Multi-system automatic control method, system, device and equipment for interventional operation

Abstract

The invention relates to the technical field of equipment control of an interventional operation, and provides a multi-system automatic control method, system, device and equipment for the interventional operation, which can cooperatively control multiple systems and simplify the operation process of the interventional operation. The method comprises the following steps: determining a current stage of an interventional operation based on a current intraoperative image fed back by an image acquisition system; generating an automatic decision instruction matched after the current stage based on the current state data of the multiple systems; the multiple systems comprise an image acquisition system, an interventional operation robot system and a medicine injection system; and sending the automatic decision instruction to a corresponding system for execution.

Description

Technical Field

[0001] The present application relates to the technical field of device control for interventional surgery, and particularly to a multi-system automatic control method, system, device, automatic decision-making device, storage medium, and computer program product for interventional surgery. Background Art

[0002] Interventional surgery is a minimally invasive surgical method in which, under the guidance of an image acquisition device (such as an angiography machine, fluoroscopy machine, CT, MR, B-ultrasound), puncture needles, catheters, guide wires, and other instruments are used to puncture into the human body to establish a treatment channel, and specific surgical instruments such as balloons and vascular stents are introduced into the diseased part of the human body, or contrast agents, chemotherapy drugs, embolization agents, and other drugs are injected into the lesion site for local diagnosis and treatment of the lesion.

[0003] During interventional surgery, doctors are continuously exposed to the environment of X-ray radiation. To reduce the radiation impact, doctors will wear protective equipment such as lead aprons for operation. However, the heavy lead aprons will greatly consume the physical strength of doctors, and their attention and stability will decrease accordingly, which is likely to affect the operation accuracy and increase the surgical risk. Summary of the Invention

[0004] Based on this, it is necessary to provide a multi-system automatic control method, device, automatic decision-making device, storage medium, and computer program product for interventional surgery in view of the above technical problems.

[0005] The present application provides a multi-system automatic control method for interventional surgery, and the method includes:

[0006] Determine the current stage of the interventional surgery based on the current intraoperative image feedback by the image acquisition system;

[0007] Generate an automatic decision-making instruction that matches after the current stage based on the current state data of multiple systems; the multiple systems include the image acquisition system, the interventional surgery robot system, and the drug injection system;

[0008] Send the automatic decision-making instruction to the corresponding system for execution.

[0009] In one embodiment, generating an automatic decision-making instruction that matches after the current stage based on the current state data of multiple systems includes:

[0010] Generate automatic decision-making data that matches after the current stage based on the current state data of multiple systems;

[0011] In response to the user's confirmation operation on the current state data of multiple systems and the automatic decision-making data, generate an automatic decision-making instruction based on the automatic decision-making data.

[0012] In one embodiment, based on the current state data of multiple systems, generating an automatic decision instruction that matches after the current stage, including:

[0013] Based on the current state data of multiple systems, obtaining the current state data of the interventional surgical robot system;

[0014] Based on the current state data of the interventional surgical robot system and the current intraoperative image, obtaining the surgical instrument state data; the surgical instrument is the surgical instrument clamped by the interventional surgical robot of the interventional surgical robot system;

[0015] Based on the current state data of multiple systems and the surgical instrument state data, generating an automatic decision instruction that matches after the current stage.

[0016] In one embodiment, the method further includes:

[0017] Comparing the current intraoperative image and the historical image;

[0018] According to the comparison result, generating the target acquisition parameters, target sequence protocol, and target acquisition pose of the image acquisition system;

[0019] Based on the target acquisition parameters, target sequence protocol, and target acquisition pose, generating an automatic control instruction for the image acquisition system and feeding it back to the image acquisition system.

[0020] In one embodiment, based on the current intraoperative image fed back by the image acquisition system, determining the current stage of the interventional surgery, including:

[0021] Performing feature analysis on the current intraoperative image fed back by the image acquisition system to obtain a feature analysis result;

[0022] According to the feature analysis result, determining the current stage of the interventional surgery.

