144 results about "Preoperative planning" patented technology

The invention provides a unicompartmental knee arthroplasty robot navigation and positioning system and method. The system comprises a preoperative planning module, a positioning and navigation module and a mechanical arm control module. The preoperative planning module is used for carrying out knee joint segmentation and reconstruction according to the obtained knee joint medical image, carrying out preoperative planning and determining a unicompartmental knee arthroplasty scheme; the positioning navigation module is used for registering the intraoperative solid knee joint and the preoperative knee joint three-dimensional model according to the navigator and the tracer, and tracking the poses of the osteotomy tool and the solid knee joint in real time; and the mechanical arm control module is used for planning a motion path of the mechanical arm and controlling the mechanical arm to execute the motion path. In this way, the mechanical arm can be controlled to assist in completing the osteotomy operation of unicompartmental knee arthroplasty in a preoperative planning and intraoperative optical navigation mode, and the problems that the operation level is uneven and the operation effect is not expected due to different individuals in the current manual operation are solved.

The invention relates to a myocardial resection area determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a heart scanning image, and determining a heart three-dimensional model according to the heart scanning image; determining a heart short-axis section and a heart long-axis section according to the heart three-dimensional model; the clock direction angle of the scalpel is determined on the short axis section of the heart; based on the clock direction angle, the excision depth of the scalpel is determined on the long-axis section of the heart; and performing myocardial resection on the heart three-dimensional model according to the clock direction angle and the resection depth through a scalpel model, determining an updated three-dimensional model after myocardial resection, and marking a resection area on the updated three-dimensional model. According to the scheme, accurate preoperative planning guidance and comprehensive heart structure information presentation are provided for the myocardial rotary cutting operation, and therefore the accuracy and safety of the myocardial rotary cutting operation are improved.

The invention provides an implant immediate denture precise manufacturing system based on preoperative planning and three-dimensional registration. An example method includes obtaining first oral data, the first oral data including three-dimensional data of a denture model and three-dimensional data of a marker; acquiring second oral cavity data, wherein the second oral cavity data comprises scanning data of a plurality of bases fixed in the oral cavity and a marker; registering the first scanning data and the second scanning data based on the matching of the three-dimensional data of the marker and the scanning data of the marker; a denture model to be processed is generated based on a result of the registration, the denture model to be processed comprising three-dimensional data of the denture model and positioning information of a plurality of holes, each hole being for accommodating one of the plurality of abutment. According to the embodiment of the invention, the accurate positioning of the false tooth model and the abutment is realized by using a digital technology, the accurate matching of the false tooth and the abutment is ensured, and the comfort and experience of a dental implant patient are improved.

Systems and methods for fully automated anatomical analysis of an anatomical structure are provided to facilitate pre-operative planning. The computerized method may include obtaining a plurality of images, e.g., MSCT images, of patient-specific cardiovascular anatomy, and analyzing the MSCT images with a trained artificial intelligence module to identify one or more anatomical landmarks and to construct a virtual three-dimensional model of the anatomical structure. For example, the trained artificial intelligence module may execute segmentation, point detection, curve detection, or plane detection deep learning modules, independently or in combination, to identify the anatomical landmarks. The method further may include deriving anatomical measurements of the one or more identified anatomical landmarks, and displaying the virtual three-dimensional model alongside the anatomical measurements of the one or more identified anatomical landmarks.

The invention discloses a medical image intelligent diagnosis and three-dimensional visualization interaction method and system based on artificial intelligence and Unreal Engine. The system is composed of a data acquisition module, an artificial intelligence analysis module, a three-dimensional reconstruction module, a rendering interaction module and a report generation module. The method comprises the following steps: firstly, carrying out voxel normalization on a DICOM / NIfTI image; the improved 3D U-Net is combined with CBAM attention and WGAN-GP training, and a focus initial density field is output; an AI enhanced implicit voxel reconstruction (AEIVR) algorithm is proposed, an enhanced density field is generated by using position coding + MLP, and grid extraction is completed by using improved Marking Cubes of a dynamic threshold; high-fidelity real-time rendering is realized in combination with a Nand micro polygon and Lumen global illumination in Unreal Engine, and VR / AR interaction and virtual surgery (real-time updating of resection mask driving) are supported. According to the method, the problems of large artifacts and insufficient interactivity and real-time performance of existing two-dimensional output and three-dimensional reconstruction are solved, and the end-to-end segmentation-reconstruction-rendering-interaction-reporting process is realized. On typical CT / MRI data, the segmentation Dice is about 0.90-0.94, the reconstruction voxel resolution is 0.1-0.5 mm, the artifacts are reduced by about 20%-30%, the PSNR is improved by about 3-7 dB, and the rendering interaction delay lt is achieved; the system is suitable for scenes such as lung CT, brain MRI, orthopaedic X-ray and cardiac ultrasound, and can be expanded to preoperative planning, remote consultation and teaching.

