Computer-assisted medical equipment, method, device and medium

Abstract

The invention relates to computer-aided medical equipment, a method, a device and a medium. The computer-aided medical equipment comprises a human-computer interaction interface, at least one memory and a processor, the human-computer interaction interface comprises a working mode definition area; the working mode definition area is used for receiving a working mode selection instruction; the at least one memory is used for storing a control instruction; the processor is used for executing the control instruction to realize the computer-aided medical equipment control method, and comprises the following steps: determining a working mode according to a working mode selection instruction; configuring a corresponding functional component according to the working mode; the functional assembly comprises an optical tracking unit, an image acquisition lower computer and an operation execution arm lower computer; and according to the workflow configuration nodes corresponding to the working modes, at each workflow configuration node, controlling at least one of the configured optical tracking unit, the image acquisition lower computer and the operation execution arm lower computer to execute a corresponding control instruction. By adopting the method, the problem of system redundancy can be solved.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to a computer-aided medical device, method, apparatus, and medium. Background Technology

[0002] With the rapid development of medical imaging and robotic arm technologies, surgical robots are increasingly being integrated with medical imaging data to assist doctors in completing surgical procedures.

[0003] Existing surgical robot-assisted systems and medical imaging equipment are two independent and separate systems, which occupy bedside resources when used in the operating room. Moreover, medical imaging systems, such as C-arm machines, need to be connected to the surgical robot-assisted system to transmit images captured during surgery to the surgical robot-assisted system for display.

[0004] However, both C-arm machines and surgical robot-assisted systems have displays on their surgical navigation trolleys, which creates a system redundancy issue for the display function. Summary of the Invention

[0005] Therefore, it is necessary to provide a computer-aided medical device, method, apparatus, and medium that can solve the problem of system redundancy in order to address the aforementioned technical issues.

[0006] In a first aspect, this application provides a computer-aided medical device, the device including a human-computer interaction interface, at least one memory, and a processor;

[0007] The human-computer interaction interface includes a working mode definition area; the working mode definition area is used to receive working mode selection instructions.

[0008] At least one memory for storing control instructions;

[0009] A processor is used to execute control instructions to implement a computer-aided medical device control method, the method including:

[0010] The working mode is determined based on the working mode selection instruction;

[0011] Configure the corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine.

[0012] Based on the workflow configuration node corresponding to the working mode, at least one of the configured optical tracking unit, image acquisition lower unit, and surgical execution arm lower unit is controlled to execute corresponding control commands at each workflow configuration node.

[0013] In one embodiment, the working mode includes an intraoperative navigation mode, and the workflow configuration nodes corresponding to the intraoperative navigation mode include a surgical planning sub-node, an image registration sub-node, and a real-time navigation sub-node.

[0014] The processor is also used to perform the following steps:

[0015] The system runs to the surgical planning sub-node to receive preoperative images, which are used to plan the target position of the lower-level surgical execution arm.

[0016] The system runs to the image registration sub-node to receive intraoperative images sent by the image acquisition lower-level machine, and uses the intraoperative images to achieve registration between the preoperative images and the surgical execution arm lower-level machine;

[0017] The system runs to the real-time navigation sub-node, which controls the lower-level surgical arm to move to the target location.

[0018] In one embodiment, intraoperative imaging is used to register preoperative images with the surgical arm lower unit, including...

[0019] A three-dimensional model is constructed based on preoperative images, and the three-dimensional model is registered with intraoperative images to obtain the first registration matrix;

[0020] The second registration matrix is ​​obtained by registering the intraoperative images with the lower surgical arm.

[0021] The preoperative images are registered with the lower-level surgical arm based on the first and second registration matrices.

[0022] In one embodiment, the intraoperative images include two-dimensional images of a first position and two-dimensional images of a second position.

[0023] A 3D model is constructed based on preoperative images. The 3D model is then registered with the intraoperative images to obtain the first registration matrix, which includes:

[0024] A three-dimensional model is constructed based on two-dimensional images of the first and second body positions, and physiological feature points of the three-dimensional model are extracted.

[0025] Based on physiological feature points, registration is performed on intraoperative images to obtain a three-dimensional model. The registration matrix is ​​then obtained by registering the model with the intraoperative images.

[0026] In one embodiment, the second registration matrix obtained by registering intraoperative images with the surgical arm lower unit includes:

[0027] The system acquires a first conversion relationship between intraoperative images and the imaging calibration target, a second conversion relationship between the imaging calibration target and the surgical execution arm, and a third conversion relationship between the surgical execution arm and the robotic arm base; the second conversion relationship is determined based on the imaging time of the intraoperative images.

[0028] Based on the first, second, and third transformation relationships, the intraoperative images and the lower-level surgical arm are registered to obtain the second registration matrix.

[0029] In one embodiment, the registration of preoperative images with the surgical arm lower unit is achieved according to a first registration matrix and a second registration matrix, including:

[0030] The sum of the first and second registration matrices is used as the fourth transformation relationship between the preoperative image and the surgical arm.

[0031] Based on the fourth conversion relationship, the preoperative images are registered with the lower-level machine of the surgical execution arm.

[0032] In one embodiment, the operating mode includes an image acquisition mode, and the workflow configuration node corresponding to the image acquisition mode includes a parameter setting node and an image scanning node; the processor is also used to perform the following steps:

[0033] Run to the parameter setting node, and set the acquisition parameters during the image acquisition process based on the information input by the user in the human-computer interaction interface;

[0034] When the process reaches the image scanning node, it controls the lower-level image acquisition machine to scan the target object based on the set acquisition parameters.