[0023] In one embodiment, the method further includes:

[0024] During the process of the corresponding system executing the automatic decision instruction, if manual decision data input by the user is received, controlling the corresponding system to stop executing the automatic decision instruction, and generating a manual decision instruction based on the manual decision data;

[0025] Sending the manual decision instruction to the corresponding system for execution.

[0026] The present application provides a multi-system automatic control system for interventional surgery, and the system includes: an automatic decision-making device, an image acquisition system, an interventional surgical robot system, and a drug injection system;

[0027] The image acquisition system is configured to acquire the current intraoperative image and feed it back to the automatic decision-making device;

[0028] The automatic decision-making device is used to determine the current stage of the interventional surgery based on the current intraoperative image.

[0029] The image acquisition system, the interventional surgery robot system, and the drug injection system are used to feedback their respective system status data to the automatic decision-making device.

[0030] The automatic decision-making device is further used to generate an automatic decision-making instruction that matches the stage after the current stage based on the current status data of multiple systems.

[0031] The automatic decision-making device is further used to send the automatic decision-making instruction to the corresponding system for execution.

[0032] This application provides a multi-system automatic control device for interventional surgery. The device includes:

[0033] A surgical stage determination module is used to determine the current stage of the interventional surgery based on the current intraoperative image feedback by the image acquisition system.

[0034] A decision-making instruction generation module is used to generate an automatic decision-making instruction that matches the stage after the current stage based on the current status data of multiple systems. The multiple systems include the image acquisition system, the interventional surgery robot system, and the drug injection system.

[0035] A decision-making instruction sending module is used to send the automatic decision-making instruction to the corresponding system for execution.

[0036] This application provides an automatic decision-making device, including a memory and a processor. The memory stores a computer program, and the processor executes the above method.

[0037] This application provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by the processor to execute the above method.

[0038] This application provides a computer program product, on which a computer program is stored, and the computer program is executed by the processor to execute the above method.

[0039] This application determines the current stage of the interventional surgery based on the current intraoperative image feedback by the image acquisition system, generates an automatic decision-making instruction that matches the stage after the current stage based on the current status data of multiple systems. The multiple systems include the image acquisition system, the interventional surgery robot system, and the drug injection system, and sends the automatic decision-making instruction to the corresponding system for execution, which can collaboratively control multiple systems without the participation of doctors and simplify the operation process of interventional surgery. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the drawings required for use in the description of the embodiments or the related art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a schematic flow chart of a multi-system automatic control method for interventional surgery in an embodiment;

[0042] Figure 2 It is an application environment diagram of a multi-system automatic control method for interventional surgery in an embodiment;

[0043] Figure 3(a) is a schematic diagram of an interventional surgery system in an embodiment;

[0044] Figure 3(b) is a schematic flow chart of a multi-system automatic control method for interventional surgery in another embodiment;

[0045] Figure 4 It is a structural block diagram of a multi-system automatic control device for interventional surgery in an embodiment;

[0046] Figure 5 It is an internal structure diagram of an automatic decision-making device in an embodiment. Detailed implementation manners

[0047] In order to make the purpose, technical solutions and advantages of the present application clearer, the following further details the present application in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

[0048] Referring to "embodiment" in the present application means that the specific features, structures or characteristics described in connection with the embodiment may be included in at least one embodiment of the present application. The appearance of this phrase at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments.

[0049] The multi-system automatic control method for interventional surgery provided by the present application can collaboratively control multiple systems of interventional surgery and automatically complete each process of the placement of surgical instruments, the setting of image acquisition parameters, the acquisition of image data, and the injection of drugs such as contrast agents. This method involves an automatic decision-making device, and the steps executed by the automatic decision-making device are as Figure 1 shown.

[0050] Step S101: Determine the current stage of the interventional surgery based on the current intraoperative image fed back by the image acquisition system.

[0051] The image acquisition system can be an angiography machine, a fluoroscope, X-ray Computed Tomography (CT), Magnetic Resonance (MR), B-ultrasound, etc. During the interventional surgery, after the image acquisition system acquires the current intraoperative image, it can feed back the current intraoperative image to the automatic decision-making device, and the automatic decision-making device analyzes the current intraoperative image to determine the current stage of the interventional surgery.

