Orthopedic surgery navigation system and method and electronic equipment

Abstract

The invention provides an orthopedic surgery navigation system and method and electronic device.The system comprises a structured light camera, a surgery planning module, a registration module and a navigation guiding module.The structured light camera is used for collecting a depth image of a target osteotomy area in the surgery in real time; the operation planning module is used for performing operation planning on a target osteotomy area based on the preoperative medical image data of the patient and generating planning information; the registration module is used for performing registration on the depth image and a three-dimensional model reconstructed based on preoperative medical image data so as to determine navigation positioning information of an operation executing mechanism in a space; the technical problems that in the prior art, a physical marker is still depended on, the operation process is complex, and cost is high are solved, miniaturization and low cost of an orthopedic surgery navigation system are achieved, and the operation efficiency is improved. And the positioning precision and the operation reliability of the osteotomy operation are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of orthopedic surgical navigation technology, specifically to an orthopedic surgical navigation system and method, and electronic equipment. Background Technology

[0002] Robot-assisted orthopedic surgery, such as total knee replacement, has become an important area of ​​development for improving surgical precision. Currently, the mainstream technology for surgical navigation is marker tracking based on optical positioning. In this paradigm, the system typically includes an optical positioning camera and multiple optical markers (or trackers) fixed to the patient's bones (such as the femur and tibia) and surgical instruments. During the operation, the optical positioning camera continuously captures the spatial position of these markers, calculates and displays the relative pose of the bones and surgical instruments in real time, thereby guiding the surgeon or controlling the robotic arm to complete the predetermined surgical procedure.

[0003] However, this marker-based navigation technology has some inherent drawbacks. During surgery, doctors, assistants, or instruments can easily enter the field of view of the optical camera, causing temporary obstruction of the markers, resulting in interruption or loss of navigation signals, affecting the smoothness and safety of the surgery. Simultaneously, other strong light sources in the operating room environment can also interfere with the optical signals. To achieve bone tracking, a dedicated tracking reference frame is usually implanted into the patient's healthy bones. This process is invasive, increasing not only additional trauma and postoperative pain for the patient but also introducing the potential risks of screw loosening and surgical site infection. Furthermore, the entire navigation system relies on a high-precision optical camera, multiple accurately identifiable markers, and a complex calibration process, resulting in a complex system structure, high cost, and significant space requirements in the operating room, making it difficult to popularize this technology in primary hospitals or underdeveloped areas. Existing systems require cumbersome registration operations (such as point registration or area registration) before or during surgery to align the patient's preoperative imaging data (such as CT scans) with the actual anatomical structures during surgery. This process relies heavily on the surgeon's manual experience and subjective judgment, which is not only time-consuming but also prone to human error, directly affecting the final navigation accuracy. This is especially true for surgeries involving multiple osteotomy surfaces, such as knee replacement, where ensuring consistent registration between these surfaces is difficult, potentially leading to inaccurate relationships and impacting prosthesis implantation outcomes. Therefore, there is currently a lack of a miniaturized orthopedic surgical navigation system that can eliminate reliance on physical markers, simplify the procedure, reduce system cost and complexity, while maintaining high accuracy and stability.

[0004] Therefore, existing technologies still need further development. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned technical deficiencies and provide an orthopedic surgical navigation system and method, and an electronic device, so as to solve the problems existing in the prior art.

[0006] To achieve the above-mentioned technical objectives, according to a first aspect of the present invention, the present invention provides an orthopedic surgical navigation system, comprising: Structured light camera is used to acquire depth images of the target osteotomy area in real time during surgery; The surgical planning module is used to plan the surgical area of ​​the target osteotomy region based on the patient's preoperative medical imaging data and generate planning information. The registration module is used to register the depth image with the three-dimensional model reconstructed based on the preoperative medical image data to determine the navigation and positioning information of the surgical execution agency in space. The navigation guidance module is used to guide the surgical execution mechanism to perform osteotomy operations based on the planning information and the navigation positioning information.

[0007] Specifically, the structured light camera is an adaptive pose structured light camera with degree of freedom adjustment capability. The adaptive pose structured light camera is mounted on a camera pose adjustment bracket, which is used to adjust the height and tilt angle of the adaptive pose structured light camera.

[0008] Specifically, the structured light camera integrates a laser guidance device, which is used to indicate the location of the surgical operation by projecting a laser beam.

[0009] Specifically, the system also includes a positioning and fixation bracket, on which a rigid-flexible coupling locator is provided. The rigid-flexible coupling locator is used to locate the osteotomy site of the patient during the operation, while restraining the movement of the patient's limbs.

[0010] Specifically, the surgical execution mechanism includes an osteotomy guide plate, which is used to locate the spatial position and angle of the osteotomy based on the planning information generated by the surgical planning module, so as to provide guidance information for performing the osteotomy operation.

