CN119498952B

CN119498952B - Total orthopedics multi-disease artificial intelligent operation robot system

Info

Publication number: CN119498952B
Application number: CN202411398172.9A
Authority: CN
Inventors: 刘星宇; 张逸凌
Original assignee: Beijing Changmugu Medical Technology Co Ltd
Current assignee: Longwood Valley Medtech Co Ltd
Priority date: 2024-10-09
Filing date: 2024-10-09
Publication date: 2025-10-17
Anticipated expiration: 2044-10-09
Also published as: CN119498952A

Abstract

The application provides a full orthopaedics multi-disease artificial intelligent operation robot system, which comprises a full hip joint replacement module, a full hip joint replacement module and a full hip joint replacement module, wherein the full hip joint replacement module is used for planning before operation and displaying full hip joint replacement in real time; the device comprises a total knee replacement module, a unicondylar joint replacement module, a periacetabular osteotomy module, a sports medical module, a spine nail positioning navigation module, a trauma positioning navigation module and a trauma positioning navigation module, wherein the total knee replacement module is used for preoperative planning, intra-operative total knee replacement and real-time display, the unicondylar joint replacement module is used for preoperative planning, intra-operative unicondylar joint replacement and real-time display, the periacetabular osteotomy module is used for preoperative planning, intra-operative periacetabular osteotomy and real-time display, the sports medical module is used for bone tunnel planning, ligament reconstruction and real-time display, the spine nail positioning navigation module is used for intra-operative spine nail positioning navigation and real-time display, and the trauma positioning navigation module is used for intra-operative trauma positioning navigation and real-time display. According to the embodiment of the application, the auxiliary operation can be performed quickly and accurately.

Description

Total orthopedics multi-disease artificial intelligent operation robot system

Technical Field

The application belongs to the technical field of surgical robots, and particularly relates to an artificial intelligent surgical robot system for multiple diseases of orthopaedics.

Background

At present, the method mainly depends on doctors to perform full hip joint replacement, full knee joint replacement, unicondylar joint replacement, bone cutting around acetabulum, sports medicine, spine nail positioning navigation and wound positioning navigation according to experience, but has poor efficiency and accuracy.

Therefore, how to perform auxiliary operations quickly and accurately is a technical problem that needs to be solved by those skilled in the art.

Disclosure of Invention

The embodiment of the application provides an artificial intelligent surgical robot system for multiple diseases in a whole orthopaedics, which can quickly and accurately perform auxiliary surgery.

The embodiment of the application provides an artificial intelligent surgical robot system for multiple diseases of a whole orthopedics department, which comprises:

The total hip replacement module is used for preoperative planning, intra-operative total hip replacement and real-time display;

the total knee replacement module is used for preoperative planning, intra-operative total knee replacement and real-time display;

the unicondylar joint replacement module is used for pre-operation planning, intraoperative unicondylar joint replacement and real-time display;

The periacetabular osteotomy module is used for preoperative planning, intraoperative periacetabular osteotomy and real-time display;

The sports medical module is used for bone tunnel planning and ligament reconstruction and real-time display;

The spine nail positioning navigation module is used for positioning and navigation of the spine nail during operation and displaying in real time;

and the trauma positioning navigation module is used for positioning and navigating the trauma in the operation and displaying the trauma in real time.

Optionally, a total hip replacement module for:

the method comprises the steps of (1) segmenting and three-dimensionally reconstructing a hip joint CT image before operation to obtain a hip joint three-dimensional model;

performing preoperative planning based on the three-dimensional model of the hip joint;

Cloud registration, file grinding, press fitting, positioning, navigation and real-time display are carried out on the surgical points.

Optionally, the total knee replacement module is configured to:

the CT image of the knee joint is segmented and three-dimensionally reconstructed before operation, so that a three-dimensional model of the knee joint is obtained;

performing preoperative planning based on the knee joint three-dimensional model;

the point cloud registration, osteotomy and gap balance in the operation are displayed in real time.

Optionally, a unicondylar joint replacement module for:

Optionally, the surrounding acetabulum osteotomy module is used for preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display.

Optionally, the preoperative planning, registration, osteotomy, positioning, navigation and real-time display during the operation comprises:

Acquiring a hip joint image of a patient;

dividing and three-dimensionally reconstructing the hip joint image to obtain a hip joint three-dimensional model;

Utilizing a three-dimensional model of the hip joint, pre-operatively planning an osteotomy face, a guide line and a safety zone of an osteotomy surrounding an acetabulum, determining a boundary of the safety zone, and rendering coloring, wherein the pre-operatively planning result comprises planning the osteotomy according to the anterior ischial portion, the suprapubic ramus, the upper ilium and the posterior column;

And the infrared camera NDI light-reflecting positioning navigation system is combined in the operation, and the position of the tail end of the osteotome is obtained in real time when the osteotome is cut according to the result of preoperative planning.

Optionally, the sports medical module is configured to:

acquiring a first knee joint CT image;

Neural network CT image segmentation based on deep learning;

performing knee joint 3D modeling according to the segmentation result;

Setting a preoperative guide point and a preoperative registration point on the knee joint;

bone tunnel planning and ligament reconstruction;

The method comprises the steps that a probe is used for collecting an intraoperative registration point according to a preoperative guide point in an intraoperative manner;

Utilizing a probe to complete rigid registration of preoperative registration points and intraoperative registration points based on a digital twin technology, wherein the rigid registration comprises a coarse registration part and a fine registration part;

Completing the establishment of a coordinate system of the mechanical arm, the optical positioning tracker and the knee joint according to the registration result;

And controlling the mechanical arm to autonomously move to reconstruct the bone tunnel.

Optionally, the rigid registration of the preoperative registration point and the intraoperative registration point based on the digital twinning technique is accomplished with a probe, comprising:

Firstly, performing initial registration by using an intraoperative registration point and a preoperative registration point, positioning the position of a probe by using a digital twinning method, mapping a three-dimensional skeleton into a color image, monitoring the position of the three-dimensional skeleton in real time by using the position of a probe tip, and correcting an initial registration matrix;

performing automatic adjustment of the registration matrix again according to the corrected initial registration matrix to obtain a final rigid registration matrix;

The digital twinning method is to track the probe in real time based on a multi-mode multi-scale fusion probe tracking algorithm, and to position the probe tip in real time by using a multi-mode multi-scale fusion-based tip positioning algorithm.

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

Filling in basic information of a patient in an operation;

Shooting a spine CT image of a patient;

performing three-dimensional registration based on a three-dimensional calibrator;

intraoperative planning and real-time positioning navigation.

