All-bone multi-disease artificial intelligence surgical robot system

Abstract

The application provides a full-orthopedic multi-disease artificial intelligence surgical robot system, comprising: a total hip replacement module for preoperative planning, intraoperative total hip replacement and real-time display; a total knee replacement module for preoperative planning, intraoperative total knee replacement and real-time display; a unicompartmental arthroplasty module for preoperative planning, intraoperative unicompartmental arthroplasty and real-time display; a periacetabular osteotomy module for preoperative planning, intraoperative periacetabular osteotomy and real-time display; a sports medicine module for bone tunnel planning and ligament reconstruction and real-time display; a spine nail positioning navigation module for intraoperative spine nail positioning navigation and real-time display; and a trauma positioning navigation module for intraoperative trauma positioning navigation and real-time display. According to the embodiment of the application, the auxiliary surgery can be quickly and accurately performed.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of surgical robots, and particularly relates to a full-orthopedic multi-disease artificial intelligence surgical robot system. BACKGROUND

[0002] At present, for total hip arthroplasty, total knee arthroplasty, unicompartmental arthroplasty, periacetabular osteotomy, sports medicine, spine nail positioning navigation and trauma positioning navigation, mainly rely on doctors according to experience, but the efficiency and accuracy are not good.

[0003] Therefore, how to quickly and accurately assist in surgery is a technical problem that those skilled in the art need to solve. SUMMARY

[0004] The application provides a full-orthopedic multi-disease artificial intelligence surgical robot system, which can quickly and accurately assist in surgery.

[0005] The application provides a full-orthopedic multi-disease artificial intelligence surgical robot system, which comprises:

[0006] A total hip arthroplasty module is configured to preoperatively plan, intraoperatively perform total hip arthroplasty, and display in real time;

[0007] A total knee arthroplasty module is configured to preoperatively plan, intraoperatively perform total knee arthroplasty, and display in real time;

[0008] A unicompartmental arthroplasty module is configured to preoperatively plan, intraoperatively perform unicompartmental arthroplasty, and display in real time;

[0009] A periacetabular osteotomy module is configured to preoperatively plan, intraoperatively perform periacetabular osteotomy, and display in real time;

[0010] A sports medicine module is configured to plan bone tunnel and reconstruct ligament, and display in real time;

[0011] A spine nail positioning navigation module is configured to intraoperatively perform spine nail positioning navigation, and display in real time;

[0012] A trauma positioning navigation module is configured to intraoperatively perform trauma positioning navigation, and display in real time.

[0013] Optionally, the total hip arthroplasty module is configured to:

[0014] Segment and three-dimensionally reconstruct a hip joint CT image to obtain a hip joint three-dimensional model;

[0015] Preoperatively plan based on the hip joint three-dimensional model;

[0016] Intraoperatively perform point cloud registration, grinding, compression fitting, positioning, navigation, and real-time display.

[0017] Optionally, a total knee arthroplasty module is used for:

[0018] Segmenting and three-dimensionally reconstructing a knee CT image to obtain a knee three-dimensional model;

[0019] Planning preoperatively based on the knee three-dimensional model;

[0020] Intraoperative point cloud registration, osteotomy, gap balancing, and real-time display.

[0021] Optionally, a unicompartmental knee arthroplasty module is used for:

[0022] Segmenting and three-dimensionally reconstructing a knee CT image to obtain a knee three-dimensional model;

[0023] Planning preoperatively based on the knee three-dimensional model;

[0024] Intraoperative point cloud registration, osteotomy, gap balancing, and real-time display.

[0025] Optionally, a periacetabular osteotomy module is used for: preoperative planning, intraoperative registration, osteotomy, positioning, navigation, and real-time display.

[0026] Optionally, preoperative planning, intraoperative registration, osteotomy, positioning, navigation, and real-time display, include:

[0027] Obtaining a patient's hip image;

[0028] Segmenting and three-dimensionally reconstructing the hip image to obtain a hip three-dimensional model;

[0029] Using the hip three-dimensional model, preoperatively planning the osteotomy surface, guide line, and safety zone of periacetabular osteotomy, determining the safety zone boundary, and rendering coloring; wherein the preoperative planning result includes planning osteotomy according to the anterior ischium, suprapubic branch, upper ilium, and posterior column;

[0030] Intraoperatively, combining the infrared camera NDI reflective positioning navigation system and the positioning bracket on the arc blade of the bone knife, and performing osteotomy according to the preoperative planning result, the bone knife end position is obtained in real time.

[0031] Optionally, a sports medicine module is used for:

[0032] Obtaining a first knee CT image;

[0033] Deep learning-based neural network CT image segmentation;

[0034] Knee 3D modeling according to the segmentation result;

[0035] Setting preoperative guide points and planning preoperative registration points in the knee;

[0036] Bone tunnel planning and ligament reconstruction;

[0037] Intraoperative acquisition of registration points using a probe according to preoperative guide points;

[0038] Rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology is completed by using a probe; wherein the rigid registration includes two parts of coarse registration and fine registration;

[0039] According to the registration result, the coordinate systems of the mechanical arm, the optical positioning tracker and the knee joint are established;

[0040] The mechanical arm is controlled to move autonomously to reconstruct the bone tunnel.

[0041] Optionally, the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology is completed by using a probe, including:

[0042] First, the intraoperative registration points and the preoperative registration points are used for initial registration, and the position of the probe is located by using the digital twin method, and the three-dimensional bone is mapped into the color image, the position of the three-dimensional bone is monitored in real time by using the position of the probe tip, and the initial registration matrix is corrected;

[0043] According to the corrected initial registration matrix, the automatic adjustment of the registration matrix is performed again to obtain the final rigid registration matrix;

[0044] The method of digital twin is to track the probe in real time based on the multi-modal multi-scale fusion probe tracking algorithm, and to locate the position of the probe tip in real time by using the needle tip positioning algorithm based on multi-modal multi-scale fusion.

[0045] Optionally, the spine nail positioning navigation module is used for:

[0046] Fill in the basic information of the patient intraoperatively;

[0047] Take CT images of the patient's spine;

[0048] Three-dimensional registration is performed based on a three-dimensional calibrator;

[0049] Intraoperative planning and real-time positioning navigation.

[0050] Optionally, the trauma positioning navigation module is used for:

[0051] Fill in the basic information of the patient intraoperatively;

[0052] Take X-ray images of the trauma site of the patient;

[0053] Two-dimensional registration is performed based on a two-dimensional calibrator;

[0054] Intraoperative planning and real-time positioning navigation.

[0055] The embodiment of the present application provides a full orthopedic multi-disease artificial intelligence surgical robot system, which can quickly and accurately assist surgery.

[0056] The embodiment of the present application provides a full orthopedic multi-disease artificial intelligence surgical robot system, comprising:

[0057] A total hip replacement module is used for preoperative planning, intraoperative total hip replacement and real-time display;

[0058] A total knee replacement module is used for preoperative planning, intraoperative total knee replacement and real-time display;

[0059] A unicompartmental arthroplasty module is used for preoperative planning, intraoperative unicompartmental arthroplasty and real-time display;

[0060] A periacetabular osteotomy module is used for preoperative planning, intraoperative periacetabular osteotomy and real-time display;

[0061] A sports medicine module is used for bone tunnel planning and ligament reconstruction and real-time display;

[0062] A spine nail positioning navigation module is used for intraoperative spine nail positioning navigation and real-time display;

[0063] A trauma positioning navigation module is used for intraoperative trauma positioning navigation and real-time display. BRIEF DESCRIPTION OF DRAWINGS

[0064] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0065] Figure 1 is a module structure schematic diagram of the full orthopedic multi-disease artificial intelligence surgical robot system provided by an embodiment of the present application;

[0066] Figure 2 is a structure schematic diagram of an end gripper for total hip replacement provided by an embodiment of the present application;

[0067] Figure 3 is a structure schematic diagram of a medical bone drill for total hip replacement provided by an embodiment of the present application;

[0068] Figure 4 is a structure schematic diagram of an end connector for total knee or unicompartmental arthroplasty provided by an embodiment of the present application;

[0069] Figure 5It is a structural schematic diagram of a medical swing saw for total knee or unicompartmental knee arthroplasty provided by an embodiment of the present application.

