Multi-disease artificial intelligence surgical robot system for whole orthopedics department

Abstract

The invention provides a multi-disease artificial intelligence surgical robot system for the whole orthopedics department, and the system comprises a total hip joint replacement module which is used for preoperative planning, intraoperative total hip joint replacement and real-time display; the total knee joint replacement module is used for preoperative planning, intraoperative total knee joint replacement and real-time display; the unicondylar joint replacement module is used for preoperative planning, intraoperative unicondylar joint replacement and real-time display; the acetabulum periphery osteotomy module is used for pre-operation planning, acetabulum periphery osteotomy during operation and real-time display; the sports medicine module is used for bone tunnel planning and ligament reconstruction and real-time display; the spine screw placement positioning navigation module is used for positioning navigation and real-time display of intraoperative spine screw placement; and the trauma positioning and navigation module is used for performing trauma positioning and navigation and real-time display during operation. According to the embodiment of the invention, the auxiliary operation can be quickly and accurately carried out.

Description

Technical Field

[0001] The present application belongs to the field of surgical robot technology, and in particular, relates to an artificial intelligence surgical robot system for all orthopedic diseases. Background Art

[0002] At present, total hip replacement, total knee replacement, unicompartmental hip replacement, periacetabular osteotomy, sports medicine, spinal screw placement navigation and trauma positioning navigation are mainly performed by doctors based on their experience, but with poor efficiency and accuracy.

[0003] Therefore, how to perform assisted surgery quickly and accurately is a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0004] The embodiment of the present application provides an artificial intelligence surgical robot system for all orthopedic diseases, which can perform assisted surgery quickly and accurately.

[0005] The present application provides an artificial intelligence surgical robot system for all orthopedic diseases, including:

[0006] Total hip replacement module, used for preoperative planning, intraoperative total hip replacement and real-time display;

[0007] Total knee replacement module, used for preoperative planning, intraoperative total knee replacement and real-time display;

[0008] Unicompartmental hip replacement module, used for preoperative planning, intraoperative unicompartmental hip replacement and real-time display;

[0009] Acetabular osteotomy module, used for preoperative planning, intraoperative acetabular osteotomy and real-time display;

[0010] Sports medicine module, used for bone tunnel planning and ligament reconstruction with real-time display;

[0011] Spinal screw placement navigation module, used for intraoperative spinal screw placement navigation and real-time display;

[0012] Trauma localization and navigation module, used for intraoperative trauma localization and navigation and real-time display.

[0013] Optional, Total Hip Replacement Module for:

[0014] Before surgery, the hip joint CT images were segmented and 3D reconstructed to obtain a 3D model of the hip joint;

[0015] Preoperative planning based on a three-dimensional model of the hip joint;

[0016] Intraoperative point cloud registration, filing, press-fitting, positioning, navigation and real-time display.

[0017] Optional, Total Knee Replacement Module for:

[0018] Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint;

[0019] Preoperative planning based on a three-dimensional model of the knee joint;

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

[0021] Optional, Unicompartmental Hip Replacement Module for:

[0022] Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint;

[0023] Preoperative planning based on a three-dimensional model of the knee joint;

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

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

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

[0027] Obtain an image of the patient's hip joint;

[0028] Segment and 3D reconstruct the hip joint image to obtain a 3D model of the hip joint;

[0029] Using the three-dimensional model of the hip joint, the osteotomy surface, guide line and safety zone of the acetabular periarthrodesis are preoperatively planned, the safety zone boundary is determined, and the image is rendered and colored; the results of preoperative planning include planning osteotomy according to the anterior part of the sciatic bone, the superior pubic ramus, the upper ilium, and the posterior column;

[0030] During the operation, the infrared camera NDI reflective positioning navigation system and the positioning frame on the curved blade of the bone knife are combined to obtain the end position of the bone knife in real time when osteotomy is performed according to the results of preoperative planning.

[0031] Optional, Sports Medicine module for:

[0032] Obtain the first knee joint CT image;

[0033] CT image segmentation based on neural network based on deep learning;

[0034] Perform 3D modeling of the knee joint based on the segmentation results;

[0035] Set preoperative guidance points and plan preoperative registration points at the knee joint;

[0036] Bone tunnel planning and ligament reconstruction;

[0037] During surgery, a probe was used to collect intraoperative registration points based on the preoperative guidance points;

[0038] The probe is used to complete the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology; among them, rigid registration includes coarse registration and fine registration;

[0039] The coordinate system of the robot arm, optical positioning tracker and knee joint is established according to the registration results;

[0040] Control the autonomous movement of the robotic arm to perform bone tunnel reconstruction.

[0041] Optionally, the probe is used to complete the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology, including:

[0042] First, the intraoperative registration points and preoperative registration points are used for initial registration. At the same time, the digital twin method is used to locate the position of the probe and map the 3D bone into the color image. The position of the probe tip is used to monitor the position of the 3D bone in real time and correct the initial registration matrix.

[0043] The registration matrix is ​​automatically adjusted again according to the corrected initial registration matrix to obtain the final rigid registration matrix;

[0044] 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.

[0045] Optional spinal screw placement navigation module for:

[0046] Fill in the patient's basic information during the operation;

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

[0048] Perform 3D registration based on 3D calibrator;

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

[0050] Optional, trauma localization navigation module for:

[0051] Fill in the patient's basic information during the operation;

[0052] Take X-ray images of the patient's injured area;

[0053] Perform 2D registration based on 2D calibrator;

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

[0055] The embodiment of the present application provides an artificial intelligence surgical robot system for all orthopedic diseases, which can perform assisted surgery quickly and accurately.