Optionally, the wound positioning navigation module is configured to:

Filling in basic information of a patient in an operation;

Taking an X-ray image of a wound site of a patient;

performing two-dimensional registration based on a two-dimensional calibrator;

intraoperative planning and real-time positioning navigation.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic block diagram of an artificial intelligent surgical robot system for multiple diseases in orthopaedics, according to an embodiment of the present application;

FIG. 2 is a schematic view of an end effector for total hip replacement according to one embodiment of the present application;

FIG. 3 is a schematic view of a medical bone drill for total hip replacement according to one embodiment of the present application;

FIG. 4 is a schematic illustration of the configuration of an end connector for total knee or unicondylar joint replacement provided in accordance with one embodiment of the present application;

FIG. 5 is a schematic view of a medical pendulum saw for total knee or unicondylar joint replacement according to one embodiment of the present application;

FIG. 6 is a schematic view of an active light tip for periacetabular osteotomies, sports medicine, spinal staple positioning navigation, trauma positioning navigation, in accordance with one embodiment of the present application;

FIG. 7 is a schematic structural view of a guide for periacetabular osteotomies, sports medicine, spinal staple positioning navigation, trauma positioning navigation, according to one embodiment of the application;

fig. 8 is a schematic diagram of a system structure of an artificial intelligent surgical robot for multiple diseases in orthopaedics, according to an embodiment of the present application.

Fig. 9 shows a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings and the detailed embodiments. It should be understood that the particular embodiments described herein are meant to be illustrative of the application only and not limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the application by showing examples of the application.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that comprises the element.

In order to solve the problems in the prior art, the embodiment of the application provides a multi-disease artificial intelligent surgical robot system for orthopaedics. The following first describes the artificial intelligent surgical robot system for multiple diseases in orthopaedics provided by the embodiment of the application.

Fig. 1 is a schematic block diagram of an artificial intelligent surgical robot system for multiple diseases in orthopaedics according to an embodiment of the present application. As shown in fig. 1, the artificial intelligent surgical robot system for multiple diseases of the whole orthopaedics comprises:

s101, a total hip replacement module which is used for preoperative planning, intra-operative total hip replacement and real-time display;

S102, a total knee replacement module which is used for preoperative planning, intra-operative total knee replacement and real-time display;

s103, a unicondylar joint replacement module which is used for pre-operation planning, intraoperative unicondylar joint replacement and real-time display;

S104, an acetabular surrounding osteotomy module is used for preoperative planning, intraoperative acetabular surrounding osteotomy and real-time display;

S105, a sports medical module which is used for bone tunnel planning and ligament reconstruction and real-time display;

s106, a spine nail positioning navigation module which is used for positioning and navigation of the spine nail during operation and displaying in real time;

s107, a trauma positioning navigation module which is used for positioning and navigation of the intraoperative trauma and displaying in real time.

In one embodiment, a total hip replacement module for:

The function of the module comprises the contents of hip joint CT image segmentation and three-dimensional reconstruction, preoperative planning, operative point cloud registration, grinding and filing, press fit, positioning, navigation, real-time display and the like. The specific steps are as follows:

1. Preoperative preparation:

1.1 acquisition of hip CT images:

The aim is to acquire CT scan data of the hip joint of a patient for subsequent processing.

The steps are as follows:

CT scanning, namely performing multi-layer CT scanning on the hip joint part of a patient to obtain high-resolution tomographic image data.

2. Image data transmission, namely transmitting the original data of CT scanning to an image processing system of the total hip replacement module.

1.2CT image segmentation:

the aim is to separate the hip joint and the surrounding tissues from the CT image through an automatic or semi-automatic segmentation algorithm.

The steps are as follows:

1. Image preprocessing, namely denoising the CT image, enhancing contrast and filtering the image, and improving the effect of subsequent segmentation.

2. The segmentation algorithm is applied to segment the structures such as the hip joint, the femoral head, the acetabulum and the like by using a deep learning-based or traditional segmentation algorithm (such as region growing, threshold segmentation or convolutional neural network CNN) to generate a binary or multi-class segmentation image of the hip joint region.

3. And correcting the segmentation result, namely manually correcting the automatic segmentation result to ensure the accurate segmentation of the joint part.

1.3 Three-dimensional reconstruction:

the method aims at reconstructing a three-dimensional model of the hip joint based on the segmented CT image.

The steps are as follows:

1. The three-dimensional reconstruction algorithm is applied to reconstruct the segmented hip joint image into a three-dimensional model by using three-dimensional modeling techniques such as volume drawing, surface reconstruction and the like, and key structures such as femoral heads, acetabulum and the like are clearly displayed.

2. Model refinement treatment, namely smoothing the reconstructed three-dimensional model to remove noise and irregular surfaces, so that the model is more real.

3. And marking a three-dimensional model, namely marking key points and anatomical structures of all parts of the hip joint for subsequent preoperative planning.

1.4 Preoperative planning:

the method aims at carrying out operation simulation planning based on the three-dimensional reconstruction model, and ensuring accurate operation in operation.

The steps are as follows:

1. prosthesis selection, selecting the appropriate model and size of the hip prosthesis according to the anatomy of the patient's hip.

2. And (3) planning the implantation position of the prosthesis, namely simulating the implantation position, angle and depth of the prosthesis on a three-dimensional model, and ensuring the optimal functional recovery of the prosthesis after operation.

3. Designing a surgical path, namely designing an operation path for grinding, cutting and prosthesis implantation to generate a surgical plan.

2. Intraoperative manipulation:

2.1 Point cloud registration:

The method aims at registering the three-dimensional model planned before operation with point cloud data acquired during operation to realize accurate positioning.

The steps are as follows:

1. and acquiring point cloud data, namely acquiring the point cloud data of the hip joint of the patient in real time by using an intraoperative three-dimensional scanner (such as laser scanning and optical scanning).

2. The registration algorithm is applied to carry out rigid registration or non-rigid registration on the point cloud data acquired in the operation and the three-dimensional model planned before the operation, so as to ensure that the navigation in the operation is consistent with the planning.

3. Error correction, namely optimizing and correcting errors through a registration algorithm, and ensuring the accuracy of real-time display.

2.2 Grinding file and prosthesis implantation:

The purpose is to grind and file the femoral head and acetabulum and implant the prosthesis under the guidance of the navigation system.

The steps are as follows:

1. guiding the position and angle of the surgical instrument through a navigation system, and ensuring the precision of grinding and filing.

2. And 3, grinding the femoral head, namely guiding a surgical instrument on the registered three-dimensional model to accurately grind and file the femoral head, removing pathological tissues and preparing for prosthesis implantation.

3. Acetabular revision, namely cutting and shaping the acetabular part to ensure the fitting degree of the acetabular part with a prosthesis.

4. Prosthesis implantation-the prosthesis is accurately implanted in the femoral head and acetabulum position according to the position and angle planned before operation.