[0035] Secondly, this application provides a computer-aided medical device control method, the method comprising:

[0036] Determine the working mode based on user input;

[0037] Configure the corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine.

[0038] Based on the workflow configuration node corresponding to the working mode, at least one of the configured optical tracking unit, image acquisition lower unit, and surgical execution arm lower unit is controlled to execute corresponding control commands at each workflow configuration node.

[0039] Thirdly, this application also provides a computer-aided medical device control device, comprising:

[0040] The determination module is used to determine the working mode based on the working mode selection instruction; the working modes include image acquisition mode and intraoperative navigation mode.

[0041] The acquisition module is used to acquire the functional components corresponding to the working mode; the functional components include the optical tracking unit, the image acquisition lower-level machine, and the surgical execution arm lower-level machine.

[0042] The control module is used to determine the workflow configuration node of the working mode according to the workflow configuration instructions, and to control the functional components to execute the corresponding commands according to the workflow configuration node.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the content of any embodiment of the computer-aided medical device control method in the second aspect described above.

[0044] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the content of any embodiment of the computer-aided medical device control method in the second aspect described above.

[0045] The aforementioned computer-assisted medical device, method, apparatus, and medium include a human-computer interface, at least one memory, and a processor. The human-computer interface includes a working mode definition area for receiving working mode selection instructions. The working mode definition area is used to receive working mode selection instructions. At least one memory is used to store control instructions. The processor is used to execute the control instructions to implement a computer-assisted medical device control method. This method includes: determining a working mode based on the working mode selection instruction; configuring corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine; and, according to the workflow configuration node corresponding to the working mode, controlling at least one of the configured optical tracking unit, image acquisition lower-level machine, and surgical execution arm lower-level machine to execute corresponding control instructions at each workflow configuration node. This computer-assisted medical device integrates all working modes during the surgical process. Working mode selection can be achieved through a human-computer interface, and the corresponding functional components can be determined based on the selected working mode. The corresponding functional components are then controlled to operate according to the workflow configuration node of the working mode. In other words, the intraoperative environment includes computer-assisted medical equipment and a surgical arm, with the computer-assisted medical equipment containing only a human-computer interface. This solves the problem of redundant display functions caused by two monitors. The optical tracking unit is integrated into the image acquisition equipment, and the host computer of the surgical arm is integrated into the computer-assisted medical equipment, which greatly reduces the space occupied in the operating room, making the operating room more spacious. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of a surgical procedure in one embodiment;

[0048] Figure 2 This is a schematic diagram of the system architecture of the separated system in one embodiment;

[0049] Figure 3 This is a schematic diagram of the human-machine interface of a C-arm machine in one embodiment;

[0050] Figure 4 This is a schematic diagram of the human-computer interaction interface of a surgical cart in one embodiment.

[0051] Figure 5 This is a schematic diagram of a computer-aided medical device in one embodiment;

[0052] Figure 6 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0053] Figure 7 This is a schematic diagram of a computer-aided medical device in one embodiment;

[0054] Figure 8 This is a schematic diagram of the system architecture of a computer-aided medical device in one embodiment;

[0055] Figure 9 This is a schematic diagram of the system architecture of a computer-aided medical device in one embodiment;

[0056] Figure 10 This is a schematic diagram of the architecture of a computer-aided medical device in one embodiment;

[0057] Figure 11 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0058] Figure 12 This is a schematic diagram of the interface of the surgical planning sub-node in one embodiment;

[0059] Figure 13 This is a schematic diagram of the first interface of an image registration sub-node in one embodiment;

[0060] Figure 14 This is a schematic diagram of the second interface of an image registration sub-node in one embodiment;

[0061] Figure 15 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0062] Figure 16 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0063] Figure 17 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0064] Figure 18 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0065] Figure 19 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0066] Figure 20 This is a flowchart illustrating a computer-aided medical device control method in one embodiment;

[0067] Figure 21 This is a structural block diagram of a computer-aided medical device control device in one embodiment;

[0068] Figure 22 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0070] Before introducing the technical solution of this application, let me briefly introduce the background technology of this application.

[0071] Figure 1 This is a schematic diagram of a surgical procedure. In the current surgical process, the operating room includes a surgical robot-assisted system, medical imaging equipment, a hospital bed, the patient, and the surgeon. The surgical robot-assisted system includes an Omnidirectional Tracking System (OTS) trolley and a surgical trolley. The OTS trolley tracks the reference points between the end effector of the surgical trolley's robotic arm and the patient's position, while the surgical trolley is used to perform surgical procedures on the patient. The medical imaging equipment can be a C-arm scanner, used to acquire preoperative and intraoperative images of the patient.

[0072] The operating room environment is complex, and space is limited. The aforementioned surgical robot-assisted system and medical imaging equipment are two independent systems, which would occupy bedside resources if used in the operating room. Furthermore, the medical imaging system, such as a C-arm machine, needs to connect with the surgical robot-assisted system to transmit intraoperative images for display.

[0073] Figure 2The diagram illustrates the system architecture of the separation system. As shown, the C-arm imaging system includes a monitor and workstation, the surgical cart includes a workstation and an industrial control computer (ICC), and the navigation cart includes a monitor and an OTS (Optical Time System). During surgery, the C-arm imaging system's workstation acquires intraoperative images, displays these images on the C-arm's monitor, and sends them to the workstation on the surgical cart. The surgical cart's workstation can control the navigation cart's monitor to display the tracking robotic arm's end effector and the user's operating position reference points. It can also send control commands to the ICC to control the robotic arm on the surgical cart to perform surgical operations and control the navigation cart for navigation tracking. The workstation in the surgical cart is equipped with navigation control software, and the surgical cart can connect to the monitor on the navigation cart via DP / HDMI, etc. The ICC in the surgical cart connects to the binocular camera in the OTS via Ethernet, and the C-arm imaging system connects to the workstation in the surgical cart via Ethernet to transmit images captured by the C-arm imaging device to the workstation on the surgical cart during surgery.

