Integrated visual guidance system based on adaptive learning algorithm

Abstract

The invention belongs to the technical field of medical equipment, and discloses an integrated visual guidance system based on an adaptive learning algorithm. Comprising a self-adaptive image acquisition module, a multi-modal data fusion and navigation module, a personalized surgical planning and intelligent guiding module, a real-time monitoring and early warning module, a user interface and operation control module and a data analysis and postoperative optimization module. According to the invention, through adaptive image acquisition, multi-modal data fusion, personalized operation planning, intelligent guidance and assistance, real-time monitoring and early warning, multi-modal man-machine interaction, big data analysis and postoperative optimization innovative improvement, precise positioning, real-time monitoring, intelligent guidance and personalized adjustment of an operation process are realized; therefore, the safety and the efficiency of an operation are improved, wounds and postoperative complications of a patient are reduced, better medical services are provided for the patient, and meanwhile, a new thought and a new direction are provided for future medical technology innovation.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical equipment, and in particular relates to an integrated visual guidance system based on an adaptive learning algorithm. Background Art

[0002] An infusion port is a long-term intravenous infusion device implanted subcutaneously and is widely used in patients who require long-term infusion therapy, such as tumor chemotherapy, long-term antibiotic treatment, and parenteral nutrition support. Traditional infusion port implantation surgery mainly relies on the surgeon's experience and feel, and positioning is performed through surface landmarks and anatomical knowledge.

[0003] In recent years, with the development of medical imaging technology, image-guided technologies such as ultrasound, CT and X-ray have been used in infusion port implantation surgery. However, these technologies still have the following shortcomings: strong equipment dependence: additional imaging equipment and professional operators are required, which increases the cost and complexity of surgery; lack of personalization: the surgical plan lacks consideration of individual differences among patients, making it difficult to achieve true precision medicine; lack of real-time performance: there are delays in the processing and feedback of imaging data, making it difficult to achieve true real-time monitoring and intelligent guidance; complex operation: the system operation is complex, and high technical requirements are placed on doctors, making it difficult to popularize and apply; low data utilization: existing technologies have low utilization of data generated during surgery, making it difficult to conduct effective postoperative analysis and surgical optimization, so improvements are needed. Summary of the Invention

[0004] The purpose of the present invention is to provide an integrated visual guidance system based on an adaptive learning algorithm to solve the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: an integrated visual guidance system based on an adaptive learning algorithm, comprising: an adaptive image acquisition module, a multimodal data fusion and navigation module, a personalized surgical planning and intelligent guidance module, a real-time monitoring and early warning module, a user interface and operation control module, and a data analysis and postoperative optimization module, wherein:

[0006] The adaptive image acquisition module adaptively adjusts image acquisition parameters according to the progress of the operation and the doctor's operating habits, and continuously acquires image data of the surgical area;

[0007] The multimodal data fusion and navigation module is used to perform multimodal data fusion on the real-time acquired image data and the three-dimensional anatomical model established before the operation, so as to locate the surgical position and navigate the surgical instruments;

[0008] The personalized surgical planning and intelligent guidance module is used to formulate a personalized surgical plan based on the patient's anatomical structure and pathological characteristics, the doctor's operating habits and experience, plan the optimal puncture path, and guide the doctor in the operation;

[0009] The real-time monitoring and warning module is used to monitor the image data of the surgical area and the position of surgical instruments in real time and to perform abnormal detection and alarm;

[0010] The user interface and operation control module are used to provide an intuitive user interface to support doctors in multimodal interaction;

[0011] The data analysis and postoperative optimization module is used to record surgical process data and patient data, perform analysis based on the recorded data, and then perform parameter adjustment and optimization based on the analysis results.

[0012] As a preferred technical solution of the present invention, the adaptive image acquisition module is composed of a high-resolution ultrasound probe, a micro CT device and an MRI device, and the adaptive adjustment of image acquisition parameters includes resolution, scanning depth and scanning frequency.

[0013] As a preferred technical solution of the present invention, the multimodal data fusion and navigation module is divided into a data fusion unit and a navigation unit. The data fusion unit includes multimodal image data fusion and real-time image and three-dimensional model fusion. The navigation unit includes optical navigation, electromagnetic navigation and inertial navigation.

[0014] As a preferred technical solution of the present invention, the personalized surgical planning and intelligent guidance module is divided into a surgical plan formulation unit and an intelligent guidance unit. The surgical plan formulation unit includes optimal puncture path planning and surgical parameter setting, and the intelligent guidance unit includes voice prompts, visual instructions and robotic arm assistance.