2.3 Press fitting and positioning:

the purpose is to ensure the firm combination of the prosthesis and the bone of the patient and to perform accurate positioning in operation.

The steps are as follows:

1. Press-fit operation, namely press-fitting the prosthesis with the femoral head or acetabulum of a patient through a special tool, so as to ensure the stability of the prosthesis.

2. And (3) positioning and confirming in operation, namely confirming that the actual position of the prosthesis is consistent with the planned position through an imaging device in operation (such as X-ray or CT in operation), and ensuring that the prosthesis has good function after operation.

2.4 Intra-operative navigation and real-time display:

The purpose is that the operation is guided by a real-time navigation system and a display, so that the accuracy of each operation in the operation process is ensured.

The steps are as follows:

1. the real-time navigation system is started, and the navigation system tracks the positions of the surgical tool and the prosthesis in real time through the registered three-dimensional model to provide dynamic guidance for the surgery.

2. Real-time display in operation, namely displaying information such as a three-dimensional model, surgical instruments, prosthesis positions and the like on a display in real time, and helping surgeons to perform accurate operation.

3. Dynamic adjustment, namely if deviation occurs in the operation process, adjusting the operation path and the tool position in real time, and ensuring accurate operation.

3. Postoperative evaluation and tracking:

3.1 postoperative image evaluation

The purpose is to evaluate the operation effect through the image.

The steps are as follows:

1. and (3) performing postoperative CT or X-ray image inspection, namely performing postoperative image inspection on a patient to confirm whether the implantation position and angle of the prosthesis are consistent with the preoperative planning.

2. Image comparison, namely comparing and analyzing the postoperative image with the preoperative three-dimensional model, and evaluating the success rate of the operation and the accuracy of the prosthesis.

3.2 Post-operative tracking:

the purpose is to track the postoperative recovery condition of the patient and ensure the long-term stability of the prosthesis.

The steps are as follows:

1. periodic imaging examination, namely, imaging examination is carried out on a patient regularly, and the stability of the prosthesis and the functional recovery condition of the hip joint are tracked.

2. Functional assessment, namely helping the patient to recover the hip joint function through physical therapy and rehabilitation training, and periodically assessing the exercise capacity of the patient and the using effect of the prosthesis.

The specific flow of the total hip replacement module covers the segmentation and three-dimensional reconstruction of a preoperative CT image and preoperative operation planning, point cloud registration, navigation guidance, grinding and filing, prosthesis implantation and real-time display in the operation, and image evaluation and function tracking after the operation, so that the high precision of the operation process and the postoperative rehabilitation effect of a patient are ensured.

Wherein, the three-dimensional model generation and the registration formula in the operation of the hip joint are as follows:

M _hip the generated three-dimensional model of the hip joint is used for intra-operative navigation.

I _CT (xyzt) the three-dimensional voxel values of the CT image over time t are defined in xyz space coordinates.

The Laplacian of the CT image is used for enhancing the edge information of the image.

Alpha is an adjustment coefficient for controlling the smoothness of the image.

Omega _CT is the three-dimensional volume of CT image, and the integral area is the three-dimensional structure of hip joint.

And lambda _i, weight coefficient, controlling the influence of point cloud registration in surgery.

The ith pre-processed point cloud registers coordinates, which change over time.

And registering the coordinates of the ith post-operation point cloud.

The registration matrix corresponding to the rigid transformation matrix R _ij (t) is used to align the post-operative coordinates with the pre-operative coordinates.

Fig. 2 is a schematic view of an end effector for total hip replacement according to one embodiment of the present application, which is attached to the end of a mechanical arm for grasping an rasp bar and a press-fit bar.

Fig. 3 is a schematic structural view of a medical bone drill for total hip replacement, which is a power for rasping an acetabulum, according to one embodiment of the present application.

In one embodiment, a total knee replacement module is configured to:

The specific step flow of the total knee replacement module comprises pre-operation CT image segmentation and three-dimensional reconstruction, pre-operation planning, and point cloud registration, osteotomy, gap balance and real-time display in operation. The method comprises the following specific steps:

1. Preoperative preparation:

1.1 CT image acquisition of knee joint:

The method aims at acquiring CT scan data of the knee joint of a patient for subsequent model construction and operation planning.

The steps are as follows:

CT scanning, namely performing high-resolution CT scanning on the knee joint of a patient, acquiring multi-layer tomographic images, and ensuring the definition of each key part of the knee joint.

2. And importing image data, namely importing the acquired knee joint CT image into a processing system of the total knee joint replacement module.

1.2 Knee CT image segmentation:

the method aims at extracting the bone and soft tissue structures of the knee joint from the CT image through a segmentation algorithm.

The steps are as follows:

1. Image preprocessing, namely performing noise reduction, image enhancement and filtering treatment on the CT image, enhancing the contrast of joint edges and improving the segmentation accuracy.

2. The segmentation algorithm is applied by adopting a deep learning algorithm (such as convolutional neural network CNN) or a traditional image processing method (such as region growing, threshold segmentation and the like) to segment bones (femur, tibia, patella) of the knee joint and peripheral soft tissues.

3. And (3) manually correcting the segmentation result according to the requirements of a clinician, so as to ensure that the segmentation accuracy meets the operation requirement.

1.3 Three-dimensional reconstruction:

The method aims at reconstructing a three-dimensional model of the knee joint based on the segmented CT image so as to facilitate subsequent preoperative planning.

The steps are as follows:

1. The three-dimensional reconstruction technology is applied to reconstruct the segmented knee joint structure into a three-dimensional model by utilizing a volume rendering or surface reconstruction technology. The three-dimensional model should accurately exhibit bone structures such as femur, tibia, and patella.

2. And model smoothing treatment, namely carrying out smoothing, noise elimination and other treatments on the reconstructed model, and ensuring the smoothness and the authenticity of the surface of the model.

3. Marking key structures, namely marking important anatomical structures of knee joints and marking important osseous mark points so as to facilitate subsequent operation planning and navigation.

1.4 Preoperative planning:

The method aims at carrying out preoperative planning of total knee replacement based on the reconstructed knee three-dimensional model, and ensuring accurate implementation of the operation.

The steps are as follows:

1. prosthesis selection, namely selecting proper model and specification of the knee joint prosthesis according to the three-dimensional model and the anatomical structure of the knee joint, and considering the size, the type and the material of the prosthesis.

2. Osteotomy planning, namely designing an osteotomy scheme on a knee joint three-dimensional model, determining the tangent plane, angle and depth of osteotomy, and ensuring perfect fit between the postoperative prosthesis and bones.

3. Gap balance design, namely planning gap balance between femur and tibia, ensuring balance state of the knee joint after operation when the knee joint is straightened and bent, and avoiding the phenomenon of joint loosening or tension.