[0056] The present application provides an artificial intelligence surgical robot system for all orthopedic diseases, including:

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

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

[0059] Unicompartmental hip replacement module, used for preoperative planning, intraoperative unicompartmental hip replacement and real-time display;

[0060] Acetabular osteotomy module, used for preoperative planning, intraoperative acetabular osteotomy and real-time display;

[0061] Sports medicine module, used for bone tunnel planning and ligament reconstruction with real-time display;

[0062] Spinal screw placement navigation module, used for intraoperative spinal screw placement navigation and real-time display;

[0063] Trauma localization and navigation module, used for intraoperative trauma localization and navigation and real-time display. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

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

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

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

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

[0069] Figure 5It is a schematic structural diagram of a medical oscillating saw for total knee or unicompartmental knee replacement provided by one embodiment of the present application;

[0070] Figure 6 It is a schematic diagram of the structure of an active light-emitting terminal 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 schematic diagram of the structure 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 This is a schematic diagram of the system structure of an artificial intelligence surgical robot for all orthopedics and multiple diseases provided by an embodiment of the present application.

[0073] Fig. 9 A schematic diagram of the structure of an electronic device provided in 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. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0075] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" 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 includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, 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] In order to solve the problems of the prior art, the embodiment of the present application provides an artificial intelligence surgical robot system for all orthopedic diseases. The artificial intelligence surgical robot system for all orthopedic diseases provided by the embodiment of the present application is first introduced below.

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

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

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

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

[0081] S104, periacetabular osteotomy module, used for preoperative planning, periacetabular osteotomy during surgery and real-time display;

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

[0083] S106, spinal nail placement positioning navigation module, used for spinal nail placement positioning navigation and real-time display during surgery;

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

[0085] In one embodiment, a total hip replacement module is used to:

[0086] Before surgery, the hip joint CT images were segmented and 3D reconstructed to obtain a 3D model of the hip joint;

[0087] Preoperative planning based on a three-dimensional model of the hip joint;

[0088] Intraoperative point cloud registration, filing, press-fitting, positioning, navigation and real-time display.

[0089] The functions of this module include hip joint CT image segmentation and 3D reconstruction, preoperative planning, intraoperative point cloud registration, grinding and filing, press-fitting, positioning, navigation and real-time display, etc. The specific steps are as follows:

[0090] 1. Preoperative preparation:

[0091] 1.1 Acquisition of hip CT images:

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

[0093] step:

[0094] 1. CT scan: Perform a multi-layer CT scan on the patient's hip joint to obtain high-resolution tomographic image data.

[0095] 2. Image data transmission: The raw data of the CT scan is transmitted to the image processing system of the total hip replacement module.

[0096] 1.2 CT image segmentation:

[0097] Objective: To separate the hip joint and surrounding tissues from CT images using automatic or semi-automatic segmentation algorithms.

[0098] step:

[0099] 1. Image preprocessing: reduce noise, enhance contrast and filter images on CT images to improve the effect of subsequent segmentation.

[0100] 2. Application of segmentation algorithm: Use deep learning 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, acetabulum, etc. to generate binary or multi-class segmentation images of the hip joint area.

[0101] 3. Correction of segmentation results: Manually correct the automatic segmentation results to ensure accurate segmentation of joints.

[0102] 1.3 3D reconstruction:

[0103] Objective: To reconstruct the three-dimensional model of the hip joint based on segmented CT images.

[0104] step:

[0105] 1. Application of 3D reconstruction algorithm: Use 3D modeling techniques such as volume rendering and surface reconstruction to reconstruct the segmented hip joint image into a 3D model to clearly display key structures such as the femoral head and acetabulum.

[0106] 2. Model refinement: Smooth the reconstructed 3D model, remove noise and irregular surfaces, and make the model more realistic.

[0107] 3. 3D model annotation: Annotate the key points and anatomical structures of each part of the hip joint for subsequent preoperative planning.

[0108] 1.4 Preoperative planning:

[0109] Objective: To conduct surgical simulation planning based on three-dimensional reconstruction models to ensure accurate intraoperative operation.

[0110] step:

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

[0112] 2. Prosthesis implantation position planning: Simulate the implantation position, angle and depth of the prosthesis on a three-dimensional model to ensure optimal functional restoration of the prosthesis after surgery.

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

[0114] 2. Intraoperative operation:

[0115] 2.1 Point cloud registration:

[0116] Objective: To register the preoperatively planned three-dimensional model with the point cloud data obtained during surgery to achieve precise positioning.

[0117] step:

[0118] 1. Point cloud data acquisition: Use an intraoperative 3D scanner (such as laser scanning, optical scanning) to obtain point cloud data of the patient's hip joint in real time.

[0119] 2. Application of registration algorithm: rigidly or non-rigidly register the point cloud data collected during surgery with the preoperatively planned 3D model to ensure that the intraoperative navigation is consistent with the plan.

[0120] 3. Error correction: Correct errors through registration algorithm optimization to ensure the accuracy of real-time display.

[0121] 2.2 Rasp and prosthesis implantation:

[0122] Objective: To perform reaming and prosthesis implantation on the femoral head and acetabulum under the guidance of a navigation system.

[0123] step:

[0124] 1. Navigation guidance: The position and angle of surgical instruments are guided by the navigation system to ensure the accuracy of grinding and filing.

[0125] 2. Femoral head grinding and filing: Guide the surgical instruments on the aligned 3D model to perform precise grinding and filing of the femoral head to remove diseased tissue and prepare for prosthesis implantation.

[0126] 3. Acetabular trimming: Cut and reshape the acetabulum to ensure it fits the prosthesis well.

[0127] 4. Prosthesis implantation: The prosthesis is accurately implanted into the femoral head and acetabulum according to the position and angle planned before surgery.

