A surgery navigation and quality control system based on multi-source information fusion

Abstract

The application relates to the technical field of medical information systems, in particular to a surgery navigation and quality control system based on multi-source information fusion, which comprises an image acquisition module, which is used for acquiring CT images of a patient before surgery; and an endoscope video during surgery; a surgery navigation module, which is in communication connection with the image acquisition module, and is used for receiving the CT images and the endoscope video sent by the image acquisition module; acquiring the real-time position of a surgical instrument in a patient coordinate system based on the CT images and the endoscope video; and displaying the relative position of a virtual surgery knife and a lesion in real time; and a surgery quality scoring module, which is in communication connection with the surgery navigation module, and is used for receiving the position information of the surgical instrument sent by the surgery navigation module; evaluating the deviation between the operation of a doctor and a surgery target and scoring; and fusing the preoperative CT images, the intraoperative endoscope video and other key information, so that high-precision real-time surgery navigation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of medical information systems, and in particular to a surgical navigation and quality control system based on multi-source information fusion. Background Art

[0002] In recent years, with the continuous advancement of medical technology, surgical navigation systems have played an increasingly important role in clinical practice. Traditional surgical navigation systems rely primarily on a single image source, such as preoperative CT or MRI images, to guide surgical procedures. However, this approach often falls short in complex surgical environments. This is particularly true in soft tissue surgery, where tissue deformation and movement make it difficult for a single image source to provide accurate, real-time navigation information.

[0003] Some advanced systems attempt to incorporate intraoperative images, such as endoscopic video, to improve real-time navigation. However, these systems often struggle to effectively align preoperative planning with the actual intraoperative situation, resulting in insufficient navigation accuracy. Furthermore, existing surgical navigation systems mostly focus on spatial positioning, with insufficient attention paid to assessing and controlling surgical quality. This makes it difficult for surgical teams to objectively evaluate surgical progress and to promptly identify and correct potential problems.

[0004] Current methods for surgical quality control rely heavily on post-procedure manual evaluation, lacking a real-time, objective assessment mechanism. Some systems have attempted to incorporate automated assessments, but these often focus on a single metric, such as instrument trajectory or procedure time, making it difficult to fully reflect the quality and risks of surgery.

[0005] Furthermore, existing systems are plagued by information silos. Navigation systems, imaging systems, and quality control systems are often independent of each other, making data difficult to effectively integrate and utilize. This not only increases the cognitive burden on physicians but also limits the system's ability to achieve its full potential.

[0006] In the face of these challenges, there is an urgent need for a surgical assistance system that can integrate multi-source information to achieve precise navigation and comprehensive quality control. This invention addresses the above issues and proposes a surgical navigation and quality control system based on multi-source information fusion. Summary of the Invention

[0007] The present invention proposes a surgical navigation and quality control system based on multi-source information fusion, aiming to solve the technical problem of the contradiction between accurate navigation and real-time performance in existing systems.

[0008] The present invention proposes a surgical navigation and quality control system based on multi-source information fusion, comprising:

[0009] Image acquisition module, used for:

[0010] Obtain preoperative CT images of the patient;

[0011] Acquisition of intraoperative endoscopic video;

[0012] The surgical navigation module is in communication with the image acquisition module and is used to:

[0013] Receiving CT images and endoscopic videos sent by the image acquisition module;

[0014] Based on the CT image and the endoscopic video, obtaining the real-time position of the surgical instrument in the patient coordinate system;

[0015] Real-time display of the relative position of the virtual scalpel and the lesion;

[0016] A surgery quality scoring module is in communication with the surgery navigation module and is used to:

[0017] receiving surgical instrument position information sent by the surgical navigation module;

[0018] The deviation between the doctor's operation and the surgical goal was evaluated and scored.

[0019] As an option, it also includes:

[0020] A management system is in communication with the surgical navigation module and the surgical quality scoring module, and the management system includes:

[0021] Operation evaluation module, used to evaluate the standardization of surgical procedures and intraoperative operations;

[0022] Remote communication module, used for image and data transmission between systems.

