A multi-channel intelligent injection method, device, computer equipment and storage medium

Abstract

The application relates to a multi-channel intelligent injection method and device, computer equipment and a storage medium. The method comprises the following steps: collecting, by an ultrasonic imaging module, an ultrasonic image of a target injection area in an injection process, and collecting, by a feedback parameter monitoring module, a feedback parameter of the target injection area in the injection process; processing and calculating, by an intelligent control calculation module, the ultrasonic image and the feedback parameter, obtaining a current tissue state of the target injection area, and generating optimized injection parameters according to the current tissue state; wherein the injection parameters comprise an injection rate, a dose or / and an injection depth; and performing, by a multi-channel injection execution module, multi-channel injection according to the optimized injection parameters. The application integrates ultrasonic imaging technology and multi-dimensional sensor feedback, monitors the injection process in real time, dynamically adjusts the injection parameters, ensures the accurate release of drugs, enhances the treatment effect, and improves the accuracy, safety and flexibility of drug injection.

Description

Technical Field

[0001] This application belongs to the field of medical device and intelligent control technology, and specifically relates to a multi-channel intelligent injection method, device, computer equipment and storage medium. Background Technology

[0002] With the development of precision medicine, the clinical requirements for drug delivery are gradually increasing, especially in areas such as cancer treatment, cell therapy, and local anesthesia, where the accuracy, real-time monitoring, and safety of injections are paramount. However, traditional injection systems are typically based on manual operation or simple mechanical control, making it difficult to achieve high-precision, personalized drug delivery. This deficiency is particularly problematic in treatments involving complex anatomical structures or high-risk areas, potentially leading to inaccurate drug delivery, damage to healthy tissue, or uneven drug diffusion, thus affecting treatment outcomes and even increasing patient risk. In certain high-precision medical procedures, such as tumor-targeted drug injection or intraspinal injection, traditional injection methods cannot monitor needle position and injection site conditions in real time. Physicians must rely on personal experience and cannot adjust injection parameters based on the patient's tissue condition or real-time feedback, resulting in significant limitations. Especially for the needs of multi-target or multi-drug combination therapy, existing injection systems cannot deliver multiple drugs simultaneously, further limiting their application in complex treatment scenarios.

[0003] Currently, existing intelligent injection technologies on the market are mainly based on feedback parameter adjustment and mechanical control, relying on physiological feedback parameters to adjust the injection pattern. While this technology possesses a certain degree of intelligence, it is primarily limited to simple adjustments of a single feedback parameter and lacks real-time image guidance and monitoring of tissue changes. In addition, some ultrasound-guided injection systems exist on the market, relying on ultrasound imaging to help doctors locate the injection needle in complex anatomical areas. However, these systems still heavily rely on manual operation, lacking integrated automated control mechanisms to adjust the injection process in real time, and cannot dynamically adjust injection parameters based on real-time tissue feedback. Furthermore, they fail to achieve multi-channel injection and pathway planning.

[0004] In summary, while existing intelligent injection technologies can adjust injection patterns to some extent, they still have the following shortcomings:

[0005] 1) Lack of real-time imaging guidance: Existing intelligent injection systems mostly rely on physiological feedback parameters for injection adjustments, but they do not integrate real-time imaging technology. They cannot dynamically monitor the position of the needle and the range of drug diffusion during the injection process. In complex anatomical structures such as the spinal cord and brain, this may lead to needle deviation or accidental injection of drugs into healthy tissue, increasing the operational risk.

[0006] 2) Limited feedback mechanism: Existing intelligent injection systems rely only on limited physiological feedback and cannot combine real-time feedback on tissue status for fine-tuning, resulting in a lack of targeted and flexible adjustments during the injection process.

[0007] 3) Lack of path planning and obstacle avoidance functions: Existing intelligent injection systems rely mainly on manual operation by doctors for needle path planning and do not integrate intelligent path planning and obstacle avoidance functions. When injecting in complex areas, important tissues such as blood vessels and nerves may be encountered, leading to unnecessary trauma.