[0052] Step S102: Generate an automatic decision-making instruction that matches the stage after the current stage based on the current state data of multiple systems; the multiple systems include an image acquisition system, an interventional surgery robot system, and a drug injection system.

[0053] The systems involved in the interventional surgery include an image acquisition system, an interventional surgery robot system, and a drug injection system. Each system can feed back its own system's current state data to the automatic decision-making device. Thus, the automatic decision-making device can obtain the current state data of multiple systems. The interventional surgery can be divided into multiple stages with a chronological order. After determining the current stage, the automatic decision-making device determines the next stage of the current stage based on the pre-divided multiple stages and the chronological order between the stages. The automatic decision-making device can generate an automatic decision-making instruction that matches the next stage after the current stage based on the current state data of multiple systems. This automatic decision-making instruction can be an instruction for at least one of the image acquisition system, the interventional surgery robot system, and the drug injection system.

[0054] Step S103: Send the automatic decision-making instruction to the corresponding system for execution.

[0055] The automatic decision-making instruction can include, but is not limited to, adjustment and control of the following: the acquisition parameters, protocol sequence, acquisition pose, acquisition duration, and whether to perform acquisition of the image acquisition system; the parameters for the interventional surgery robot to automatically deliver surgical instruments, such as the type of surgical instrument to be delivered, the delivery distance, the rotation angle, the delivery speed, etc.; the operating parameters of the drug injection system, such as the injection speed, injection volume, upper limit of injection pressure, etc. After generating the automatic decision-making instruction, the automatic decision-making device can send the automatic decision-making instruction to the corresponding system for execution.

[0056] In this embodiment, based on the current intraoperative image feedback by the image acquisition system, the current stage of the interventional surgery is determined; based on the current state data of multiple systems, an automatic decision-making instruction matching the stage after the current stage is generated; the multiple systems include an image acquisition system, an interventional surgery robot system, and a drug injection system; sending the automatic decision-making instruction to the corresponding system for execution can collaboratively control the multiple systems without the participation of a doctor, simplifying the operation process of the interventional surgery.

[0057] In one embodiment, generating an automatic decision-making instruction matching the stage after the current stage based on the current state data of multiple systems may specifically include: generating automatic decision-making data matching the stage after the current stage based on the current state data of multiple systems; in response to the user's confirmation operation on the current state data of multiple systems and the automatic decision-making data, generating an automatic decision-making instruction based on the automatic decision-making data.

[0058] After obtaining the current state data of multiple systems, the automatic decision-making device can display the current state data of multiple systems to users such as doctors through a display device for confirmation. Moreover, after generating automatic decision-making data matching the next stage after the current stage based on the current state data of multiple systems, the automatic decision-making device can also display the automatic decision-making data to users such as doctors through the display device for confirmation. In response to the user's confirmation operation on the current state data of multiple systems and the automatic decision-making data, the automatic decision-making device can generate an automatic decision-making instruction based on the automatic decision-making data.

[0059] In one embodiment, generating an automatic decision-making instruction matching the stage after the current stage based on the current state data of multiple systems may specifically include: obtaining the current state data of the interventional surgery robot system based on the current state data of multiple systems; obtaining the surgical instrument state data based on the current state data of the interventional surgery robot system and the current intraoperative image; the surgical instrument is the surgical instrument clamped by the interventional surgery robot of the interventional surgery robot system; generating an automatic decision-making instruction matching the stage after the current stage based on the current state data of multiple systems and the surgical instrument state data.

[0060] The interventional surgery robot of the interventional surgery robot system can clamp the surgical instrument to move the surgical instrument to a specified position.

[0061] Referring to Figure 2 , after obtaining the current state data of multiple systems, the automatic decision-making device can obtain the current state data of the interventional surgery robot system from the current state data of multiple systems. Based on the current state data of the interventional surgery robot system and the current intraoperative image, the surgical instrument state data can be obtained; the automatic decision-making device can also display the current state data of multiple systems to users such as doctors for confirmation. In the case of user confirmation, combining the surgical instrument state data and the current state data of multiple systems, an automatic decision-making instruction matching the next stage after the current stage is generated.