[0023] Preferably, the remote communication module adopts a communication module with medical security encryption function.

[0024] Preferably, the image acquisition module is further used for:

[0025] collecting a plurality of endoscopic video images through a plurality of endoscopes;

[0026] Before the operation, the patient is scanned by magnetic resonance imaging or CT scanning equipment to obtain CT images of the patient;

[0027] During the operation, multiple sets of endoscopes are placed inside the patient's body to collect endoscopic video images.

[0028] Preferably, the image acquisition module is further used for:

[0029] A multi-source information fusion and multi-modal navigation-based image registration strategy are adopted to integrate preoperative planning CT images, intraoperative endoscopic images, fluorescent images and intraoperative anatomical landmarks to accurately locate the position of surgical instruments in three-dimensional space.

[0030] Preferably, the surgical navigation module is further used for:

[0031] Registration is performed based on the image acquisition module, and the registration adopts a virtual coordinate system registration method to locate the real-time positions of surgical instruments, endoscopes and optical fibers in the patient space.

[0032] Preferably, the surgery quality scoring module is further used to:

[0033] A surgical quality standard evaluation system is established based on surgical process data and patient information. In the surgical quality standard evaluation system, quantitative scores are given to standardization, accuracy, and risk avoidance evaluation items.

[0034] Preferably, the surgery quality scoring module is further used to:

[0035] Obtain preoperative CT image data, extract the lesion area from the CT image using multi-voxel segmentation technology, and build a three-dimensional lesion model, using the three-dimensional coordinate information of the surgical target as a reference;

[0036] The position of the surgical instrument relative to the surgical target is tracked in real time, and the surgical quality is scored based on the real-time tracked position of the surgical instrument.

[0037] As an advantage, it also includes:

[0038] Management module, used for real-time remote display of surgical quality assessment results;

[0039] Statistics module, used to evaluate surgical quality based on surgical data.

[0040] Preferably, the image acquisition module is further used for:

[0041] Acquire images of the surgical target area and surrounding blood vessels and tissues through the multiple endoscopes to achieve real-time tracking;

[0042] According to the positional relationship between the real-time endoscope shooting points and the surgical target, the closed surface formed by the multiple endoscope shooting points is tracked, and the coordinates of the center point of the closed surface are calculated as the surgical target point;

[0043] The offset position of the surgical target is acquired according to the center point coordinates.

[0044] The beneficial effects of the present invention are mainly reflected in the following aspects:

[0045] The system of this invention achieves high-precision, real-time surgical navigation by innovatively integrating preoperative CT images, intraoperative endoscopic videos, and other key information. Furthermore, the system incorporates a comprehensive quality assessment mechanism that provides real-time scoring of surgical compliance, accuracy, and safety, providing timely and objective feedback to the surgical team.

[0046] From a macro perspective, the system of this invention achieves information integration and intelligent assistance throughout the entire surgical process. It breaks the isolation of functional modules in traditional systems and establishes a complete closed loop from preoperative planning, intraoperative navigation, to postoperative evaluation. This comprehensive solution significantly improves the overall efficiency and safety of surgery.

[0047] At the micro level, the various modules of the present invention achieve deep synergy. For example, the image acquisition module not only provides basic data for the navigation module but also works closely with the quality scoring module to achieve real-time assessment of surgical procedures. This inter-module synergy significantly enhances the overall performance of the system, far exceeding the simple addition of each module's individual effects.

[0048] Particularly noteworthy is that this invention cleverly resolves the conflict between precise navigation and real-time performance. Through multi-source information fusion and advanced image registration technology, the system achieves millisecond-level response speeds while maintaining high precision. This is particularly important in rapidly changing surgical environments.

[0049] Furthermore, the quality control mechanism of the present invention not only provides objective scoring but also identifies potential risk factors. This proactive risk management significantly improves surgical safety and provides a strong safeguard against medical accidents.