[0011] Specifically, the surgical execution mechanism also includes a handheld multi-functional power module, which includes a power unit, an instrument interface detachably connected to the front end of the power unit, and at least one surgical instrument that can be mounted on the instrument interface.

[0012] Specifically, the handheld multi-functional power module is used to perform positioning hole drilling operations in the osteotomy area under the guidance of the navigation guidance module to fix the osteotomy guide plate. Then, the handheld multi-functional power module carries surgical instruments and performs osteotomy operations according to the guidance information provided by the osteotomy guide plate.

[0013] Specifically, the system also includes an intelligent operating table for adaptive posture adjustment based on the patient's body shape and the location of the osteotomy area. The positioning and fixing bracket is set on the surface of the intelligent operating table to restrain the movement of the patient's limbs.

[0014] Specifically, the registration module uses a mutual information registration algorithm based on grayscale voxels and depth fields to perform the registration.

[0015] According to a second aspect of the present invention, a method for orthopedic surgical navigation is provided, comprising: S100: Obtain the patient's preoperative medical imaging data, and perform surgical planning for the target osteotomy area based on the preoperative medical imaging data, generating planning information; S200: Real-time acquisition of depth images of the target osteotomy area during surgery using a structured light camera; S300: Register the depth image with the three-dimensional model reconstructed based on the preoperative medical image data to determine the navigation and positioning information of the surgical execution agency in space; S400. Based on the planning information and the navigation and positioning information, guide the surgical execution mechanism to perform osteotomy.

[0016] Specifically, S300 includes: Once the lesion area of ​​the target osteotomy area is exposed, the depth image acquired in real time by the structured light camera is registered with the patient's preoperative medical imaging data to obtain the positioning point of the osteotomy guide plate on the first osteotomy surface. After the first osteotomy surface is determined, at least one osteotomy guide plate positioning point of the second osteotomy surface is obtained based on the positioning point of the osteotomy guide plate of the first osteotomy surface.

[0017] Specifically, the method for registering the depth images acquired in real time by the structured light camera with the patient's preoperative medical imaging data includes: An algorithm based on maximizing mutual information between grayscale voxels and depth fields is adopted. Through a camera projection model, a spatial mapping relationship is established between the three-dimensional voxel coordinates of the preoperative medical image and the pixel coordinates of the intraoperative depth image, so as to map the three-dimensional voxel coordinates of the preoperative medical image to the pixel coordinates of the depth image.

[0018] According to a third aspect of the present invention, an electronic device is provided, comprising: a memory; and a processor, wherein the memory stores computer-readable instructions that, when executed by the processor, implement the above-described orthopedic surgical navigation method.

[0019] Beneficial effects: This invention provides an orthopedic surgical navigation system and method. It utilizes a markerless structured light camera to acquire real-time depth images of the osteotomy area, and combines this with a preoperative planning and registration module to achieve precise spatial guidance of the surgical procedure. This architecture abandons the complex paradigm of traditional reliance on optical markers and robotic arms, solving the infection risks caused by marker occlusion and invasive implantation, as well as the cost burden of expensive hardware. It successfully achieves miniaturization and cost reduction of the orthopedic surgical navigation system. Furthermore, through high-precision image registration and intuitive navigation guidance, this invention significantly improves the positioning accuracy and operational reliability of osteotomy surgery, enabling robot-assisted orthopedic surgery to be applied to a wider range of scenarios such as primary healthcare and emergency rescue, greatly improving surgical safety and efficiency. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the system composition of the orthopedic surgical navigation system provided in a specific embodiment of the present invention; Figure 2 This is a flowchart of the orthopedic surgical navigation method provided in a specific embodiment of the present invention; Figure 3 This is a schematic diagram of the orthopedic surgical navigation system provided in a specific embodiment of the present invention; Figure 4 This is a structural schematic diagram of the handheld multi-functional power module provided in a specific embodiment of the present invention; Figure 5 This is an operation flowchart of the orthopedic surgical navigation system provided in a specific embodiment of the present invention; The reference numerals in the above figures are as follows: 1. Adaptive pose structured light camera; 2. Joint replacement surgery planning module; 3. Camera pose adjustment bracket; 4. Positioning and fixation bracket; 5. Rigid-flexible coupling positioner; 6. Intelligent operating table; 7. Power unit; 8. Instrument interface; 9. Surgical instruments. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Other similar embodiments obtained by those skilled in the art based on the embodiments in this application without creative effort should all fall within the scope of protection of this application. Furthermore, directional terms mentioned in the following embodiments, such as "up," "down," "left," and "right," are only for reference to the directions in the accompanying drawings; therefore, the directional terms used are for illustrative purposes and not for limiting the invention.

[0022] The present invention will be further described below with reference to the accompanying drawings and preferred embodiments.