4. Surgical path and tool planning, namely designing a specific surgical path, planning tools used in surgery, and determining the operation sequence of key positions.

2. Intraoperative manipulation:

2.1 Point cloud registration

The method aims at accurately registering the three-dimensional model planned before operation and the point cloud data acquired during operation, and realizing real-time navigation.

The steps are as follows:

1. And acquiring point cloud data, namely acquiring real-time point cloud data of the knee joint through 3D scanning equipment (such as an optical scanner and a laser scanner) in operation.

2. And the registration algorithm is used for aligning the point cloud acquired in the operation with the three-dimensional model planned before the operation through a rigid registration or non-rigid registration algorithm, so as to ensure that the model is accurately matched with the actual anatomical structure.

3. And correcting errors, namely correcting alignment errors of point cloud data and the model by using registration algorithms such as Iterative Closest Point (ICP) and the like, and ensuring the accuracy of operation in operation.

2.2 Osteotomy:

aims to accurately cut the femur and the tibia according to preoperative planning so as to install the knee joint prosthesis.

The steps are as follows:

1. Osteotomy navigation, namely guiding a surgical instrument through a navigation system in operation, so that an osteotomy tool is accurately positioned on a planned cutting surface.

2. Femur osteotomy, namely osteotomy is carried out on the distal end of the femur according to the angle and the position designed before operation. Ensuring the smoothness and flatness of the mounting surface of the femoral prosthesis.

3. Cutting the proximal end of the tibia according to the plan, and ensuring the accurate butt joint of the joint surface of the tibia prosthesis and the prosthesis.

4. Osteotomy verification, in which the accuracy of osteotomy is checked by navigation or X-ray imaging, so as to ensure that the cut surface and angle are consistent with the preoperative planning.

2.3 Gap balance:

The purpose is to ensure the clearance balance of the knee joint under different buckling angles after osteotomy, so that the prosthesis can obtain a stable movement range after implantation.

The steps are as follows:

1. gap test, namely after osteotomy is completed, evaluating the front-back and left-right gaps between the femur and the tibia through a gap test tool, and ensuring balance in buckling and stretching states.

2. Adjusting and optimizing, namely adjusting the installation angle of the prosthesis or further correcting the osteotomy surface according to the result of the gap test, ensuring that the gap is balanced in the extending and bending process, and avoiding the joint from loosening or overtightening.

3. And (3) real-time balance adjustment, namely displaying the gap balance condition of the knee joint in real time through an intraoperative navigation system, and guiding a doctor to further optimize the balance state.

2.4 Intraoperative real-time display and navigation:

the purpose is to ensure the accurate operation of each step in the operation process through a real-time navigation and display system.

The steps are as follows:

1. The navigation system is started, and the intraoperative navigation system displays the positions of the surgical instrument, the bone of the patient and the prosthesis on the three-dimensional model in real time to assist the doctor to accurately execute each operation.

2. The real-time display is used for updating the states of osteotomy, prosthesis implantation and gap balance on the intraoperative display screen in real time, thereby helping doctors to make immediate adjustment.

3. Error correction and feedback, in which, with the help of a real-time navigation and display system, a doctor can finely adjust the operation path, tool operation and the like according to the feedback in operation, so as to ensure that the final result of the operation is consistent with the preoperative planning.

3. Postoperative evaluation and tracking:

3.1 post-operative image examination:

The purpose is to confirm the accuracy of the implantation position of the prosthesis and the recovery condition of the knee joint function through the postoperative image.

The steps are as follows:

1. And (3) image inspection, namely evaluating whether the implantation position and angle of the postoperative prosthesis are consistent with the preoperative planning through imaging means such as X-ray, CT or MRI.

2. Image comparison, namely comparing the postoperative image with a three-dimensional model planned before operation, and confirming the position of the prosthesis and the recovery condition of the knee joint.

3.2 Post-operative tracking and rehabilitation:

the purpose is to track the functional recovery of the knee joint after the operation of the patient and monitor the usage condition of the prosthesis for a long time.

The steps are as follows:

1. Periodic examination by periodic visual examination and functional assessment, the use of the knee prosthesis and the progress of recovery of the patient are monitored.

2. Functional rehabilitation assessment, namely helping a patient to recover knee joint functions through motion assessment and rehabilitation training, and ensuring flexible and stable joint motion.

The flow of the total knee replacement module is from the knee CT image segmentation and three-dimensional reconstruction before operation, the preoperation planning, the point cloud registration, osteotomy and gap balance during operation, and the real-time display and navigation, and finally the postoperative image evaluation and rehabilitation tracking, so that the accurate implementation of operation is ensured, and the postoperative function recovery effect of a patient is improved to the greatest extent.

Wherein, the three-dimensional model reconstruction and osteotomy path formula of knee joint is:

M _knee A three-dimensional model of the knee joint is generated for surgery.

Segmentation function based on CT image gradientExtracting the three-dimensional structure of the knee joint.

Omega _knee knee joint region of CT image.

Mu _i (t) controlling the time variation coefficient of the knee osteotomy path.

Osteotomy path coordinates of the knee joint.

Lambda is regularization coefficient to control the smoothness of osteotomy path.

The laplace operator of the osteotomy path is used to adjust the cutting surface smoothness.

In one embodiment, a unicondylar joint replacement module is configured to:

Specifically, the preoperative segmentation and intraoperative cutting optimization formula in unicondylar joint replacement is as follows:

M _{unicompartment} three-dimensional model of unicondylar joint and osteotomy result.

P _{unicompartment} (x, y, z) Structure of the unicondylar joint in the (x, y, z) space.

Gradient information of the unicondylar joint is used for segmenting and extracting the structure.

And beta _i, controlling the weight coefficient of the cutting path.

F _i (θ (t), φ (t)) represents a function of the cutting angles θ (t) and φ (t).

Γ _cut an intraoperative cleavage path.

And gamma, smoothing coefficient for regulating smoothness of cutting path.

The gradient of the cutting angle indicates the rate of change of the cutting angle with time.

Fig. 4 is a schematic structural view of an end connector for total knee or unicondylar joint replacement, which is fixed at the end of a mechanical arm for connecting a medical swing saw according to an embodiment of the present application.

Fig. 5 is a schematic structural view of a medical pendulum saw for total knee or unicondylar joint replacement for performing osteotomy procedures on a femur and tibia, in accordance with one embodiment of the present application.

In one embodiment, the periacetabular osteotomy module is used for pre-operative planning, intraoperative registration, osteotomy, positioning, navigation, and real-time display.