[0008] 4) Does not support multi-channel combination therapy: Existing smart injection systems typically only support the delivery of a single drug and cannot perform multi-channel injection, which limits their application in combination therapies that require the simultaneous delivery of multiple drugs, such as cancer treatment or cell therapy. Summary of the Invention

[0009] This application provides a multi-channel intelligent injection method, apparatus, computer device, and storage medium, which aims to at least partially solve one of the aforementioned technical problems in the prior art.

[0010] To address the above problems, this application provides the following technical solution:

[0011] A multi-channel intelligent injection method, comprising:

[0012] The ultrasound imaging module acquires ultrasound images of the target injection area during the injection process, and the feedback parameters of the target injection area during the injection process are acquired through the feedback parameter monitoring module.

[0013] The intelligent control and calculation module processes and calculates the ultrasound image and feedback parameters to obtain the current tissue state of the target injection area, and generates optimized injection parameters based on the current tissue state; wherein, the injection parameters include injection rate, dose and / or injection depth;

[0014] The multi-channel injection execution module performs multi-channel injection based on the optimized injection parameters.

[0015] The technical solution adopted in this application embodiment further includes: acquiring ultrasound images of the target injection area during the injection process using an ultrasound imaging module, specifically:

[0016] During the injection process, the ultrasound imaging module uses a programmable ultrasound imaging platform and a linear array transducer to acquire ultrasound data, obtain the needle position, tissue state of the target injection area and drug diffusion in real time, and generate an ultrasound image of the target injection area.

[0017] The technical solution adopted in this application embodiment further includes: the step of collecting feedback parameters of the target injection area during the injection process through the feedback parameter monitoring module, specifically:

[0018] The feedback parameter monitoring module includes a pressure sensor, a flow rate sensor, a temperature sensor, and a tissue stiffness sensor, used to collect feedback parameters in real time during the injection process; the feedback parameters include physiological parameters and injection status data, and the set of feedback parameters is represented as follows:

[0019] F(t)={P(t),V(t),T(t),H(t)}

[0020] Where P(t) represents the injection pressure, V(t) is the flow rate, T(t) is the tissue temperature, and H(t) is the tissue stiffness.

[0021] The technical solution adopted in this application embodiment further includes: processing and calculating the ultrasound image and feedback parameters through the intelligent control calculation module to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, specifically:

[0022] The intelligent control calculation module combines feedback closed-loop control and uses machine learning prediction and fuzzy control algorithms to process and calculate the ultrasound images and feedback parameters, and generate optimized injection parameters.

[0023] The machine learning prediction algorithm is as follows: based on historical feedback data, a machine learning model is used to predict injection parameters, and the model parameters are optimized using historical feedback data and injection results to minimize the error between the predicted results and the actual injection effect; the specific process of the machine learning prediction algorithm is as follows:

[0024] y = f(x, θ)

[0025]

[0026] Where y is the injection parameter, and x = [x1, x2, ..., x n [ ] represents the feature vector of historical feedback data, θ represents the parameters of the machine learning model, f represents the machine learning model, and θ * For the optimized model parameters, L is the loss function, using mean squared error (MSE):

[0027] The fuzzy control algorithm is as follows: assuming the control input is the physiological state S and the output is the injection rate R, the fuzzy rule is described as follows: if S is high, then the injection rate R increases; the membership functions corresponding to the physiological state S and the injection rate R are:

[0028]

[0029] Where S0 and R0 are the center values, σ S and σ R For a fuzzy range;

[0030] The fuzzy rule is then expressed as:

[0031] R = R0 + ΔR·μ S (S)

[0032] Where ΔR represents the adjustment range of the injection rate.