[0023] Example 1 Please see Figure 1 This embodiment provides an orthopedic surgical navigation system, including a structured light camera 100, a surgical planning module 200, a registration module 300, and a navigation guidance module 400. The structured light camera 100 is used to acquire depth images of the target osteotomy area in real time during surgery. The surgical planning module 200 is used to plan the surgical procedure for the target osteotomy area based on the patient's preoperative medical imaging data, generating planning information. The registration module 300 is used to register the depth images with a three-dimensional model reconstructed based on the preoperative medical imaging data to determine the navigation positioning information of the surgical execution mechanism in space. The navigation guidance module 400 is used to guide the surgical execution mechanism to perform the osteotomy operation based on the planning information and the navigation positioning information.

[0024] See Figure 3 In this embodiment, the structured light camera 100 is an adaptive pose structured light camera 1 with adjustable degrees of freedom. The adaptive pose structured light camera 1 is mounted on a camera pose adjustment bracket 3, which is used to adjust the height and tilt angle of the adaptive pose structured light camera 1. Furthermore, the structured light camera 100 integrates a laser guidance device, which is used to indicate the position of the surgical operation by projecting a laser beam.

[0025] Understandably, the adaptive pose structured light camera 1 is the core sensor for this system to achieve markerless navigation. It acquires depth images of the target area during surgery by emitting structured light in a specific mode and receiving its deformation. To further optimize the field of view and avoid occlusion during surgery, the adaptive pose structured light camera 1 is mounted on an adjustable camera pose adjustment bracket 3, giving it multiple degrees of freedom of adjustment. Its height and tilt can be adjusted in real time according to the needs of the surgery to ensure that the surgical field of view of the target osteotomy area (such as the knee joint) can always be clearly captured.

[0026] See Figure 3 In this embodiment, the orthopedic surgical navigation system also includes a positioning and fixation bracket 4, on which a rigid-flexible coupling locator 5 is provided. The rigid-flexible coupling locator 5 is used to locate the osteotomy site of the patient during the operation and to restrain the movement of the patient's limbs.

[0027] It should be noted that, taking knee replacement surgery as an example, the positioning and fixation bracket 4 in this embodiment is used to support and fix the patient's knee joint during surgery. Its core is the setting of a rigid-flexible coupling locator 5. This rigid-flexible coupling locator 5 can provide stable support and limit the large-range unintended movement of the knee joint, while also having a certain degree of flexibility to avoid excessive pressure or damage to the patient's limb, thus providing a stable mechanical environment for achieving precise navigation.

[0028] See Figure 3 The orthopedic surgical navigation system in this embodiment also includes an intelligent operating table 6, which is used to adaptively adjust the posture according to the patient's body shape and the position of the osteotomy area. The positioning and fixing bracket 4 is set on the surface of the intelligent operating table 6 to restrain the movement of the patient's limbs.

[0029] It should be noted that the intelligent operating table 6 in this embodiment can adaptively adjust its posture according to the patient's specific body shape and lesion location, thereby providing doctors with a better surgical field of vision and operating angle, and improving the convenience and comfort of the operation. The positioning and fixing bracket 4 is usually set on the surface of the intelligent operating table 6 to facilitate the restraint of the patient's limb movement.

[0030] Specifically, in this embodiment, the surgical execution mechanism is the physical entity that ultimately completes the surgical operation. The surgical execution mechanism includes an osteotomy guide plate, which is used to locate the spatial position and angle of the osteotomy according to the planning information generated by the surgical planning module 200, so as to provide guidance information for performing the osteotomy operation.

[0031] Preferably, the osteotomy guide plate in this embodiment is an adjustable-size osteotomy guide plate. This guide plate is not a traditional fixed-size instrument, but can be adjusted in size and spatial position according to the planning information output by the preoperative planning system to ensure that it is precisely matched with the patient's unique skeletal anatomy. The core function of the osteotomy guide plate is to provide a precise and physical guiding reference for the final osteotomy operation.

[0032] Further, see Figure 4 The surgical execution mechanism also includes a handheld multi-functional power module, which includes a power body 7, an instrument interface 8 detachably connected to the front end of the power body 7, and at least one surgical instrument 9 that can be mounted on the instrument interface 8.

[0033] It should be noted that the aforementioned handheld multi-functional power module adopts a lightweight and portable design, serving as the main body for doctors' handheld operation. It includes a power unit 7, an instrument interface 8 that can be quickly detached from the front end of the power unit 7, and various surgical instruments 9 (such as drills, oscillating saws, etc.) that can be mounted on this interface. Crucially, the surface of the handheld multi-functional power module's outer shell is designed with specific texture features that are easily identifiable and tracked by the structured light camera 100, thereby enabling real-time tracking and positioning by the navigation system without the need for additional markers.