[0070] Figure 6 It is a structural schematic diagram of a main light-emitting end for periacetabular osteotomy, sports medicine, spinal screw positioning navigation, and trauma positioning navigation provided by an embodiment of the present application.

[0071] Figure 7 It is a structural schematic diagram of a guide for periacetabular osteotomy, sports medicine, spinal screw positioning navigation, and trauma positioning navigation provided by an embodiment of the present application.

[0072] Figure 8 It is a system structural schematic diagram of a total orthopedic multi-disease artificial intelligence surgical robot provided by an embodiment of the present application.

[0073] Figure 9 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0074] The features and exemplary embodiments of various aspects of the present application will be described in detail below with reference to the drawings. The following description is merely intended to explain the present application, and is not intended to limit the present application. The present application can be implemented without some of the specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.

[0075] It should be noted that, in this document, the terms such as first and second are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between the entities or operations. Moreover, the terms “include”, “contain” or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the elements defined by the statement “include” do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0076] To solve the problems in the prior art, an embodiment of the present application provides a total orthopedic multi-disease artificial intelligence surgical robot system. First, the total orthopedic multi-disease artificial intelligence surgical robot system provided by an embodiment of the present application is introduced as follows.

[0077] Figure 1 is a module structure schematic diagram of the full orthopedic multi-disease artificial intelligence surgical robot system provided by an embodiment of the present application. As shown in the figure, the full orthopedic multi-disease artificial intelligence surgical robot system comprises: Figure 1

[0078] S101, a total hip arthroplasty module, for preoperative planning, intraoperative total hip arthroplasty, and real-time display;

[0079] S102, a total knee arthroplasty module, for preoperative planning, intraoperative total knee arthroplasty, and real-time display;

[0080] S103, a unicompartmental arthroplasty module, for preoperative planning, intraoperative unicompartmental arthroplasty, and real-time display;

[0081] S104, a periacetabular osteotomy module, for preoperative planning, intraoperative periacetabular osteotomy, and real-time display;

[0082] S105, a sports medicine module, for bone tunnel planning and ligament reconstruction, and real-time display;

[0083] S106, a spine screw placement positioning navigation module, for intraoperative spine screw placement positioning navigation, and real-time display;

[0084] S107, a trauma positioning navigation module, for intraoperative trauma positioning navigation, and real-time display.

[0085] In an embodiment, the total hip arthroplasty module is used for:

[0086] segmenting and three-dimensionally reconstructing a hip joint CT image to obtain a hip joint three-dimensional model;

[0087] performing preoperative planning based on the hip joint three-dimensional model;

[0088] performing intraoperative point cloud registration, grinding, pressing, positioning, navigation, and real-time display.

[0089] The functions of this module include hip joint CT image segmentation and three-dimensional reconstruction, preoperative planning, intraoperative point cloud registration, grinding, pressing, positioning, navigation, and real-time display. The specific step-by-step process is as follows:

[0090] 1. Preoperative preparation:

[0091] 1.1 Hip joint CT image acquisition:

[0092] Objective: To obtain the patient's hip joint CT scan data for subsequent processing.

[0093] Steps:

[0094] ​1. CT Scan: Perform multi-slice CT scan on the patient's hip joint area to obtain high-resolution cross-sectional image data.

[0095] 2. Image Data Transmission: Transmit the raw data from the CT scan to the image processing system of the total hip arthroplasty module.

[0096] 1.2 CT Image Segmentation:

[0097] Objective: Separate the hip joint and surrounding tissues from the CT image through automatic or semi-automatic segmentation algorithms.

[0098] Steps:

[0099] 1. Image Preprocessing: Perform noise reduction, contrast enhancement, and image filtering on the CT image to improve the effectiveness of subsequent segmentation.

[0100] 2. Segmentation Algorithm Application: Use deep learning-based or traditional segmentation algorithms (such as region growing, threshold segmentation, or convolutional neural network CNN) to segment structures such as the hip joint, femoral head, and acetabulum, generating binary or multi-class segmentation images of the hip joint area.

[0101] 3. Segmentation Result Correction: Manually correct the automatic segmentation results to ensure accurate segmentation of the joint area.

[0102] 1.3 Three-Dimensional Reconstruction:

[0103] Objective: Perform three-dimensional model reconstruction of the hip joint based on the segmented CT image.

[0104] Steps:

[0105] 1. Three-Dimensional Reconstruction Algorithm Application: Use volume rendering, surface reconstruction, and other three-dimensional modeling techniques to reconstruct the segmented hip joint image into a three-dimensional model, clearly displaying key structures such as the femoral head and acetabulum.

[0106] 2. Model Refinement: Smooth the reconstructed three-dimensional model to remove noise and irregular surfaces, making the model more realistic.

[0107] 3. Three-Dimensional Model Annotation: Annotate key points and anatomical structures of the hip joint for subsequent preoperative planning.

[0108] 1.4 Preoperative Planning:

[0109] Objective: Based on the three-dimensional reconstruction model, perform surgical simulation planning to ensure accurate intraoperative operation.

[0110] Steps:

[0111] 1. Prosthesis Selection: Select appropriate hip joint prosthesis size and size based on the patient's hip joint anatomical structure.

[0112] 2. Prosthetic implant position planning: Simulate the implant position, angle, and depth of the prosthesis on the three-dimensional model to ensure the best functional recovery of the prosthesis after surgery.

[0113] 3. Surgical path design: Design the operation path of grinding, cutting, and prosthesis implantation, and generate a surgical plan.

[0114] 2. Intraoperative operation:

[0115] 2.1 Point cloud registration:

[0116] Objective: Register the preoperative planned three-dimensional model with the point cloud data obtained during surgery to achieve accurate positioning.

[0117] Steps:

[0118] 1. Point cloud data acquisition: Use intraoperative three-dimensional scanners (such as laser scanning, optical scanning) to obtain point cloud data of the patient's hip joint in real time.

[0119] 2. Registration algorithm application: Perform rigid or non-rigid registration between the intraoperative point cloud data and the preoperative three-dimensional model to ensure consistency between intraoperative navigation and planning.

[0120] 3. Error correction: Optimize and correct errors through registration algorithms to ensure the accuracy of real-time display.

[0121] 2.2 Grinding and prosthesis implantation:

[0122] Objective: Under the guidance of the navigation system, grind and implant the prosthesis in the femoral head and acetabulum.

[0123] Steps:

[0124] 1. Navigation guidance: Guide the position and angle of surgical instruments through the navigation system to ensure the accuracy of grinding.

[0125] 2. Femoral head grinding: Guide surgical instruments to accurately grind the femoral head on the registered three-dimensional model, removing diseased tissue to prepare for prosthesis implantation.

[0126] 3. Acetabular modification: Cut and shape the acetabulum to ensure its fit with the prosthesis.

[0127] 4. Prosthesis implantation: According to the preoperative planned position and angle, accurately implant the prosthesis in the femoral head and acetabulum.

[0128] 2.3 Compression and positioning:

[0129] Objective: Ensure the firm combination of the prosthesis with the patient's bone and perform accurate intraoperative positioning.