[0033] The technical solution adopted in this application embodiment further includes: processing and calculating the ultrasound image and feedback parameters through the intelligent control calculation module to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, further including:

[0034] The closed-loop feedback control equation is expressed as:

[0035]

[0036] Where R(t) is the current injection rate, and S(t) is the real-time feedback of physiological state, S desired For the desired physiological state, K p K i K d To control the gain, corresponding to the proportional, integral, and derivative control sections respectively;

[0037] The overall adjustment formula for the injection parameters, obtained by combining feedback closed-loop control, machine learning prediction, and fuzzy control algorithms, is as follows:

[0038] R final = f(x, θ) + μ S (S)·ΔR+K p ·(S(t)-S desired )

[0039] The technical solution adopted in this application embodiment further includes: after processing and calculating the ultrasound image and feedback parameters through the intelligent control calculation module to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, it further includes:

[0040] The injection path of the needle is optimized based on the ultrasound image, and an injection command is generated based on the optimized injection parameters and injection path; wherein, the optimization model of the injection path is represented as:

[0041]

[0042] Where, d i，jThis represents the distance from point i to point j of the needle, with the constraint that the needle must avoid a specific area containing critical tissue.

[0043] The technical solution adopted in this application embodiment further includes: after multi-channel injection is performed through the multi-channel injection execution module, it further includes:

[0044] The display module displays ultrasound images, feedback parameters, injection parameters, and injection path in real time.

[0045] Another technical solution adopted in this application embodiment is: a multi-channel intelligent injection device, comprising:

[0046] Ultrasound imaging module: used to acquire ultrasound images of the target injection area during the injection process;

[0047] Feedback parameter monitoring module: used to collect feedback parameters of the target injection area during the injection process;

[0048] Intelligent control calculation module: used to process and calculate the ultrasound image and feedback parameters, obtain the current tissue state of the target injection area, and generate optimized injection parameters based on the current tissue state; wherein, the injection parameters include injection rate, dose and / or injection depth;

[0049] Multi-channel injection execution module: used to perform multi-channel injection according to the optimized injection parameters.

[0050] Another technical solution adopted in this application embodiment is: a computer device, the computer device including a processor and a memory coupled to the processor, wherein,

[0051] The memory stores program instructions for implementing the multi-channel intelligent injection method;

[0052] The processor is used to execute the program instructions stored in the memory to control the multi-channel smart injection method.

[0053] Another technical solution adopted in this application embodiment is: a storage medium storing processor-executable program instructions, the program instructions being used to execute the multi-channel intelligent injection method.

[0054] Compared to existing technologies, the beneficial effects of the embodiments of this application are as follows: The multi-channel intelligent injection method, device, computer equipment, and storage medium of the embodiments of this application integrate ultrasound imaging technology and multi-dimensional sensor feedback to monitor the injection process in real time and dynamically adjust injection parameters, ensuring precise drug release, enhancing therapeutic effects, and providing an innovative solution for personalized treatment of complex clinical diseases. Utilizing intelligent algorithms for needle path planning and obstacle avoidance, it can automatically avoid critical tissues in complex anatomical environments, reducing risks and complications in medical operations and improving the accuracy, safety, and flexibility of drug injection. By designing a multi-channel injection system, it allows for the simultaneous delivery of multiple drugs, meeting the current clinical needs for combined treatment of complex diseases with multi-drug delivery. The embodiments of this application are applicable to various clinical scenarios such as clinical research and drug development, cancer treatment, cell and gene therapy, vaccination, anesthesia management, and emergency medical care, expanding the application scope of injection systems. Attached Figure Description

[0055] Figure 1 This is a flowchart of the multi-channel intelligent injection method according to an embodiment of this application;

[0056] Figure 2 This is a schematic diagram of the structure of the multi-channel intelligent injection device according to an embodiment of this application;

[0057] Figure 3 This is a schematic diagram of the computer device structure according to an embodiment of this application;

[0058] Figure 4 This is a schematic diagram of the structure of the storage medium according to an embodiment of this application. Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0060] The terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or computer device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or computer devices.