[0034] In practical applications, surgeons can quickly change the surgical instruments 9 mounted on the instrument interface 8 according to surgical needs, such as switching from a drill to an oscillating saw, to meet the operational requirements of different surgical steps. This flexibility and convenience greatly improves surgical efficiency and reduces waiting time during surgery. Simultaneously, due to the specific textured surface design of the handheld multi-functional power module's casing, the structured light camera 100 can accurately capture its position and orientation information, thus providing precise positioning data for the navigation system. This real-time tracking and positioning method, which requires no additional markers, not only simplifies the surgical preparation process but also reduces the risk of infection during surgery, providing patients with a safer and more reliable surgical environment.

[0035] Furthermore, the handheld multi-functional power module is used to perform positioning hole drilling operations in the osteotomy area under the guidance of the navigation guidance module 400 to fix the osteotomy guide plate. Then, the handheld multi-functional power module carries the surgical instrument 9 and performs osteotomy operations according to the guidance information provided by the osteotomy guide plate.

[0036] In actual operation, the handheld multi-functional power module first receives precise positioning signals from the navigation guidance module 400, determines the specific location of the osteotomy area, and performs positioning hole drilling. This step ensures that the osteotomy guide plate can be firmly and accurately fixed in the predetermined position, laying a solid foundation for subsequent osteotomy operations. Subsequently, according to the needs of the surgery, the doctor will select appropriate surgical instruments 9 (such as oscillating saws) and mount them on the handheld multi-functional power module. Based on the precise guidance information provided by the osteotomy guide plate, the doctor will perform meticulous and accurate osteotomy operations. Throughout the process, the real-time feedback of the navigation system and the precise execution of the handheld multi-functional power module work together to ensure the smooth progress and high-quality completion of the surgery.

[0037] Specifically, the registration module 300 employs a registration algorithm based on mutual information between grayscale voxels and the depth field. This algorithm achieves high-precision registration between image data and the patient's actual anatomical structure by calculating the mutual information between grayscale voxels and the depth field. In practical applications, the registration module 300 first preprocesses the acquired medical image data, extracting grayscale voxel information and simultaneously acquiring depth field data of the patient's surgical site. Then, using the mutual information registration algorithm based on grayscale voxels and the depth field, it calculates the mutual information value between the two. By continuously optimizing the algorithm parameters, the mutual information value is maximized, thereby achieving accurate registration between the image data and the patient's actual anatomical structure. This registration method has high accuracy and stability, effectively reducing registration errors and providing a reliable benchmark for subsequent navigation guidance and surgical operations.

[0038] See Figures 3-5The working principle of this invention will be explained below using knee replacement surgery as an example: This example is a miniaturized orthopedic surgical navigation system for knee replacement surgery. The system includes a joint replacement surgery planning module 2, an adaptive pose structured light camera 1, an intelligent operating table 6, an adjustable-size osteotomy guide plate, a handheld multi-functional power module, and a positioning and fixation bracket 4.

[0039] Among them, the joint replacement surgery planning module 2 is used to generate a personalized osteotomy plan based on the patient's preoperative CT images, that is, to realize the planning of the osteotomy surface in the knee replacement surgery, and to provide a basis for subsequent osteotomy execution. In addition, the joint replacement surgery planning module 2 in this example also includes an information display module, which can display the real-time pose information during the operation through the screen. The adaptive pose structured light camera 1 provides positioning and navigation for surgical procedures. To avoid optical path obstruction during surgery, it is configured to have a certain degree of freedom for adjustment, thereby improving the adaptive capability of the navigation device. The adaptive pose structured light camera 1 integrates a laser guidance device to provide the drilling position. The intelligent operating table 6 can adjust its posture according to the patient's body shape and specific lesion condition, so that doctors can better view the location of the lesion and perform surgery; The adjustable-size osteotomy guide plate is used to determine the amount of osteotomy. It can be set according to the patient's individual characteristics and the preoperative planning results to meet the patient's personalized surgical needs. The fixed position of the osteotomy plate will be determined according to the preoperative planning results to locate the spatial position and angle of the osteotomy, and precise drilling will be performed by laser-guided power tools. The handheld multi-functional power module is easy to assemble and disassemble. The handheld multi-functional power module in this example can be quickly replaced and equipped with commonly used instruments in joint replacement surgery such as drills and oscillating saws. The power tools are marked with textures that are easily recognizable by the structured light camera 100 to facilitate real-time tracking by navigation devices. The positioning and fixing bracket 4 is used to support the patient's knee joint. A rigid-flexible coupling positioner 5 is set above the positioning and fixing bracket 4 to position the patient's knee joint, restrict its large range of movement, and prevent inaccurate positioning and navigation caused by the patient's specific posture changes.