[0074] Figure 3 This is a schematic diagram of the human-machine interface of the C-arm machine. The operating system can control the C-arm to enter the workflow configuration nodes (C-App1, C-App2, C-App3) through basic applications. Figure 4 This is a schematic diagram of the human-machine interface for the surgical cart. The operating system can control the surgical cart to enter the workflow configuration nodes (R-App1, R-App2, R-App3) through basic applications. These two control software architectures are completely separate and different.

[0075] However, both C-arm machines and surgical robot-assisted systems have displays on their surgical navigation trolleys, which creates a system redundancy issue for the display function.

[0076] To address the aforementioned issues, this application provides a computer-aided medical device, method, apparatus, and medium that integrates the OTS trolley and C-arm machine in a surgical robot-assisted system into a single unit. This eliminates the need for the existing OTS trolley in the operating room, freeing up operating room space, saving hardware costs, and thus resolving the issue of system redundancy in the display function.

[0077] The technical solutions of this application and how they solve the aforementioned technical problems will be described in detail below through embodiments and in conjunction with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that when describing the feature classification method provided in the embodiments of this application below, the executing entity is a processor in a computer-assisted medical device. The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments.

[0078] In one exemplary embodiment, such as Figure 5 As shown, a computer-assisted medical device 10 is provided, which includes: a human-computer interaction interface 101, at least one memory 102 and a processor 103;

[0079] The human-computer interaction interface 101 includes a working mode definition area; the working mode definition area is used to receive working mode selection instructions.

[0080] At least one memory 102 is used to store control instructions;

[0081] Processor 103 is used to execute control instructions to implement the control method of computer-aided medical device 10, such as... Figure 6 As shown, the method includes:

[0082] S101, determine the working mode according to the working mode selection instruction;

[0083] S102, configured with corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower unit, and a surgical execution arm lower unit;

[0084] S103, according to the workflow configuration node corresponding to the working mode, controls at least one of the configured optical tracking unit, image acquisition lower unit and surgical execution arm lower unit to execute corresponding control commands at each workflow configuration node.

[0085] The computer-assisted medical device 10 refers to an integrated device that combines an optical tracking unit and an image acquisition device. The human-computer interface 101 in this computer-assisted medical device 10 can reuse the display on the image acquisition device. In this case, the optical tracking unit is installed on the image acquisition device, resulting in the computer-assisted medical device 10. Alternatively, the human-computer interface 101 can also reuse the display on the optical tracking unit. In this case, the image acquisition device is installed on the optical tracking unit. Alternatively, the human-computer interface 101 can also be a display added separately to the integrated device formed by the optical tracking unit and the image acquisition device.

[0086] Taking an OTS cart as the optical tracking unit and a C-arm camera as the image acquisition device as an example, Figure 7 This is a schematic diagram of a computer-aided medical device, showing the OTS cart removed and the binocular camera from the OTS mounted on a C-arm machine. The C-arm machine provides an interface that allows for flexible and quick-release installation and removal of the binocular camera and linkage from the OTS. This allows the C-arm machine to be used independently even with the binocular camera and linkage removed from the OTS. With the binocular camera and linkage from the OTS mounted on the C-arm machine, both image acquisition and positioning / navigation needs can be met simultaneously. It should be noted that the binocular camera linkage can be a multi-degree-of-freedom linkage, allowing for flexible adjustment of the binocular camera's angle and length while maintaining rigidity. This enables the binocular camera to simultaneously track the C-arm calibration target array, the user array, and the surgical cart array.

[0087] Based on this, Figure 8 This is a system architecture diagram of a computer-assisted medical device. The computer-assisted medical device 10 can reuse the display and workstation of a C-arm machine. Thus, the computer-assisted medical device includes a workstation (host computer), a display, and a binocular camera in the OTS (Operating System). The C-arm machine's workstation communicates with the industrial control computer of the surgical arm via a network port. The workstation in the computer-assisted medical device can not only control the C-arm machine for image acquisition, but also send control commands to the industrial control computer (slave computer) of the surgical arm. These control commands can control the surgical arm to perform surgical operations and can also control the binocular camera in the computer-assisted medical device 10 for positioning and tracking. Figure 9This is a schematic diagram of the human-computer interface (HCI) of a computer-assisted medical device. Users can select operating modes on the HCI, including image acquisition mode and intraoperative navigation mode. After selecting image acquisition mode, the operating system can control the C-arm via basic applications to enter workflow configuration nodes (C-App1, C-App2, C-App3). After selecting intraoperative navigation mode, the operating system can control the surgical cart via basic applications to enter workflow configuration nodes (R-App1, R-App2, R-App3). These two control software architectures are integrated and unified.

[0088] Figure 10 This is a schematic diagram of the architecture of a computer-aided medical device. The integrated software host computer refers to the host computer of the computer-aided medical device. The user selects the mode on this host computer. When the selected mode is image acquisition mode, control commands are sent to the image acquisition slave computer to control it to acquire images. When the selected mode is intraoperative navigation mode, control commands are sent to the lower-level computer of the surgical arm to control the lower-level computer of the surgical arm and the optical tracking unit to execute control commands. Specifically, the control commands can control the lower-level computer of the surgical arm to perform surgical operations on the target surgical site, such as suturing, puncture, etc. Furthermore, the control commands can also control the binocular camera on the optical tracking unit to track the surgical operation process of the surgical arm.

