target frequency domain data is determined, the spectrum corresponding to the target frequency domain data is output in the visual interactive interface (see [link]). Figure 10 This allows users to determine the wide-area noise value of the target frequency domain data by selecting the desired spectral location or harmonic interval. The peaks in this figure represent harmonics, and wide-area noise exists within each harmonic interval.

[0115] In one embodiment, while outputting the spectral curve corresponding to the target frequency domain data in the visual interactive interface, a recommended spectral location range is also output to allow the user to quickly and accurately determine the required spectral location. Here, the spectral location refers to the coordinates of a point on the spectrum graph.

[0116] In one embodiment, the set frequency band range is a recommended harmonic interval distribution range, the harmonic interval is determined according to the harmonic interval selected by the user, and the wide-area noise value is determined according to the mean of all spectral values ​​corresponding to the harmonic interval.

[0117] The user selects the desired harmonic range from the spectrum curve output by the visual interactive interface. The processor responds to this operation by outputting the wide-area noise value corresponding to that harmonic range. This wide-area noise value is the wide-area noise value of the target frequency domain data. Figure 10 The average wide-area noise value for each harmonic interval of a spectrum curve is shown.

[0118] By responding to the user's selection of harmonic intervals within a set frequency band in the spectrogram, the wide-area noise value of the target frequency domain data is output, allowing the user to combine the performance of the ultrasonic device with their own experience to select a more accurate harmonic interval, thus improving the flexibility and accuracy of wide-area noise value determination.

[0119] S53012. Given the wide-area noise values ​​corresponding to all ultrasonic energy values ​​in the set ultrasonic energy set, draw wide-area noise curves based on all ultrasonic energy values ​​and the wide-area noise values ​​corresponding to each ultrasonic energy value.

[0120] Given the wide-area noise values ​​corresponding to all ultrasonic energy values ​​in the set of energy ultrasonics, a wide-area noise curve is plotted with ultrasonic energy values ​​on the x-axis and wide-area noise values ​​on the y-axis.

[0121] In one embodiment, for any ultrasonic energy value, at least two sets of radio frequency data are acquired, and the average of the wide-area noise values ​​corresponding to each radio frequency data is taken as the intermediate wide-area noise value corresponding to the ultrasonic energy value. A wide-area noise curve is plotted with the ultrasonic energy value on the horizontal axis and the wide-area noise value on the vertical axis.

[0122] S53013. Determine the wide-area noise value corresponding to the target inflection point in the wide-area noise curve, and take the wide-area noise value as the target wide-area noise value. The target inflection point is the end point of the rising edge of the wide-area noise curve that meets the set curvature condition, and all wide-area noise values ​​corresponding to the ultrasonic energy value of the end point are distributed within the set noise value range.

[0123] The set noise value range can be understood as the maximum distribution range of all wide-area noise values ​​corresponding to the ultrasonic energy value of the coordinate point that can be used as the target inflection point. If the difference between the maximum and minimum wide-area noise values ​​among all wide-area noise values ​​corresponding to the end point of the rising edge that meets the set curvature condition in the wide-area noise curve exceeds this range, it can be determined that the end point is not the target inflection point; otherwise, the end point is the target inflection point.

[0124] In one embodiment, when any ultrasonic energy value corresponds to at least two wide-area noise values, the average of the at least two wide-area noise values ​​corresponding to each ultrasonic energy value is used to obtain an intermediate wide-area noise value. An intermediate wide-area noise curve is plotted with the ultrasonic energy value on the x-axis and the intermediate wide-area noise value on the y-axis, and this intermediate wide-area noise curve is used as the wide-area noise curve, as shown below. Figure 11A , Figure 11B and Figure 11C As shown.

[0125] like Figure 11A and Figure 11C If all the wide-area noise values ​​corresponding to each energy value in each wide-area noise curve are within the set noise value range, then the point connecting the rising edge with the larger slope (first rising edge) and the rising edge with the smaller slope (stable segment) can be taken as the target inflection point.

[0126] like Figure 11BAs shown, it includes two rising edges with larger slopes, and each of these larger rising edges is followed by a smaller rising edge (a smooth segment). Therefore... Figure 11B The wide-area noise curve includes two rising edges, each followed by a rising edge with a smaller slope. The endpoints of these two rising edges correspond to the coordinates of 104% and 157% ultrasonic energy in the wide-area noise curve, respectively. For the former, the corresponding multiple wide-area noise values ​​are distributed within a larger noise value range, which is outside the set noise value range. For the latter, the corresponding multiple wide-area noise values ​​are distributed within a smaller noise value range, which is within the set noise value range. Therefore, the latter is taken as the target inflection point of the wide-area noise curve.

[0127] In one embodiment, after executing S53012, the processor outputs a wide-area noise curve and marks the target inflection point on the curve, while simultaneously outputting an accept option and a reject option. If the user accepts the target inflection point, they can click or touch the accept option, and the processor responds by executing S53013. If the user does not accept the target inflection point, they can click or touch the reject option, and the processor responds by marking candidate inflection points on the wide-area noise curve and outputting a candidate inflection point selection prompt. The user selects the desired inflection point from the marked candidate inflection points, and the processor responds by executing S53013.