[0130] Steps:

[0131] 1. Press-fit operation: The prosthesis is press-fitted together with the patient's femoral head or acetabulum through a special tool, ensuring the stability of the prosthesis.

[0132] 2. Intraoperative positioning confirmation: The actual position of the prosthesis is confirmed to be consistent with the planned position through intraoperative imaging equipment (such as X-ray or intraoperative CT), ensuring good postoperative prosthesis function.

[0133] 2.4 Intraoperative navigation and real-time display:

[0134] Objective: Guide the operation through real-time navigation system and display, ensure the accuracy of each step in the operation process.

[0135] Steps:

[0136] 1. Real-time navigation system starts: The navigation system tracks the position of surgical tools and prostheses in real time through the registered three-dimensional model, providing dynamic guidance for the operation.

[0137] 2. Real-time display during operation: Real-time display of three-dimensional models, surgical instruments, and prosthesis positions on the display helps surgeons perform precise operations.

[0138] 3. Dynamic adjustment: If deviations occur during the operation, adjust the operation path and tool position in real time to ensure accurate operation.

[0139] 3. Postoperative evaluation and tracking:

[0140] 3.1 Postoperative image evaluation

[0141] Objective: Evaluate the operation effect through imaging.

[0142] Steps:

[0143] 1. Postoperative CT or X-ray imaging examination: Postoperative imaging examination is performed on the patient to confirm whether the implantation position, angle of the prosthesis is consistent with the preoperative planning.

[0144] 2. Image comparison: Compare and analyze the postoperative image with the preoperative three-dimensional model to evaluate the success rate of the operation and the accuracy of the prosthesis.

[0145] 3.2 Postoperative tracking:

[0146] Objective: Track the postoperative recovery of patients to ensure the long-term stability of the prosthesis.

[0147] Steps:

[0148] 1. Regular imaging examination: Regular imaging examination is performed on the patient to track the stability of the prosthesis and the functional recovery of the hip joint.

[0149] 2. Functional assessment: through physical therapy and rehabilitation training, help patients recover hip joint function, regularly assess the patient's motor ability and the use effect of the prosthesis.

[0150] The specific process of the total hip replacement module covers segmentation and three-dimensional reconstruction of preoperative CT images, preoperative surgical planning, intraoperative point cloud registration, navigation guidance, grinding and polishing, prosthesis implantation and real-time display, postoperative image evaluation and functional tracking, ensuring high precision of the surgical process and postoperative rehabilitation effect of the patient.

[0151] Among them, the formula for generating a three-dimensional model of the hip joint and intraoperative registration is:

[0152]

[0153] M hip : the generated three-dimensional model of the hip joint for intraoperative navigation.

[0154] I CT (xyzt): three-dimensional voxel values of CT images changing with time t, defined in xyz space coordinates.

[0155] Laplacian operator of CT image, used to enhance the edge information of the image.

[0156] α: adjustment coefficient, used to control the smoothness of the image.

[0157] Ω CT : three-dimensional volume of CT image, integral region is the three-dimensional structure of the hip joint.

[0158] λ i : weight coefficient, controls the influence of intraoperative point cloud registration.

[0159] The i-th pre-processing point cloud registration coordinate changes with time.

[0160] The i-th postoperative point cloud registration coordinate.

[0161] Rigid transformation matrix R ij (t) is the corresponding registration matrix, used to align the postoperative coordinates with the preoperative coordinates.

[0162] Figure 2 is the structural diagram of the end gripper for total hip replacement provided by an embodiment of the present application, which is fixed at the end of the mechanical arm and used to hold the grinding and polishing rod and the press-fit rod.

[0163] Figure 3It is a structural schematic diagram of a medical bone drill for total hip arthroplasty provided by an embodiment of the present application. The medical bone drill is a power tool for reaming the acetabulum.

[0164] In one embodiment, a total knee arthroplasty module is provided for:

[0165] Segmenting and three-dimensionally reconstructing the knee CT image preoperatively to obtain a knee three-dimensional model;

[0166] Planning preoperatively based on the knee three-dimensional model;

[0167] Registering point clouds, cutting bones, balancing gaps, and displaying in real time intraoperatively.

[0168] The specific step-by-step procedure for the "total knee arthroplasty module" covers CT image segmentation and three-dimensional reconstruction preoperatively, preoperative planning, and point cloud registration, bone cutting, gap balancing, and real-time display intraoperatively. The specific steps are as follows:

[0169] 1. Preoperative preparation:

[0170] 1.1 Knee CT image acquisition:

[0171] Objective: To obtain the patient's knee CT scan data for subsequent model construction and surgical planning.

[0172] Steps:

[0173] 1. CT scanning: Perform high-resolution CT scanning of the patient's knee joint to obtain multi-slice tomographic images, ensuring the clarity of key parts of the knee joint.

[0174] 2. Image data import: Import the acquired knee CT images into the processing system of the total knee arthroplasty module.

[0175] 1.2 Knee CT image segmentation:

[0176] Objective: To extract the bone and soft tissue structures of the knee joint from the CT images through segmentation algorithms.

[0177] Steps:

[0178] 1. Image preprocessing: Perform noise reduction, image enhancement, and filtering on the CT images to enhance the contrast of joint edges and improve the accuracy of segmentation.

[0179] 2. Apply segmentation algorithms: Use deep learning algorithms (such as convolutional neural networks CNN) or traditional image processing methods (such as region growing, threshold segmentation, etc.) to segment the bones (femur, tibia, patella) and surrounding soft tissues of the knee joint.

[0180] 3. Manual correction: Based on the needs of the clinician, manually correct the segmentation results to ensure that the segmentation accuracy meets the requirements of the surgery.

[0181] 1.3 Three-dimensional reconstruction:

[0182] Objective: Based on the segmented CT images, reconstruct a three-dimensional model of the knee joint for subsequent preoperative planning.

[0183] Steps:

[0184] 1. Application of three-dimensional reconstruction technology: Use volume rendering or surface reconstruction technology to reconstruct the segmented knee joint structure into a three-dimensional model. The three-dimensional model should accurately display the bone structures such as femur, tibia and patella.

[0185] 2. Model smoothing: Smooth and eliminate noise on the reconstructed model to ensure the smoothness and authenticity of the model surface.

[0186] 3. Label key structures: Label important anatomical structures of the knee joint and mark important bone landmarks for subsequent surgical planning and navigation.

[0187] 1.4 Preoperative planning:

[0188] Objective: Based on the reconstructed three-dimensional model of the knee joint, perform preoperative planning for total knee arthroplasty to ensure accurate implementation of the surgery.

[0189] Steps:

[0190] 1. Prosthesis selection: Select the appropriate knee prosthesis size and specifications based on the three-dimensional model of the knee joint and anatomical structure, considering the size, type and material of the prosthesis.

[0191] 2. Bone cutting planning: Design the bone cutting plan on the three-dimensional model of the knee joint to determine the cutting surface, angle and depth, ensuring perfect fit of the prosthesis with the bone after surgery.

[0192] 3. Gap balancing design: Plan the gap balance between the femur and tibia to ensure the balance of the knee joint in extension and flexion after surgery, avoiding joint laxity or tension.

[0193] 4. Surgical path and tool planning: Design the specific surgical path and plan the tools used during the operation to determine the sequence of operations at key positions.

[0194] 2. Intraoperative operation:

[0195] 2.1 Point cloud registration

[0196] Objective: Accurately register the preoperative three-dimensional model with the point cloud data obtained during the operation to achieve real-time navigation.

[0197] Steps:

[0198] 1. Point Cloud Data Collection: Intraoperatively acquire real-time point cloud data of the knee joint using 3D scanning devices such as optical scanners or laser scanners.