[0040] like Figure 5 As shown, the specific working process of the miniaturized knee replacement surgery orthopedic surgical navigation system in this example includes: Step 1: Based on the patient's preoperative CT medical images, intelligent planning of the osteotomy surfaces of the femur and tibia is performed to obtain information such as the location of the positioning bone pin drill holes of the osteotomy guide plate, the osteotomy angle and thickness of each osteotomy surface. The adaptive pose structured light camera 1 is placed near the intelligent operating table 6, and its height and tilt angle are adjusted to facilitate direct observation of the patient's knee joint. Step 2: The doctor places the knee joint on the positioning and fixation bracket 4, uses the rigid-flexible coupling locator 5 to constrain the large range of movement of the knee joint, and then manually cuts to the lesion in the target osteotomy area of ​​the knee joint for reasonable exposure. Step 3: Perform registration and mapping of the navigation system, intelligent operating table 6, and patient lesion site, and register the points in the preoperative CT voxel space. P w Intraoperative depth field pixel coordinates Perform spatial correspondence mapping and establish a spatial transformation model. ,in The registration transformation parameters include rotation, translation, and scale information. Through rigid or non-rigid registration algorithms, accurate registration between CT images and the actual surgical scene is achieved. Step 4: According to the planned drilling location, the laser beam of the laser guide device guides the bone needle. The doctor inserts the guide needle into the predetermined position at the distal end of the femur according to the laser indication. Then, an adaptive osteotomy tool adapted to the hole position of the guide needle is selected and fixed to the femoral plate or osteotomy guide plate. In particular, based on the positioning hole of the distal osteotomy guide plate, the guide plate components corresponding to other osteotomy surfaces are installed in sequence to form a multi-faceted collaborative osteotomy guidance system to ensure the spatial consistency and accuracy of each osteotomy surface.

[0041] Step 5: Guided by the surgical guide, the surgeon operates the adaptive oscillating saw, performing the osteotomy according to the order of removal of the osteotomy surfaces during the operation, until all osteotomy surfaces are successfully completed. The oscillating saw can adjust its angle and control its stroke based on the geometric characteristics of different osteotomy surfaces, achieving personalized osteotomy. Throughout the process, the navigation system continuously monitors the tool's position and osteotomy trajectory, providing real-time feedback to avoid miscutting or overcutting. In addition, postoperative imaging data will be recorded to enhance the system's intelligent osteotomy surface planning capabilities. Step 6: Determine if osteotomy is complete. The system determines whether the current osteotomy operation has been fully completed. If not, return to Step 4 and continue to the next osteotomy surface; if completed, proceed to the postoperative stage. Step 7: Record postoperative imaging data to enhance intelligent planning capabilities. After the surgery, collect postoperative CT or intraoperative depth imaging data and upload them to the central database. Compare and analyze the actual postoperative osteotomy results with the preoperative planning plan, extract error information and clinical feedback, and use them to train and optimize the intelligent planning algorithm model, thereby continuously improving the system's automation level and individualized matching capabilities.

[0042] Understandably, the above example presents a miniaturized orthopedic surgical navigation system for knee replacement surgery. Based on preoperative medical images, this system utilizes markerless navigation equipment to provide navigation and positioning for total knee replacement surgery, enabling precise and efficient osteotomy. The system is small in size and easy to operate, abandoning the existing robot-assisted navigation method based on a robotic arm equipped with a multi-functional osteotomy guide plate. It combines the navigation system with traditional osteotomy instruments, achieving the clinical requirement of accurate "registration-execution." It eliminates the need for invasive implantation of trackers in the femur and tibia, breaking the paradigm of existing mainstream surgical robot systems. The system's registration is only used for precise positioning at the osteotomy plate positioning holes. That is, based on preoperative planning results, it unifies the patient's femoral and tibial coordinate systems with the navigation and positioning system coordinate systems in the surgical scene, thereby obtaining the position of the osteotomy guide plate positioning pins. Real-time intraoperative positioning is unnecessary, significantly reducing the system's requirements for accuracy and real-time data processing. Simultaneously, it lowers the operational threshold for doctors, allowing them to maintain their existing clinical workflows and familiar port layouts, reducing the training burden, shortening the learning curve, and enabling more doctors to quickly master the operational skills.

[0043] It should be further noted that this invention can not only be used for total knee replacement surgery, but also provide surgical implementation references for other procedures, such as pedicle screw implantation, intervertebral disc fusion and other spinal surgeries, unicompartmental replacement surgery, etc., greatly expanding the application scenarios of this invention.

[0044] It should be noted that this embodiment provides an orthopedic surgical navigation system. A markerless structured light camera 100 acquires real-time depth images of the osteotomy area, and combined with a preoperative planning and registration module 300, achieves precise spatial guidance for the surgical execution mechanism. This architecture abandons the complex paradigm of traditional reliance on optical markers and robotic arms, solving the infection risks caused by marker occlusion and invasive implantation, as well as the cost burden of expensive hardware, successfully achieving miniaturization and cost reduction of the orthopedic surgical navigation system. Simultaneously, this invention significantly improves the positioning accuracy and operational reliability of osteotomy surgery through high-precision image registration and intuitive navigation guidance, enabling robot-assisted orthopedic surgery to be applied to a wider range of scenarios such as primary healthcare and emergency rescue, greatly improving surgical safety and efficiency.