[0061] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0062] Specifically, please refer to Figure 1 This is a flowchart of a multi-channel intelligent injection method according to an embodiment of this application. The multi-channel intelligent injection method according to an embodiment of this application includes the following steps:

[0063] S100: Receives the initial injection parameters input from the user interface and injects them into the target injection area according to the initial injection parameters;

[0064] In this step, the initial injection parameters include, but are not limited to, injection rate, injection dose, and injection depth.

[0065] S110: During the injection process, the ultrasound imaging module collects ultrasound data in real time, such as the needle position, tissue state of the target injection area, and drug diffusion, generates an ultrasound image of the target injection area, and sends the ultrasound image to the intelligent control and calculation module.

[0066] In this step, during the injection process, the ultrasound imaging module acquires the needle position, tissue condition of the target injection area, and drug diffusion in real time, generating an ultrasound image of the target injection area. This helps doctors accurately obtain the needle position and tissue condition in real time, thereby ensuring effective drug delivery.

[0067] Specifically, the ultrasound imaging module uses a programmable ultrasound imaging platform such as the Verasonics Vantage 256 and linear array transducers such as the L9-4 for ultrasound data acquisition. It then uses DAS (Delay and Sum) beamforming to synthesize IQ (in-phase / quadrature data of radio frequency signals) data for subsequent processing. The linear array transducer comprises 128 elements with a center frequency of 6.5MHz and a bandwidth of 4-9MHz. The ultrasound imaging module employs plane wave imaging technology, enabling the acquisition of multiple profiles in a short time, significantly improving imaging speed and resolution. Each transmission is one signal cycle, with a mechanical index set to 0.1 and a pulse repetition frequency (PRF) of 800Hz. It should be understood that the above parameters are for illustrative purposes only, and specific settings can be made according to the actual application scenario. In practical applications, other imaging technologies such as magnetic resonance imaging (MRI) or computed tomography (CT) can also be used to provide more comprehensive information support in different clinical settings.

[0068] S120: The feedback parameter monitoring module collects physiological parameters and injection status data in real time and sends the feedback parameters to the intelligent control calculation module.

[0069] In this step, the feedback parameter monitoring module includes multiple sensors such as pressure sensors, flow rate sensors, temperature sensors, and tissue stiffness sensors. These sensors collect feedback parameters in real time during the injection process and send them to the intelligent control and calculation module for tissue response evaluation, so as to dynamically optimize injection parameters and improve treatment efficacy.

[0070] Specifically, the set of feedback parameters can be represented as:

[0071] F(t)={P(t),V(t),T(t),H(t)}(1)

[0072] Where P(t) represents the injection pressure, V(t) is the flow rate, T(t) is the tissue temperature, and H(t) is the tissue stiffness.

[0073] It should be noted that the feedback parameter monitoring module can select different types of sensors according to specific treatment needs. For example, in some cases, biosensors can be used to replace traditional physical sensors to monitor the biological response of drugs to different tissues, thereby providing more accurate biological feedback and enhancing the intelligence level of the system.

[0074] S130: The intelligent control calculation module processes and calculates ultrasound images and feedback parameters, analyzes the current tissue state of the target injection area, generates optimized injection parameters based on the current tissue state, and optimizes the injection path of the needle based on the ultrasound image.

[0075] In this step, the intelligent control calculation module analyzes the current tissue state of the target injection area in real time based on ultrasound imaging and feedback parameters during the injection process. It dynamically adjusts injection parameters such as injection rate, dosage, and / or injection depth according to the current tissue state to ensure accurate drug delivery and avoid unnecessary damage. For example, when increased tissue stiffness is detected, the injection rate is automatically reduced to prevent tissue damage. This application achieves closed-loop control of injection modes and parameters through the intelligent control calculation module, adapting to the injection needs of different tissue states. Simultaneously, it optimizes the needle injection path based on ultrasound images to avoid damage to healthy tissue, ensuring effective avoidance of critical blood vessels and nerves in complex anatomical structures, reducing the risks in medical operations, and significantly improving the accuracy, safety, and flexibility of drug injection.