[0050] Overall, the system presented in this paper significantly improves surgical precision, safety, and efficiency through innovative technologies such as multi-source information fusion, real-time navigation, and comprehensive quality control. It not only provides a powerful auxiliary tool for doctors but also enhances the medical experience and treatment outcomes for patients. The application of this system is expected to promote the development of precision medicine and make a significant contribution to improving overall healthcare quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is the system logic block diagram of the present invention.

[0052] Figure 2 This is a logic block diagram of the image acquisition module of the present invention.

[0053] Figure 3 This is a logic block diagram of the surgical navigation module of the present invention.

[0054] Figure 4 This is a logic block diagram of the surgical quality scoring module of the present invention. DETAILED DESCRIPTION

[0055] See Figure 1-4 The present invention provides a surgical navigation and quality control system based on multi-source information fusion. By integrating multiple information sources, the system achieves precise surgical navigation and comprehensive quality control, significantly improving the accuracy and safety of surgery.

[0056] Specifically, the system of the present invention includes an image acquisition module 1, a surgical navigation module 2, and a surgical quality assessment module 3. Image acquisition module 1 is used to acquire preoperative CT images of the patient and intraoperative endoscopic videos. This image data provides the basis for subsequent surgical navigation and quality assessment. Preferably, the CT image resolution can reach 0.5-1mm, and the endoscopic video frame rate is typically 30-60fps to ensure image quality and real-time performance.

[0057] The surgical navigation module 2 is in communication with the image acquisition module 1, receiving CT images and endoscopic video. Based on this data, the module is able to determine the real-time position of surgical instruments within the patient's coordinate system. In one embodiment of the present invention, the surgical navigation module 2 utilizes optical tracking technology, achieving a positioning accuracy of 0.1-0.3 mm. Furthermore, the module displays the relative position of the virtual scalpel and the lesion in real time, providing intuitive visual guidance to the surgeon.

[0058] The surgical quality scoring module 3 communicates with the surgical navigation module 2 and receives surgical instrument position information. The core function of this module is to evaluate the deviation between the doctor's operation and the surgical goal and to score it. The scoring is based on a 100-point scale, with scores above 90 being excellent, 80-90 being good, 70-80 being qualified, and below 70 being unqualified. The scoring algorithm can be expressed as:

[0059]

[0060] in, is the actual surgical position vector, is the target surgical position vector, is the correction factor, usually ranging from 50 to 100.

[0061] In one embodiment of the present invention, the system further includes a management system 4. This system communicates with the surgical navigation module 2 and the surgical quality scoring module 3, further enhancing the system's functionality. The management system 4 includes an operation evaluation module and a remote communication module. The operation evaluation module assesses the standardization of the surgical process and intraoperative procedures, using deep learning-based video analysis technology to identify the implementation of standard operating procedures. The remote communication module is responsible for image and data transmission between systems, supporting real-time remote consultations and expert guidance.

[0062] In one embodiment of the present invention, the security of the remote communication module is further optimized. This module utilizes a communication module with medical security encryption capabilities, ensuring patient privacy and the security of medical data. The present invention preferably utilizes the AES-256 encryption algorithm with a 256-bit key length, which effectively prevents data leakage and tampering.

[0063] The system of the present invention achieves precise navigation and quality control of the entire surgical process through multi-source information fusion. The image acquisition module 1 provides high-quality preoperative CT and intraoperative endoscopic images, the surgical navigation module 2 achieves precise positioning and visual navigation based on these data, and the surgical quality scoring module 3 evaluates the surgical quality in real time. The introduction of the management system 4 further enhances the system's evaluation and remote collaboration capabilities. This comprehensive technical solution significantly improves the accuracy and safety of surgery, reduces the risk of complications, and provides doctors with objective skill assessments and remote expert support, which is of great significance to improving the overall quality of medical care. The system of the present invention further optimizes the function of the image acquisition module 1.