[0045] Example 2 Please see Figure 2 This embodiment provides an orthopedic surgical navigation method, applied to the orthopedic surgical navigation system in Embodiment 1. The method includes: S100: Acquire the patient's preoperative medical imaging data, and perform surgical planning for the target osteotomy area based on the preoperative medical imaging data, generating planning information, that is, using the surgical planning module 200 to perform three-dimensional reconstruction and intelligent analysis, generating a personalized osteotomy plan, and clarifying the angle and thickness of each osteotomy surface and the drilling position of the osteotomy guide plate positioning bone pin.

[0046] S200: The structured light camera 100 acquires depth images of the target osteotomy area in real time during the operation. For example, the patient's knee joint is fixed on the positioning and fixation bracket 4 and constrained by the rigid-flexible coupling locator 5. The position and angle of the adaptive pose structured light camera 1 are adjusted to ensure that its field of view completely covers the surgical field of the knee joint. Subsequently, the camera acquires depth images of the exposed target areas such as the femoral condyle in real time.

[0047] S300: Register the depth image with the three-dimensional model reconstructed based on the preoperative medical image data to determine the navigation and positioning information of the surgical execution agency in space; Understandably, registration is the core step in achieving markerless navigation. The registration module 300 performs high-precision registration between the real-time acquired depth images and the 3D model reconstructed from preoperative CT. To improve accuracy and ensure consistency between multiple osteotomy surfaces, registration is implemented in two stages: Phase 1 (Initial Registration): After the lesion area of ​​the target osteotomy area is exposed, the depth image acquired in real time by the structured light camera 100 is registered with the patient's preoperative medical imaging data to obtain the positioning point of the osteotomy guide plate on the first osteotomy surface. Preferably, in knee replacement surgery, this embodiment sets the first osteotomy surface as the distal femoral osteotomy surface.

[0048] The second stage (reference registration): After the first osteotomy surface is determined, using the osteotomy guide positioning point (e.g., its center point) of the first osteotomy surface as a reference, at least one second osteotomy guide positioning point (e.g., the anterior condyle or posterior condyle) is obtained through coordinate transformation and Boolean operations. According to the above scheme, it is ensured that the five osteotomy surfaces—distal femur, anterior condyle, posterior condyle, anterior oblique, and posterior oblique—share the same spatial reference, effectively avoiding the cumulative error introduced by multiple independent registrations.

[0049] In this embodiment, a preferred approach is to use a mutual information maximization algorithm based on grayscale voxels and depth fields. Through a camera projection model, a spatial mapping relationship is established between the three-dimensional voxel coordinates of the preoperative medical image and the pixel coordinates of the intraoperative depth image, so as to map the three-dimensional voxel coordinates of the preoperative medical image to the pixel coordinates of the depth image.

[0050] Specifically, the core idea of ​​the above registration method is to establish a spatial mapping relationship between the preoperative CT three-dimensional voxel coordinates and the intraoperative depth image pixel coordinates, specifically through a camera projection model (including an intrinsic parameter matrix). K ) and registration transformation parameters θ={R, t} CT voxel points in the world coordinate system P w Points transformed to camera coordinate system P c Then projected onto the pixel coordinates of the depth image ( u,v By maximizing the mutual information between CT grayscale information and depth field depth information. ,when When the maximum value is reached, the spatial alignment between the two is considered optimal, thus the optimal registration transformation parameters can be solved. This process achieves a precise integration of the virtual planning space and the real surgical space.

[0051] The following uses the knee joint as an example to illustrate the specific implementation process of registering the depth image with the three-dimensional model reconstructed based on the preoperative medical imaging data during knee replacement surgery: The device registration and licensing process in this embodiment mainly occurs in two stages: (1) After the femoral condyle surgical area is exposed, the real-time images captured by the adaptive depth camera are registered with the preoperative medical images based on the CT image planning results, so as to obtain the positioning point of the osteotomy guide plate for the distal femoral osteotomy surface, and laser guidance is used to assist in the placement of the bone screw. (2) After the distal osteotomy surface is determined, the positioning point of the osteotomy guide plate during the cutting of the distal osteotomy surface is used as the reference to obtain the positioning point of the osteotomy guide plate required for the remaining femoral osteotomy surface, thereby ensuring that the reference of the five osteotomy surfaces of distal, anterior condyle, posterior condyle, anterior oblique and posterior oblique is consistent, and avoiding the problem of inconsistent navigation. Preferably, the positioning point of the osteotomy guide plate during the cutting of the distal osteotomy surface can be obtained by Boolean operation, and its center is used as the reference point.