[0076] Furthermore, the intelligent control computing module combines feedback closed-loop control and uses machine learning prediction and fuzzy control algorithms to process ultrasound images and feedback parameters in real time to adjust injection parameters.

[0077] Specifically, the machine learning prediction algorithm includes: using historical feedback data such as ultrasound imaging data, patient physiological signals, and drug concentration in the body, a machine learning model is used to predict injection parameters, and the model parameters are optimized through historical feedback data and injection results to minimize the error between the predicted results and the actual injection effect; the algorithm process is as follows:

[0078] y = f(x, θ) (2)

[0079]

[0080] Where y is the output target, i.e., the injection parameter, and x = [x1, x2, ..., x...]. n ] represents the feature vector of historical feedback data, θ represents the parameters of the machine learning model, and f represents the machine learning model, including but not limited to deep learning networks or other regression algorithms. * For the optimized model parameters, L is the loss function, using mean squared error (MSE):

[0081] It should be noted that the algorithm of the intelligent control computing module can be adjusted according to different clinical needs. For example, different machine learning models can be used to optimize the prediction and adjustment strategies of injection parameters to meet the drug delivery needs under specific pathological conditions.

[0082] The fuzzy control algorithm is as follows: Assuming the control input is the patient's physiological state S and the output is the injection rate R, the fuzzy rule can be described as follows: if S is high, indicating that the feedback suggests the patient needs stronger analgesia, then the injection rate R increases. The membership functions corresponding to the physiological state S and the injection rate R are:

[0083]

[0084] Where S0 and R0 are the center values, σ S and σ R The range is ambiguous.

[0085] The fuzzy rule can then be expressed as:

[0086] R = R0 + ΔR·μ S (S) (5)

[0087] Where ΔR represents the adjustment range of the injection rate.

[0088] The above-mentioned fuzzy control algorithm is used to process data with high uncertainty, and the injection rate and dosage are adjusted according to fuzzy rules.

[0089] The closed-loop feedback control equation is expressed as:

[0090]

[0091] Where R(t) is the current injection rate, and S(t) is the real-time physiological state feedback. desired For the desired physiological state (e.g., analgesia target). K p K i K d To control the gain, corresponding to the proportional, integral, and derivative control sections, respectively.

[0092] Combining feedback closed-loop control, machine learning prediction, and fuzzy control algorithms, the overall adjustment formula for the injection parameters is obtained as follows:

[0093] R final = f(x, θ) + μ S (S)·ΔR+K p ·(S(t)-S desired (7)

[0094] Furthermore, after obtaining the optimized injection parameters, the intelligent control computing module further optimizes the injection path of the injection needle through a path optimization model. This ensures effective avoidance of critical tissues such as blood vessels and nerves in complex anatomical structures, reducing the risks during medical procedures. Specifically, the injection path optimization model is represented as follows:

[0095]

[0096] Where, d i,j This represents the distance from point i to point j of the needle, with the constraint that the needle must avoid a specific area containing critical tissues such as blood vessels and nerves.

[0097] S140: Generate injection instructions based on optimized injection parameters and injection path, and send the injection instructions to the multi-channel injection execution module;

[0098] S150: Performs multi-channel injection through the multi-channel injection execution module, and displays ultrasound images, feedback parameters, injection parameters and injection path in real time through the display module;

[0099] In this step, the injection system can simultaneously control multiple injection channels, allowing for the delivery of multiple drugs at the same time, meeting the current clinical needs for combined treatment of complex diseases with multi-drug delivery. It also supports multiple dosage delivery modes, such as continuous injection, intermittent injection, or pulsed injection, to adapt to the injection characteristics and treatment regimens of different drugs, enabling it to play a role in a wider range of medical scenarios. Simultaneously, this application uses a display module to display ultrasound imaging results, feedback parameters, injection parameters, and injection path in real time, allowing physicians to intuitively view the injection process, facilitate rapid adjustment of injection settings, and ensure the smooth progress of the treatment.