[0062] In some scenarios, the automatic decision-making device can utilize image information to identify the current stage of an interventional surgery, intelligently generate an image acquisition strategy, and, with the doctor's permission, control key decisions such as the DSA ray switch, contrast agent injection volume and injection timing, MR sequence types and scanning time, and ultrasound acquisition time, and acquire images when necessary, saving surgical time and reducing unnecessary radiation and contrast agent injection volume.

[0063] In one embodiment, the method provided by this application further includes: comparing the current intraoperative image and the historical image; generating, based on the comparison result, the target acquisition parameters, target sequence protocol, and target acquisition pose of the image acquisition system; and generating an automatic control instruction for the image acquisition system based on the target acquisition parameters, target sequence protocol, and target acquisition pose, and feeding it back to the image acquisition system.

[0064] The automatic decision-making device can obtain historical images, which can include preoperative images and images taken during previous surgeries. After obtaining the historical images, the current intraoperative image and the historical images can be compared to evaluate the quality of the current intraoperative image; after the automatic decision-making device makes the comparison, a comparison result can be obtained, and based on this comparison result, the target acquisition parameters, target sequence protocol, and target acquisition pose of the image acquisition system can be generated, and an automatic control instruction for the image acquisition system can be generated based on the target acquisition parameters, target sequence protocol, and target acquisition pose and fed back to the image acquisition system. After receiving this automatic control instruction, the image acquisition system adjusts its own acquisition parameters, sequence protocol, and acquisition pose.

[0065] In one embodiment, determining the current stage of the interventional surgery based on the current intraoperative image fed back by the image acquisition system may specifically include: performing feature analysis on the current intraoperative image fed back by the image acquisition system to obtain a feature analysis result; and determining the current stage of the interventional surgery based on the feature analysis result.

[0066] The automatic decision-making device can perform feature analysis on the current intraoperative image through methods such as neural networks. Based on the feature analysis result, it predicts the current stage of the interventional surgery. Then, among the multiple pre-divided stages, based on the chronological order between the stages, the stage that is adjacent to the current stage in time and after the current stage is used as the next stage of the current stage, thereby generating an automatic decision-making instruction that matches the next stage after the current stage.

[0067] In one embodiment, the method provided by this application further includes: during the process of the corresponding system executing the automatic decision-making instruction, if manual decision-making data input by the user is received, then control the corresponding system to stop executing the automatic decision-making instruction, generate a manual decision-making instruction based on the manual decision-making data; and send the manual decision-making instruction to the corresponding system for execution.

[0068] This application provides a multi-system automatic control system for interventional surgery. The system includes: an automatic decision-making device, an image acquisition system, an interventional surgery robot system, and a drug injection system;

[0069] Exemplarily, referring to FIG. 3(a), the image acquisition system 10 may be an imaging system such as a C-arm, 20 is an interventional surgery robot system, 30 is a drug injection system, 40 is a display device, and 50 is a doctor-side display and operation device.

[0070] The image acquisition system can be used to: acquire the current intraoperative image and feedback it to the automatic decision-making device. The automatic decision-making device can be used to: determine the current stage of the interventional surgery based on the current intraoperative image. The image acquisition system, the interventional surgery robot system, and the drug injection system can be used to: feedback their respective system status data to the automatic decision-making device. The automatic decision-making device can also be used to: generate an automatic decision-making instruction that matches after the current stage based on the current status data of multiple systems, and send the automatic decision-making instruction to the corresponding system for execution.

[0071] During the interventional surgery process, after the image acquisition system acquires the current intraoperative image, it can feedback the current intraoperative image to the automatic decision-making device. The automatic decision-making device analyzes the current intraoperative image and can determine the current stage of the interventional surgery. The image acquisition system, the interventional surgery robot system, and the drug injection system can feedback their current system status data to the automatic decision-making device. Thus, the automatic decision-making device can obtain the current status data of multiple systems; the automatic decision-making device can generate an automatic decision-making instruction that matches after the current stage based on the current status data of multiple systems. The automatic decision-making instruction can be an instruction for at least one of the image acquisition system, the interventional surgery robot system, and the drug injection system. After generating the automatic decision-making instruction, the automatic decision-making device can send the automatic decision-making instruction to the corresponding system for execution.