[0128] 2.3 Press-fit and positioning:

[0129] Purpose: To ensure a firm integration of the prosthesis and the patient's bones and to perform precise positioning during surgery.

[0130] step:

[0131] 1. Press-fit operation: Use special tools to press the prosthesis together with the patient's femoral head or acetabulum to ensure the stability of the prosthesis.

[0132] 2. Intraoperative positioning confirmation: Use intraoperative imaging equipment (such as X-ray or intraoperative CT) to confirm that the actual position of the prosthesis is consistent with the planned position to ensure that the prosthesis functions well after surgery.

[0133] 2.4 Intraoperative Navigation and Real-time Display:

[0134] Purpose: To guide the surgery through real-time navigation system and display to ensure the accuracy of each step during the operation.

[0135] step:

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

[0137] 2. Real-time display during surgery: The three-dimensional model, surgical instruments, prosthesis position and other information are displayed in real time on the monitor to help surgeons perform precise operations.

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

[0139] 3. Postoperative evaluation and follow-up:

[0140] 3.1 Postoperative imaging evaluation

[0141] Objective: To evaluate the effect of surgery through imaging.

[0142] step:

[0143] 1. Postoperative CT or X-ray examination: Perform postoperative imaging examination on the patient to confirm whether the implantation position and angle of the prosthesis are consistent with the preoperative plan.

[0144] 2. Image comparison: Compare and analyze the postoperative images with the preoperative 3D model to evaluate the success rate of the operation and the accuracy of the prosthesis.

[0145] 3.2 Postoperative follow-up:

[0146] Purpose: To follow up the patient's postoperative recovery and ensure the long-term stability of the prosthesis.

[0147] step:

[0148] 1. Regular imaging examinations: Regular imaging examinations are performed on patients 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 restore hip joint function, and regularly evaluate patients' motor ability and the effectiveness of prosthesis use.

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

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

[0152]

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

[0154] I CT (xyzt): The 3D voxel value of the CT image changing over time t, defined in xyz space coordinates.

[0155] The Laplacian operator of CT images is used to enhance the edge information of the image.

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

[0157] Ω CT : The three-dimensional volume of the CT image, the integration area is the three-dimensional structure of the hip joint.

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

[0159] The registration coordinates of the i-th preprocessed point cloud, varying over time.

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

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

[0162] Figure 2 It is a structural schematic diagram of an end holder for total hip replacement provided by an embodiment of the present application. The end holder is fixed to the end of a robotic arm and is used to hold a grinding rod and a press-fit rod.

[0163] Figure 3It is a schematic structural diagram of a medical bone drill for total hip replacement provided by an embodiment of the present application, wherein the medical bone drill is a power for grinding and filing the acetabulum.

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

[0165] Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint;

[0166] Preoperative planning based on a three-dimensional model of the knee joint;

[0167] Intraoperative point cloud registration, osteotomy, gap balance and real-time display.

[0168] The specific steps of the "Total Knee Replacement Module" cover preoperative CT image segmentation and 3D reconstruction, preoperative planning, and intraoperative point cloud registration, osteotomy, gap balance and real-time display. The specific steps are as follows:

[0169] 1. Preoperative preparation:

[0170] 1.1 Acquisition of knee CT images:

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

[0172] step:

[0173] 1. CT scan: Perform a high-resolution CT scan on the patient's knee joint to obtain multi-slice images to ensure the clarity of all key parts of the knee joint.

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

[0175] 1.2 Knee CT image segmentation:

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

[0177] step:

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

[0179] 2. Application of segmentation algorithm: 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: According to the needs of clinicians, the segmentation results are manually corrected to ensure that the segmentation accuracy meets the surgical requirements.

[0181] 1.3 3D reconstruction:

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

[0183] step:

[0184] 1. Application of 3D reconstruction technology: Use volume rendering or surface reconstruction technology to reconstruct the segmented knee joint structure into a 3D model. The 3D model should accurately show the bone structures such as the femur, tibia and patella.

[0185] 2. Model smoothing: Smoothing and noise elimination are performed on the reconstructed model to ensure the smoothness and authenticity of the model surface.

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

[0187] 1.4 Preoperative planning:

[0188] Objective: To conduct preoperative planning of total knee replacement based on the reconstructed three-dimensional model of the knee joint and ensure the precise implementation of the operation.

[0189] step:

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

[0191] 2. Osteotomy planning: Design the osteotomy plan on the three-dimensional model of the knee joint, determine the cutting surface, angle and depth of the osteotomy, and ensure perfect fit between the prosthesis and the bone after surgery.

[0192] 3. Gap balance design: Plan the gap balance between the femur and tibia to ensure the balance of the knee joint during extension and flexion after surgery and avoid joint relaxation or tension.

[0193] 4. Surgical path and tool planning: Design a specific surgical path, plan the tools used during the operation, and determine the operation sequence at key locations.

[0194] 2. Intraoperative operation:

[0195] 2.1 Point Cloud Registration

[0196] Objective: To accurately align the preoperative planned three-dimensional model with the point cloud data obtained during surgery to achieve real-time navigation.

[0197] step:

[0198] 1. Point cloud data acquisition: During the operation, real-time point cloud data of the knee joint is obtained through 3D scanning equipment (such as optical scanner, laser scanner).

[0199] 2. Registration algorithm: Through rigid or non-rigid registration algorithms, the point cloud collected during surgery is aligned with the 3D model planned before surgery to ensure that the model accurately matches the actual anatomical structure.

[0200] 3. Error correction: Use registration algorithms such as iterative closest point (ICP) to correct the alignment error between point cloud data and the model to ensure the accuracy of intraoperative operations.