[0100] Based on the above, the multi-channel intelligent injection method of this application integrates ultrasound imaging technology and multi-dimensional sensor feedback to monitor the injection process in real time and dynamically adjust injection parameters, ensuring precise drug release, enhancing therapeutic effects, and providing an innovative solution for personalized treatment of complex clinical diseases. Utilizing intelligent algorithms for needle path planning and obstacle avoidance, it can automatically avoid critical tissues in complex anatomical environments, reducing risks and complications in medical operations and improving the accuracy, safety, and flexibility of drug injection. By designing a multi-channel injection system, it allows for the simultaneous delivery of multiple drugs, meeting the current clinical needs for combined treatment of complex diseases with multiple drug deliveries. The embodiments of this application are applicable to various clinical scenarios such as clinical research and drug development, cancer treatment, cell and gene therapy, vaccination, anesthesia management, and emergency medical care, expanding the application scope of injection systems.

[0101] Please see Figure 2 This is a schematic diagram of the structure of a multi-channel intelligent injection device according to an embodiment of this application. The multi-channel intelligent injection method device 40 according to an embodiment of this application includes:

[0102] Ultrasonic imaging module 41: used to acquire ultrasound images of the target injection area during the injection process;

[0103] Feedback parameter monitoring module 42: Used to collect feedback parameters of the target injection area during the injection process;

[0104] Intelligent control calculation module 43: used to process and calculate the ultrasound image and feedback parameters, obtain the current tissue state of the target injection area, and generate optimized injection parameters based on the current tissue state; wherein, the injection parameters include injection rate, dose and / or injection depth;

[0105] Multi-channel injection execution module 44: used to perform multi-channel injection according to the optimized injection parameters.

[0106] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0107] The apparatus provided in this application can be applied to the foregoing method embodiments. For details, please refer to the description of the above method embodiments, which will not be repeated here.

[0108] Please see Figure 3 This is a schematic diagram of a computer device structure according to an embodiment of this application. The computer device 50 includes:

[0109] Memory 51 storing executable program instructions;

[0110] Processor 52 connected to memory 51;

[0111] The processor 52 is used to call the executable program instructions stored in the memory 51 and perform the following steps: acquiring ultrasound images of the target injection area during the injection process through the ultrasound imaging module, and acquiring feedback parameters of the target injection area during the injection process through the feedback parameter monitoring module; processing and calculating the ultrasound images and feedback parameters through the intelligent control calculation module to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state; wherein, the injection parameters include injection rate, dose and / or injection depth; and performing multi-channel injection according to the optimized injection parameters through the multi-channel injection execution module.

[0112] The processor 52 can also be referred to as a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0113] Please see Figure 4This is a schematic diagram of the structure of the storage medium in an embodiment of this application. The storage medium in this embodiment stores program instructions 61 capable of implementing the following steps: acquiring ultrasound images of the target injection area during the injection process via an ultrasound imaging module, and acquiring feedback parameters of the target injection area during the injection process via a feedback parameter monitoring module; processing and calculating the ultrasound images and feedback parameters via an intelligent control calculation module to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state; wherein the injection parameters include injection rate, dose, and / or injection depth; and performing multi-channel injection based on the optimized injection parameters via a multi-channel injection execution module. This program instruction 61 can be stored in the aforementioned storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network computer device, etc.) or processor to execute all or part of the steps of the methods in various embodiments of this application. The aforementioned storage media include: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program instructions, or terminal computer devices such as computers, servers, mobile phones, and tablets. Servers can be independent servers or cloud servers providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, apparatuses, or units, and may be electrical, mechanical, or other forms.