[0015] As a preferred technical solution of the present invention, the intelligent guidance unit is based on an artificial intelligence algorithm, which analyzes real-time image data and navigation information through the artificial intelligence algorithm to generate an optimal puncture path.

[0016] As a preferred technical solution of the present invention, the real-time monitoring and early warning module is divided into a real-time monitoring unit and an early warning mechanism unit. The real-time monitoring unit includes image monitoring and sensor monitoring. The image monitoring is used to monitor the image data of the surgical area in real time, and the sensor monitoring is used to monitor the sensor data of surgical instruments in real time. The early warning mechanism unit adopts an anomaly detection algorithm to identify abnormal situations and performs multi-level early warnings according to the severity of the abnormal situations.

[0017] As a preferred technical solution of the present invention, the multi-level warning is divided into level one warning, level two warning and level three warning. The level one warning is used to remind doctors to pay attention to potential risks, the level two warning is used to suggest doctors to adjust operating parameters, and the level three warning is used to stop the operation urgently and provide emergency treatment suggestions.

[0018] As a preferred technical solution of the present invention, the user interface and operation control module are divided into a user interface unit and an operation control unit. The user interface unit is used to provide an intuitive visual interface and multi-window display function, and the operation control unit is used to provide a multimodal interaction method of touch operation, voice control and gesture recognition.

[0019] As a preferred technical solution of the present invention, the data analysis and postoperative optimization module is divided into a data recording unit, a postoperative analysis unit and a postoperative optimization unit. The data recording unit is used to record surgical process data and patient data. The postoperative analysis unit adopts big data analysis technology to analyze the surgical process data recorded in the data recording unit, and at the same time uses machine deep learning technology to perform data mining and extract valuable information. The postoperative optimization unit is used to optimize the surgical plan and adjust system parameters according to the analysis results of the postoperative analysis unit.

[0020] The beneficial effects of the present invention are as follows:

[0021] The present invention uses adaptive image acquisition, multimodal data fusion, personalized surgical planning, intelligent guidance and assistance, real-time monitoring and early warning, multimodal human-computer interaction, big data analysis and innovative improvements in postoperative optimization to achieve precise positioning, real-time monitoring, intelligent guidance and personalized adjustment of the surgical process, thereby improving the safety and efficiency of the operation, reducing patient trauma and postoperative complications, providing better medical services to patients, and providing new ideas and directions for future medical technology innovation. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] like Figure 1As shown, the embodiment of the present invention provides an integrated visual guidance system based on an adaptive learning algorithm, including: an adaptive image acquisition module, a multimodal data fusion and navigation module, a personalized surgical planning and intelligent guidance module, a real-time monitoring and early warning module, a user interface and operation control module, and a data analysis and postoperative optimization module, wherein:

[0025] The adaptive image acquisition module adaptively adjusts image acquisition parameters according to the progress of the surgery and the doctor's operating habits, and continuously collects image data of the surgical area;

[0026] The multimodal data fusion and navigation module is used to fuse the real-time acquired image data with the preoperative 3D anatomical model to locate the surgical site and navigate the surgical instruments.

[0027] The personalized surgical planning and intelligent guidance module is used to formulate a personalized surgical plan based on the patient's anatomical structure and pathological characteristics, the doctor's operating habits and experience, plan the optimal puncture path, and guide the doctor during the operation;

[0028] The real-time monitoring and early warning module is used to monitor the image data of the surgical area and the position of surgical instruments in real time and to perform abnormal detection and alarm;

[0029] The user interface and operation control module is used to provide an intuitive user interface to support doctors in multimodal interaction;

[0030] The data analysis and postoperative optimization module is used to record surgical process data and patient data, analyze the recorded data, and then adjust and optimize parameters based on the analysis results.

[0031] During use, a preoperative CT, MRI, and ultrasound scan is first performed to obtain the patient's multimodal imaging data. Other relevant patient data, such as pathology data and surgical history, are then integrated into the system. The multimodal imaging data is then imported into the system to create a 3D anatomical model of the patient. Subsequently, a personalized surgical plan, including the optimal puncture path and surgical parameter settings, is developed based on the patient's data and the physician's operating habits. During the operation, the adaptive image acquisition module is activated to acquire real-time imaging data of the surgical area. Image acquisition parameters are adaptively adjusted based on the surgical progress and the physician's operating habits. The multimodal data fusion and navigation module then fuses the real-time imaging data with the 3D anatomical model to achieve precise positioning and navigation. The personalized surgical planning and intelligent guidance module analyzes the data to generate the optimal puncture path and provides prompts to the physician through the user interface, assisting the physician in performing precise punctures. Meanwhile, the real-time monitoring and early warning module continuously monitors the surgical process, detects potential complications, and provides immediate feedback and treatment suggestions through an early warning mechanism. After the operation, the data analysis and postoperative optimization module records and analyzes the surgical process data, summarizes lessons learned, and optimizes the surgical plan based on the analysis results to provide reference for subsequent operations.