[0199] 2. Registration Algorithm: Align the intraoperatively collected point cloud with the preoperatively planned three-dimensional model using rigid or non-rigid registration algorithms, ensuring accurate matching of the model with the actual anatomy.

[0200] 3. Error Correction: Utilize registration algorithms like Iterative Closest Point (ICP) to correct alignment errors between the point cloud data and the model, ensuring precision during intraoperative procedures.

[0201] 2.2 Bone Resection:

[0202] Objective: Perform precise bone resection on the femur and tibia according to preoperative planning for the installation of knee joint prostheses.

[0203] Steps:

[0204] 1. Bone Resection Navigation: Guide surgical instruments through the navigation system during surgery to accurately position the resection tools on the planned cutting surface.

[0205] 2. Femoral Bone Resection: Resect the distal end of the femur according to the preoperatively designed angle and position, ensuring a smooth and flat surface for the femoral prosthesis.

[0206] 3. Tibial Bone Resection: Cut the proximal end of the tibia according to the plan, ensuring precise interfacing of the tibial prosthesis with the prosthesis.

[0207] 4. Bone Resection Verification: Verify the accuracy of the resection during surgery through navigation or X-ray imaging, ensuring that the cutting surface and angle are consistent with the preoperative plan.

[0208] 2.3 Gap Balancing:

[0209] Objective: After bone resection, ensure gap balancing of the knee joint at different flexion angles, allowing the prosthesis to achieve a stable range of motion after implantation.

[0210] Steps:

[0211] 1. Gap Testing: After bone resection is complete, use gap testing tools to evaluate the anterior-posterior and medial-lateral gaps between the femur and tibia, ensuring balance in flexion and extension states.

[0212] 2. Adjustment and Optimization: Based on the results of gap testing, adjust the installation angle of the prosthesis or further modify the resection surface to ensure that the gap remains balanced during flexion and extension, avoiding joint laxity or tightness.

[0213] 3. Real-time balance adjustment: Display the gap balance of the knee joint in real-time through intraoperative navigation system, guide the doctor to further optimize the balance state.

[0214] 2.4 Intraoperative real-time display and navigation:

[0215] Objective: Ensure accurate operation at every step of the procedure through real-time navigation and display systems.

[0216] Steps:

[0217] 1. Navigation system activation: The intraoperative navigation system displays the surgical instruments, patient's bones, and the position of the prosthesis on a three-dimensional model in real-time, assisting the surgeon in accurately performing each step.

[0218] 2. Real-time display: Update the status of osteotomy, prosthesis implantation, and gap balance in real-time on the intraoperative display screen, helping the surgeon make immediate adjustments.

[0219] 3. Error correction and feedback: With the help of real-time navigation and display systems, the surgeon can fine-tune the surgical path, tool operation, etc. based on intraoperative feedback to ensure that the final result of the surgery is consistent with the preoperative plan.

[0220] 3. Postoperative evaluation and tracking:

[0221] 3.1 Postoperative imaging examination:

[0222] Objective: Confirm the accuracy of prosthesis implantation and the recovery of knee joint function through postoperative imaging.

[0223] Steps:

[0224] 1. Imaging examination: Through imaging methods such as X-ray, CT or MRI, evaluate whether the postoperative prosthesis implantation position, angle, and preoperative planning are consistent.

[0225] 2. Image comparison: Compare the postoperative image with the preoperative three-dimensional model to confirm the position of the prosthesis and the recovery of the knee joint.

[0226] 3.2 Postoperative tracking and rehabilitation:

[0227] Objective: Track the recovery of knee joint function in patients after surgery and monitor the long-term use of the prosthesis.

[0228] Steps:

[0229] 1. Regular examination: Monitor the use of knee joint prosthesis and the progress of patient recovery through regular imaging examination and functional evaluation.

[0230] 2. Functional rehabilitation evaluation: Help patients recover knee joint function through motion evaluation and rehabilitation training to ensure joint movement is flexible and stable.

[0231] The process of total knee arthroplasty module includes preoperative knee CT image segmentation and three-dimensional reconstruction, preoperative planning, intraoperative point cloud registration, osteotomy, gap balancing, real-time display and navigation, postoperative image evaluation and rehabilitation tracking, to ensure accurate implementation of the operation and maximize the effect of postoperative functional recovery of patients.

[0232] The three-dimensional model reconstruction of the knee joint and the osteotomy path formula are as follows:

[0233]

[0234] M knee : three-dimensional model of the knee joint, generated for surgery.

[0235] Segmentation function based on CT image gradient Extract the three-dimensional structure of the knee joint.

[0236] Ω knee : knee joint region of the CT image.

[0237] μ i (t): time-varying coefficient for controlling the osteotomy path of the knee joint.

[0238] Osteotomy path coordinates of the knee joint.

[0239] λ: regularization coefficient, controls the smoothness of the osteotomy path.

[0240] Laplacian of the osteotomy path, used to adjust the smoothness of the cutting surface.

[0241] In one embodiment, the unicompartmental arthroplasty module is used for:

[0242] Segmenting and three-dimensionally reconstructing the knee CT image to obtain a three-dimensional model of the knee joint;

[0243] Preoperative planning based on the three-dimensional model of the knee joint;

[0244] Intraoperative point cloud registration, osteotomy, gap balancing and real-time display.

[0245] Specifically, the preoperative segmentation and intraoperative cutting optimization formula in unicompartmental arthroplasty are as follows:

[0246]

[0247] M unicompartment : three-dimensional model of the unicompartmental joint and osteotomy result.

[0248] P unicompartment(x, y, z): structure of the unicompartmental joint in (x, y, z) space.

[0249] Gradient information of the unicompartmental joint, for segmentation and extraction of the structure.

[0250] β i : weight coefficient of the control cutting path.

[0251] f i (θ(t), φ(t)): function representing the cutting angle θ(t) and φ(t).

[0252] Γ cut : intraoperative cutting path.

[0253] γ: smoothing coefficient, for adjusting the smoothness of the cutting path.

[0254] Gradient of the cutting angle, representing the rate of change of the cutting angle over time.

[0255] Figure 4 is a structural schematic diagram of an end connector for total knee or unicompartmental joint replacement provided by an embodiment of the present application, which is fixed at the end of a mechanical arm and used for connecting a medical swing saw.

[0256] Figure 5 is a structural schematic diagram of a medical swing saw for total knee or unicompartmental joint replacement provided by an embodiment of the present application, which is used for bone cutting operation on femur and tibia.

[0257] In an embodiment, the acetabular periacetabular osteotomy module is used for preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display.

[0258] In an embodiment, the preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display include:

[0259] Obtaining the hip joint image of the patient;

[0260] Segmenting and three-dimensionally reconstructing the hip joint image to obtain a three-dimensional hip joint model;

[0261] Using the three-dimensional hip joint model, preoperatively planning the osteotomy surface, guide line and safety zone of the acetabular periacetabular osteotomy, determining the boundary of the safety zone, and rendering coloring; wherein the preoperative planning result includes planning osteotomy according to the anterior ischium, suprapubic branch, superior iliac bone and posterior column;

[0262] When performing osteotomy according to the preoperative planning result in combination with the infrared camera NDI reflective positioning navigation system and the positioning bracket on the arc blade of the osteotome, the position of the osteotome end is obtained in real time.

[0263] The specific procedure for the "Periacetabular Osteotomy Module" is explained as follows:

[0264] 1. Preoperative Preparation:

[0265] 1.1 Acquire Hip Joint Images:

[0266] Objective: To ensure clear and detailed joint images to guide subsequent processing.

[0267] Steps:

[0268] 1. Image Acquisition: Obtain image data of the patient's hip joint through CT or MRI scanning, focusing on joint structures and surrounding soft tissues.