Disclosed herein is a system and method for performing pre-operative planning of total joint arthroplasty. The planning tool builds a model and analyzes and visualizes movement of the joint for various selections of implant models and placement of the components on the implants on the patient's anatomy. The tool also analyzes and visualizes motions of the joint during common activities of daily living and analyzes and functional ranges. The tool provides real time clinically relevant parameters to inform pre-surgery planning. The tool provides screw orientation visualization.

The invention relates to the technical field of edge segmentation, in particular to a tumor interventional therapy preoperative planning system based on artificial intelligence image recognition, and the method comprises the steps: preliminarily screening out an infiltration edge region based on the gray distribution asymmetry condition of a sliding window in a CT image and the texture disorder condition in an MRI image; further fusing DSA blood vessel data, and screening a concerned infiltration region by analyzing the position distribution condition of the blood vessel region of the infiltration edge region; analyzing curvature mutation conditions of the tumor associated blood vessel segments on the basis of the concerned infiltration region to generate a blood vessel anomaly index; and finally, fusing the infiltration index and the blood vessel characteristics to construct a blood vessel-infiltration coupling index, and correcting the edge strength map according to the blood vessel-infiltration coupling index, so that the boundary optimization based on risk classification is realized, the accuracy of the obtained tumor region edge structure curve is higher, and the accuracy of tumor region segmentation according to the tumor region edge structure curve is improved.

The invention discloses a hypertrophic cardiomyopathy (HCM) preoperative planning and operation effect evaluation method based on accurate digital labeling. The method comprises the following steps: performing digital labeling on the thickness of each wall of a left ventricle of a preoperative heart 3D digital model; according to the digital labeling result of the preoperative heart 3D digital model and the normal value of the thickness of the left ventricular wall, a doctor manually depicts the predicted resection range and confirms the predicted retention thickness; measuring the predicted resection volume, the predicted resection area and the left ventricular end diastolic volume after the predicted resection volume is resected; digitally marking the thickness of each wall of the left ventricle of the postoperative heart 3D digital model, and measuring the volume of the corresponding left ventricle in the end diastole; and taking the predicted resection range, the predicted retention thickness, the predicted resection volume, the predicted resection area and the predicted volume as first evaluation data, taking corresponding parameters of the postoperative heart 3D digital model as second evaluation data, and generating an operation evaluation result according to the conformity of the first evaluation data and the second evaluation data.

The invention provides a preoperative planning method for ligament reconstruction operation based on multi-modal data. The preoperative planning method of the ligament reconstruction operation based on the multi-modal data comprises the following steps: acquiring joint medical images of multiple modals of an operation site, and performing registration and fusion processing on the acquired joint medical images of multiple modals to obtain a joint medical image multi-modal fusion result; performing segmentation processing according to the joint medical image multi-modal fusion result to obtain a joint segmentation result; performing key point detection according to the joint segmentation result to obtain a key point detection result; according to the key point detection result, a ligament reconstruction preoperative planning scheme is generated.

The present disclosure includes methods (100, 200) for improving surgical accuracy and effectiveness in medical procedures by using an augmented reality system (300). The method (100, 200) involves: generating a preoperative plan in an augmented reality environment by visualizing a holographic representation of a patient's anatomy; recording program data according to the preoperative plan; using the recorded data to update the augmented reality system; and applying the updated system to establish a continuously improved feedback loop. According to the method, by integrating real-time data feedback into the operation process, the accuracy of the operation is improved, the effect of the patient is improved, the program is optimized, and continuous improvement of medical practice is promoted.