[0201] 2.2 Osteotomy:

[0202] Purpose: To perform precise osteotomies of the femur and tibia according to preoperative planning in order to install a knee prosthesis.

[0203] step:

[0204] 1. Osteotomy navigation: The surgical instruments are guided by the intraoperative navigation system so that the osteotomy tools are accurately positioned on the planned cutting surface.

[0205] 2. Femoral osteotomy: Perform osteotomy on the distal end of the femur according to the angle and position designed before surgery. Ensure that the installation surface of the femoral prosthesis is smooth and flat.

[0206] 3. Tibial osteotomy: Cut the proximal tibia according to the plan to ensure that the fitting surface of the tibial prosthesis is accurately docked with the prosthesis.

[0207] 4. Osteotomy verification: During the operation, the accuracy of osteotomy is checked through navigation or X-ray imaging to ensure that the cutting surface and angle are consistent with the preoperative plan.

[0208] 2.3 Gap balance:

[0209] Purpose: After osteotomy, ensure that the gap of the knee joint is balanced at different flexion angles so that the prosthesis can obtain a stable range of motion after implantation.

[0210] step:

[0211] 1. Gap test: After the osteotomy is completed, the gap test tool is used to evaluate the anterior-posterior and left-right gaps between the femur and tibia to ensure balance in flexion and extension.

[0212] 2. Adjustment and optimization: According to the results of the gap test, adjust the installation angle of the prosthesis or further modify the osteotomy surface to ensure that the gap remains balanced during extension and flexion to avoid joint loosening or excessive tightness.

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

[0214] 2.4 Real-time display and navigation during surgery:

[0215] Purpose: To ensure precise operation at every step during surgery through real-time navigation and display system.

[0216] step:

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

[0218] 2. Real-time display: The status of osteotomy, prosthesis implantation and gap balance is updated in real time on the intraoperative display screen to help doctors make immediate adjustments.

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

[0220] 3. Postoperative evaluation and follow-up:

[0221] 3.1 Postoperative imaging examination:

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

[0223] step:

[0224] 1. Imaging examination: Use imaging methods such as X-ray, CT or MRI to evaluate whether the implantation position and angle of the prosthesis after surgery are consistent with the preoperative plan.

[0225] 2. Image comparison: Compare the postoperative images with the preoperatively planned 3D model to confirm the position of the prosthesis and the recovery of the knee joint.

[0226] 3.2 Postoperative follow-up and rehabilitation:

[0227] Objective: To follow up the recovery of knee joint function after surgery and monitor the long-term use of prosthesis.

[0228] step:

[0229] 1. Regular check-ups: Monitor the use of knee prostheses and the patient's recovery progress through regular imaging examinations and functional assessments.

[0230] 2. Functional rehabilitation assessment: Through exercise assessment and rehabilitation training, help patients restore knee joint function and ensure flexible and stable joint movement.

[0231] The process of the total knee replacement module starts from preoperative knee joint CT image segmentation and three-dimensional reconstruction, preoperative planning, to intraoperative point cloud registration, osteotomy, gap balance, real-time display and navigation, and finally to postoperative imaging evaluation and rehabilitation tracking, to ensure the precise implementation of the operation and maximize the patient's postoperative functional recovery effect.

[0232] Among them, the three-dimensional model reconstruction and osteotomy path formula of the knee joint are:

[0233]

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

[0235] Segmentation function, based on CT image gradient Extract the 3D structure of the knee joint.

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

[0237] μ i (t): time variation coefficient of controlling knee osteotomy path.

[0238] Coordinates of the osteotomy path of the knee joint.

[0239] λ: Regularization coefficient, controlling the smoothness of the osteotomy path.

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

[0241] In one embodiment, a unicompartmental knee replacement module is provided for:

[0242] Before surgery, the knee joint CT images were segmented and 3D reconstructed to obtain a 3D model of the knee joint;

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

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

[0245] Specifically, the optimization formula for preoperative segmentation and intraoperative cutting in unicompartmental knee arthroplasty is:

[0246]

[0247] M unicompartment : Three-dimensional model and osteotomy results of unicompartmental joint.

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

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

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

[0251] f i (θ(t), φ(t)): represents the function of cutting angles θ(t) and φ(t).

[0252] Γ cut : Intraoperative cutting path.

[0253] γ: Smoothing coefficient, used to adjust the smoothness of the cutting path.

[0254] The gradient of the cutting angle represents the rate of change of the cutting angle over time.

[0255] Figure 4 It is a schematic structural diagram of an end connector for total knee or unicompartmental knee replacement provided by an embodiment of the present application. The end connector is fixed at the end of a robotic arm and is used for connecting a medical oscillating saw.

[0256] Figure 5 It is a schematic structural diagram of a medical oscillating saw for total knee or unicompartmental knee replacement provided by one embodiment of the present application, wherein the medical oscillating saw is used for performing osteotomy operations on the femur and tibia.

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

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

[0259] Obtain an image of the patient's hip joint;

[0260] Segment and 3D reconstruct the hip joint image to obtain a 3D model of the hip joint;

[0261] Using the three-dimensional model of the hip joint, the osteotomy surface, guide line and safety zone of the acetabular periarthrodesis are preoperatively planned, the safety zone boundary is determined, and the image is rendered and colored; the results of preoperative planning include planning osteotomy according to the anterior part of the sciatic bone, the superior pubic ramus, the upper ilium, and the posterior column;

[0262] During the operation, the infrared camera NDI reflective positioning navigation system and the positioning frame on the curved blade of the bone knife are combined to obtain the end position of the bone knife in real time when osteotomy is performed according to the results of preoperative planning.

[0263] The specific steps of the "Acetabular Osteotomy Module" are as follows:

[0264] 1. Preoperative preparation:

[0265] 1.1 Obtain the patient's hip joint image:

[0266] Purpose: To ensure clear and detailed joint images to guide subsequent treatment.