In one embodiment, preoperative planning, intraoperative registration, osteotomy, positioning, navigation, and real-time display, includes:

Acquiring a hip joint image of a patient;

The specific procedure flow for the "periacetabular osteotomy module" is described as follows:

1. Preoperative preparation:

1.1 acquiring hip joint images of a patient:

the purpose is to ensure that clear and detailed joint images are obtained to guide the subsequent processing.

The steps are as follows:

1. image acquisition, namely acquiring image data of the hip joint of a patient through CT or MRI scanning, wherein the joint structure and surrounding soft tissues are focused on.

2. And (3) image importing, namely importing the acquired image data into a processing system for subsequent analysis.

1.2 Image segmentation and three-dimensional reconstruction:

The method aims at extracting the three-dimensional structure of the hip joint and providing a foundation for operation planning.

The steps are as follows:

1. Image preprocessing, namely improving the image quality and enhancing the visibility of joint edges through denoising and enhancing technologies.

2. Segmentation algorithm application, namely segmenting the hip joint by using deep learning (such as CNN) or a traditional image processing method, and extracting key structures such as acetabulum, femur and the like.

3. Three-dimensional reconstruction, namely, creating a three-dimensional model of the hip joint by utilizing the segmented data, and ensuring that the model accurately reflects the anatomical features of a patient.

1.3 Preoperative planning:

The purpose is to make an accurate osteotomy plan to ensure successful operation.

The steps are as follows:

1. Osteotomy planning, namely designing an osteotomy around the acetabulum according to a three-dimensional model, and planning according to anatomical structures such as the anterior ischial bones, the suprapubic ramus, the upper ilium and the posterior column.

2. And determining a guide line and a safety zone, namely drawing an operation guide line, defining the safety zone of the osteotomy, and calibrating the boundary of the safety zone to avoid damaging important structures in operation.

3. And the result rendering, namely visualizing the planning result by using a rendering technology, highlighting the osteotomy face and the safety area by coloring, and facilitating preoperative evaluation of doctors.

2. Intraoperative manipulation:

2.1 intraoperative registration

The aim is to ensure accurate alignment of the intra-operative navigation system with the patient anatomy.

The steps are as follows:

1. The infrared camera is provided with an NDI reflection positioning navigation system, so that the NDI reflection positioning navigation system can capture positioning data of an operation area in real time.

2. Initial positioning, namely performing preliminary registration according to the preoperative planning model and the actual anatomical structure, and ensuring that a navigation system is accurate.

2.2 Osteotomy:

The purpose is to accurately implement osteotomy according to the plan.

The steps are as follows:

1. And (3) positioning the bone knife, namely fixing the arc-shaped blade of the bone knife at a preset osteotomy position through a positioning frame, and ensuring the compliance with preoperative planning.

2. And (3) monitoring in real time, wherein in the process of osteotomy, the navigation system acquires the position of the tail end of the osteotome in real time, and monitors the deviation between the position and the planning result.

3. Osteotomy is implemented according to preoperative planning, and the cutting angle and depth are ensured to be accurate.

2.3 Positioning and navigation:

The purpose is to realize real-time feedback and ensure the operation precision.

The steps are as follows:

1. And feeding back in real time, wherein in the process of osteotomy, the system displays the comparison between the position of the osteotome and the preoperative planning, so that the operation accuracy is ensured.

2. And (3) adjusting and optimizing, namely carrying out necessary adjustment on the position of the bone knife according to the real-time data, and ensuring that the final effect of the operation meets the expectations.

3. Post-operative evaluation:

3.1 post-operative examination

The aim is to verify the osteotomy effect and the joint function recovery.

The steps are as follows:

1. Imaging examination, namely, evaluating the accuracy of osteotomy and the recovery condition of bone structure by using imaging technologies such as X-ray or CT.

2. And (3) effect evaluation, namely confirming the functional state of the hip joint after operation, including the activity range and the stability, and evaluating the operation effect.

The whole process of the acetabular surrounding osteotomy module comprises the steps of preoperative image acquisition, segmentation and three-dimensional reconstruction, preoperative accurate planning, intraoperative real-time registration, osteotomy and navigation, postoperative examination and evaluation, and high accuracy of operation implementation and good recovery of patients are ensured. The module combines the modern imaging technology and the navigation system, so that the safety and effectiveness of the operation are improved, and the development of the joint replacement operation is promoted.

Specifically, the osteotomy face and positioning optimization formula of the osteotomies around the acetabulum is as follows:

S _cut, an osteotomy face of the acetabulum osteotomy.

P _acetadular (x, y, z), three-dimensional structure around the acetabulum.

P _safe (x, y, z), three-dimensional coordinates of the security area.

Kappa (theta, phi): curvature function on osteotomy path, depends on angles theta and phi.

Omega _acetabular: three-dimensional spatial region of the acetabulum.

And lambda _i, a weight coefficient, which is used for adjusting the positioning accuracy of the infrared camera.

Real-time position information of the distal end of the osteotome changes with time t.

In one embodiment, the sports medical module is for:

acquiring a first knee joint CT image;

Neural network CT image segmentation based on deep learning;

performing knee joint 3D modeling according to the segmentation result;

bone tunnel planning and ligament reconstruction;

In one embodiment, the rigid registration of the preoperative registration point with the intraoperative registration point based on digital twinning techniques is accomplished with a probe, comprising:

The detailed description of the specific step flow of the sports medical module is as follows:

1. Preoperative preparation:

1.1 acquiring a first knee CT image:

the steps are as follows:

1. patient preparation, ensuring patient comfort and informing the scanning process.

CT scanning, namely imaging knee joints by using a high-resolution CT scanner, ensuring that the scanning covers all important structures of the joints, and acquiring high-quality images.

3. And data storage, namely storing the scanning result in a DICOM format, so that the subsequent processing is convenient.

1.2 Neural network CT image segmentation based on deep learning:

the steps are as follows:

1. And (3) preprocessing the data, namely preprocessing the CT image, including denoising and contrast enhancement, so as to improve the segmentation effect.

2. Model training, namely selecting a proper deep learning model (such as U-Net), training by using the marked knee joint image, and optimizing model parameters.

3. Image segmentation, namely, a trained model is applied to segment a CT image, structures such as knee joints, bones and soft tissues are automatically extracted, and a binarization segmentation result is generated.

1.3 Knee 3D modeling based on segmentation results:

the steps are as follows:

1. And generating a three-dimensional model, namely converting the segmented binary image data into a three-dimensional grid model and using three-dimensional reconstruction software (such as MeshLab).

2. Model optimization, namely smoothing the three-dimensional model to remove noise and unnecessary details so as to ensure the accuracy and the visualization effect of the model.

3. Model verification, namely comparing the model with the professional knowledge of a doctor to verify whether the three-dimensional model accurately reflects the anatomical structure of the knee joint.