[0269] 2. Image Import: Import the collected image data into the processing system for subsequent analysis.

[0270] 1.2 Image Segmentation and 3D Reconstruction:

[0271] Objective: Extract the three-dimensional structure of the hip joint to provide a basis for surgical planning.

[0272] Steps:

[0273] 1. Image Preprocessing: Improve image quality and enhance the visibility of joint edges through denoising and enhancement techniques.

[0274] 2. Apply Segmentation Algorithm: Use deep learning (such as CNN) or traditional image processing methods to segment the hip joint and extract key structures such as the acetabulum and femur.

[0275] 3. 3D Reconstruction: Create a three-dimensional model of the hip joint using segmented data to ensure that the model accurately reflects the patient's anatomical features.

[0276] 1.3 Preoperative Planning:

[0277] Objective: Develop an accurate osteotomy plan to ensure surgical success.

[0278] Steps:

[0279] 1. Osteotomy Surface Planning: Design the osteotomy surface around the acetabulum based on the three-dimensional model, following anatomical structures such as the anterior ischium, suprapubic branch, superior iliac bone, and posterior column.

[0280] 2. Guide Line and Safe Zone Determination: Draw surgical guide lines, define the safe zone for osteotomy, and mark its boundaries to avoid damaging important structures during surgery.

[0281] 3. Result Rendering: Visualize the planning results using rendering techniques, highlighting the osteotomy surface and safe zone through colorization, making it easier for doctors to assess preoperatively.

[0282] 2. Intraoperative procedure:

[0283] 2.1 Intraoperative registration

[0284] Objective: To ensure accurate alignment of the intraoperative navigation system with the patient's anatomy.

[0285] Steps:

[0286] 1. Infrared camera setup: Install the NDI reflective positioning navigation system to ensure real-time capture of positioning data in the surgical area.

[0287] 2. Initial positioning: Preliminary registration based on preoperative planning models and actual anatomical structures to ensure accurate navigation system.

[0288] 2.2 Osteotomy:

[0289] Objective: Accurately implement osteotomy operations according to the plan.

[0290] Steps:

[0291] 1. Bone knife positioning: Fix the curved blade of the bone knife through the positioning frame at the predetermined osteotomy position, ensuring compliance with the preoperative plan.

[0292] 2. Real-time monitoring: During the osteotomy process, the navigation system obtains the position of the bone knife tip in real time, monitoring its deviation from the planned results.

[0293] 3. Implement osteotomy: Perform osteotomy according to the preoperative plan to ensure the accuracy of the cutting angle and depth.

[0294] 2.3 Positioning and navigation:

[0295] Objective: Achieve real-time feedback to ensure surgical precision.

[0296] Steps:

[0297] 1. Real-time feedback: During the osteotomy process, the system displays the comparison of the bone knife position with the preoperative plan to ensure surgical accuracy.

[0298] 2. Adjustment and optimization: Based on real-time data, adjust the position of the bone knife as needed to ensure that the final results of the operation meet expectations.

[0299] 3. Postoperative evaluation:

[0300] 3.1 Postoperative examination

[0301] Objective: Verify the effectiveness of osteotomy and the recovery of joint function.

[0302] Steps:

[0303] 1. Imaging examination: Use imaging techniques such as X-ray or CT to evaluate the accuracy of osteotomy and the recovery of bone structure.

[0304] 2. Effect evaluation: confirm the functional status of the hip joint after surgery, including range of motion and stability, and evaluate the effectiveness of the surgery.

[0305] The entire acetabular periacetabular osteotomy module includes preoperative image acquisition, segmentation and three-dimensional reconstruction, preoperative accurate planning, intraoperative real-time registration, osteotomy and navigation, postoperative examination and evaluation, to ensure high precision of surgical implementation and good recovery of patients. This module combines modern imaging technology and navigation system to improve the safety and effectiveness of surgery and promote the development of joint replacement surgery.

[0306] Specifically, the osteotomy surface and positioning optimization formula for periacetabular osteotomy are as follows:

[0307]

[0308] S cut : Osteotomy surface of acetabulum.

[0309] P acetadular (x, y, z): Three-dimensional structure around the acetabulum.

[0310] P safe (x, y, z): Three-dimensional coordinates of the safety area.

[0311] κ(θ, ψ): Curvature function on the osteotomy path, which depends on angles θ and ψ.

[0312] Ω acetabular : Three-dimensional spatial region of the acetabulum.

[0313] λ i : Weight coefficient for adjusting the positioning accuracy of the infrared camera.

[0314] Real-time position information of the bone cutter tip changes with time t.

[0315] In one embodiment, the sports medicine module is used for:

[0316] Obtaining a first knee joint CT image;

[0317] Deep learning-based neural network CT image segmentation;

[0318] According to the segmentation result, knee joint 3D modeling is performed;

[0319] Setting preoperative guide points and planning preoperative registration points in the knee joint;

[0320] Bone tunnel planning and ligament reconstruction;

[0321] During the operation, the probe is used to collect intraoperative registration points according to the preoperative guide points;

[0322] The rigid registration of the preoperative registration point and the intraoperative registration point based on the digital twin technology is completed by using the probe; wherein, the rigid registration includes two parts of coarse registration and fine registration;

[0323] The coordinate system of the mechanical arm, the optical positioning tracker and the knee joint is established according to the registration result;

[0324] The bone tunnel reconstruction is performed by controlling the autonomous movement of the mechanical arm.

[0325] In one embodiment, the rigid registration of the preoperative registration point and the intraoperative registration point based on the digital twin technology is completed by using the probe, including:

[0326] First, the initial registration is performed using the intraoperative registration point and the preoperative registration point, and the position of the probe is located by using the digital twin method, and the three-dimensional bone is mapped into the color image, the position of the three-dimensional bone is monitored in real time by using the position of the probe tip, and the initial registration matrix is corrected;

[0327] According to the corrected initial registration matrix, the automatic adjustment of the registration matrix is performed again to obtain the final rigid registration matrix;

[0328] The method of digital twin is to track the probe in real time based on the multi-modal multi-scale fusion probe tracking algorithm, and to locate the position of the probe tip in real time by using the needle tip positioning algorithm based on multi-modal multi-scale fusion.

[0329] The detailed description of the specific step process of the "sports medicine module" is as follows:

[0330] 1. Preoperative preparation:

[0331] 1.1 Obtain the first knee CT image:

[0332] Steps:

[0333] 1. Patient preparation: Ensure patient comfort and inform the scanning process.

[0334] 2. CT scanning: Use a high-resolution CT scanner to image the knee joint, ensure that the scan covers all important structures of the joint, and obtain high-quality images.

[0335] 3. Data saving: Store the scan results in DICOM format for subsequent processing.

[0336] 1.2 CT image segmentation based on deep learning neural network:

[0337] Steps:

[0338] 1. Data preprocessing: Preprocess the CT image, including denoising and contrast enhancement, to improve the segmentation effect.

[0339] 2. Model training: Select an appropriate deep learning model (e.g., U-Net) and train it using labeled knee joint images to optimize model parameters.

[0340] 3. Image segmentation: Apply the trained model to segment the CT images, automatically extracting structures such as the knee joint, bones, and soft tissues, and generating binary segmentation results.

[0341] 1.3 Knee joint 3D modeling based on segmentation results:

[0342] Steps:

[0343] 1. Generate a three-dimensional model: Convert the segmented binary image data into a three-dimensional mesh model using three-dimensional reconstruction software (e.g., MeshLab).

[0344] 2. Model optimization: Smooth the three-dimensional model to remove noise and unnecessary details, ensuring the accuracy and visualization of the model.