[0064] In one embodiment of the present invention, the module can not only capture a single endoscopic video, but also simultaneously capture multiple video images from multiple endoscopes. This multi-view acquisition method significantly improves the visualization of the surgical area and provides doctors with a more comprehensive surgical field of view.

[0065] Preferably, the present invention utilizes three to five endoscopes, each providing observation of the surgical area from different angles. These endoscopes can be flexible, typically with a diameter of 3 to 5 mm, enabling flexible access to various parts of the human body. Each endoscope has a field of view of 120-140 degrees and a resolution of 1920x1080 or higher, ensuring image clarity and detail.

[0066] During the preoperative phase, the system of the present invention uses magnetic resonance imaging (MRI) or computed tomography (CT) scanning to obtain high-precision CT images. CT scan slice thickness is typically set at 0.5-1 mm to ensure adequate spatial resolution. MRI provides superior soft tissue contrast, making it particularly suitable for surgical planning in areas such as the brain and joints.

[0067] During surgery, multiple endoscopes are placed inside the patient to capture real-time video images of the surgical area. These endoscopes can employ various imaging modes, such as white light and narrow-band imaging (NBI), to enhance the contrast between different tissues. The captured video is typically transmitted at a frame rate of 30-60 fps, ensuring smooth and real-time image quality.

[0068] In one embodiment of the present invention, the advanced functionality of image acquisition module 1 lies in its use of multi-source information fusion technology and an image registration strategy based on multimodal navigation. This advanced approach integrates preoperative planning CT images, intraoperative endoscopic images, fluorescence images, and intraoperative anatomical landmarks to achieve precise positioning of surgical instruments in three-dimensional space.

[0069] Specifically, the image registration process of the present invention can be divided into the following steps:

[0070] 1. Feature extraction: Extracting significant feature points from CT images and endoscopic images, such as vascular bifurcations and bone structures.

[0071] 2. Feature matching: Use a robust matching algorithm, such as RANSAC (Random Sample Consensus), to match the extracted feature points.

[0072] 3. Transformation calculation: Based on the matching results, the transformation matrix from the CT coordinate system to the endoscope coordinate system is calculated. Usually, a rigid body transformation or affine transformation model is used.

[0073] 4. Image fusion: The registered CT image is fused with the real-time endoscopic image to generate an augmented reality view.

[0074] In a preferred embodiment of the present invention, a deep learning-based registration method, such as one using a convolutional neural network (CNN) to automatically extract and match features, is employed. This method offers greater robustness and accuracy than traditional methods, particularly when dealing with soft tissue deformation.

[0075] In one embodiment of the present invention, the registration process of surgical navigation module 2 is described in detail. This module performs registration based on image acquisition module 1, using a virtual coordinate system registration method to locate the real-time position of surgical instruments, endoscopes, and optical fibers within the patient's space. The advantage of this registration method is that it establishes a unified reference coordinate system, allowing spatial information from different sources to be integrated and analyzed within the same framework.

[0076] The system of this invention uses an optical tracking system to position instruments, achieving a typical tracking accuracy of 0.1-0.3 mm. Optical markers are typically attached to surgical instruments, endoscopes, and optical fibers, and tracked in real time by an infrared camera. The system establishes a correspondence between the optical tracking coordinate system and the patient coordinate system through pre-calibration methods.

[0077] Preferably, the present invention also uses an inertial measurement unit (IMU) to assist in positioning to cope with situations such as optical occlusion. The IMU data is fused with the optical tracking data through a Kalman filter algorithm, further improving the stability and continuity of positioning.

[0078] In one embodiment of the present invention, the core function of the surgical quality scoring module 3 is to establish a comprehensive surgical quality assessment system based on surgical process data and patient information. This assessment system quantitatively scores multiple aspects of surgical standardization, accuracy, and risk avoidance, providing a reliable basis for objective evaluation of surgical quality.