The invention discloses a real-time operation process feedback system for a spine endoscopic operation, and the system comprises a preoperative planning module which is used for obtaining a preoperative medical image, and extracting an outer contour of a specific structure from the preoperative medical image; the channel tool module is used for exposing an operation field, and the camera assembly is used for collecting binocular images and RGB images of an operation area in real time; the image registration module is used for reconstructing a three-dimensional surface point cloud of the operation area according to the binocular image of the operation area, and registering the three-dimensional surface point cloud with the outer contour of the specific structure; and the visualization module is used for segmenting the RGB image to obtain the surgical instrument, acquiring a pose relationship between the surgical instrument and the three-dimensional point cloud according to the internal reference of the camera assembly, and rendering the pose relationship to a three-dimensional model. Through the integrated transparent structural design, the working channel and the nerve drag hook are integrated, instrument interference is avoided, nerve protection is visualized in real time, the operation safety is improved, and the operation progress and the nucleus pulposus removal condition can be fed back in real time in the operation process.

This invention provides a method and system for generating simulated laparoscopic robot operation videos, relating to the field of generative artificial intelligence technology. The method includes acquiring a single frame RGB image of the laparoscopic robot's working scene; responding to the instrument dragging path executed by the user on the laparoscopic robot's interactive screen, processing the RGB image using an image segmentation model to obtain an instrument binary mask, and generating an instrument condition sequence based on the instrument binary mask and the instrument dragging path; and processing the RGB image and the instrument condition sequence using a pre-trained video generation model to generate a simulated laparoscopic robot operation video. This application generates a simulated robot operation video by inputting the first frame image and instrument motion conditions, which can be used to simulate potential surgical procedures under different instrument operation strategies and for different target personnel, providing an intuitive reference for preoperative planning, surgical teaching, and risk assessment.

The present application relates to the technical field of medical image processing, and provides a knee femur and tibia segmentation method based on region growing, comprising the following steps: S1, acquiring knee medical images; S2, selecting a growth seed point; S3, coarsely segmenting the knee medical images to obtain knee stem data; S4, finely segmenting the knee medical images to obtain knee connection data; S5, fusing the knee stem data and the knee connection data to obtain knee femur and tibia image data with complete contours; S6, coarsely filling the knee femur and tibia image data to obtain knee femur and tibia image data after coarse filling; and S7, iteratively filling holes in the knee femur and tibia image data by using a three-dimensional sliding window, so as to obtain image data that is consistent with the surrounding data in shape, position and completeness and smoothness. The present application solves the problems of slow segmentation speed, unstable segmentation effect, incomplete segmentation and adhesion in preoperative planning of knee replacement surgery.

To provide a device, a system, and a method for a preoperative plan and an intraoperative guidance for orthopedic surgery of a fractured joint suffering bone fragmentation.SOLUTION: A surgery system can be configured to acquire image data of a joint including at least a portion of humerus, segment the image data to determine a shape of a diaphysis of the humerus, determine a shape of the humerus before it becomes the estimated pathosis on the basis of the determined shape of the diaphysis, identify one or more bone chips in the image data on the basis of the estimated shape of the humerus, and generate an output on the basis of the bone chips identified in the image data.SELECTED DRAWING: Figure 35

The application discloses an oval foramen automatic detection and fine segmentation method based on an anatomic landmark gravity field and a tubular topology enhancement, and specifically relates to the technical field of medical image processing. Firstly, the head CT or MRI image to be processed is subjected to multi-modal space alignment and adaptive contrast enhancement; subsequently, the image is input into an anatomic landmark gravity field network, macroscopic landmarks of a skull base are extracted, a spatial gravity field matrix is constructed, and the model attention is adaptively focused on a small oval foramen high probability area; then, a multi-view tubular structure enhancement encoder is used to extract features of a three-dimensional hole track of the oval foramen, and the interference of non-penetrating bone depressions is inhibited; finally, a three-dimensional penetrating topology constraint mechanism is introduced in the decoding stage, so that the generated three-dimensional model of the oval foramen has correct anatomic connectivity. The application can effectively solve the detection problem of the oval foramen caused by the large individual variation, the small volume and the easy confusion with surrounding holes and fissures, and significantly improves the preoperative planning accuracy of trigeminal neuralgia puncture and other surgeries.