[0089] The human-computer interface 101 can display the entire working mode definition area or only a portion of it. The working mode definition area is used to define the working modes of the computer-assisted medical device. For example, the working mode definition area may include an image acquisition mode selection area and an intraoperative navigation mode selection area. Users can trigger working mode selection commands in the working mode definition area as needed, either by clicking the mouse or by touching the display screen. For example, clicking the image acquisition mode selection area triggers a working mode selection command corresponding to the image acquisition mode; clicking the intraoperative navigation mode selection area triggers a working mode selection command corresponding to the intraoperative navigation mode.

[0090] Alternatively, the working mode area may also include a switching area and a confirmation area. The default working mode is image acquisition mode. If the user requires image acquisition mode, clicking the confirmation area will trigger image acquisition mode. If the user requires intraoperative navigation mode, clicking the switching area will switch from image acquisition mode to intraoperative navigation mode, and clicking the confirmation area will trigger intraoperative navigation mode. This application embodiment does not limit the definition method of the working mode definition area on the human-computer interaction interface.

[0091] The memory in the computer-assisted medical device 10 can be used to store control commands during the surgical procedure after the mode selection is completed. For example, these control commands can be used to control the optical tracking unit for tracking and positioning, to control the image acquisition device for image acquisition, or to control the surgical arm for surgical operations.

[0092] During actual surgery, the user can trigger a working mode selection command in the working mode definition area of ​​the human-computer interaction interface 102. The processor 103 of the computer-assisted medical device determines the required working mode based on the user's command. For example, if the user requires an image acquisition mode, in this mode, the lower-level image acquisition device needs to be controlled to acquire the user's preoperative images and plan the surgical path based on those images. If the user requires an intraoperative navigation mode, in this mode, the lower-level image acquisition device, the optical tracking unit, and the lower-level surgical execution arm device need to be controlled simultaneously. In other words, different working modes correspond to different devices.

[0093] Based on this, after determining the working mode, the processor 103 can select the functional component corresponding to that working mode from all functional components. For example, when the working mode is image acquisition mode, the functional component corresponding to this working mode is the image acquisition lower unit; when the working mode is intraoperative navigation mode, the functional components corresponding to this working mode are the image acquisition lower unit, the optical tracking unit, and the surgical execution arm lower unit.

[0094] Different work modes correspond to different workflow configuration nodes. The image acquisition mode corresponds to the preoperative workflow configuration node, while the intraoperative navigation mode corresponds to the intraoperative workflow configuration node. The preoperative workflow configuration node can include a user management workflow configuration sub-node (C-App1), an image scanning workflow configuration sub-node (C-App2), and an image browsing workflow configuration sub-node (C-App3). The user management workflow configuration sub-node includes basic information about multiple users, such as name, age, and surgical site. The image scanning workflow configuration sub-node can include user examination, scan parameter settings, and interactions during the scanning process. The image browsing workflow configuration sub-node is used to display preoperative images or preoperative images with preoperative surgical path planning to the user. The intraoperative workflow configuration node includes a surgical planning sub-node (R-App1), an image registration sub-node (R-App2), and a real-time navigation sub-node (R-App3).

[0095] After determining the workflow configuration node based on the working mode, the processor can control the human-machine interface to display the interface corresponding to the workflow configuration node, and control the functional components corresponding to the working mode to execute control commands.

[0096] The aforementioned computer-assisted medical device includes a human-computer interface, at least one memory, and a processor. The human-computer interface includes a working mode definition area for receiving working mode selection instructions. At least one memory stores control instructions. The processor executes the control instructions to implement a computer-assisted medical device control method. This method includes: determining a working mode based on the working mode selection instruction; configuring corresponding functional components based on the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine; and controlling at least one of the configured optical tracking unit, image acquisition lower-level machine, and surgical execution arm lower-level machine to execute corresponding control instructions at each workflow configuration node corresponding to the working mode. This computer-assisted medical device integrates all working modes during surgery. Working mode selection can be achieved through a single human-computer interface, and the corresponding functional components can be determined based on the selected working mode. The corresponding functional components are then controlled to operate according to the workflow configuration nodes of the working mode. In other words, the intraoperative environment includes the computer-assisted medical device and the surgical execution arm, and the computer-assisted medical device only includes a single human-computer interface, thus solving the problem of display redundancy caused by two monitors. The optical tracking unit is integrated into the image acquisition device, and the host computer of the surgical execution arm is integrated into the computer-aided medical device, which can greatly reduce the space occupied in the operating room and make the operating room more spacious.

[0097] The above embodiments describe the control flow after different working modes are triggered. Next, we will introduce the intraoperative navigation mode and image acquisition mode through different real-time examples.

[0098] In one scenario, a detailed explanation will be provided using the user-triggered intraoperative navigation mode as an example. In one embodiment, such as... Figure 11 As shown, if the working mode includes intraoperative navigation mode, the workflow configuration nodes corresponding to the intraoperative navigation mode include surgical planning sub-node, image registration sub-node and real-time navigation sub-node.

[0099] Processor 103 is also used to perform the following steps:

[0100] S201, run to the surgical planning sub-node to receive preoperative images, which are used to plan the target position of the lower-level surgical execution arm;

[0101] S202, run to the image registration sub-node to receive intraoperative images sent by the image acquisition lower-level machine, and realize the registration of preoperative images and surgical execution arm lower-level machine through intraoperative images;

[0102] S203, the real-time navigation sub-node controls the lower-level surgical arm to move to the target position.