2. Preoperative planning:

2.1 setting preoperative guide points and planning preoperative registration points

The steps are as follows:

1. Guide point calibration-key anatomical landmarks are selected on the 3D model, and preoperative guide points, such as anterior cruciate ligament and posterior cruciate ligament attachment points of the knee joint, are set.

2. And selecting registration points, namely selecting a plurality of registration points according to bone tunnel planning, and recording coordinates of the registration points on a three-dimensional model to serve as a reference for registration in operation.

2.2 Bone tunnel planning and ligament reconstruction:

the steps are as follows:

1. and (3) tunnel planning and design, namely designing a path of the bone tunnel by using professional software (such as chemicals) to ensure that the bone tunnel and surrounding structures are safe and meet biomechanical requirements.

2. Ligament reconstruction strategy, determining a reconstruction scheme, defining ligament types and positions to be reconstructed, and making operation steps.

3. Intraoperative manipulation:

3.1 acquisition of intraoperative registration Point Using probes

The steps are as follows:

1. the probe preparation, namely selecting a probe suitable for operation, and ensuring accurate positioning.

2. Positioning in operation, in the operation process, using the probe to conduct actual positioning against the guide point and the registration point set before operation, and recording the position of the probe.

3.2 Rigid registration based on digital twinning technique:

the steps are as follows:

1. And performing initial registration, namely performing initial registration on the registration points acquired in the operation and the points arranged before the operation to form an initial registration matrix.

2. Digital twin positioning, namely positioning the probe in real time by using a digital twin technology, and ensuring the accurate mapping of the probe in the three-dimensional space.

3. And (3) three-dimensional mapping and monitoring, namely mapping the three-dimensional skeleton model into a real-time color image, monitoring the three-dimensional model by using the position of the probe tip, and correcting the initial registration matrix.

3.3 Automatically adjusting the registration matrix:

the steps are as follows:

1. And (3) matrix correction, namely correcting the initial registration matrix according to real-time data feedback, so as to ensure the accuracy of the initial registration matrix.

2. And finally registering, namely further adjusting the registering matrix through an automatic algorithm to generate a final rigid registering matrix.

4. And (3) establishing a coordinate system:

4.1 establishing a coordinate System of the mechanical arm, the optical positioning tracker and the knee joint

The steps are as follows:

1. and (3) calibrating a coordinate system, namely calibrating the coordinate systems of the mechanical arm and the optical positioning system according to the final rigid registration matrix.

2. Coordinate system integration, namely ensuring that the coordinate systems of the mechanical arm, the optical system and the knee joint are consistent so as to realize seamless cooperation.

5. Bone tunnel reconstruction:

5.1 controlling autonomous movement of mechanical arm to reconstruct bone tunnel

The steps are as follows:

1. And (3) a control program of the mechanical arm is written according to the registration result, so that the operation of reconstructing the bone tunnel can be accurately executed.

2. And executing the reconstruction operation, namely starting the mechanical arm, reconstructing according to a preset tunnel planning path, and monitoring parameters and states in the process in real time to ensure the accuracy of the operation.

6. Digital twinning technique application:

6.1 probe tracking and localization:

the steps are as follows:

1. And (3) tracking the probe in real time, namely continuously tracking the position of the probe in a three-dimensional space by adopting a multi-mode multi-scale fusion probe tracking algorithm.

2. The needle point positioning algorithm is applied, namely, the specific position of the probe needle point is obtained in real time by utilizing the needle point positioning algorithm based on multi-mode and multi-scale fusion, and the positioning accuracy and stability of the probe needle point are ensured.

The module describes in detail the complete flow of bone tunnel reconstruction from preoperative CT image acquisition, deep learning segmentation, three-dimensional modeling, setting of preoperative guide points and registration points, use of an intraoperative probe, application of digital twin technology and autonomous movement of a mechanical arm. By combining advanced image processing, artificial intelligence, real-time monitoring and mechanical control technologies, the module remarkably improves the accuracy and safety of knee joint operation, and is beneficial to improving the postoperative recovery effect of patients.

Specifically, the optimization formula of bone tunnel reconstruction and registration is as follows:

t _bone (x, y, z, T) the three-dimensional model of bone tunnel reconstruction, which varies with time T, is used for intra-operative navigation.

Omega _bone three-dimensional region of bone tunnel.

The expected coordinates of the preoperative bone tunnel are defined in x ', y ', z ' space and vary with time t.

G (x-x ', y-y ', z-z ') is a Gaussian kernel function for smoothing bone tunnel coordinate changes and adjusting smoothness between different locations.

Regularization coefficient, controlling the influence of registration points before and after operation.

The coordinates of the postoperative bone tunnel change with time t.

In one embodiment, the spinal staple positioning navigation module is configured to:

Filling in basic information of a patient in an operation;

Shooting a spine CT image of a patient;

intraoperative planning and real-time positioning navigation.

The specific step flow of the 'spine nail positioning navigation module' is further detailed and complicated as follows:

1. Preoperative preparation:

1.1 filling in basic information of patients in operation:

the steps are as follows:

1. Patient information collection:

Basic information of a patient is entered, including name, age, gender, medical record number, etc., using an electronic health record system.

The patient's past history, allergic reactions, and existing diseases are recorded so that the surgical team can fully understand the patient's condition.

2. Preoperative discussion:

team meetings are held before operation, specific situations of patients are discussed, and an optimal operation scheme is determined.

The surgical team members, anesthesia protocol, and post-operative care schedule were confirmed.

1.2 Taking a CT image of the spine of a patient:

the steps are as follows:

1. Patient positioning:

The patient is placed on the CT scanner, so that the median line of the spine is ensured to be aligned with the scanning center, and image distortion caused by posture deviation is avoided.

Positioning tools (e.g., laser positioners) are used to ensure accuracy of patient position.

Ct scan execution:

the selection of appropriate scan parameters (e.g., layer thickness, reconstruction algorithm) ensures that a high quality image of the spine is obtained.

A multi-phase scan (e.g., transverse, sagittal, and coronal) is performed to obtain more comprehensive anatomical information.

3. Data processing and storage:

after scanning is completed, the image is subjected to post-processing by using professional image processing software, including denoising, contrast enhancement and reconstruction.

The results are saved to a secure storage server in DICOM format, ensuring that the images can be recalled at any time during the procedure.

2. Intraoperative manipulation:

2.1 three-dimensional registration based on a three-dimensional calibrator:

the steps are as follows:

1. And (3) mounting a three-dimensional calibrator:

the three-dimensional sizer is precisely positioned at the patient's spinal location to ensure alignment with anatomical features such as the edges of the vertebral body.

The calibrator is fixed using a special clamp to prevent movement during the procedure.