[0128] This embodiment determines the target wide-area noise value of high-energy focused ultrasound that can cause non-inertial cavitation effects in the tissue corresponding to the energy calibration point based on the trend of the wide-area noise curve within the wide-area noise value range, with high accuracy.

[0129] In some embodiments, the high-energy focused ultrasound therapy model determination method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as... Figure 1 Storage unit 18 in the middle. In some embodiments, such as Figure 1 As shown, part or all of the computer program can be loaded and / or installed onto the high-intensity focused ultrasound (HIFU) therapy model determination 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 HIFU therapy model determination method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the HIFU therapy model determination method by any other suitable means (e.g., by means of firmware).

[0130] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-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.

[0131] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may 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 performed. The computer programs may 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.

[0132] In the context of this invention, 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 may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0133] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include 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.

[0134] 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 to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. 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 invention should be included within the scope of protection of this invention.

Claims

1. A system for determining a high-energy focused ultrasound therapy model, characterized in that, Includes a processor configured to perform the following high-energy focused ultrasound therapy model determination method, including: Acquire a three-dimensional ultrasound image of the target object, a planned target area in the three-dimensional ultrasound image, and at least two energy calibration points in a set edge layer of the planned target area, wherein the at least two energy calibration points are uniformly distributed in the set edge layer; The calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area is determined. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point. Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, each treatment point in the planned target area and the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point are determined to generate a treatment model. Acquiring a three-dimensional ultrasound image of the target object, a planned target region in the three-dimensional ultrasound image, and at least two energy calibration points in the defined edge layer of the planned target region, including: Acquire a localization image of the target object and the planned target area in the localization image; At least two energy calibration points are generated at the designated edge layer of the planned target area; A three-dimensional ultrasound image of the target object is acquired, and the positioning image is image registered with the three-dimensional ultrasound image to determine the location of the planned target area and the at least two energy calibration points in the three-dimensional ultrasound image, wherein the three-dimensional ultrasound image includes a tissue region corresponding to the planned target area; The process of acquiring the location image of the target object and the planned target area in the location image includes: If the tissue type around the target area is detected to be uniform, a planned target area including the target area is determined in the positioning image. If the number of detected tissue types is greater than or equal to 2, tissue segmentation is performed on the target region in the localization image to obtain a tissue segmentation result. The tissue segmentation result includes at least two sub-tissue regions, and the tissue types of each sub-tissue region are singular and different. Based on the tissue segmentation result, the target region is segmented to obtain the target region segmentation result. The target region includes the target region. The target region segmentation result includes at least two sub-target regions. Each sub-target region corresponds to a unique sub-tissue region. A comprehensive planned target area is determined within the target area, comprising at least two planned target areas. Each planned target area is configured to include a corresponding sub-target area and part or all of the sub-organizational areas corresponding to that sub-target area. The rules for determining planned target areas differ for different organization types.

2. The system according to claim 1, characterized in that, The acquisition of a three-dimensional ultrasound image of the target object, the planned target region in the three-dimensional ultrasound image, and at least two energy calibration points in the edge layer of the planned target region include: Acquire three-dimensional ultrasound images of the target object; In response to the user's delineation of the planned target area in the three-dimensional ultrasound image, a planned target area is generated in the three-dimensional ultrasound image; In response to the energy calibration point generation command, at least two energy calibration points are generated at a designated edge layer in the planned target area.

3. The system according to claim 1, characterized in that, The planned target area is an ellipsoid or a sphere.

4. The system according to any one of claims 1-3, characterized in that, The number of energy calibration points is 6, and the 6 energy calibration points are evenly arranged at the intersection of the three coordinate axes and the set edge layer.

5. The system according to claim 1, characterized in that, Determining the calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area includes: For any given energy calibration point, determine whether the set of set ultrasound energy values ​​contains an ultrasound energy value that can cause non-inertial cavitation effects in the tissue corresponding to that energy calibration point; If so, then the calibration energy value of the energy calibration point is determined based on the ultrasonic energy value; If not, delete the energy calibration point and determine an alternative energy calibration point in the set edge layer within the set neighborhood of the energy calibration point; if there is an ultrasound energy value in the set of set ultrasound energy values ​​that can cause non-inertial cavitation effect in the tissue corresponding to the alternative energy calibration point, use the alternative energy calibration point as the new energy calibration point.

6. The system according to claim 5, characterized in that, Determining a candidate energy calibration point within a defined edge layer within a defined neighborhood of the energy calibration point includes: At least two alternative energy calibration points are generated in the defined edge layer within the defined neighborhood of the energy calibration point; In response to the user's calibration point selection operation, a target alternative energy calibration point is determined from the at least two alternative energy calibration points, and the target alternative energy calibration point is used as a replacement energy calibration point for the deleted energy calibration point.

7. The system according to claim 5, characterized in that, The distance between the alternative energy calibration point and the corresponding energy calibration point is greater than or equal to one focal length.