[0103] In this embodiment, the intraoperative navigation mode requires the completion of three sub-nodes: surgical planning, image registration, and real-time navigation. These three sub-nodes are completed sequentially. That is, the image registration sub-node can only be performed after the surgical planning sub-node is completed, and the real-time navigation sub-node can only be performed after the image registration sub-node is completed.

[0104] The following explanations will follow the order of the workflow configuration nodes corresponding to the intraoperative navigation mode.

[0105] First, let's introduce the surgical planning sub-nodes. Figure 12 The interface diagram for the surgical planning sub-nodes is shown below. Figure 12 The image shown is a preoperative image with surgical path planning already completed. Of course, preoperative images can also be shown separately.

[0106] Then, there can also be a system preparation sub-node between the surgical planning sub-node and the image registration sub-node. At this node, the robotic arm can be registered and the field of view of the binocular camera on the optical tracking unit can be adjusted, that is, preoperative preparation work can be carried out.

[0107] Next, we will introduce the image registration sub-node. Figure 13 The first interface diagram for registering the image sub-node shows the received preoperative images, including the user's anteroposterior and lateral images. The user can select at least one image for image registration. Figure 14 This is a schematic diagram of the second interface for registering sub-nodes for images. The second interface diagram is a schematic diagram after registration. This process is the surgical operation process. During this process, the image acquisition device can acquire the user's intraoperative images and achieve registration between the preoperative images and the lower-level machine of the surgical execution arm through the intraoperative images.

[0108] Finally, with the preoperative images and the surgical arm lower-level machine registered, this node can send control commands to the surgical arm lower-level machine, and these commands carry the target position of the surgical arm lower-level machine. After receiving the control command, the surgical arm lower-level machine moves from its current position to the target position.

[0109] The aforementioned operating modes include an intraoperative navigation mode. The workflow configuration nodes for this mode include a surgical planning sub-node, an image registration sub-node, and a real-time navigation sub-node. The processor is also used to execute the following steps: running to the surgical planning sub-node to receive preoperative images, which are used to plan the target position of the surgical arm lower-level machine; running to the image registration sub-node to receive intraoperative images sent by the image acquisition lower-level machine, and using the intraoperative images to register the preoperative images with the surgical arm lower-level machine; and running to the real-time navigation sub-node to control the surgical arm lower-level machine to move to the target position. In intraoperative navigation mode, the process of planning the received preoperative images, registering the preoperative images with the surgical arm lower-level machine, and controlling the surgical arm lower-level machine through multiple sub-nodes sequentially, through the interrelationship and cooperation between multiple sub-nodes, results in higher intraoperative control precision and more accurate control results.

[0110] The most crucial step in intraoperative control is registering preoperative images with the surgical arm's lower-level imaging system using intraoperative imaging. Therefore, in one embodiment, such as... Figure 15 As shown, the above steps will be explained in detail below.

[0111] S301, a three-dimensional model is constructed based on preoperative images, and the three-dimensional model is registered with intraoperative images to obtain the first registration matrix.

[0112] If the preoperative images are images of the user's target area, the 3D model refers to the 3D model corresponding to the user's target area. The preoperative images here can be directly 3D images acquired by the image acquisition device, or multiple 2D images in different positions. For example, multiple 2D images can include anteroposterior 2D images and lateral 2D images.

[0113] In this embodiment, after acquiring the preoperative image, the processor can extract feature information from the preoperative image using a feature extraction model and contour information from the preoperative image using a contour extraction model. Based on the feature information and contour information, an initial 3D model is created. This initial 3D model is then refined and modified to obtain the 3D model corresponding to the preoperative image.

[0114] Furthermore, after acquiring the intraoperative images, the processor can obtain the pose of the 3D model and the pose of the intraoperative images, and determine the transformation relationship between the 3D model and the intraoperative images based on the difference between the pose of the 3D model and the pose of the intraoperative images, and determine the transformation relationship as the first registration matrix.

[0115] S302 is the second registration matrix obtained by registering the intraoperative images with the lower-level surgical arm.

[0116] In this embodiment of the application, the processor can analyze the lower-level surgical arm to determine the pose of the lower-level surgical arm, and based on the difference between the pose of the lower-level surgical arm and the pose of the intraoperative image, determine the conversion relationship between the intraoperative image and the lower-level surgical arm, and determine the conversion relationship as the second registration matrix.

[0117] S303, the preoperative image is registered with the lower-level machine of the surgical execution arm according to the first registration matrix and the second registration matrix.

[0118] In this embodiment, after obtaining the first registration matrix and the second registration matrix, the processor can fuse the first registration matrix and the second registration matrix to obtain the conversion relationship between the preoperative image and the lower-level surgical arm. Based on this conversion relationship, the preoperative image and the lower-level surgical arm are registered.

[0119] The processor of the aforementioned computer-aided medical device executes the following steps: constructing a 3D model based on preoperative images; registering the 3D model with intraoperative images to obtain a first registration matrix; registering the intraoperative images with the surgical arm lower-level machine to obtain a second registration matrix; and registering the preoperative images with the surgical arm lower-level machine based on the first and second registration matrices. This process, through the registration relationships between preoperative and intraoperative images, and between intraoperative images and the surgical arm lower-level machine, can accurately deduce the registration relationship between the preoperative images and the surgical arm lower-level machine, thus enabling accurate registration of the preoperative images with the surgical arm lower-level machine based on this registration relationship.