2. Image registration process:

And acquiring real-time position information of the calibrator through an optical or laser tracking system, and registering with the CT image.

Registration algorithms (e.g., rigid registration and non-rigid registration) are applied to align the CT image with the actual anatomy of the patient through iterative optimization calculations.

3. Registration verification:

by comparing the position of the marker in the CT image with the actual position, statistical analysis methods (e.g., root mean square error) are used to evaluate registration accuracy.

If the deviation exists, the position of the calibrator is adjusted, and the registration process is repeated until the precision requirement is met.

2.2 Intraoperative planning and real-time positioning navigation:

the steps are as follows:

1. Navigation path planning:

based on the registered CT images, a specialized software (such as navigation system integrated software) is used for designing a nail placement path, so that important nerves and vascular structures are avoided.

Determining the angle, depth and relative position of the nail, making a detailed operation scheme, and generating an operation guiding graph.

2. Real-time monitoring and feedback:

The navigation system is started, the position of the probe or the nail is monitored through the optical or electromagnetic positioner, and the position information is updated on the display screen in real time.

And (3) superposing the real-time position information and the CT image by applying a data fusion technology, and providing visual navigation support.

3. Navigation operation:

The doctor adjusts the direction and position of the probe or nail according to the real-time feedback provided by the navigation system, so as to ensure accurate insertion to the preset position.

In the whole operation process, communication with an operation team is kept, potential problems are handled in time, and smooth operation is ensured.

3. The post-operation steps are as follows:

3.1 data recording and analysis

The steps are as follows:

1. Post-operation data arrangement:

key data in the surgical procedure is recorded, including parameters such as position, angle, depth, etc. provided by the navigation system.

And collecting the real-time image and the final image in the operation, and comparing and analyzing.

2. Evaluation of results:

and comparing the navigation path with the actual nail placement position after operation, and evaluating the accuracy and success rate of nail placement.

And providing improved suggestions for future operations according to postoperative evaluation results.

The module describes the complete flow from preoperative patient information input, CT image shooting, installation and registration of a three-dimensional calibrator, and finally real-time navigation planning and monitoring. By introducing complicated technical means and data analysis methods, the accuracy and the safety of the spine nailing operation are ensured, and the treatment effect and the recovery efficiency of a patient are finally improved.

Specifically, the three-dimensional registration and positioning formula in the spine nail is as follows:

e _spine (x, y, z, t) registration error function in spinal fixation, as a function of time t.

Omega _spine three-dimensional spatial region of the spine.

The pre-operative spinal registration point coordinates change over time.

Post-operative spinal registration point coordinates.

R _spine (x, y, z) rigid rotation matrix for rotating post-operative coordinates to pre-operative positions.

The gradient of the spine is used to calculate the rate of change of coordinates.

Lambda regularization parameters for controlling positioning smoothness.

Surgical tool position information during surgery.

In one embodiment, the wound localization navigation module is configured to:

Filling in basic information of a patient in an operation;

Taking an X-ray image of a wound site of a patient;

performing two-dimensional registration based on a two-dimensional calibrator;

intraoperative planning and real-time positioning navigation.

The specific step flow of the wound positioning navigation module is further detailed and complicated as follows:

1. Preoperative preparation:

1.1 filling in basic information of patients in operation:

the steps are as follows:

1. electronic information system input:

basic information (name, sex, age, medical record number, etc.) of a patient is accurately recorded in an operating room by using an electronic health record system.

The past medical history of the patient (including allergies, chronic diseases, etc.) is recorded, ensuring that the surgical team has a full understanding of the patient's health.

2. Preoperative case discussion:

A multidisciplinary team meeting is held, patient history and imaging results are reviewed, and surgical risks and expected effects are discussed.

And determining the division of the operation team and the postoperative rehabilitation plan, and ensuring that each team member knows the respective responsibility.

1.2 Taking X-ray images of the wound site of the patient:

the steps are as follows:

1. Patient positioning:

The patient is placed under an X-ray machine and his posture is adjusted to ensure optimal visualization of the wound area.

The use of a balloon stent or other fixation device stabilizes the wound site, ensuring that it does not move during the imaging procedure.

2. Multi-angle X-ray photographing:

And selecting a plurality of visual angles (such as normal position, lateral position and oblique position) for X-ray shooting, so as to ensure that comprehensive wound information is acquired.

Appropriate exposure parameters (e.g., kilovolt features, milliamps) are set to improve image quality and reduce radiation dose.

3. Image post-processing:

and (3) performing post-processing on the X-ray image through image processing software, wherein the post-processing comprises denoising, contrast enhancement and pseudo-color processing, so that the visibility of an anatomical structure is improved.

The processed images are stored in DICOM format and associated with the patient file to ensure ready access during surgery.

2. Intraoperative manipulation:

2.1 two-dimensional registration based on a two-dimensional calibrator

The steps are as follows:

1. Calibration device installation and calibration:

The two-dimensional calibrator is accurately fixed at the wound part of the patient, so that the key points of the calibrator are consistent with surrounding anatomical structures (such as bones and soft tissues).

And a three-dimensional laser scanner is used for carrying out preliminary scanning on the calibrator and surrounding structures so as to ensure stable and accurate recording of the positions of the calibrator and surrounding structures.

2. Two-dimensional registration process:

registering the X-ray image shot in the operation with a calibrator, and performing feature matching and position correction by using professional image processing software.

And combining the preoperative CT image with the intraoperative X-ray image by adopting an image fusion technology, and accurately aligning the position of the calibrator with the wound part through algorithm optimization.

3. Registration accuracy verification:

and comparing the registration result with the actual position of the calibrator in the X-ray image, and evaluating the registration accuracy through statistical analysis (such as standard deviation and root mean square error).

If the deviation is found, the position of the calibrator is readjusted, and the registration is performed again until the registration result meets clinical requirements.

2.2 Intraoperative planning and real-time positioning navigation:

the steps are as follows:

1. navigation path and target point planning:

Based on the registration, navigation system software is used to formulate a surgical path of the wound site, and define key points (such as bone nail positions, incision positions and the like).

Based on the anatomical features, wound type, and expected outcome, a detailed surgical guidance map is generated, including coordinates, angles, and depths of each key operating point.

2. Starting a real-time monitoring and feedback system:

The navigation system is activated to continuously track the real-time position of the surgical instrument (e.g., probe, bone nail) via an optical or electromagnetic positioner.

The real-time position information is dynamically compared with the planned path, real-time feedback is provided, and the doctor is ensured to adjust the operation direction and the operation force in time.

3. The precise operation is performed:

the doctor adjusts the position of the probe or the bone nail according to the real-time data provided by the navigation system, so as to ensure accurate insertion to the preset position.