[0052] During registration, this scheme abandons the existing method of using near-infrared (IR) light to track navigation markers attached to objects such as surgical instruments 9 and obtaining information about the objects in three-dimensional space in real time by detecting the position and orientation of these markers. In this embodiment, intraoperative images are captured in real time by a depth camera and registered with preoperative images. The registration uses an algorithm based on mutual information registration between grayscale voxels and the depth field. The specific implementation process is as follows: Step 1: First, the 3D voxel coordinates of the pinhole camera model CT are mapped to the pixel coordinates of the depth field through the camera projection model, thereby achieving the spatial correspondence from "CT voxels to depth field pixels". Specifically: (1) (2) (3) Wherein, the coordinates of the CT 3D voxel in the world coordinate system are: It is necessary to transform the parameters through registration. Transform to camera coordinate system , Depth in camera coordinate system For the intrinsic parameters of the structured light camera 100, where , Focal length in pixels (unit: pixels). The coordinates of the main point are the center of the depth-long image.

[0053] Step 2: The next step is to maximize mutual information, that is, to maximize the mutual information between CT grayscale information and depth field depth information. When the CT and depth field are at their maximum, the statistical correlation is strongest, indicating optimal spatial alignment. This can be achieved by: (4) (5) in: (6) (7) (8) in, This represents CT grayscale entropy, which describes the uncertainty of CT grayscale values. The higher the entropy, the more dispersed the distribution of CT grayscale values, and the higher the uncertainty. Represents the depth entropy of the depth field, used to describe the uncertainty of depth values; This represents the joint entropy, used to describe the uncertainty of the joint distribution of CT grayscale and depth values. This represents the registration transformation parameter that maximizes mutual information.

[0054] Understandably, according to the above technical solution, the registration process uses a structured light camera 100 to acquire images during the operation, and employs an algorithm based on mutual information registration of grayscale voxels and depth fields for registration. The overall accuracy of the system is improved by simplifying the registration process. In knee replacement surgery, the simplified registration only needs to be performed after the femoral condyle surgical area is exposed and the distal osteotomy surface is determined. Furthermore, the registration of the osteotomy plate positioning holes for other osteotomy surfaces after the distal osteotomy surface is determined is based on the positioning point of the osteotomy guide plate during distal osteotomy cutting. This ensures that the references for the five osteotomy surfaces are consistent, avoiding navigation inconsistencies and further improving the accuracy of navigation and positioning in knee replacement surgery, thus increasing surgical efficiency.

[0055] S400: Based on the planning information and the navigation positioning information, the surgical execution mechanism is guided to perform osteotomy, without the need for additional implantation of medical devices. This not only reduces the risk of infection for patients but also greatly shortens the registration, alignment, and surgical operation time, thereby improving surgical efficiency and accelerating patient recovery.

[0056] It should be noted that this embodiment provides a method for orthopedic surgical navigation. A markerless structured light camera 100 acquires real-time depth images of the osteotomy area, and combined with a preoperative planning and registration module 300, achieves precise spatial guidance for the surgical execution mechanism. This architecture abandons the complex paradigm of traditional reliance on optical markers and robotic arms, solving the infection risks caused by marker occlusion and invasive implantation, as well as the cost burden of expensive hardware. It successfully achieves miniaturization and cost reduction of the orthopedic surgical navigation system. Simultaneously, this invention significantly improves the positioning accuracy and operational reliability of osteotomy surgery through high-precision image registration and intuitive navigation guidance, enabling robot-assisted orthopedic surgery to be applied to a wider range of scenarios such as primary healthcare and emergency rescue, greatly improving surgical safety and efficiency.

[0057] In a preferred embodiment, this application also provides an electronic device, the electronic device comprising: The computer device includes a memory and a processor, wherein the memory stores computer-readable instructions that, when executed by the processor, implement the orthopedic surgical navigation method described herein. The computer device can be broadly categorized as a server, terminal, or any other electronic device with the necessary computing and / or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc., connected via a system bus. The processor of the computer device can be used to provide the necessary computing, processing, and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and internal memory. The non-volatile storage medium may store an operating system, computer programs, etc. The internal memory can provide an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface and communication interface of the computer device can be used to connect and communicate with external devices via a network. When the computer program is executed by the processor, it performs the steps of the method of the present invention.

[0058] This invention can be implemented as a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, causes the steps of the methods of embodiments of the invention to be performed. In one embodiment, the computer program is distributed across multiple network-coupled computer devices or processors, such that the computer program is stored, accessed, and executed in a distributed manner by one or more computer devices or processors. A single method step / operation, or two or more method steps / operations, may be executed by a single computer device or processor or by two or more computer devices or processors. One or more method steps / operations may be executed by one or more computer devices or processors, and one or more other method steps / operations may be executed by one or more other computer devices or processors. One or more computer devices or processors may execute a single method step / operation, or execute two or more method steps / operations.