[0120] Assuming the intraoperative images include two-dimensional images of a first position and two-dimensional images of a second position, in one embodiment, such as Figure 16 As shown, the specific steps for constructing a 3D model based on preoperative images and registering the 3D model with intraoperative images to obtain the first registration matrix may include the following:

[0121] S401, construct a three-dimensional model based on two-dimensional images of the first body position and two-dimensional images of the second body position, and extract physiological feature points from the three-dimensional model.

[0122] The first two-dimensional image can be a anteroposterior two-dimensional image acquired by an image acquisition device, while the second two-dimensional image is a lateral two-dimensional image acquired by an image acquisition device. See also Figure 13 The left side shows a lateral 2D image, and the right side shows a frontal 2D image.

[0123] Since the two-dimensional images of the two body positions only contain partial information about the user's target area, it is impossible to extract all physiological feature points when extracting physiological feature points from the two-dimensional images of the two body positions. Therefore, after receiving the two-dimensional images of the first and second body positions sent by the image acquisition lower-level machine, the processor can fuse the two two-dimensional images of the first and second body positions and extract the features and contours of the two two-dimensional images of the two body positions. Based on the features and contours, a three-dimensional model corresponding to the user's target area is generated. This three-dimensional model can include more complete information about the user's target area. Therefore, the user's physiological feature points can be extracted from this three-dimensional model. Among them, physiological feature points can be reference points for the user's surgical site.

[0124] S402, and based on physiological feature points, registration is performed on intraoperative images to obtain a three-dimensional model. The registration matrix is ​​obtained by registering the model with the intraoperative images.

[0125] In this embodiment, the processor can analyze intraoperative images and extract physiological feature points from them. Based on the pose difference between the physiological feature points on the intraoperative images and the corresponding physiological feature points on the 3D model, the transformation relationship between the intraoperative images and the 3D model is obtained. This transformation relationship is then used to register the 3D model with the intraoperative images to obtain a first registration matrix.

[0126] The processor of the aforementioned computer-aided medical device performs the following steps: Based on two-dimensional images of the first and second patient positions, physiological feature points are extracted from the preoperative images; and based on these physiological feature points, registration is performed on the two-dimensional images of the first and second patient positions respectively to obtain a three-dimensional model. This model is then registered with the intraoperative images to obtain a first registration matrix. This process registers the two-dimensional images with the three-dimensional model using physiological feature points in the images, thus significantly reducing the workload of registration and improving registration efficiency.

[0127] The following embodiment details the process of registering the intraoperative images with the lower-level surgical arm to obtain the second registration matrix, as described above. Figure 17 As shown, the process may include:

[0128] S501, acquire the first conversion relationship between the intraoperative image and the imaging calibration target, the second conversion relationship between the imaging calibration target and the surgical execution arm, and the third conversion relationship between the surgical execution arm and the robotic arm base; the second conversion relationship is determined based on the imaging time of the intraoperative image.

[0129] The surgical execution arm refers to the robotic arm that performs surgical operations, which is mounted on a robotic arm base.

[0130] In this embodiment, the imaging calibration target refers to a target point with imaging points and OTS array spheres. During intraoperative image acquisition, the imaging calibration target can be mounted on the image acquisition device. Specifically, after image acquisition is completed, the imaging points on the imaging calibration target can be imaged and developed on the intraoperative image to obtain the first conversion relationship between the intraoperative image and the imaging calibration target.

[0131] Simultaneously, during image acquisition, the imaging time can be tracked and positioned using an optical tracking unit, and a second conversion relationship between the imaging calibration target and the surgical arm can be determined based on the imaging time. After the robotic arm is registered, a third conversion relationship between the surgical arm and the robotic arm base can be obtained based on the registration results.

[0132] S502, based on the first transformation relationship, the second transformation relationship and the third transformation relationship, the intraoperative images and the lower-level machine of the surgical execution arm are registered to obtain the second registration matrix.

[0133] In this embodiment, after obtaining three transformation relationships, the processor can fuse the first, second, and third transformation relationships. The fused transformation relationship represents the relationship between the intraoperative image and the robotic arm base, and the fused transformation relationship is determined as the second registration matrix. For example, the fusion process can be to add the first, second, and third transformation relationships to obtain the fused transformation relationship.

[0134] The processor of the aforementioned computer-aided medical device executes the following steps: acquiring a first conversion relationship between intraoperative images and the imaging calibration target, a second conversion relationship between the imaging calibration target and the surgical execution arm, and a third conversion relationship between the surgical execution arm and the robotic arm base; the second conversion relationship is determined based on the imaging time of the intraoperative images; based on the first, second, and third conversion relationships, the intraoperative images and the lower-level surgical execution arm are registered to obtain a second registration matrix. This process, by analyzing the conversion relationships between intraoperative images and the imaging calibration target, the imaging calibration target and the surgical execution arm, and the surgical execution arm and the robotic arm base, can obtain the conversion relationships between each pair of devices, and by fusing these conversion relationships, the second registration matrix obtained has higher accuracy.

[0135] In one embodiment, such as Figure 18 As shown below, one implementation process for registering preoperative images with the surgical arm lower unit based on the first and second registration matrices will be explained.

[0136] S601, the sum of the first registration matrix and the second registration matrix is ​​used as the fourth transformation relationship between the preoperative image and the surgical arm.

[0137] In this embodiment of the application, the processor can add the first registration matrix and the second registration matrix. The result of the addition represents the conversion relationship between the preoperative image and the surgical execution arm. Therefore, the result of the addition can be used as the fourth conversion relationship between the preoperative image and the surgical execution arm.

[0138] S602, based on the fourth conversion relationship, register the preoperative images with the lower-level machine of the surgical execution arm.