[0345] 3. Model verification: Compare the three-dimensional model with the doctor's professional knowledge to verify whether it accurately reflects the anatomical structure of the knee joint.

[0346] 2. Preoperative planning:

[0347] 2.1 Set preoperative guide points and plan preoperative registration points

[0348] Steps:

[0349] 1. Guide point calibration: Select key anatomical landmarks on the 3D model and set preoperative guide points, such as the anterior cruciate ligament and posterior cruciate ligament attachment points of the knee joint.

[0350] 2. Registration point selection: Select multiple registration points according to the bone tunnel planning and record their coordinates on the three-dimensional model as the basis for intraoperative registration.

[0351] 2.2 Bone tunnel planning and ligament reconstruction:

[0352] Steps:

[0353] 1. Tunnel planning design: Use professional software (e.g., Mimics) to design the path of the bone tunnel, ensuring its safety and compliance with biomechanical requirements.

[0354] 2. Ligament reconstruction strategy: Determine the reconstruction scheme, define the type and location of ligaments to be reconstructed, and develop the surgical steps.

[0355] 3. Intraoperative operation:

[0356] 3.1 Use a probe to collect intraoperative registration points

[0357] Steps:

[0358] 1. Probe Preparation: Select a suitable probe for the procedure, ensuring it can be accurately positioned.

[0359] 2. Intraoperative Positioning: During the procedure, use the probe to physically locate the guide points and registration points set preoperatively, recording the probe's position.

[0360] 3.2 Rigid Registration Based on Digital Twin Technology:

[0361] Steps:

[0362] 1. Initial Registration Implementation: Preliminary registration of intraoperative registration points with preoperative points to form an initial registration matrix.

[0363] 2. Digital Twin Positioning: Use digital twin technology to position the probe in real-time, ensuring accurate mapping of the probe's position in three-dimensional space.

[0364] 3. Three-Dimensional Mapping and Monitoring: Map the three-dimensional bone model onto real-time color images, monitor the three-dimensional model using the probe tip position, and correct the initial registration matrix.

[0365] 3.3 Automatic Adjustment of Registration Matrix:

[0366] Steps:

[0367] 1. Matrix Correction: Correct the initial registration matrix based on real-time data feedback to ensure accuracy.

[0368] 2. Final Registration: Further adjust the registration matrix through automatic algorithms to generate a final rigid registration matrix.

[0369] 4. Coordinate System Establishment:

[0370] 4.1 Establishing the Coordinate Systems of the Robotic Arm, Optical Positioning Tracker, and Knee Joint

[0371] Steps:

[0372] 1. Coordinate System Calibration: Calibrate the coordinate systems of the robotic arm and optical positioning system based on the final rigid registration matrix.

[0373] 2. Coordinate System Integration: Ensure the coordinate systems of the robotic arm, optical system, and knee joint are consistent to achieve seamless collaboration.

[0374] 5. Bone Tunnel Reconstruction:

[0375] 5.1 Control the Robotic Arm to Independently Move for Bone Tunnel Reconstruction

[0376] Steps:

[0377] 1. Robotic Arm Control Program: Based on the registration results, write a control program for the robotic arm to accurately perform bone tunnel reconstruction operations.

[0378] 2. Reconstruction Operation Execution: Start the robotic arm, follow the preset tunnel planning path for reconstruction, and monitor parameters and status in real time to ensure the accuracy of the operation.

[0379] 6. Digital Twin Technology Application:

[0380] 6.1 Probe Tracking and Positioning:

[0381] Steps:

[0382] 1. Real-time Probe Tracking: Use a multi-modal and multi-scale fusion probe tracking algorithm to continuously track the position of the probe in three-dimensional space.

[0383] 2. Needle Tip Positioning Algorithm Application: Use a multi-modal and multi-scale fusion needle tip positioning algorithm to obtain the specific position of the probe needle tip in real time, ensuring the accuracy and stability of its positioning.

[0384] This module describes the complete process of bone tunnel reconstruction, from preoperative CT image acquisition, deep learning segmentation, three-dimensional modeling, to preoperative guide point and registration point setting, to the use of intraoperative probes, digital twin technology application, and autonomous movement of the robotic arm. By combining advanced image processing, artificial intelligence, real-time monitoring, and mechanical control technologies, this module significantly improves the accuracy and safety of knee surgery, helping to improve postoperative recovery outcomes for patients.

[0385] Specifically, the optimization formula for bone tunnel reconstruction and registration is:

[0386]

[0387] T bone (x,y,z,t): Three-dimensional model of bone tunnel reconstruction, changes with time t, used for intraoperative navigation.

[0388] Ω bone : Three-dimensional region of the bone tunnel.

[0389] Expected coordinates of the preoperative bone tunnel, defined in the x', y', z' space, and changes with time t.

[0390] G(x-x', y-y', z-z'): Gaussian kernel function, used to smooth the changes in bone tunnel coordinates and adjust the smoothness between different positions.

[0391] α: Regularization coefficient, controls the influence of preoperative and postoperative registration points.

[0392] Coordinates of the postoperative bone tunnel as a function of time t.

[0393] In one embodiment, the spinal nail positioning navigation module is used for:

[0394] Filling in the patient's basic information during surgery;

[0395] Taking CT images of the patient's spine;

[0396] Three-dimensional registration based on three-dimensional calibrators;

[0397] Intraoperative planning and real-time positioning navigation.

[0398] The specific step-by-step process of the "spinal nail positioning navigation module" is further detailed and complexed as follows:

[0399] 1. Preoperative preparation:

[0400] 1.1 Fill in the patient's basic information during surgery:

[0401] Step:

[0402] 1. Patient information collection:

[0403] Use the electronic health record system to input the patient's basic information, including name, age, gender, medical record number, etc.

[0404] Record the patient's medical history, allergic reactions, and existing diseases to fully understand the patient's condition for the surgical team.

[0405] 2. Preoperative discussion:

[0406] Hold a team meeting before surgery to discuss the patient's specific situation and decide on the best surgical plan.

[0407] Confirm the surgical team members, anesthesia plan, and postoperative care arrangements.

[0408] 1.2 Take CT images of the patient's spine:

[0409] Step:

[0410] 1. Patient positioning:

[0411] Place the patient on the CT scanner, ensuring that the midline of the spine is aligned with the scanning center to avoid image distortion due to posture deviation.

[0412] Use positioning tools such as laser positioners to ensure the accuracy of the patient's position.

[0413] 2. CT scan execution:

[0414] Select appropriate scanning parameters (such as slice thickness, reconstruction algorithm) to ensure high-quality spine images.

[0415] Multiple phase scans (e.g., transverse, sagittal, and coronal) are performed to obtain more comprehensive anatomical information.

[0416] 3. Data processing and storage:

[0417] After scanning, the images are post-processed using specialized image processing software, including denoising, contrast enhancement, and reconstruction.

[0418] The results are saved in DICOM format to a secure storage server, ensuring that the images can be called upon at any time during the operation.

[0419] 2. Intraoperative procedures:

[0420] 2.1 Three-dimensional registration based on three-dimensional calibrator:

[0421] Steps:

[0422] 1. Installation of three-dimensional calibrator:

[0423] The three-dimensional calibrator is precisely installed on the patient's spinal area, ensuring alignment with anatomical features such as vertebral body edges.

[0424] Use a special fixture to secure the calibrator to prevent movement during the operation.

[0425] 2. Image registration process:

[0426] Through an optical or laser tracking system, real-time position information of the calibrator is obtained and registered with the CT image.

[0427] Apply registration algorithms (such as rigid registration and non-rigid registration) to align the CT image with the actual anatomical structure of the patient through iterative optimization calculations.