[0079] Specifically, the evaluation system of the present invention includes the following main indicators:

[0080] 1. Normative scoring : Evaluate whether the surgical operation complies with standard procedures, with a full score of 100 points.

[0081] 2. Accuracy score : Evaluates the deviation of surgical instrument position from the predetermined target, with a maximum score of 100 points.

[0082] 3. Risk Aversion Score : Assess the degree of protection of critical structures during surgery, with a maximum score of 100 points.

[0083] Final surgical quality score Calculated by weighted average:

[0084]

[0085] in, 、 、 are the weights of each indicator, and satisfy + + =1. In a preferred embodiment of the present invention, =0.3, =0.4, =0.3 to balance the importance of various indicators.

[0086] This multi-dimensional scoring method not only comprehensively reflects surgical quality but also helps doctors identify specific areas for improvement. Through long-term data accumulation and analysis, the system can provide valuable quality management and training guidance for medical institutions, thereby continuously improving surgical standards and patient safety.

[0087] In one embodiment of the present invention, the surgical quality scoring module 3 first acquires preoperative CT image data, then processes the CT images using advanced multi-voxel segmentation technology to extract the lesion area and create a three-dimensional lesion model. This process lays the foundation for subsequent surgical navigation and quality assessment.

[0088] The multi-voxel segmentation technology employed in this invention combines traditional image processing methods with deep learning algorithms. Specifically, the system first performs preliminary segmentation using a method based on grayscale thresholding and region growing, and then applies deep learning networks such as 3D U-Net for refined segmentation. This hybrid approach ensures segmentation accuracy while improving the algorithm's robustness and generalization capabilities. Preferably, the present invention can achieve a Dice coefficient of segmentation accuracy exceeding 95%.

[0089] This paper uses an improved 3D U-Net structure for lesion segmentation. Its loss function combines Dice loss and cross entropy loss:

[0090]

[0091] in, is the Dice loss, is the cross entropy loss, is the balancing factor (usually 0.5). Dice loss is defined as:

[0092]

[0093] in, is the predicted probability map, is the true label, is the total number of voxels.

[0094] Based on the segmentation results, the system builds a high-precision three-dimensional lesion model, which not only contains the lesion's geometric information but also incorporates metabolic activity information obtained from functional imaging such as PET-CT.

[0095] This multimodal fusion lesion model provides comprehensive information support for surgical planning. The spatial resolution of the model can typically reach 0.5mm, which is sufficient to support precise surgical navigation.

[0096] During surgery, the system of this invention can track the position of surgical instruments relative to the surgical target in real time. This functionality is achieved through a combination of optical and electromagnetic tracking systems, ensuring stability in various surgical environments. The optical tracking system has a refresh rate of up to 60Hz, while the electromagnetic tracking system has a refresh rate of over 100Hz, ensuring real-time position information.

[0097] Based on the real-time tracking of the surgical instrument position, the system dynamically calculates and scores the surgical quality.

[0098] The present invention uses the Extended Kalman Filter (EKF) to estimate the position of the device. The state vector X contains the position and velocity:

[0099]

[0100] State transition equation:

[0101]

[0102] in, is the state transition matrix, Process noise.

[0103] Observation equation:

[0104]

[0105] in, is the observation matrix, is the observation noise.

[0106] The scoring algorithm takes into account multiple factors, including the accuracy of the instrument position, the smoothness of the motion trajectory, and the safe distance from critical anatomical structures. The scoring function can be expressed as:

[0107]

[0108] Where d is the distance between the instrument and the target position, v is the velocity vector of the instrument, and s is the minimum distance to the critical structure. 、 and are the evaluation functions for accuracy, smoothness and safety respectively, 、 and is the corresponding weight coefficient.

[0109] In one embodiment of the present invention, the present invention also proposes a comprehensive scoring function:

[0110]

[0111] in, is the position accuracy function, d is the distance vector between the instrument and the target, is the motion smoothness function, v is the instrument velocity vector, is the risk assessment function, s is the safety distance vector from the critical structure , , is the weight coefficient.