[0139] In this embodiment, the fourth transformation relationship can be a transformation matrix, which refers to the transformation matrix between the preoperative image and the lower-level surgical arm. Based on this fourth transformation relationship, the processor can adjust the pose of the lower-level surgical arm to match the pose of the preoperative image, thereby completing the registration process.

[0140] The processor of the aforementioned computer-aided medical device performs the following steps: The sum of the first and second registration matrices is used as the fourth transformation relationship between the preoperative image and the surgical execution arm; based on this fourth transformation relationship, the preoperative image is registered with the lower-level machine of the surgical execution arm. This process, by adding the two registration matrices of the preoperative image and the intraoperative image, and the intraoperative image and the surgical execution arm, obtains the transformation relationship between the preoperative image and the surgical execution arm. Based on this transformation relationship, the preoperative image and the lower-level machine of the surgical execution arm can be registered more accurately.

[0141] In one scenario, we will take the user-triggered image acquisition mode as an example for detailed explanation. In one embodiment, such as... Figure 19 As shown, if the working mode includes an image acquisition mode, the workflow configuration node corresponding to the image acquisition mode includes a parameter setting node and an image scanning node.

[0142] Processor 103 is also used to perform the following steps:

[0143] S701 runs to the parameter setting node and sets the acquisition parameters during the image acquisition process based on the information input by the user in the human-computer interaction interface.

[0144] In this embodiment, when the process reaches the parameter setting node, a user information template is displayed on the human-computer interaction interface. This template includes basic user information, and may also include basic user information and image acquisition parameters. For example, the basic user information may include the user's age, gender, name, and surgical site, while the image acquisition parameters may include image scanning time, scanning interval, and scanning site. A blank table is provided after each item in the template. The user can fill in the corresponding information in the blank table after each item. After all information is filled in, the parameter setting node is completed. After the user clicks "complete," the process transitions from the parameter setting node to the image scanning node.

[0145] S702 runs to the image scanning node and, based on the set acquisition parameters, controls the lower-level image acquisition machine to scan the target object.

[0146] The acquisition parameters can be set by the user in the parameter setting node, or they can be the default acquisition parameters of the image acquisition device.

[0147] In this embodiment, when in the image scanning node, the processor can control the image acquisition device to scan the target object according to the acquisition parameters set in the parameter setting node. After scanning, a scanned image of the target object is obtained. It should be emphasized that this scanned image can be a preoperative image or an intraoperative image.

[0148] The processor of the aforementioned computer-aided medical device executes the following steps: It runs to the parameter setting node, where it sets the acquisition parameters during the image acquisition process based on the information input by the user through the human-computer interaction interface; it then runs to the image scanning node, where it controls the lower-level image acquisition device to scan the target object based on the set acquisition parameters. In image acquisition mode, image scanning can be performed more specifically using the information and acquisition parameters set by the user, resulting in more accurate scanned images.

[0149] In one embodiment, a computer-aided medical device control method is provided. The method is applied to a processor in the computer-aided medical device and includes the following steps: determining a working mode based on user input; configuring corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine; and, according to the workflow configuration node corresponding to the working mode, controlling at least one of the configured optical tracking unit, image acquisition lower-level machine, and surgical execution arm lower-level machine to execute corresponding control instructions at each workflow configuration node.

[0150] This method has already been mentioned in the section on computer-assisted medical devices. For specific limitations of this method, please refer to the limitations of computer-assisted medical devices mentioned above, which will not be repeated here.

[0151] In one embodiment, such as Figure 20 As shown, the details of computer-aided medical device control methods are introduced.

[0152] S801, determines the working mode according to the working mode selection instruction;

[0153] S802, if the working mode includes intraoperative navigation mode, run to the surgical planning sub-node to receive preoperative images, and the preoperative images are used to plan the target position of the lower-level surgical execution arm.

[0154] S803 runs to the image registration sub-node to receive intraoperative images sent by the image acquisition lower-level machine, constructs a three-dimensional model based on the two-dimensional images of the first position and the two-dimensional images of the second position, and extracts the physiological feature points of the three-dimensional model.

[0155] S804, based on physiological feature points, is registered on intraoperative images to obtain a three-dimensional model. The three-dimensional model is then registered with the intraoperative images to obtain the first registration matrix.

[0156] S805, acquire the first conversion relationship between intraoperative images and imaging calibration target, the second conversion relationship between imaging calibration target and surgical execution arm, and the third conversion relationship between surgical execution arm and robotic arm base;

[0157] S806, based on the first transformation relationship, the second transformation relationship and the third transformation relationship, registers the intraoperative images with the lower-level machine of the surgical execution arm to obtain the second registration matrix;

[0158] S807, the sum of the first registration matrix and the second registration matrix is ​​used as the fourth transformation relationship between the preoperative image and the surgical execution arm;

[0159] S808, according to the fourth conversion relationship, registers the preoperative images with the lower-level machine of the surgical execution arm;

[0160] S809, runs to the parameter setting node, and sets the acquisition parameters during the image acquisition process based on the information input by the user in the human-computer interaction interface;

[0161] S810 runs to the image scanning node and, based on the set acquisition parameters, controls the lower-level image acquisition machine to scan the target object.

[0162] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed 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 performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0163] Based on the same inventive concept, this application also provides a computer-aided medical device control apparatus for implementing the computer-aided medical device control method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the computer-aided medical device control apparatus provided below can be found in the limitations of the computer-aided medical device control method described above, and will not be repeated here.