[0072] Referring to FIG. 3(b), the current state data of multiple systems may include: the current intraoperative image of the image acquisition system (the current intraoperative image carries anatomical position, blood vessel morphology, the position, size and morphology of surgical instruments, image quality, and information on the stage of the interventional surgery), the injection data of the drug injection system (such as the injection speed, real-time pressure, maximum pressure limit, and dose of the drug), the data of the interventional surgery robot system (such as the force and motion information of surgical instruments), and the parameters of each system (such as pose, working parameters, etc.). Based on the system current state data fed back by each system, the automatic decision-making device can obtain the current state data of multiple systems, determine the current stage of the interventional surgery based on the current intraoperative image, and process the current state data of multiple systems based on the decision-making algorithm to obtain an automatic decision-making instruction that matches the stage after the current stage. For example: the operations that the interventional surgery robot needs to perform and parameters such as the advancement amount and rotation amount of controlling each surgical instrument, the working parameters of the drug injection system, whether the image acquisition system needs to acquire images, adjust the position and posture, and the specific parameters and sequences of image acquisition.

[0073] The control strategy can be completed through logical control. For example: a series of states and conditions are set based on image and sensor information, different states correspond to different control instructions, and when the conditions are met, the state transition is triggered to execute the corresponding control instruction; the control strategy can also be implemented through intelligent algorithms such as deep learning and reinforcement learning.

[0074] In one embodiment, the automatic decision-making device can perform the following processing according to the image information: obtain the real-time spatial position of the surgical instrument, determine whether the interventional instrument is within the safe range of the blood vessel, and obtain the state of the surgical instrument, such as the morphology and curvature of the interventional instrument.

[0075] Obtain from the sensor: the magnitude of the force, the curve change of the force, the force change pattern, the distribution of the force in space, the change trend of the force over a period of time, and the motion state of the interventional instrument;

[0076] Based on the content obtained from the image information and the content obtained from the sensor, it can be determined whether there is a risk in the operation of the surgical instrument and whether the control strategy needs to be changed.

[0077] Furthermore, the spatial position and state of the interventional surgical instrument can be estimated after receiving the control instruction. When there is a risk in the estimated position and state, the control strategy is dynamically adjusted, and new control instructions are generated and executed in real time.

[0078] According to the current state of the surgical equipment, the operation and fault state of the surgical equipment can be judged.

[0079] In one embodiment, there are overlaps of anatomical structures such as blood vessels in the real-time 2D images (i.e., two-dimensional images) during the operation. At this time, the 3D data (i.e., three-dimensional data) collected before or during the operation can be used to register the 2D and 3D data, calculate the optimal acquisition angle to reduce projection reduction and projection overlap, compare the calculated angle with the current pose of the image acquisition device, generate a control strategy, and adjust the image acquisition device to the optimal pose.

[0080] In one embodiment, when the interventional surgical robot delivers the interventional instrument, due to certain information loss in the real-time 2D image compared to the real 3D movement, as the interventional instrument keeps moving, the interventional instrument may be occluded and overlapped in the 2D image. At this time, there will be a mismatch between the position information of the interventional instrument obtained through image information and the movement information of the interventional instrument obtained through the sensor, resulting in a decrease in the output confidence of the control strategy. Therefore, the pose of the image acquisition device can be adjusted to collect multi-angle image information to compensate for the lost information.

[0081] In one embodiment, when the interventional surgery is in different stages or the surgical equipment is in different working states, there are different requirements for the image acquisition frequency and duration. Therefore, the control strategy of the image acquisition device can be dynamically adjusted according to the surgical stage or the state of the surgical equipment.

[0082] Furthermore, when it is judged that there may be risks in the current surgical instrument operation based on the image information and sensor information, the control strategy of the image acquisition device can be changed, appropriately increasing the image acquisition frequency and duration, increasing the input of information, and accurately determining the current risks.