[0032] Among them, the adaptive image acquisition module consists of a high-resolution ultrasound probe, a micro CT device and an MRI device, and adaptively adjusts image acquisition parameters including resolution, scanning depth and scanning frequency.

[0033] High-resolution ultrasound probes are used to provide real-time ultrasound images; micro-CT devices are used to provide high-resolution tomographic images; MRI devices are optional equipment and are used to provide more detailed soft tissue images; adjusting the image resolution according to surgical requirements can improve image clarity, adjusting the scanning depth can adapt to different anatomical structures, and adjusting the scanning frequency can balance image quality and real-time performance.

[0034] Among them, the multimodal data fusion and navigation module is divided into a data fusion unit and a navigation unit. The data fusion unit includes multimodal image data fusion and real-time image and three-dimensional model fusion. The navigation unit includes optical navigation, electromagnetic navigation and inertial navigation.

[0035] Multimodal image data fusion is used to combine preoperative CT, MRI, ultrasound and other imaging data to establish a three-dimensional anatomical model of the patient; real-time image and three-dimensional model fusion is used to fuse real-time acquired ultrasound images with three-dimensional anatomical models to achieve precise positioning; optical navigation uses optical sensors to track the position and direction of surgical instruments; electromagnetic navigation uses electromagnetic sensors for more precise positioning; inertial navigation improves navigation stability and accuracy by combining inertial measurement unit (IMU) data.

[0036] Among them, the personalized surgical planning and intelligent guidance module is divided into a surgical plan formulation unit and an intelligent guidance unit. The surgical plan formulation unit includes optimal puncture path planning and surgical parameter setting, and the intelligent guidance unit includes voice prompts, visual instructions and robotic arm assistance.

[0037] The surgical plan-making unit can plan the optimal puncture path by combining the doctor's operating habits and experience with the patient's anatomical structure and pathological characteristics, and set surgical parameters such as puncture speed, angle, depth, etc., to achieve personalized surgical planning; the intelligent guidance unit can guide the doctor's operation through voice prompts, and display path markings, navigation arrows and other visual instructions on the display screen, while using a robotic arm to assist the doctor in performing precise puncture.

[0038] Among them, the intelligent guidance unit is based on artificial intelligence algorithms, which analyze real-time image data and navigation information through artificial intelligence algorithms to generate the optimal puncture path.

[0039] By adopting advanced intelligent guidance algorithms, surgical plans and guidance parameters can be dynamically adjusted to improve the accuracy and safety of surgery.

[0040] Among them, the real-time monitoring and early warning module is divided into a real-time monitoring unit and an early warning mechanism unit. The real-time monitoring unit includes image monitoring and sensor monitoring. Image monitoring is used to monitor the image data of the surgical area in real time, and sensor monitoring is used to monitor the sensor data of surgical instruments in real time; the early warning mechanism unit uses anomaly detection algorithms to identify abnormal situations and perform multi-level early warnings according to the severity of the abnormal situations.

[0041] Image monitoring can promptly detect potential complications, such as vascular damage and pneumothorax. Sensor monitoring can promptly detect abnormal operations based on sensor data such as the position, direction, speed, and acceleration of surgical instruments. Anomaly detection algorithms use isolation forests and autoencoders, among others.

[0042] Among them, the multi-level warning is divided into level one, level two and level three. The level one warning is used to remind doctors to pay attention to potential risks, the level two warning is used to suggest doctors to adjust operating parameters, and the level three warning is to stop the operation immediately and provide emergency treatment suggestions.

[0043] Through multi-level warnings, abnormal situations during surgery can be quickly identified and warned, and corresponding treatment suggestions can be provided, thereby ensuring safety during surgery and improving surgical quality.

[0044] Among them, the user interface and operation control module is divided into a user interface unit and an operation control unit. The user interface unit is used to provide an intuitive visual interface and multi-window display function, and the operation control unit is used to provide a multimodal interaction method of touch operation, voice control and gesture recognition.

[0045] The visual interface can display real-time images, navigation information, surgical parameters and warning information, while the multi-window display function can support multi-window display of different types of data, such as ultrasound images, CT images, navigation paths, etc. At the same time, multimodal human-computer interaction can provide a more convenient and intuitive operation method, reduce the doctor's workload and improve surgical efficiency.