[0428] 3. Registration verification:

[0429] By comparing the position of the calibrator in the CT image with the actual position, use statistical analysis methods (such as root mean square error) to evaluate the registration accuracy.

[0430] If there is a deviation, adjust the position of the calibrator and repeat the registration process until the accuracy requirements are met.

[0431] 2.2 Intraoperative planning and real-time positioning navigation:

[0432] Steps:

[0433] 1. Navigation path planning:

[0434] Based on the registered CT image, use professional software (such as navigation system integrated software) to design the screw placement path, ensuring avoidance of important neural and vascular structures.

[0435] Determine the angle, depth, and relative position of the nail placement, develop a detailed surgical plan, and generate a surgical guide map.

[0436] 2. Real-time monitoring and feedback:

[0437] Start the navigation system, monitor the position of the probe or nail through optical or electromagnetic locators, and update the position information in real time on the display screen.

[0438] Apply data fusion technology to superimpose real-time position information on CT images to provide visual navigation support.

[0439] 3. Navigation operation:

[0440] The doctor adjusts the direction and position of the probe or nail according to the real-time feedback provided by the navigation system to ensure accurate insertion into the predetermined position.

[0441] Throughout the operation, maintain communication with the surgical team and handle potential problems in a timely manner to ensure smooth operation.

[0442] 3. Postoperative steps:

[0443] 3.1 Data recording and analysis

[0444] Step:

[0445] 1. Postoperative data processing:

[0446] Record key data during the operation, including position, angle, depth, and other parameters provided by the navigation system.

[0447] Collect intraoperative real-time images and final images for comparative analysis.

[0448] 2. Result evaluation:

[0449] Postoperative comparison of navigation path and actual nail placement to evaluate the accuracy and success rate of nail placement.

[0450] Based on the postoperative evaluation results, provide improvement suggestions for future operations.

[0451] This module describes the complete process from preoperative patient information entry, CT image shooting, to three-dimensional marker installation and registration, and finally to real-time navigation planning and monitoring. By introducing complex technical means and data analysis methods, the accuracy and safety of spinal nail placement surgery are ensured, and the treatment effect and recovery efficiency of patients are ultimately improved.

[0452] Specifically, the three-dimensional registration and positioning formula in spinal nail placement is:

[0453]

[0454] Espine (x, y, z, t): registration error function in spine drilling, varies with time t.

[0455] Ω spine : three-dimensional spatial region of the spine.

[0456] Preoperative spine registration point coordinates, vary with time.

[0457] Postoperative spine registration point coordinates.

[0458] R spine (x, y, z): rigid rotation matrix, used to rotate postoperative coordinates to preoperative position.

[0459] Gradient of the spine, used to calculate the rate of coordinate change.

[0460] λ: regularization parameter, used to control the smoothness of positioning.

[0461] Intraoperative position information of surgical tools.

[0462] In one embodiment, the trauma positioning and navigation module is used for:

[0463] Fill in the patient's basic information during surgery;

[0464] Take X-ray images of the patient's trauma site;

[0465] Two-dimensional registration based on two-dimensional calibrator;

[0466] Intraoperative planning and real-time positioning and navigation.

[0467] Regarding the specific step-by-step process of "trauma positioning and navigation module", further details and complexity are as follows:

[0468] 1. Preoperative preparation:

[0469] 1.1 Fill in the patient's basic information during surgery:

[0470] Step:

[0471] 1. Electronic information system input:

[0472] Use electronic health record system in operating room, accurately enter patient's basic information (name, gender, age, medical record number, etc.).

[0473] Record patient's medical history (including allergy, chronic disease, etc.), ensure that the surgical team fully understands the patient's health status.

[0474] 2. Preoperative case discussion:

[0475] Conduct a multidisciplinary team meeting to review the patient's medical history, imaging results, and discuss surgical risks and expected outcomes.

[0476] Determine the division of labor among the surgical team and postoperative rehabilitation plan, ensuring that each team member understands their responsibilities.

[0477] 1.2 Take X-ray images of the patient's trauma site:

[0478] Steps:

[0479] 1. Patient positioning:

[0480] Position the patient under the X-ray machine and adjust their posture to ensure optimal visualization of the trauma area.

[0481] Use airbag supports or other fixation devices to stabilize the trauma site, ensuring it does not move during the shooting process.

[0482] 2. Multiple-angle X-ray shooting:

[0483] Choose multiple viewing angles (such as frontal, lateral, and oblique) for X-ray shooting to ensure comprehensive trauma information is obtained.

[0484] Set appropriate exposure parameters (such as kilovoltage characteristics and milliamperage) to improve image quality and reduce radiation dose.

[0485] 3. Image post-processing:

[0486] Post-process X-ray images through image processing software, including noise reduction, contrast enhancement, and pseudo-color processing, to improve the visibility of anatomical structures.

[0487] Store the processed images in DICOM format and associate them with the patient's file, ensuring they can be accessed at any time during surgery.

[0488] 2. Intraoperative operation:

[0489] 2.1 Two-dimensional registration based on two-dimensional markers

[0490] Steps:

[0491] 1. Marker installation and calibration:

[0492] Accurately fix the two-dimensional marker on the patient's trauma site, ensuring that the key points of the marker are consistent with the surrounding anatomical structures (such as bones and soft tissues).

[0493] Use a three-dimensional laser scanner to perform preliminary scanning of the marker and surrounding structures to ensure their position is stable and accurately recorded.

[0494] 2. Two-dimensional registration process:

[0495] The X-ray images taken during the operation are registered with the marker, and professional image processing software is used for feature matching and position correction.

[0496] Using image fusion technology, the preoperative CT images are combined with the intraoperative X-ray images, and the position of the marker is accurately aligned with the trauma site through algorithm optimization.

[0497] 3. Verification of registration accuracy:

[0498] Compare the registration results with the actual position of the marker in the X-ray image, and evaluate the accuracy of registration through statistical analysis (such as standard deviation, root mean square error).

[0499] If deviations are found, adjust the position of the marker and perform re-registration until the registration results meet the clinical requirements.

[0500] 2.2 Intraoperative planning and real-time positioning navigation:

[0501] Steps:

[0502] 1. Navigation path and target point planning:

[0503] Based on registration, use the navigation system software to develop the surgical path of the trauma site and clearly define the key points (such as the position of the bone nail, incision position, etc.).

[0504] According to the anatomical features, trauma type and expected results, generate a detailed surgical guide map, including the coordinates, angles and depths of each key operation point.

[0505] 2. Real-time monitoring and feedback system starts:

[0506] Start the navigation system and continuously track the real-time position of surgical instruments (such as probes, bone nails) through optical or electromagnetic locators.

[0507] Compare the real-time position information with the planned path dynamically to provide real-time feedback and ensure that the doctor adjusts the operation direction and intensity in time.

[0508] 3. Precise operation execution:

[0509] The doctor adjusts the position of the probe or bone nail according to the real-time data provided by the navigation system to ensure accurate insertion into the predetermined position.

[0510] Continuously monitor the motion trajectory of the probe or bone nail during the operation and use intelligent algorithms to identify potential risks and issue warnings in time.

[0511] 3. Postoperative steps:

[0512] 3.1 Data recording and analysis:

[0513] Steps:

[0514] 1. Surgical data organization and archiving:

[0515] Record key data during the procedure, including position, angle, depth, and other parameters provided by the navigation system.

[0516] Integrate surgical images, navigation data, registration results, and procedure records into the patient's electronic health record.

[0517] 2. Postoperative outcome analysis and evaluation:

[0518] Compare the navigation path during the procedure with the actual trauma treatment results, evaluate the accuracy of the nail placement, the success rate of the operation, and possible complications.