[0112] Among them, the position accuracy function is defined as:

[0113]

[0114] in, is the standard deviation parameter, which controls the strictness of the accuracy requirement.

[0115] In one embodiment of the present invention, the management module 5 and the statistics module 6 are introduced to further enhance the functionality of the system. The management module 5 is responsible for remotely displaying the surgical quality assessment results in real time. This function enables the surgical team and remote experts to promptly understand the progress and quality of the surgery, providing a basis for necessary intervention.

[0116] In a preferred embodiment of the present invention, management module 5 employs web-based real-time data visualization technology. The system uses the WebSocket protocol for low-latency data transmission, while the front-end utilizes libraries such as D3.js for dynamic data rendering. This approach ensures real-time display (latency typically <100ms) while providing rich interactive features such as data zooming and filtering.

[0117] Statistics Module 6 comprehensively assesses surgical quality based on accumulated surgical data. This module employs advanced data mining and machine learning techniques to extract valuable patterns and insights from massive amounts of surgical data. For example, the system can identify key factors influencing surgical quality, predict surgical risks, and develop customized quality standards for different types of surgeries.

[0118] In one embodiment of the present invention, the statistics module 6 uses a random forest algorithm to perform feature importance analysis, identifying the factors that most impact surgical quality. Furthermore, the module applies a long short-term memory (LSTM) network to perform time-series predictions of surgical quality, providing physicians with real-time quality trend alerts. These advanced analytical capabilities provide powerful data support for quality management and continuous improvement at medical institutions.

[0119] Finally, in one embodiment of the present invention, the functionality of the image acquisition module 1 is further optimized, particularly in image processing and analysis capabilities in a multi-endoscope scenario. This module uses multiple endoscopes to capture images of the surgical target area and surrounding blood vessels and tissues, enabling comprehensive, real-time tracking.

[0120] This invention employs an innovative algorithm to track the closed surface formed by multiple endoscopic camera points based on their real-time positional relationship relative to the surgical target. This approach not only improves positioning accuracy but also adapts to complex situations such as soft tissue deformation. Specifically, the system uses SLAM (Simultaneous Localization and Mapping) technology to reconstruct the motion trajectory of the endoscopic camera and a stereo vision algorithm to restore the 3D structure of the scene.

[0121] The coordinates of the center point of the closed surface are calculated using the weighted centroid method, namely:

[0122]

[0123] in, is the center point coordinate, is the coordinate of the i-th shooting point, is the corresponding weight (which can be determined based on image clarity or confidence).

[0124] The present invention adopts the improved SLAM algorithm to perform multi-view fusion. Define the objective function

[0125]

[0126] Among them, X is the camera pose set, P is the 3D landmark point set, is the observed value, is the observation model, is the robust kernel function, is the information matrix. By minimizing the above objective function, the camera pose and 3D structure can be optimized simultaneously.

[0127] The advantage of this method is its ability to dynamically adapt to the movement and deformation of the surgical target. The system calculates the displacement of the center point between consecutive frames to determine the offset position of the surgical target. To filter out noise and transient fluctuations, the present invention employs a Kalman filter to smooth the offset trajectory. This process ensures real-time tracking while improving the stability and reliability of position estimation.

[0128] In summary, the surgical navigation and quality control system based on multi-source information fusion of the present invention achieves precise navigation and comprehensive quality control throughout the entire surgical process through a series of innovative technical solutions. The various modules of the system work closely together, forming a complete closed loop from image acquisition and surgical navigation to quality assessment and management. This not only significantly improves surgical precision and safety, but also provides strong technical support for the continuous improvement of medical quality.

[0129] Through the above method, the system of the present invention can realize the security analysis of sensitive data in a dynamic and intelligent manner, taking into account both privacy protection and performance optimization, and has strong practicality and innovation.