[0083] In one embodiment, when drug injection is required, the interventional robot delivers the interventional instrument to the corresponding position, and the drug injection system performs the injection operation according to the preset working parameters. During this process, the working parameters of the injection device are dynamically adjusted and executed according to the real-time image information (such as the image signal intensity of drugs such as contrast agents and the position of the interventional instrument) and sensor information (such as the injection dose, speed, pressure, and the force condition of the interventional instrument). After completing the injection at one position, the interventional instrument is automatically pushed to the next injection position, and the working parameters of the injection device are dynamically adjusted and the injection operation is executed until all injection operations are completed.

[0084] In one embodiment, the currently acquired image data is compared with the historical image data or standard image parameters, and the image signal intensity, signal-to-noise ratio, and acquisition frame rate are analyzed to determine whether the image quality meets the requirements and whether the image acquisition parameters and protocols need to be adjusted.

[0085] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of the steps or stages in other steps or other steps.

[0086] Based on the same inventive concept, an embodiment of the present application further provides a multi-system automatic control device for an interventional operation for implementing the above-mentioned multi-system automatic control method for an interventional operation. The implementation solution provided by this device to solve the problem is similar to the implementation solution described in the above method. Therefore, the specific limitations in one or more embodiments of the multi-system automatic control device for an interventional operation provided below can refer to the limitations on the multi-system automatic control method for an interventional operation in the above text, and will not be repeated here.

[0087] In one embodiment, as Figure 4 shown, a multi-system automatic control device for an interventional operation is provided, including:

[0088] A surgical stage determination module 401, configured to determine the current stage of the interventional operation based on the current intraoperative image feedback by the image acquisition system;

[0089] A decision instruction generation module 402, configured to generate an automatic decision instruction that matches after the current stage based on the current state data of the multi-system; the multi-system includes the image acquisition system, the interventional operation robot system, and the drug injection system;

[0090] A decision instruction sending module 403, configured to send the automatic decision instruction to the corresponding system for execution.

[0091] In one embodiment, the decision instruction generation module 402 is further configured to: generate automatic decision data that matches after the current stage based on the current state data of the multi-system; in response to the user's confirmation operation on the current state data of the multi-system and the automatic decision data, generate an automatic decision instruction based on the automatic decision data.

[0092] In one embodiment, the decision instruction generation module 402 is further configured to: obtain the current state data of the interventional surgical robot system based on the current state data of multiple systems; obtain the surgical instrument state data based on the current state data of the interventional surgical robot system and the current intraoperative image; the surgical instrument is the surgical instrument clamped by the interventional surgical robot of the interventional surgical robot system; generate an automatic decision instruction matching the stage after the current stage based on the current state data of multiple systems and the surgical instrument state data.

[0093] In one embodiment, the decision instruction generation module 402 is further configured to: compare the current intraoperative image with the historical image; generate the target acquisition parameters, the target sequence protocol, and the target acquisition pose of the image acquisition system according to the comparison result; generate an automatic control instruction for the image acquisition system based on the target acquisition parameters, the target sequence protocol, and the target acquisition pose; the decision instruction sending module 403 is further configured to: feedback the automatic control instruction for the image acquisition system to the image acquisition system.

[0094] In one embodiment, the surgical stage determination module 401 is further configured to: perform feature analysis on the current intraoperative image fed back by the image acquisition system to obtain a feature analysis result; determine the current stage of the interventional surgery according to the feature analysis result.

[0095] In one embodiment, the device further includes a manual decision processing module, which is configured to: during the execution of the automatic decision instruction by the corresponding system, if manual decision data input by the user is received, control the corresponding system to stop executing the automatic decision instruction, and generate a manual decision instruction based on the manual decision data; the decision instruction sending module 403 is further configured to: send the manual decision instruction to the corresponding system for execution.

[0096] Each module in the above multi-system automatic control device for interventional surgery can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in or independent of the processor in the automatic decision device in the form of hardware, or stored in the memory in the automatic decision device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0097] In an exemplary embodiment, an automatic decision device is provided, and its internal structure diagram can be as Figure 5As shown in the figure. The automatic decision-making device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the automatic decision-making device is used to provide computing and control capabilities. The memory of the automatic decision-making device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the automatic decision-making device is used to store the data involved in the above method. The input / output interface of the automatic decision-making device is used to exchange information between the processor and external devices. The communication interface of the automatic decision-making device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a multi-system automatic control method for interventional surgery.