[0164] In one exemplary embodiment, such as Figure 21 As shown, a computer-aided medical device control device is provided, comprising: a determining module 11, an acquiring module 12, and a control module 13, wherein:

[0165] The determination module 11 is used to determine the working mode based on the working mode selection instruction; the working modes include image acquisition mode and intraoperative navigation mode.

[0166] The acquisition module 12 is used to acquire the functional components corresponding to the working mode; the functional components include the optical tracking unit, the image acquisition lower unit, and the surgical execution arm lower unit.

[0167] The control module 13 is used to determine the workflow configuration node of the working mode according to the workflow configuration instruction, and to control the functional components to execute corresponding commands according to the workflow configuration node.

[0168] Each module in the aforementioned computer-aided medical device control unit can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0169] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 22As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data used in the computer device's computer-aided medical device control process. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a computer-aided medical device control method.

[0170] Those skilled in the art will understand that Figure 22 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0171] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the content of any one embodiment of the computer-aided medical device control method described above.

[0172] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the content of any one of the embodiments of the computer-aided medical device control method described above.

[0173] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0174] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. 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), magnetic 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 take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0175] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this application.

[0176] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A computer-aided medical device, characterized in that, The device includes a human-computer interaction interface, at least one memory, and a processor; The human-computer interaction interface includes a working mode definition area; the working mode definition area is used to receive working mode selection instructions. The at least one memory is used to store control instructions; The processor is configured to execute the control instructions to implement a computer-aided medical device control method, the method comprising: The working mode is determined according to the working mode selection instruction; Configure the corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine; According to the workflow configuration node corresponding to the working mode, at least one of the configured optical tracking unit, image acquisition lower unit, and surgical execution arm lower unit is controlled to execute corresponding control commands at each workflow configuration node.

2. The device according to claim 1, characterized in that, The working mode includes an intraoperative navigation mode, and the workflow configuration nodes corresponding to the intraoperative navigation mode include a surgical planning sub-node, an image registration sub-node, and a real-time navigation sub-node. The processor is also used to perform the following steps: The system runs to the surgical planning sub-node to receive preoperative images, which are used to plan the target position of the lower-level surgical execution arm. The system runs to the image registration sub-node to receive intraoperative images sent by the image acquisition lower-level machine, and uses the intraoperative images to achieve registration between the preoperative images and the surgical execution arm lower-level machine; The system operates in real-time navigation sub-node mode to control the lower-level surgical arm to move to the target position.

3. The device according to claim 2, characterized in that, The process of registering preoperative images with the surgical arm lower-level machine using the intraoperative images includes... A three-dimensional model is constructed based on the preoperative images, and the three-dimensional model is registered with the intraoperative images to obtain the first registration matrix; The second registration matrix is ​​obtained by registering the intraoperative images with the lower-level surgical arm. The preoperative images are registered with the surgical arm lower unit based on the first registration matrix and the second registration matrix.

4. The device according to claim 3, characterized in that, The intraoperative images include two-dimensional images of the first position and two-dimensional images of the second position. The process of constructing a three-dimensional model based on the preoperative images and registering the three-dimensional model with the intraoperative images to obtain a first registration matrix includes: A three-dimensional model is constructed based on the two-dimensional images of the first body position and the two-dimensional images of the second body position, and the physiological feature points of the three-dimensional model are extracted. Based on the physiological feature points, registration is performed on the intraoperative images to obtain the first registration matrix by registering the three-dimensional model with the intraoperative images.

5. The device according to claim 3, characterized in that, The second registration matrix obtained by registering the intraoperative images with the lower-level surgical arm includes: The system acquires a first conversion relationship between the intraoperative image and the imaging calibration target, a second conversion relationship between the imaging calibration target and the surgical execution arm, and a third conversion relationship between the surgical execution arm and the robotic arm base; the second conversion relationship is determined based on the imaging time of the intraoperative image. Based on the first transformation relationship, the second transformation relationship, and the third transformation relationship, the intraoperative images are registered with the surgical arm lower unit to obtain the second registration matrix.

6. The device according to claim 3, characterized in that, The registration of preoperative images with the surgical arm lower unit is achieved based on the first registration matrix and the second registration matrix, including: The sum of the first registration matrix and the second registration matrix is ​​used as the fourth transformation relationship between the preoperative image and the surgical arm; According to the fourth conversion relationship, the preoperative image is registered with the surgical execution arm lower unit.

7. The device according to any one of claims 1 to 6, characterized in that, The operating mode includes an image acquisition mode, and the workflow configuration node corresponding to the image acquisition mode includes a parameter setting node and an image scanning node; the processor is also used to perform the following steps: The process proceeds to the parameter setting node, where the acquisition parameters are set based on the information input by the user in the human-computer interaction interface. The system runs to the image scanning node and, based on the set acquisition parameters, controls the image acquisition slave device to scan the target object.

8. A computer-aided medical device control method, characterized in that, The method includes: Determine the working mode based on user input; Configure the corresponding functional components according to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine; According to the workflow configuration node corresponding to the working mode, at least one of the configured optical tracking unit, image acquisition lower unit, and surgical execution arm lower unit is controlled to execute corresponding control commands at each workflow configuration node.

9. A computer-aided medical equipment control device, characterized in that, The device includes: The determination module is used to determine the working mode based on the working mode selection instruction; the working mode includes image acquisition mode and intraoperative navigation mode. The acquisition module is used to acquire the functional components corresponding to the working mode; the functional components include an optical tracking unit, an image acquisition lower-level machine, and a surgical execution arm lower-level machine. The control module is used to determine the workflow configuration node of the working mode according to the workflow configuration instruction, and to control the functional components to execute corresponding commands according to the workflow configuration node.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the computer-aided medical device control method of claim 8.

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