[0115] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A multi-channel intelligent injection device, characterized in that, include: Ultrasound imaging module: used to acquire ultrasound images of the target injection area during the injection process; Feedback parameter monitoring module: used to collect feedback parameters of the target injection area during the injection process; Intelligent control calculation module: used to process and calculate the ultrasound image and feedback parameters, obtain the current tissue state of the target injection area, and generate optimized injection parameters based on the current tissue state; wherein, the injection parameters include injection rate, dose and / or injection depth; Multi-channel injection execution module: used to perform multi-channel injection according to the optimized injection parameters; wherein: The process of processing and calculating the ultrasound image and feedback parameters to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, specifically involves: The intelligent control calculation module combines feedback closed-loop control and uses machine learning prediction and fuzzy control algorithms to process and calculate the ultrasound images and feedback parameters, and generate optimized injection parameters. The machine learning prediction algorithm is as follows: based on historical feedback data, a machine learning model is used to predict injection parameters, and the model parameters are optimized using historical feedback data and injection results to minimize the error between the predicted results and the actual injection effect; the specific process of the machine learning prediction algorithm is as follows: in, For injection parameters, For historical feedback data feature vectors, For machine learning model parameters, Machine learning models For optimized model parameters, For the loss function, use the mean squared error (MSE): ; The fuzzy control algorithm is as follows: assuming the control input is a physiological state. The output is the injection rate. Then the fuzzy rule is described as: if High, then injection rate Increase; the physiological state and injection rate The corresponding membership function is: , in and As the center value, and For a fuzzy range; The fuzzy rule is then expressed as: in This refers to the adjustment range of the injection rate.

2. The multi-channel intelligent injection device according to claim 1, characterized in that, The acquisition of ultrasound images of the target injection area during the injection process specifically includes: During the injection process, the ultrasound imaging module uses a programmable ultrasound imaging platform and a linear array transducer to acquire ultrasound data, obtain the needle position, tissue state of the target injection area and drug diffusion in real time, and generate an ultrasound image of the target injection area.

3. The multi-channel intelligent injection device according to claim 2, characterized in that, The feedback parameters of the target injection area during the injection process are specifically as follows: The feedback parameter monitoring module includes a pressure sensor, a flow rate sensor, a temperature sensor, and a tissue stiffness sensor, used to collect feedback parameters in real time during the injection process; the feedback parameters include physiological parameters and injection status data, and the set of feedback parameters is represented as follows: in, P(t) Indicates injection pressure. V(t) For flow rate, T(t) For tissue temperature, H(t) This refers to tissue stiffness.

4. The multi-channel intelligent injection device according to claim 3, characterized in that, The step of processing and calculating the ultrasound image and feedback parameters to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, further includes: The closed-loop feedback control equation is expressed as: in The current injection rate, For real-time feedback of physiological status. For the desired physiological state, , , To control the gain, corresponding to the proportional, integral, and derivative control sections respectively; The overall adjustment formula for the injection parameters, obtained by combining feedback closed-loop control, machine learning prediction, and fuzzy control algorithms, is as follows: 。 5. The multi-channel intelligent injection device according to claim 4, characterized in that, After processing and calculating the ultrasound image and feedback parameters to obtain the current tissue state of the target injection area, and generating optimized injection parameters based on the current tissue state, the process further includes: The injection path of the needle is optimized based on the ultrasound image, and an injection command is generated based on the optimized injection parameters and injection path; wherein, the optimization model of the injection path is represented as: in, Indicates the needle from point i Time The distance is subject to the constraint that the needle must avoid a specific area containing critical tissue.

6. The multi-channel intelligent injection device according to claim 5, characterized in that, The device also includes a display module: It is used to display ultrasound images, feedback parameters, injection parameters, and injection path in real time after multi-channel injection.

Images