[0098] Those skilled in the art can understand that Figure 5 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the automatic decision-making device to which the solution of this application is applied. The specific automatic decision-making device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0099] In one embodiment, an automatic decision-making device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0100] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0101] In one embodiment, a computer program product is provided, on which a computer program is stored, and the computer program executes the steps in the above method embodiments by the processor.

[0102] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0103] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0104] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A multi-system automatic control method for interventional surgery, characterized in that, The method includes: Determining a current stage of an interventional surgery based on a current intraoperative image fed back by an image acquisition system; Generating an automatic decision instruction matching after the current stage based on current state data of multiple systems; the multiple systems include the image acquisition system, an interventional surgery robot system, and a drug injection system; Sending the automatic decision instruction to a corresponding system for execution.

2. The method according to claim 1, wherein, Generating an automatic decision instruction matching after the current stage based on current state data of multiple systems includes: Generating automatic decision data matching after the current stage based on current state data of multiple systems; In response to a user's confirmation operation on the current state data of the multiple systems and the automatic decision data, generating an automatic decision instruction based on the automatic decision data.

3. The method according to claim 1, characterized in that, Generating an automatic decision instruction matching after the current stage based on current state data of multiple systems includes: Obtaining current state data of the interventional surgery robot system based on current state data of multiple systems; Obtaining surgical instrument state data based on the current state data of the interventional surgery robot system and the current intraoperative image; the surgical instrument is a surgical instrument held by an interventional surgery robot of the interventional surgery robot system; Generating an automatic decision instruction matching after the current stage based on current state data of multiple systems and the surgical instrument state data.

4. The method according to claim 1, wherein The method further includes: Comparing the current intraoperative image and a historical image; Generating target acquisition parameters, a target sequence protocol, and a target acquisition pose of the image acquisition system according to the comparison result; Generating an automatic control instruction for the image acquisition system based on the target acquisition parameters, the target sequence protocol, and the target acquisition pose, and feeding it back to the image acquisition system.

5. The method according to claim 1, characterized in that, Determining a current stage of an interventional surgery based on a current intraoperative image fed back by an image acquisition system includes: Performing feature analysis on the current intraoperative image fed back by the image acquisition system to obtain a feature analysis result; Determining the current stage of the interventional surgery according to the feature analysis result.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: During the process of a corresponding system executing an automatic decision instruction, if manual decision data input by the user is received, controlling the corresponding system to stop executing the automatic decision instruction, and generating a manual decision instruction based on the manual decision data; Sending the manual decision instruction to a corresponding system for execution.

7. A multi-system automatic control system for interventional surgery, characterized in that, The system includes: an automatic decision device, an image acquisition system, an interventional surgery robot system, and a drug injection system; The image acquisition system is configured to acquire a current intraoperative image and feed it back to the automatic decision device; The automatic decision device is configured to determine a current stage of an interventional surgery based on the current intraoperative image; The image acquisition system, the interventional surgery robot system, and the drug injection system are configured to feed back their respective system state data to the automatic decision device; The automatic decision device is further configured to generate an automatic decision instruction matching after the current stage based on current state data of multiple systems; The automatic decision device is further configured to send the automatic decision instruction to a corresponding system for execution.

8. A multi-system automatic control device for interventional surgery, characterized in that, The device includes: A surgical stage determination module, configured to determine a current stage of an interventional surgery based on a current intraoperative image fed back by an image acquisition system; A decision instruction generation module, configured to generate an automatic decision instruction that matches after the current stage based on the current state data of multiple systems; the multiple systems include the image acquisition system, the interventional surgical robot system, and the drug injection system; A decision instruction sending module, configured to send the automatic decision instruction to the corresponding system for execution.

9. An automatic decision-making device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, the method described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the method described in any one of claims 1 to 6 is implemented.

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