[0046] Among them, the data analysis and postoperative optimization module is divided into a data recording unit, a postoperative analysis unit and a postoperative optimization unit. The data recording unit is used to record surgical process data and patient data. The postoperative analysis unit uses big data analysis technology to analyze the surgical process data recorded in the data recording unit, and uses machine deep learning technology to perform data mining and extract valuable information. The postoperative optimization unit is used to optimize the surgical plan and adjust the system parameters according to the analysis results of the postoperative analysis unit.

[0047] Surgical process data includes imaging data, navigation data, operation data, sensor data, etc.; patient data includes basic patient information, preoperative evaluation data, postoperative follow-up data, etc.; through big data analysis technology and machine deep learning technology, surgical data can be deeply analyzed, valuable information can be extracted, lessons learned can be summarized, and reference and optimization suggestions can be provided for subsequent operations. At the same time, according to the data analysis results, the system parameters can be adjusted to improve the performance and adaptability of the system.

[0048] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0049] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An integrated visual guidance system based on an adaptive learning algorithm, characterized by: It includes: adaptive image acquisition module, multimodal data fusion and navigation module, personalized surgery planning and intelligent guidance module, real-time monitoring and early warning module, user interface and operation control module, data analysis and postoperative optimization module, among which, The adaptive image acquisition module adaptively adjusts image acquisition parameters according to the progress of the operation and the doctor's operating habits, and continuously acquires image data of the surgical area; The multimodal data fusion and navigation module is used to perform multimodal data fusion on the real-time acquired image data and the three-dimensional anatomical model established before the operation, so as to locate the surgical position and navigate the surgical instruments; The personalized surgical planning and intelligent guidance module is used to formulate a personalized surgical plan based on the patient's anatomical structure and pathological characteristics, the doctor's operating habits and experience, plan the optimal puncture path, and guide the doctor in the operation; The real-time monitoring and warning module is used to monitor the image data of the surgical area and the position of surgical instruments in real time and to perform abnormal detection and alarm; The user interface and operation control module are used to provide an intuitive user interface to support doctors in multimodal interaction; The data analysis and postoperative optimization module is used to record surgical process data and patient data, perform analysis based on the recorded data, and then perform parameter adjustment and optimization based on the analysis results.

2. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The adaptive image acquisition module is composed of a high-resolution ultrasound probe, a micro CT device and an MRI device. The adaptive adjustment of image acquisition parameters includes resolution, scanning depth and scanning frequency.

3. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The multimodal data fusion and navigation module is divided into a data fusion unit and a navigation unit. The data fusion unit includes multimodal image data fusion and real-time image and three-dimensional model fusion. The navigation unit includes optical navigation, electromagnetic navigation and inertial navigation.

4. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The personalized surgical planning and intelligent guidance module is divided into a surgical plan formulation unit and an intelligent guidance unit. The surgical plan formulation unit includes optimal puncture path planning and surgical parameter setting, and the intelligent guidance unit includes voice prompts, visual instructions and robotic arm assistance.

5. The integrated visual guidance system based on the adaptive learning algorithm according to claim 4, characterized in that: The intelligent guidance unit is based on an artificial intelligence algorithm, which analyzes real-time image data and navigation information through the artificial intelligence algorithm to generate the optimal puncture path.

6. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The real-time monitoring and early warning module is divided into a real-time monitoring unit and an early warning mechanism unit. The real-time monitoring unit includes image monitoring and sensor monitoring. The image monitoring is used to monitor the image data of the surgical area in real time, and the sensor monitoring is used to monitor the sensor data of surgical instruments in real time. The early warning mechanism unit uses an anomaly detection algorithm to identify abnormal situations and performs multi-level early warnings according to the severity of the abnormal situation.

7. The integrated visual guidance system based on the adaptive learning algorithm according to claim 6, characterized in that: The multi-level warning is divided into level one, level two and level three. The level one warning is used to remind doctors to pay attention to potential risks, the level two warning is used to suggest doctors to adjust operating parameters, and the level three warning is used to stop the operation urgently and provide emergency treatment suggestions.

8. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The user interface and operation control module is divided into a user interface unit and an operation control unit. The user interface unit is used to provide an intuitive visual interface and multi-window display function, and the operation control unit is used to provide a multimodal interaction method of touch operation, voice control and gesture recognition.

9. The integrated visual guidance system based on the adaptive learning algorithm according to claim 1, characterized in that: The data analysis and postoperative optimization module is divided into a data recording unit, a postoperative analysis unit and a postoperative optimization unit. The data recording unit is used to record surgical process data and patient data. The postoperative analysis unit adopts big data analysis technology to analyze the surgical process data recorded in the data recording unit, and uses machine deep learning technology to perform data mining to extract valuable information. The postoperative optimization unit is used to optimize the surgical plan and adjust the system parameters according to the analysis results of the postoperative analysis unit.

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