The application provides a surgical robot system and control method for proximal femur osteotomy, the system comprises: a preoperative planning module for constructing a hip joint three-dimensional model and performing preoperative planning according to the hip joint three-dimensional model to generate a proximal femur osteotomy scheme, which is one of a femoral head rotation osteotomy scheme, a femoral neck rotation osteotomy scheme, an intertrochanteric rotation osteotomy scheme and a subtrochanteric rotation osteotomy scheme; a navigation positioning module for registering the entity femur in operation and the hip joint three-dimensional model before operation according to an optical positioner and an optical positioning frame to map the proximal femur osteotomy scheme, real-time tracking the pose of the surgical tool and the entity femur, and displaying and comparing the proximal femur osteotomy scheme and the real-time osteotomy process on a display screen. In the application, the preoperative planning-intraoperative optical positioning navigation can track the osteotomy condition of the surgical tool in real time during operation, and multiple medical imaging is avoided, thereby greatly improving the surgical effect.

Disclosed are computer visual guidance systems for guiding surgeons through arthroscopic debridement of bony pathologies, including by automatically generating annotations relating to characteristics of bony pathology in an image. The annotation may be generated in accordance with a determination as to whether a femoral head of the bony pathology is endospherical or exospherical. The annotation may be generated in accordance with a mathematical model created based on anatomies of subjects other than the patient. Further disclosed is a user interfaces for guiding a surgeon through arthroscopic debridement of a bony pathology, wherein intraoperative images are displayed simultaneously with a preoperative plan comprising interactive three-dimensional models of an anatomical feature of a patient. Further disclosed is a user interface for guiding a physician in categorizing images of a patient, wherein the interface comprises an image viewing window and an interactive checklist for different image categories to be captured.

The application provides a three-dimensional CT image reconstruction method and system for lumbar disease diagnosis, and belongs to the technical field of three-dimensional medical image reconstruction; a plurality of two-dimensional CT images are acquired to train a deep neural network; a two-dimensional CT image to be segmented is input into the trained deep neural network for segmentation, and the segmented image is used as a pre-reconstruction image; three-dimensional CT image reconstruction is performed on the pre-reconstruction image based on a VTK rendering method, so that the visualization of the three-dimensional CT image is realized. The application can accurately and efficiently simultaneously segment the vertebrae, intervertebral discs and nerve structures in the lumbar CT image, and realizes image visualization through three-dimensional reconstruction of the segmented CT image, thereby providing strong support for lumbar disease diagnosis, preoperative planning and intraoperative guidance.

The application relates to the technical field of orthopedic surgery navigation, and discloses a high-position tibial osteotomy navigation method, a system and a storage medium, and a communication method which comprises the following steps: generating a 3D bone model of a lower limb of a patient based on medical images and performing preoperative osteotomy planning; performing visual positioning system detection and spatial calibration of a surgical instrument; installing an optical marker array, collecting actual bone point cloud data, and realizing alignment of the model and the bone through a registration algorithm; in-surgery real-time calculation and display of deviation of an operation track and planning parameters; post-surgery reconstruction of a lower limb force line, and comparison and evaluation with preoperative planning and in-surgery navigation records. The system comprises a hardware execution unit and preoperative planning, calibration verification, in-surgery registration, real-time navigation and post-surgery evaluation modules. The application realizes full-process integration of preoperative accurate planning, in-surgery real-time closed-loop navigation and post-surgery quantitative evaluation, and significantly improves the precision, repeatability and predictability of clinical effects of surgery.

Disclosed are computer visual guidance systems for guiding surgeons through arthroscopic debridement of bony pathologies, including by automatically generating annotations relating to characteristics of bony pathology in an image. The annotation may be generated in accordance with a determination as to whether a femoral head of the bony pathology is endospherical or exospherical. The annotation may be generated in accordance with a mathematical model created based on anatomies of subjects other than the patient. Further disclosed is a user interfaces for guiding a surgeon through arthroscopic debridement of a bony pathology, wherein intraoperative images are displayed simultaneously with a preoperative plan comprising interactive three-dimensional models of an anatomical feature of a patient. Further disclosed is a user interface for guiding a physician in categorizing images of a patient, wherein the interface comprises an image viewing window and an interactive checklist for different image categories to be captured.