[0267] step:

[0268] 1. Image acquisition: Obtain imaging data of the patient's hip joint through CT or MRI scanning, focusing on the joint structure and its surrounding soft tissue.

[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: To extract the three-dimensional structure of the hip joint and provide a basis for surgical planning.

[0272] step:

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

[0274] 2. Application of segmentation algorithm: Use deep learning (such as CNN) or traditional image processing methods to segment the hip joint and extract key structures such as acetabulum, femur, etc.

[0275] 3. 3D reconstruction: Using the segmented data, create a 3D model of the hip joint to ensure that the model accurately reflects the patient's anatomical characteristics.

[0276] 1.3 Preoperative planning:

[0277] Objective: To develop an accurate osteotomy plan to ensure the success of the operation.

[0278] step:

[0279] 1. Osteotomy surface planning: The osteotomy surface around the acetabulum is designed based on the three-dimensional model and is planned according to the anatomical structures such as the anterior part of the ischium, the superior pubic ramus, the upper ilium, and the posterior column.

[0280] 2. Determination of guide lines and safety zones: Draw surgical guide lines, define the safety zone for osteotomy and mark its boundaries to avoid damage to important structures during surgery.

[0281] 3. Result rendering: Use rendering technology to visualize the planning results, highlight the osteotomy surface and safety zone through coloring, and facilitate the doctor's preoperative evaluation.

[0282] 2. Intraoperative operation:

[0283] 2.1 Intraoperative Registration

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

[0285] step:

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

[0287] 2. Initial positioning: Perform preliminary alignment between the preoperative planning model and the actual anatomical structure to ensure the accuracy of the navigation system.

[0288] 2.2 Osteotomy:

[0289] Objective: To perform osteotomy accurately according to the plan.

[0290] step:

[0291] 1. Bone knife positioning: Fix the curved blade of the bone knife at the predetermined osteotomy position through the positioning frame to ensure that it is consistent with the preoperative plan.

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

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

[0294] 2.3 Positioning and Navigation:

[0295] Purpose: To achieve real-time feedback and ensure surgical accuracy.

[0296] step:

[0297] 1. Real-time feedback: During the osteotomy process, the system displays the comparison between the osteotome position and the preoperative plan to ensure surgical accuracy.

[0298] 2. Adjustment and optimization: Make necessary adjustments to the position of the osteotomy knife based on real-time data to ensure that the final effect of the surgery meets expectations.

[0299] 3. Postoperative evaluation:

[0300] 3.1 Postoperative examination

[0301] Objective: To verify the osteotomy effect and the recovery of joint function.

[0302] step:

[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 effect of the surgery.

[0305] The entire periacetabular osteotomy module process includes preoperative image acquisition, segmentation and 3D reconstruction, preoperative precise planning, intraoperative real-time registration, osteotomy and navigation, and postoperative examination and evaluation, ensuring high precision of surgical implementation and good recovery of patients. This module improves the safety and effectiveness of surgery and promotes the development of joint replacement surgery by combining modern imaging technology and navigation systems.

[0306] Specifically, the osteotomy surface and positioning optimization formula for periacetabular osteotomy is:

[0307]

[0308] S cut : Osteotomy surface of acetabular osteotomy.

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

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

[0311] κ(θ,ψ): curvature function of the osteotomy path, depending on the angles θ and ψ.

[0312] Ω acetabular : The three-dimensional spatial area of ​​the acetabulum.

[0313] λ i : Weight coefficient, used to adjust the positioning accuracy of the infrared camera.

[0314] The real-time position information of the end of the bone knife changes with time t.

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

[0316] Obtain the first knee joint CT image;

[0317] CT image segmentation based on neural network based on deep learning;

[0318] Perform 3D modeling of the knee joint based on the segmentation results;

[0319] Set preoperative guidance points and plan preoperative registration points at the knee joint;

[0320] Bone tunnel planning and ligament reconstruction;

[0321] During surgery, a probe was used to collect intraoperative registration points based on the preoperative guidance points;

[0322] The probe is used to complete the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology; among them, rigid registration includes coarse registration and fine registration;

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

[0324] Control the autonomous movement of the robotic arm to perform bone tunnel reconstruction.

[0325] In one embodiment, the probe is used to complete the rigid registration of the preoperative registration points and the intraoperative registration points based on the digital twin technology, including:

[0326] First, the intraoperative registration points and preoperative registration points are used for initial registration. At the same time, the digital twin method is used to locate the position of the probe and map the 3D bone into the color image. The position of the probe tip is used to monitor the position of the 3D bone in real time and correct the initial registration matrix.

[0327] The registration matrix is ​​automatically adjusted again according to the corrected initial registration matrix to obtain the final rigid registration matrix;

[0328] 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.

[0329] The detailed description of the specific steps of the "Sports Medicine Module" is as follows:

[0330] 1. Preoperative preparation:

[0331] 1.1 Obtain the first knee joint CT image:

[0332] step:

[0333] 1. Patient preparation: Make sure the patient is comfortable and informed about the scanning process.

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

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

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

[0337] step:

[0338] 1. Data preprocessing: Preprocess CT images, including denoising and contrast enhancement, to improve segmentation results.

[0339] 2. Model training: Select a suitable deep learning model (such as U-Net), use labeled knee joint images for training, and optimize model parameters.

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

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

[0342] step:

[0343] 1. Generate a 3D model: Convert the segmented binary image data into a 3D mesh model using 3D reconstruction software (such as MeshLab).

[0344] 2. Model optimization: Smooth the 3D model and remove noise and unnecessary details to ensure the accuracy and visualization of the model.