The motion trail of the probe or the bone nail is continuously monitored in the operation, the potential risk is identified by utilizing an intelligent algorithm, and a warning is timely sent out.

3. The post-operation steps are as follows:

3.1 data recording and analysis:

the steps are as follows:

1. surgical data arrangement and archiving:

The surgical image, navigation data, registration results, and surgical records are integrated into an electronic health record of the patient.

2. Post-operative result analysis and assessment:

and comparing the navigation path with the actual wound treatment result in the operation process, and evaluating the accuracy of the nail placement, the success rate of the operation and possible complications.

Based on the evaluation results, post-operative discussions are performed to provide improvement suggestions for future similar cases, enhancing team collaboration and learning.

The module describes the complete flow from preoperative patient information input, X-ray image shooting, installation and registration of a two-dimensional calibrator, and finally real-time navigation planning and monitoring. By introducing complicated technical means and data analysis methods, the accuracy and safety of the wound operation are ensured, the treatment effect and recovery efficiency of patients are improved, and the development of medical technology is promoted.

Specifically, the two-dimensional registration and navigation formula of the wound part is as follows:

The two-dimensional registration of the wound site varies with time.

Omega _trauma two-dimensional image area of the wound site.

The registration point coordinates of the initial wound site change over time.

G (x-x ', y-y') is a Gaussian kernel function for smoothing the relationship between the wound registration points.

Gradient information of the two-dimensional image.

Lambda regularization coefficient for controlling the smoothness of the positioning of the wound site.

The positional information of the intraoperative trauma positioning tool varies with time.

Fig. 6 is a schematic structural view of an active light emitting tip for periacetabular osteotomies, sports medicine, spinal nail positioning navigation, trauma positioning navigation, which is fixed to a robotic arm tip for positioning, according to one embodiment of the present application.

FIG. 7 is a schematic structural view of a guide for periacetabular osteotomies, sports medicine, spinal staple positioning navigation, trauma positioning navigation for trauma function sleeve positioning, according to one embodiment of the application.

Fig. 8 is a schematic diagram of a system structure of an artificial intelligent surgical robot for multiple diseases in orthopaedics, according to an embodiment of the present application. In fig. 8, the navigation trolley, the mechanical arm trolley and the main control trolley are respectively arranged from left to right.

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

In particular, the processor 901 may include a Central Processing Unit (CPU), or an Application SPECIFIC INTEGRATED Circuit (ASIC), or may be configured as one or more integrated circuits that implement embodiments of the present application.

Memory 902 may include mass storage for data or instructions. By way of example, and not limitation, memory 902 may comprise a hard disk drive (HARD DISK DRIVE, HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) drive, or a combination of two or more of the foregoing. The memory 902 may include removable or non-removable (or fixed) media, where appropriate. The memory 902 may be internal or external to the electronic device, where appropriate. In a particular embodiment, the memory 902 may be a non-volatile solid state memory.

In one embodiment, the Memory 902 may be a Read Only Memory (ROM). In one embodiment, the ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

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

In one example, the electronic device may also include a communication interface 903 and a bus 910. As shown in fig. 9, the processor 901, the memory 902, and the communication interface 909 are connected to each other via a bus 910 and perform communication with each other.

The communication interface 903 is mainly used to implement communication between each module, device, unit, and/or apparatus in the embodiment of the present application.

Bus 910 includes hardware, software, or both that couple components of an electronic device to each other. By way of example, and not limitation, the buses may 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 other suitable bus, or a combination of two or more of the above. Bus 910 may include one or more buses, where appropriate. Although embodiments of the application have been described and illustrated with respect to a particular bus, the application contemplates any suitable bus or interconnect.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. The method processes of the present application are not limited to the specific steps described and shown, but various changes, modifications and additions, or the order between steps may be made by those skilled in the art after appreciating the spirit of the present application.

The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.

It should also be noted that the exemplary embodiments mentioned in this disclosure describe some methods or systems based on a series of steps or devices. The present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, or may be performed in a different order from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present application, and they should be included in the scope of the present application.

Claims

1. An artificial intelligence surgical robot system for orthopedics multiple diseases, comprising:

The system comprises an acetabular surrounding osteotomy module, a preoperative planning module, an intraoperative acetabular surrounding osteotomy module, an intraoperative imaging module and an imaging module, wherein the acetabular surrounding osteotomy module is used for preoperative planning, intraoperative registration, osteotomy, positioning, navigation and real-time display and comprises the steps of acquiring hip joint images of a patient, segmenting and three-dimensionally reconstructing the hip joint images to obtain a hip joint three-dimensional model, utilizing the hip joint three-dimensional model to plan the osteotomy surrounding osteotomy section, a guide line and a safety zone, determining a safety zone boundary and rendering coloring, wherein the preoperative planning result comprises planning osteotomy according to the front part of ischium, the upper pubic ramus, the upper ilium and the rear column;

The motion medical module is used for bone tunnel planning and ligament reconstruction and displaying in real time, the motion medical module is used for acquiring a first knee joint CT image, neural network CT image segmentation based on deep learning, 3D modeling of the knee joint according to segmentation results, pre-operation guide points and pre-operation registration points planning on the knee joint, bone tunnel planning and ligament reconstruction, acquisition of the pre-operation registration points by using probes according to the pre-operation guide points in operation, rigid registration of the pre-operation registration points and the intra-operation registration points based on a digital twin technology by using the probes, wherein the rigid registration comprises coarse registration and fine registration, coordinate system establishment of the mechanical arm, the optical positioning tracker and the knee joint is completed according to registration results, and autonomous movement of the mechanical arm is controlled to reconstruct the bone tunnel;

2. The total orthopaedic multi-disease artificial intelligence surgical robotic system of claim 1, wherein the total hip replacement module is configured to:

3. The total orthopaedic multi-disease artificial intelligence surgical robotic system of claim 1, wherein the total knee replacement module is configured to:

4. The total orthopaedic multi-disease artificial intelligence surgical robotic system of claim 1, wherein the unicondylar joint replacement module is configured to:

5. The system of claim 1, wherein the rigid registration of the preoperative registration point and the intraoperative registration point based on digital twinning techniques is accomplished using a probe, comprising:

6. The total orthopaedic multi-disease artificial intelligence surgical robotic system of claim 1, wherein the spine staple positioning navigation module is configured to:

Filling in basic information of a patient in an operation;

Shooting a spine CT image of a patient;

intraoperative planning and real-time positioning navigation.

7. The system of claim 1, wherein the trauma positioning navigation module is configured to:

Filling in basic information of a patient in an operation;

Taking an X-ray image of a wound site of a patient;

performing two-dimensional registration based on a two-dimensional calibrator;

intraoperative planning and real-time positioning navigation.