The application provides a rectal cancer VR preoperative planning three-dimensional modeling system with simulated physical properties, and belongs to the technical field of surgical modeling. The system comprises a medical image three-dimensional model reconstruction module, a VR interaction module, a model physical property assignment module, a surgical behavior analysis module and a simulation control module. The medical image three-dimensional model reconstruction module is used for constructing a three-dimensional anatomical model; the VR interaction module is used for constructing an interactive operation dataset; the model physical property assignment module is used for constructing a tissue mechanical state dataset; the surgical behavior analysis module is used for constructing a surgical operation action intensity coefficient, an operation continuity coefficient and a tissue stress change coefficient; and the simulation control module is used for dynamically presenting a tissue physical response effect under rectal cancer surgical operation in a virtual reality environment. The application makes the tissue physical response presented in the virtual reality environment consistent with the current surgical operation state, and improves the real-time performance and reliability of the simulation process.

Embodiments of the present application pertain to the technical field of computer-assisted medical treatment and provide an orthopedic surgery guidance method and apparatus, and an orthopedic surgery guidance device. The method comprises: acquiring preoperative planning information of current orthopedic surgery; determining, according to the preoperative planning information, a target pose for a guide plate used during surgery, wherein the guide plate is designed to have at least one circular hole for guiding a drilling operation and at least one square groove for guiding an osteotomy operation; determining the current real-time pose of a guide plate mounted on the tail end of a robotic arm; and adjusting the guide plate from the real-time pose to the target pose by controlling movement of the robotic arm. The described method can be used to guide osteotomy operations and drilling operations in orthopedic surgery on the basis of the same guide plate. By means of accurate navigation and robotic arm control, a surgical target can be accurately positioned and operated.

This application applies to the fields of computer-aided medical technology and surgical robot technology, and provides a knee-preserving surgical robot and its control method. The knee-preserving surgical robot includes: a preoperative planning unit, used to determine the osteotomy plane based on the surgical key points on the patient's three-dimensional bone model, and plan the correction angle after establishing the target force line; an intraoperative execution unit, used to perform osteotomy operation according to the osteotomy plane with the assistance of a navigation system, so that the angle after the osteotomy site is stretched meets the requirements of the correction angle; and a postoperative evaluation unit, used to simulate postoperative bone images, calculate the force line angle based on the simulated postoperative bone images, and adjust the correction angle formed by the actual osteotomy according to the force line angle; tracers are respectively installed on the proximal and distal ends of the patient's bone and the corresponding surgical tools, and the navigation system provides position data for the operations performed by the intraoperative execution unit and the postoperative evaluation unit by tracking the position changes of the tracers.

The invention discloses an embedded tooth impacted tooth positioning traction simulation system based on a 5D bionic technology, which comprises a jaw model and a pre-operation simulation system, the jaw model is provided with an alveolar socket, a tooth root model and an embedded tooth model are detachably arranged in the alveolar socket, the jaw model is provided with a traction device in a mutual matching manner, and the traction device is provided with a tooth root model and an embedded tooth model. The traction device comprises two fixers and a traction arch wire; the two fixers are sleeved on the tooth root model; the traction arch wire is connected with the two fixers; a closed curve for hooping the embedded tooth model is arranged on the traction arch wire; a positioning guide plate is used in cooperation with the tooth root models, a positioning window is arranged on the positioning guide plate, the position of the positioning window corresponds to the position of the embedded tooth model, and a model taking device is used in cooperation with the closed curve. A real operation environment is provided for a doctor, the positioning guide plate accurately corresponding to the position of the embedded tooth is combined, the traction device can be guided to be in place rapidly and accurately, the precision and efficiency of preoperative planning are greatly improved, and the operation risk is reduced.

The embodiment of the invention discloses a three-dimensional myocardial scar visualization system. According to one specific embodiment, the system comprises a data processing end configured to perform heart structure and scar segmentation on target heart magnetic resonance data to obtain a binary tag graph for the heart and the myocardium; constructing an individualized ventricular network and a scar three-dimensional surface model based on the binary label graph; generating an initial myocardial scar three-dimensional model; generating lead implantation track information; generating a myocardial scar three-dimensional model according to the lead implantation track information; and the model application end is configured to perform model rendering on a target application page according to the model parameters corresponding to the myocardial scar three-dimensional model sent by the data processing end so as to provide an interactive operation function and generate a clinical report. According to the embodiment, accurate and visual three-dimensional visual decision support can be provided for preoperative planning and intraoperative navigation of heart diseases, so that the accuracy of surgical planning and the clinical working efficiency are remarkably improved.