[0345] 3. Model verification: By comparing with the doctor's professional knowledge, verify whether the 3D model accurately reflects the anatomical structure of the knee joint.

[0346] 2. Preoperative planning:

[0347] 2.1 Setting preoperative guidance points and planning preoperative registration points

[0348] step:

[0349] 1. Guide point calibration: Select key anatomical landmarks on the 3D model to 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: According to the bone tunnel planning, select multiple registration points and record their coordinates on the 3D model as the basis for intraoperative registration.

[0351] 2.2 Bone tunnel planning and ligament reconstruction:

[0352] step:

[0353] 1. Tunnel planning and design: Use professional software (such as Mimics) to design the path of the bone tunnel to ensure that it is safe with the surrounding structures and meets biomechanical requirements.

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

[0355] 3. Intraoperative operation:

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

[0357] step:

[0358] 1. Probe preparation: Select a probe suitable for the surgery and ensure that it can be accurately positioned.

[0359] 2. Intraoperative positioning: During the operation, the probe is used to compare the guidance points and registration points set before the operation for actual positioning, and the position of the probe is recorded.

[0360] 3.2 Rigid registration based on digital twin technology:

[0361] step:

[0362] 1. Implementation of initial registration: The registration points obtained during the operation are preliminarily registered with the points set before the operation to form an initial registration matrix.

[0363] 2. Digital twin positioning: Use digital twin technology to locate the probe in real time to ensure accurate mapping of the probe's position in three-dimensional space.

[0364] 3. 3D mapping and monitoring: Map the 3D bone model into a real-time color image, monitor the 3D model using the probe tip position, and correct the initial registration matrix.

[0365] 3.3 Automatically adjust the registration matrix:

[0366] step:

[0367] 1. Matrix correction: Based on real-time data feedback, correct the initial registration matrix to ensure its accuracy.

[0368] 2. Final registration: The registration matrix is ​​further adjusted through an automatic algorithm to generate the final rigid registration matrix.

[0369] 4. Coordinate system establishment:

[0370] 4.1 Establishing the coordinate system of the robot arm, optical positioning tracker and knee joint

[0371] step:

[0372] 1. Coordinate system calibration: According to the final rigid registration matrix, calibrate the coordinate systems of the robot and optical positioning system.

[0373] 2. Coordinate system integration: Ensure that 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 Controlling the autonomous movement of the robotic arm for bone tunnel reconstruction

[0376] step:

[0377] 1. Robotic arm control program: Based on the registration results, write the control program of the robotic arm so that it can accurately perform the bone tunnel reconstruction operation.

[0378] 2. Reconstruction operation execution: Start the robotic arm, perform reconstruction according to the preset tunnel planning path, and monitor the parameters and status of the process in real time to ensure the accuracy of the operation.

[0379] 6. Application of digital twin technology:

[0380] 6.1 Probe tracking and positioning:

[0381] step:

[0382] 1. Real-time probe tracking: A multi-modal and multi-scale fusion probe tracking algorithm is used to continuously track the position of the probe in three-dimensional space.

[0383] 2. Application of needle tip positioning algorithm: Utilize the needle tip positioning algorithm based on multi-modal and multi-scale fusion to obtain the specific position of the probe needle tip in real time to ensure the accuracy and stability of its positioning.

[0384] This module describes in detail the complete process from preoperative CT image acquisition, deep learning segmentation, 3D modeling, to the setting of preoperative guidance points and registration points, to the use of intraoperative probes, the application of digital twin technology, and the autonomous movement of the robotic arm for bone tunnel reconstruction. By combining advanced image processing, artificial intelligence, real-time monitoring and mechanical control technology, this module significantly improves the accuracy and safety of knee surgery and helps improve the patient's postoperative recovery.

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

[0386]

[0387] T bone (x, y, z, t): The reconstructed three-dimensional model of the bone tunnel, which changes with time t and is used for intraoperative navigation.

[0388] Ω bone : Three-dimensional area of ​​bone tunnel.

[0389] The expected coordinates of the bone tunnel before surgery are defined in x′, y′, z′ space and vary with time t.

[0390] G(xx′,yy′,zz′): Gaussian kernel function, used to smooth the change of bone tunnel coordinates and adjust the smoothness between different positions.

[0391] α: Regularization coefficient, controlling the influence of pre- and post-operative registration points.

[0392] Coordinates of the bone tunnel after surgery, changing with time t.

[0393] In one embodiment, the spinal screw positioning navigation module is used to:

[0394] Fill in the patient's basic information during the operation;

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

[0396] Perform 3D registration based on 3D calibrator;

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

[0398] The specific steps and processes of the "Spinal Screw Positioning Navigation Module" are further detailed and complicated as follows:

[0399] 1. Preoperative preparation:

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

[0401] step:

[0402] 1. Patient Information Collection:

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

[0404] The patient's medical history, allergies, and existing illnesses are recorded so that the surgical team is fully informed of the patient's condition.

[0405] 2. Preoperative discussion:

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

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

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

[0409] step:

[0410] 1. Patient positioning:

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

[0412] Use positioning tools (such as laser positioners) to ensure accurate patient positioning.

[0413] 2.CT Scan Execution:

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

[0415] Multiphase scanning (such as transverse, sagittal, and coronal) is performed to obtain more comprehensive anatomical information.

[0416] 3. Data processing and storage:

[0417] After scanning, professional image processing software was used to post-process the images, including denoising, contrast enhancement, and reconstruction.

[0418] The results are saved in DICOM format to a secure storage server, ensuring that the images are available at any time during the surgery.