[0519] Based on the evaluation results, conduct postoperative discussions, provide improvement suggestions for future similar cases, and enhance team collaboration and learning.

[0520] This module describes in detail the complete process from preoperative patient information entry, X-ray image shooting, to two-dimensional marker installation and registration, and finally to real-time navigation planning and monitoring. By introducing complex technical means and data analysis methods, the accuracy and safety of trauma surgery are ensured, the treatment effect and recovery efficiency of patients are improved, and the development of medical technology is promoted.

[0521] Specifically, the two-dimensional registration and navigation formula for the trauma site is:

[0522]

[0523] The two-dimensional registration result of the trauma site changes over time.

[0524] Ω trauma : Two-dimensional image area of the trauma site.

[0525] The coordinates of the registration points of the initial trauma site change over time.

[0526] G(x-x′,y-y′): Gaussian kernel function, used to smooth the relationship between trauma registration points.

[0527] Gradient information of two-dimensional image.

[0528] λ: Regularization coefficient used to control the smoothness of trauma site positioning.

[0529] The position information of the intraoperative trauma positioning tool changes over time.

[0530] Figure 6is a structural schematic diagram of an active light-emitting tip for periacetabular osteotomy, sports medicine, spine screw positioning navigation, and trauma positioning navigation provided by an embodiment of the present application. The active light-emitting tip is fixed at the end of a mechanical arm and is used for positioning.

[0531] Figure 7 is a structural schematic diagram of a guide for periacetabular osteotomy, sports medicine, spine screw positioning navigation, and trauma positioning navigation provided by an embodiment of the present application. The guide is used for trauma function sleeve positioning.

[0532] Figure 8 is a system structure schematic diagram of an all-orthopedic multi-disease artificial intelligence surgical robot provided by an embodiment of the present application. Figure 8 The navigation trolley, the mechanical arm trolley, and the main control trolley are arranged from left to right in the middle.

[0533] Figure 9 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown.

[0534] The electronic device can include a processor 901 and a memory 902 having stored computer program instructions.

[0535] Specifically, the processor 901 described above can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured as one or more integrated circuits that implement an embodiment of the present application.

[0536] The memory 902 can include a mass storage for data or instructions. By way of example and not limitation, the memory 902 can include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 902 can include removable or non-removable (or fixed) media. Where appropriate, the memory 902 can be internal or external to the electronic device. In a particular embodiment, the memory 902 can be a non-volatile solid-state memory.

[0537] In one embodiment, the memory 902 can be a read-only memory (ROM). In one embodiment, the ROM can be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0538] The processor 901 implements any of the above-described methods by reading and executing computer program instructions stored in the memory 902.

[0539] In one example, the electronic device can further include a communication interface 903 and a bus 910. Wherein, as shown in the figure, the processor 901, the memory 902, the communication interface 909 are connected through the bus 910 and complete the communication between each other. Figure 9

[0540] The communication interface 903 is mainly used to realize the communication between each module, device, unit and / or equipment in the embodiments of the present application.

[0541] The bus 910 includes hardware, software or both to couple components of the electronic device to each other. By way of example, and not limitation, the bus can include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or combination of two or more of these. Where appropriate, the bus 910 can include one or more buses. Although the present application describes and illustrates a particular bus, the present application contemplates any suitable bus or interconnect.

[0542] It needs to be clear that the present application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of well-known methods are omitted here. In the above-described embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between steps, after understanding the spirit of the present application.

[0543] ​The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in unit, a function card or the like. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0544] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0545] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. This processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be implemented by the dedicated hardware that performs the specified function or action, or can be implemented by the combination of dedicated hardware and computer instructions.

[0546] The above merely describes a specific implementation of the present application. Those skilled in the art can clearly understand the specific working processes of the system, modules and units described above for the convenience and brevity of description, and can refer to the corresponding processes in the foregoing method embodiments, which will not be described herein again. It should be understood that the protection scope of the present application is not limited to this, and any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. An artificial intelligence surgical robot system for all orthopedic diseases, characterized by: include: Total hip replacement module, used for preoperative planning, intraoperative total hip replacement and real-time display; Total knee replacement module, used for preoperative planning, intraoperative total knee replacement and real-time display; Unicompartmental knee arthroplasty module, used for preoperative planning, intraoperative unicompartmental knee arthroplasty and real-time display; A periacetabular osteotomy module is used for preoperative planning, intraoperative periacetabular osteotomy and real-time display; the periacetabular osteotomy module is used for: preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display, including obtaining a patient's hip joint image; segmenting and 3D reconstructing the hip joint image to obtain a 3D model of the hip joint; using the 3D model of the hip joint, preoperatively planning the osteotomy surface, guide line and safety zone of the periacetabular osteotomy, determining the boundary of the safety zone, and rendering and coloring; wherein, the results of the preoperative planning include planning osteotomy according to the anterior ischium, superior pubic ramus, upper ilium and posterior column; intraoperatively, combining the infrared camera NDI reflective positioning navigation system and the positioning frame on the curved blade of the bone knife, when performing osteotomy according to the results of the preoperative planning, the end position of the bone knife is obtained in real time; A sports medicine module is used for bone tunnel planning and ligament reconstruction and real-time display; the sports medicine module is used to obtain a first knee joint CT image; perform deep learning-based neural network CT image segmentation; perform 3D modeling of the knee joint based on the segmentation results; set preoperative guidance points and plan preoperative registration points on the knee joint; perform bone tunnel planning and ligament reconstruction; use a probe to collect intraoperative registration points based on the preoperative guidance points during surgery; use the probe to perform rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology; wherein the rigid registration includes coarse registration and fine registration; establish the coordinate system of the robotic arm, optical positioning tracker, and knee joint based on the registration results; and control the autonomous movement of the robotic arm to perform bone tunnel reconstruction. Spinal nail positioning navigation module, used for intraoperative spinal nail positioning navigation and real-time display; Trauma positioning and navigation module, used for intraoperative trauma positioning and navigation and real-time display.

2. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Total hip replacement module for: Before surgery, the hip joint CT images were segmented and 3D reconstructed to obtain a 3D model of the hip joint; Preoperative planning based on a three-dimensional model of the hip joint; Intraoperative point cloud registration, filing, press-fitting, positioning, navigation and real-time display.

3. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Total knee replacement module for: Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint; Preoperative planning based on a three-dimensional model of the knee joint; Intraoperative point cloud registration, osteotomy, gap balance and real-time display.

4. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Unicompartmental knee replacement modules for: Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint; Preoperative planning based on a three-dimensional model of the knee joint; Intraoperative point cloud registration, osteotomy, gap balance and real-time display.

5. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: The probe is used to complete the rigid registration of preoperative and intraoperative registration points based on digital twin technology, including: Initial registration is performed using intraoperative and preoperative registration points. A digital twin approach is used to locate the probe and map the 3D skeleton to a color image. The probe tip position is used to monitor the 3D skeleton position in real time and to correct the initial registration matrix. The registration matrix is ​​automatically adjusted again according to the modified initial registration matrix to obtain the final rigid registration matrix; The digital twin method is to track the probe in real time using a probe tracking algorithm based on multimodal and multiscale fusion, and to locate the position of the probe tip in real time using a needle tip positioning algorithm based on multimodal and multiscale fusion.

6. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Spinal screw positioning navigation module, used for: Fill in the patient's basic information during the operation; Take CT images of the patient's spine; Perform 3D registration based on a 3D calibrator; Intraoperative planning and real-time positioning navigation.

7. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Trauma localization navigation module, used for: Fill in the patient's basic information during the operation; Take X-ray images of the patient's injured area; Perform 2D registration based on a 2D calibrator; Intraoperative planning and real-time positioning navigation.

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