The invention provides a unicompartmental knee arthroplasty surgical robot system and a control method, and the system comprises a preoperative planning module which is used for carrying out the segmentation and reconstruction of a knee joint according to an obtained knee joint medical image, carrying out the preoperative planning, and determining a unicompartmental knee arthroplasty scheme; the positioning navigation module is used for carrying out registration on the intraoperative entity knee joint and the preoperative knee joint three-dimensional model according to the navigator and the tracer so as to map a unicompartmental knee replacement scheme and track the poses of the guide equipment and the entity knee joint in real time; and the mechanical arm control module is used for planning a path from the mechanical arm to the preparation position and controlling the mechanical arm guide equipment to move to the thighbone preparation position and the tibia preparation position. In this way, the mechanical arm can be controlled to assist in completing the osteotomy operation of unicompartmental knee arthroplasty in a pre-operation planning and intra-operation navigation mode, and the problems that the operation level is uneven and the operation effect is not expected due to different individuals in the current manual operation are solved.

An image registration method for a surgical robot, comprising: capturing a two-dimensional image of a surgical object and determining first guiding information in the two-dimensional image; acquiring a three-dimensional image of the surgical object and preoperative planning information, and determining second guiding information in the three-dimensional image; calculating first pose information according to the first guiding information and the second guiding information; adjusting the three-dimensional image according to the first pose information, and acquiring a digitally reconstructed two-dimensional image in the adjusted three-dimensional image; calculating the similarity between the two-dimensional image and the digitally reconstructed two-dimensional image; when the similarity meets a preset condition, projecting the preoperative planning information onto the two-dimensional image according to the first pose information; when the similarity does not meet the preset condition, updating the first pose information to obtain second pose information, and adjusting the three-dimensional image according to the second pose information.

The application relates to a preoperative risk scoring method for limb and trunk soft tissue sarcoma, which comprises the following steps: obtaining standardized MRI features of a patient, and classifying the standardized MRI features; and inputting the classification results of the standardized MRI features into a scoring model to obtain a preoperative risk score of the patient. The application can accurately evaluate the risk of limb and trunk soft tissue sarcoma non-invasively before operation by converting complex image information into a simple and understandable risk score through unified MRI feature definition and objective weight allocation, so as to provide a precise solution for preoperative planning and postoperative management of the patient.

The invention relates to the technical field of animal medicine, in particular to a self-adaptive control system and method for animal tracheal instillation. The system comprises a preoperative planning module which is used for reconstructing a three-dimensional model based on an individual animal airway CT image, simulating and optimizing administration parameters through computational fluid mechanics, and generating a personalized operation plan; the intraoperative navigation and execution module guides a catheter to reach a target pose through electromagnetic navigation, and performs closed-loop regulation and control on the instillation process through a respiration synchronous triggering algorithm and a pressure self-adaptive control algorithm based on real-time respiration and pressure signals; the central control module coordinates the work of each module; and the postoperative verification module quantifies actual and predicted deposition effects through image comparison. The problems that a traditional method depends on experience, cannot adapt to physiological changes in real time and is poor in drug administration precision are solved, the spanning from experience operation to individualized precise self-adaptive control is achieved, and the safety, repeatability and scientificity of animal experiments are remarkably improved.

The invention relates to the technical field of intra-operative navigation, in particular to an intra-operative brain glioma deep learning detection method and system based on hyperspectral imaging, and the method comprises the steps: analyzing the internal heterogeneity of brain glioma based on spectral difference, and evaluating the coverage earnings of a pre-operative planning path and an intra-operative detour path; analyzing oxyhemoglobin saturation distribution based on absorption peak characteristics of hemoglobin in a specific wave band, and evaluating the ischemia risk of a pre-operation planning path and an intra-operation bypassing path; respectively mapping the pre-operation planning path and the intra-operation bypassing path to a brain functional region topology network, and evaluating a functional injury risk corresponding to the paths based on a topology connection relation and a local ischemia risk; and carrying out expected income and risk trend analysis on the pre-operation planning path and the intra-operation bypassing path, and generating an operation path decision suggestion. According to the method, the accuracy and the safety of operation path decision making are effectively improved by quantifying the path coverage income and the function damage risk of the operation path.