[0419] 2. Intraoperative operation:

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

[0421] step:

[0422] 1.3D calibrator installation:

[0423] The 3D marker is precisely mounted on the patient's spine, ensuring that it is aligned with anatomical features such as the edges of vertebral bodies.

[0424] Use a special clamp to fix the marker to prevent it from moving during surgery.

[0425] 2. Image registration process:

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

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

[0428] 3. Registration verification:

[0429] The registration accuracy is evaluated by comparing the position of the calibrator in the CT image with the actual position using statistical analysis methods (such as root mean square error).

[0430] If there is any deviation, adjust the position of the calibrator and repeat the alignment process until the accuracy requirement is met.

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

[0432] step:

[0433] 1. Navigation path planning:

[0434] Based on the registered CT images, professional software (such as navigation system integration software) is used to design the nail placement path to ensure that important nerves and vascular structures are avoided.

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

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

[0437] The navigation system is activated to monitor the position of the probe or nail through optical or electromagnetic locators and update the position information in real time on the display.

[0438] Data fusion technology is used to overlay real-time location information with CT images to provide visual navigation support.

[0439] 3. Navigation operation:

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

[0441] Maintain communication with the surgical team throughout the operation to address potential issues in a timely manner and ensure the surgery goes smoothly.

[0442] 3. Postoperative steps:

[0443] 3.1 Data recording and analysis

[0444] step:

[0445] 1. Postoperative data collection:

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

[0447] Intraoperative real-time images and final images were collected for comparative analysis.

[0448] 2. Result evaluation:

[0449] After surgery, the navigation path was compared with the actual screw placement position to evaluate the accuracy and success rate of screw placement.

[0450] Based on the postoperative evaluation results, improvement suggestions are provided for future surgeries.

[0451] This module describes in detail the complete process from preoperative patient information entry, CT image capture, installation and registration of 3D calibrators, to real-time navigation planning and monitoring. By introducing complex technical means and data analysis methods, the accuracy and safety of spinal screw placement surgery are ensured, ultimately improving the patient's treatment effect and recovery efficiency.

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

[0453]

[0454] Espine (x,y,z,t): Registration error function in spinal screw placement, varying with time t.

[0455] Ω spine : The three-dimensional spatial area of ​​the spine.

[0456] Coordinates of preoperative spine registration points,over time.

[0457] Coordinates of postoperative spine registration points.

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

[0459] The gradient of the spine, used to calculate the rate of change of coordinates.

[0460] λ: Regularization parameter used to control the positioning smoothness.

[0461] The position information of surgical tools during surgery.

[0462] In one embodiment, the wound localization navigation module is used to:

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

[0464] Take X-ray images of the patient's injured area;

[0465] Perform 2D registration based on 2D calibrator;

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

[0467] The specific steps of the "Trauma Localization Navigation Module" are further detailed and complicated as follows:

[0468] 1. Preoperative preparation:

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

[0470] step:

[0471] 1. Electronic information system input:

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

[0473] Record the patient's medical history (including allergies, chronic diseases, etc.) to ensure the surgical team has a comprehensive understanding of the patient's health status.

[0474] 2. Preoperative case discussion:

[0475] A multidisciplinary team meeting was held to review the patient's medical records, imaging results, and discuss surgical risks and expected outcomes.

[0476] Determine the division of labor and postoperative recovery plan for the surgical team and ensure that each team member understands their respective responsibilities.

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

[0478] step:

[0479] 1. Patient positioning:

[0480] Position the patient under the X-ray machine to ensure optimal visualization of the injured area.

[0481] Use a balloon stent or other fixation device to stabilize the wound site to ensure that it does not move during imaging.

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

[0483] Select multiple viewing angles (such as anteroposterior, lateral, and oblique) for X-rays to ensure that comprehensive trauma information is obtained.

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

[0485] 3. Image post-processing:

[0486] The X-ray images are post-processed using image processing software, including denoising, contrast enhancement, and pseudo-color processing, to improve the visibility of anatomical structures.

[0487] The processed images are stored in DICOM format and linked to the patient's files to ensure they can be retrieved at any time during surgery.

[0488] 2. Intraoperative operation:

[0489] 2.1 Two-dimensional registration based on a two-dimensional calibrator

[0490] step:

[0491] 1. Installation and calibration of the calibrator:

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

[0493] A preliminary scan of the marker and surrounding structures was performed using a 3D laser scanner to ensure that its position was stable and accurately recorded.

[0494] 2. 2D registration process:

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

[0496] Image fusion technology is used to combine preoperative CT images with intraoperative X-ray images, and the position of the calibrator is accurately aligned with the trauma site through algorithm optimization.

[0497] 3. Registration accuracy verification:

[0498] The registration results were compared with the actual position of the calibrator in the X-ray image, and the accuracy of the registration was evaluated through statistical analysis (such as standard deviation, root mean square error).

[0499] If any deviation is found, readjust the position of the calibrator and perform re-registration until the registration result meets the clinical requirements.

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

[0501] step:

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

[0503] On the basis of the registration, the navigation system software is used to develop the surgical path of the trauma site and identify key points (such as the position of bone screws, incision position, etc.).

[0504] Generate detailed surgical guides based on anatomical features, trauma type, and expected outcomes, including coordinates, angles, and depths of each critical operating point.

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

[0506] The navigation system is activated to continuously track the real-time position of surgical instruments (such as probes and bone screws) through optical or electromagnetic locators.

[0507] The real-time location information is dynamically compared with the planned path to provide real-time feedback, ensuring that the doctor can adjust the operation direction and strength in time.

[0508] 3. Accurate operation execution:

[0509] The doctor adjusts the position of the probe or bone screw based on the real-time data provided by the navigation system to ensure that it is accurately inserted into the predetermined position.