[0059] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0060] The technical features described above can be combined arbitrarily. Although not all possible combinations of these technical features are described, any combination of these technical features should be considered to be covered by this specification, provided that such combination does not contain contradictions.

[0061] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. An orthopedic surgical navigation system, characterized in that, include: A structured light camera (100) is used to acquire depth images of the target osteotomy area in real time during surgery; The surgical planning module (200) is used to plan the surgical area of ​​the target osteotomy region based on the patient's preoperative medical imaging data and generate planning information. The registration module (300) is used to register the depth image with the three-dimensional model reconstructed based on the preoperative medical image data to determine the navigation and positioning information of the surgical execution agency in space. The navigation guidance module (400) is used to guide the surgical execution mechanism to perform osteotomy based on the planning information and the navigation positioning information.

2. The orthopedic surgical navigation system according to claim 1, characterized in that, The structured light camera (100) is an adaptive pose structured light camera (1) with the ability to adjust the degree of freedom. The adaptive pose structured light camera (1) is mounted on a camera pose adjustment bracket (3). The camera pose adjustment bracket (3) is used to adjust the height and tilt angle of the adaptive pose structured light camera (1).

3. The orthopedic surgical navigation system according to claim 1, characterized in that, The structured light camera (100) integrates a laser guidance device, which is used to indicate the location of surgical operations by projecting a laser beam.

4. The orthopedic surgical navigation system according to claim 1, characterized in that, The system also includes a positioning and fixing bracket (4), on which a rigid-flexible coupling locator (5) is provided. The rigid-flexible coupling locator (5) is used to locate the osteotomy site of the patient during the operation and to restrain the movement of the patient's limbs.

5. The orthopedic surgical navigation system according to claim 1, characterized in that, The surgical execution mechanism includes an osteotomy guide plate, which is used to locate the spatial position and angle of the osteotomy based on the planning information generated by the surgical planning module (200), so as to provide guidance information for performing the osteotomy operation.

6. The orthopedic surgical navigation system according to claim 5, characterized in that, The surgical execution mechanism also includes a handheld multi-functional power module, which includes a power body (7), an instrument interface (8) detachably connected to the front end of the power body (7), and at least one surgical instrument (9) that can be mounted on the instrument interface (8).

7. The orthopedic surgical navigation system according to claim 6, characterized in that, The handheld multi-functional power module is used to perform the positioning hole drilling operation of the osteotomy area under the guidance of the navigation guidance module (400) to fix the osteotomy guide plate. Then, the handheld multi-functional power module carries the surgical instrument (9) and performs the osteotomy operation according to the guidance information provided by the osteotomy guide plate.

8. The orthopedic surgical navigation system according to claim 4, characterized in that, The system also includes an intelligent operating table (6) for adaptive posture adjustment based on the patient's body shape and the location of the osteotomy area. The positioning and fixing bracket is set on the surface of the intelligent operating table (6) to constrain the movement of the patient's limbs.

9. The orthopedic surgical navigation system according to claim 1, characterized in that, The registration module (300) performs a registration algorithm based on mutual information registration between gray voxels and depth fields.

10. A method for navigation in orthopedic surgery, characterized in that, The method, applied to the orthopedic surgical navigation system according to any one of claims 1-9, comprises: S100: Obtain the patient's preoperative medical imaging data, and perform surgical planning for the target osteotomy area based on the preoperative medical imaging data, generating planning information; S200: Real-time acquisition of depth images of the target osteotomy area during surgery using a structured light camera (100); S300: Register the depth image with the three-dimensional model reconstructed based on the preoperative medical image data to determine the navigation and positioning information of the surgical execution agency in space; S400. Based on the planning information and the navigation and positioning information, guide the surgical execution mechanism to perform osteotomy.

11. The orthopedic surgical navigation method according to claim 10, characterized in that, The S300 includes: Once the lesion area of ​​the target osteotomy area is exposed, the depth image acquired in real time by the structured light camera (100) is registered with the patient's preoperative medical imaging data to obtain the osteotomy guide plate positioning point of the first osteotomy surface. After the first osteotomy surface is determined, at least one osteotomy guide plate positioning point of the second osteotomy surface is obtained based on the positioning point of the osteotomy guide plate of the first osteotomy surface.

12. The orthopedic surgical navigation method according to claim 11, characterized in that, The method for registering depth images acquired in real time by the structured light camera (100) with the patient's preoperative medical imaging data includes: An algorithm based on maximizing mutual information between grayscale voxels and depth fields is adopted. Through a camera projection model, a spatial mapping relationship is established between the three-dimensional voxel coordinates of the preoperative medical image and the pixel coordinates of the intraoperative depth image, so as to map the three-dimensional voxel coordinates of the preoperative medical image to the pixel coordinates of the depth image.

13. An electronic device, characterized in that, include: Memory; The memory stores computer-readable instructions that, when executed by the processor, implement the orthopedic surgical navigation method according to any one of claims 9 to 12.

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