Claims

1. A surgical navigation and quality control system based on multi-source information fusion, characterized in that: include: Image acquisition module, used for: Obtain preoperative CT images of the patient; Acquisition of intraoperative endoscopic video; The surgical navigation module is in communication with the image acquisition module and is used to: Receiving CT images and endoscopic videos sent by the image acquisition module; Based on the CT image and the endoscopic video, obtaining the real-time position of the surgical instrument in the patient coordinate system; Real-time display of the relative position of the virtual scalpel and the lesion; A surgery quality scoring module is in communication with the surgery navigation module and is used to: receiving surgical instrument position information sent by the surgical navigation module; Evaluate and score the deviation between the doctor's operation and the surgical goal; Based on the real-time tracking of the surgical instrument position, the system dynamically calculates and scores the surgical quality; The scoring algorithm considers factors such as the accuracy of the instrument position, the smoothness of the motion trajectory, and the safe distance from critical anatomical structures. The scoring function can be expressed as: ； Where d is the distance between the instrument and the target position, v is the velocity vector of the instrument, and s is the minimum distance to the critical structure. 、 ,and are the evaluation functions for accuracy, smoothness and safety respectively, 、 and is the corresponding weight coefficient.

2. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: Also includes: A management system is in communication with the surgical navigation module and the surgical quality scoring module, and the management system includes: Operation evaluation module, used to evaluate the standardization of surgical procedures and intraoperative operations; Remote communication module, used for image and data transmission between systems.

3. The surgical navigation and quality control system based on multi-source information fusion according to claim 2, characterized in that: The remote communication module adopts a communication module with medical safety encryption function.

4. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: The image acquisition module is also used for: collecting a plurality of endoscopic video images through a plurality of endoscopes; Before the operation, the patient is scanned by magnetic resonance imaging or CT scanning equipment to obtain CT images of the patient; During the operation, multiple sets of endoscopes are placed inside the patient's body to collect endoscopic video images.

5. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: The image acquisition module is also used for: A multi-source information fusion and multi-modal navigation-based image registration strategy are adopted to integrate preoperative planning CT images, intraoperative endoscopic images, fluorescent images and intraoperative anatomical landmarks to accurately locate the position of surgical instruments in three-dimensional space.

6. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: The surgical navigation module is also used to: Registration is performed based on the image acquisition module, and the registration adopts a virtual coordinate system registration method to locate the real-time positions of surgical instruments, endoscopes and optical fibers in the patient space.

7. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: The surgical quality scoring module is also used to: A surgical quality standard evaluation system is established based on surgical process data and patient information. In the surgical quality standard evaluation system, quantitative scores are given to standardization, accuracy, and risk avoidance evaluation items.

8. The surgical navigation and quality control system based on multi-source information fusion according to claim 7, characterized in that: The surgical quality scoring module is also used to: Obtain preoperative CT image data, extract the lesion area from the CT image using multi-voxel segmentation technology, and build a three-dimensional lesion model, using the three-dimensional coordinate information of the surgical target as a reference; The position of the surgical instrument relative to the surgical target is tracked in real time, and the surgical quality is scored based on the real-time tracked position of the surgical instrument.

9. The surgical navigation and quality control system based on multi-source information fusion according to claim 1, characterized in that: Also includes: Management module, used for real-time remote display of surgical quality assessment results; Statistics module, used to evaluate surgical quality based on surgical data.

10. The surgical navigation and quality control system based on multi-source information fusion according to claim 4, characterized in that: The image acquisition module is also used for: Acquire images of the surgical target area and surrounding blood vessels and tissues through the multiple endoscopes to achieve real-time tracking; According to the positional relationship between the real-time endoscope shooting points and the surgical target, the closed surface formed by the multiple endoscope shooting points is tracked, and the coordinates of the center point of the closed surface are calculated as the surgical target point; The offset position of the surgical target is acquired according to the center point coordinates.

Images