[0510] The movement trajectory of the probe or bone screw is continuously monitored during the operation, and intelligent algorithms are used to identify potential risks and issue warnings in a timely manner.

[0511] 3. Postoperative steps:

[0512] 3.1 Data recording and analysis:

[0513] step:

[0514] 1. Surgical data collation and archiving:

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

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

[0517] 2. Analysis and evaluation of postoperative results:

[0518] The navigation path during the operation was compared with the actual trauma treatment results to evaluate the accuracy of nail placement, surgical success rate and possible complications.

[0519] Based on the evaluation results, postoperative discussions are conducted to provide suggestions for improvement for similar cases in the future, thereby enhancing team collaboration and learning.

[0520] This module describes in detail the complete process from preoperative patient information entry, X-ray image capture, installation and registration of two-dimensional calibrators, and finally 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 of the wound site is:

[0522]

[0523] 2D registration results of the wound site, over time.

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

[0525] Coordinates of the registration points at the initial trauma site, over time.

[0526] G(xx′,yy′): Gaussian kernel function used to smooth the relationship between wound registration points.

[0527] Gradient information of a 2D image.

[0528] λ: Regularization coefficient used to control the smoothness of wound site localization.

[0529] Position information of intraoperative wound localization tools,over time.

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

[0531] 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. The guide is used for positioning a trauma functional sleeve.

[0532] Figure 8 This is a schematic diagram of the system structure of an artificial intelligence surgical robot for all orthopedics and multiple diseases provided by an embodiment of the present application. Figure 8 From left to right in the middle are the navigation trolley, the robotic arm trolley, and the main control trolley.

[0533] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown.

[0534] The electronic device may include a processor 901 and a memory 902 storing computer program instructions.

[0535] Specifically, the processor 901 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0536] The memory 902 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 902 may 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. In appropriate cases, the memory 902 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 902 may be inside or outside the electronic device. In a particular embodiment, the memory 902 may be a non-volatile solid-state memory.

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

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

[0539] In one example, the electronic device may further include a communication interface 903 and a bus 910. Fig. 9 As shown, the processor 901, the memory 902, and the communication interface 909 are connected via a bus 910 and communicate with each other.

[0540] The communication interface 903 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0541] Bus 910 includes hardware, software or both, and the parts of electronic equipment are coupled to each other.For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 910 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0542] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is 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 the 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, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. Programs or code segments can be stored in machine-readable media, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable media" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, 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, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0545] The above reference is according to the method of the embodiment of the present application, the flow chart of the device (system) and the computer program product and / or the block diagram described various aspects of the present application.It should be understood that each square box in the flow chart and / or the block diagram and the combination of each square box in the flow chart and / or the block diagram can be realized 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 by the processor of the computer or other programmable data processing device enable the realization of the function / action specified in one or more square boxes of the flow chart and / or the block diagram.Such a 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 can also be understood that each square box in the block diagram and / or the flow chart and the combination of the square boxes in the block diagram and / or the flow chart can also be realized by the dedicated hardware that performs the specified function or action, or can be realized by the combination of dedicated hardware and computer instructions.

[0546] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. An artificial intelligence surgical robot system for all orthopedic diseases, characterized in that: 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 hip replacement module, used for preoperative planning, intraoperative unicompartmental hip replacement and real-time display; Acetabular osteotomy module, used for preoperative planning, intraoperative acetabular osteotomy and real-time display; Sports medicine module, used for bone tunnel planning and ligament reconstruction with real-time display; Spinal screw placement navigation module, used for intraoperative spinal screw placement navigation and real-time display; Trauma localization and navigation module, used for intraoperative trauma localization 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 hip 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 periacetabular osteotomy module is used for: preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display.

6. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 5 is characterized in that: Preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display, including: Obtain images of the patient's hip joint; Segment and 3D reconstruct the hip joint image to obtain a 3D model of the hip joint; Using the three-dimensional model of the hip joint, the osteotomy surface, guide line and safety zone of the acetabular periarthrodesis are preoperatively planned, the safety zone boundary is determined, and the image is rendered and colored; the results of preoperative planning include planning osteotomy according to the anterior part of the sciatic bone, the superior pubic ramus, the upper ilium, and the posterior column; During the operation, the infrared camera NDI reflective positioning navigation system and the positioning frame on the curved blade of the bone knife are combined to obtain the end position of the bone knife in real time when osteotomy is performed according to the results of preoperative planning.

7. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 1 is characterized in that: Sports Medicine Module for: Obtain the first knee joint CT image; CT image segmentation based on neural network based on deep learning; Perform 3D modeling of the knee joint based on the segmentation results; Set preoperative guidance points and plan preoperative registration points at the knee joint; Bone tunnel planning and ligament reconstruction; During surgery, a probe was used to collect intraoperative registration points based on the preoperative guidance points; The probe is used to complete the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology; among them, rigid registration includes coarse registration and fine registration; The coordinate system of the robot arm, optical positioning tracker and knee joint is established according to the registration results; Control the autonomous movement of the robotic arm to perform bone tunnel reconstruction.

8. The orthopedic multi-disease artificial intelligence surgical robot system according to claim 7 is characterized in that: The probe is used to complete the rigid registration of preoperative registration points and intraoperative registration points based on digital twin technology, including: First, the intraoperative registration points and preoperative registration points are used for initial registration. At the same time, the digital twin method is used to locate the position of the probe and map the 3D bone into the color image. The position of the probe tip is used to monitor the position of the 3D bone in real time and correct the initial registration matrix. The registration matrix is ​​automatically adjusted again according to the corrected 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.

9. 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 3D calibrator; Intraoperative planning and real-time positioning navigation.

10. 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 2D calibrator; Intraoperative planning and real-time positioning navigation.

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