8. The system according to claim 5, characterized in that, The determination of whether the set of set ultrasonic energy values ​​contains an ultrasonic energy value that can cause non-inertial cavitation effect in the tissue corresponding to the energy calibration point includes: If any ultrasound energy value in the set of set ultrasound energy values ​​corresponds to a high-energy focused ultrasound that can cause the tissue corresponding to the applied energy calibration point to turn white in the real-time ultrasound image, and the wide-area noise value generated during the application of the high-energy focused ultrasound is a target wide-area noise value that meets the set noise conditions, then it is determined that the set of set ultrasound energy values ​​contains an ultrasound energy value that can cause the tissue corresponding to the energy calibration point to have a non-inertial cavitation effect.

9. The system according to claim 8, characterized in that, The target wide-area noise value is determined by the following steps: For any ultrasonic energy value in the set of ultrasonic energy values, apply high-energy focused ultrasound of that ultrasonic energy value to the energy calibration point, and determine the wide-area noise value of the target radio frequency data corresponding to the high-energy focused ultrasound, wherein the target radio frequency data includes the high-energy focused ultrasound. Given the wide-area noise values ​​corresponding to all ultrasonic energy values ​​in the set ultrasonic energy, draw wide-area noise curves based on all ultrasonic energy values ​​and the wide-area noise values ​​corresponding to each ultrasonic energy value. Determine the wide-area noise value corresponding to the target inflection point in the wide-area noise curve, and use this wide-area noise value as the target wide-area noise value. The target inflection point is the end point of the rising edge of the wide-area noise curve that meets the set curvature condition, and all wide-area noise values ​​corresponding to the ultrasonic energy value of the end point are distributed within the set noise value range.

10. The system according to claim 9, characterized in that, The determination of the wide-area noise value corresponding to the target radio frequency data corresponding to high-energy focused ultrasound includes: When high-energy focused ultrasound is detected output from the first transducer, the frequency domain data of the radio frequency data output from the second transducer is acquired to obtain radio frequency domain data. Obtain the background noise frequency domain data; The difference between the radio frequency domain data and the noise frequency domain data is used as the target frequency domain data corresponding to the radio frequency data. In response to the user's harmonic range selection operation, the wide-area noise value corresponding to the harmonic range in the target radio frequency data is output.

11. The system according to claim 1, characterized in that, The system also includes: An ultrasound device, comprising a first transducer for outputting high-energy focused ultrasound and a second transducer for acquiring ultrasound images, the first transducer and the second transducer being configured to operate independently, the ultrasound images being either three-dimensional ultrasound images for determining the planned target area or real-time ultrasound images for monitoring. Output device for displaying the ultrasound image; The processor is also configured to send the treatment model to the corresponding ultrasound device upon detecting a treatment model acquisition instruction; The ultrasound device is configured to acquire a treatment model via a treatment model acquisition command, and to control the first transducer to output high-energy focused ultrasound for a set duration to the corresponding position of the target object according to the treatment model, control the second transducer to acquire real-time ultrasound images of the target object, and send the real-time ultrasound images to the output device.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to perform the following steps: Acquire a three-dimensional ultrasound image of the target object, a planned target area in the three-dimensional ultrasound image, and at least two energy calibration points in a set edge layer of the planned target area, wherein the at least two energy calibration points are uniformly distributed in the set edge layer; The calibration energy value of high-energy focused ultrasound corresponding to each energy calibration point in the planned target area is determined. The calibration energy value is the ultrasound energy value of high-energy focused ultrasound that can cause non-inertial cavitation effect in the tissue at the corresponding energy calibration point. Based on the calibration energy values ​​of each energy calibration point and the set treatment point distribution rules, each treatment point in the planned target area and the calibration energy value of the high-energy focused ultrasound corresponding to each treatment point are determined to generate a treatment model. Acquiring a three-dimensional ultrasound image of the target object, a planned target region in the three-dimensional ultrasound image, and at least two energy calibration points in the defined edge layer of the planned target region, including: Acquire a localization image of the target object and the planned target area in the localization image; At least two energy calibration points are generated at the designated edge layer of the planned target area; A three-dimensional ultrasound image of the target object is acquired, and the positioning image is image registered with the three-dimensional ultrasound image to determine the location of the planned target area and the at least two energy calibration points in the three-dimensional ultrasound image, wherein the three-dimensional ultrasound image includes a tissue region corresponding to the planned target area; The process of acquiring the location image of the target object and the planned target area in the location image includes: If the tissue type around the target area is detected to be uniform, a planned target area including the target area is determined in the positioning image. If the number of detected tissue types is greater than or equal to 2, tissue segmentation is performed on the target region in the localization image to obtain a tissue segmentation result. The tissue segmentation result includes at least two sub-tissue regions, and the tissue types of each sub-tissue region are singular and different. Based on the tissue segmentation result, the target region is segmented to obtain the target region segmentation result. The target region includes the target region. The target region segmentation result includes at least two sub-target regions. Each sub-target region corresponds to a unique sub-tissue region. A comprehensive planned target area is determined within the target area, comprising at least two planned target areas. Each planned target area is configured to include a corresponding sub-target area and part or all of the sub-organizational areas corresponding to that sub-target area. The rules for determining planned target areas differ for different organization types.

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