Visual channel data optimization method and system based on augmented reality technology

Abstract

The invention provides a visual channel data optimization method and system based on an augmented reality technology, and relates to the technical field of surgical navigation assistance. The method comprises the following steps: acquiring data, evaluating the real-time performance, taking primary intervention and early warning measures, and taking secondary intervention and early warning measures. According to the method, the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient are obtained based on the image basic data, the intraoperative imaging delay data and the intraoperative imaging interference data, and whether primary intervention and early warning measures are taken or not is judged by combining the first threshold value and the second threshold value; meanwhile, whether secondary intervention and early warning measures are taken or not is judged based on the intraoperative imaging real-time interference evaluation coefficient obtained based on the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient, and the effect of improving the real-time performance of data dependent on surgical navigation is achieved; the problem that in the prior art, data which surgical navigation depends on is low in real-time performance is solved.

Description

Technical Field

[0001] The present invention relates to the field of surgical navigation assistance technology, and in particular to a method and system for optimizing visualized channel data based on augmented reality technology. Background Art

[0002] With the continuous advancement of medical technology, surgical navigation methods and systems based on augmented reality (AR) navigation technology have emerged and become an important tool in modern minimally invasive surgery. AR navigation directly superimposes virtual anatomical structures and surgical paths on the doctor's field of view, enabling the doctor to see the precise position of the patient's internal tissues and surgical instruments in real time. This technology combines high-precision imaging data (such as CT, Computed Tomography, MRI, Magnetic Resonance Imaging) with real-time feedback, significantly improving the accuracy of complex surgeries such as guide needle insertion, orthopedic implants, and neurosurgery. At the same time, augmented reality technology can also dynamically adjust the path to adapt to changes in soft tissue deformation and reduce operational errors. Systems based on this technology provide surgeons with a more intuitive operating environment, greatly improving the safety and success rate of surgery, and promoting the development of precision medicine.

[0003] Existing surgical navigation technology mainly relies on pre-acquired image data such as computed tomography (CT) or magnetic resonance imaging (MRI), and constructs a three-dimensional anatomical model of the patient through these images. However, traditional navigation systems often face problems with real-time and accuracy, especially when soft tissue deformation is encountered during surgery, the image and the actual anatomical structure may not match completely, resulting in operational errors. In addition, the information display of traditional navigation systems is usually separated, and doctors need to constantly switch their line of sight between the image screen and the actual surgical site, which increases the difficulty and fatigue of the operation. With the development of augmented reality (AR) technology, these problems have been effectively solved. By superimposing virtual images with real scenes, AR surgical navigation systems allow doctors to obtain detailed information about the surgical site in real time without leaving the surgical field of view, thereby improving the accuracy and efficiency of the operation.

[0004] For example, CN114711962B discloses an augmented reality surgical planning and navigation system and method, including: a portable intelligent terminal device, a medical image data import module, a medical image rapid marking module, a three-dimensional surgical planning module and an augmented reality surgical navigation module; the medical image data import module is used to import continuous multi-layer medical image data into the system, and complete the modeling and rendering of the virtual medical image three-dimensional model through the medical image rapid marking module and the three-dimensional surgical planning module; the augmented reality surgical navigation module preliminarily anchors the position of the medical image three-dimensional model in the real space coordinate system according to the three-dimensional space coordinate system in the established real scene; the medical image three-dimensional model is integrated with the patient's surgical area picture, and then the augmented reality navigation picture is obtained after position alignment, and displayed on the monitor.

[0005] For example, CN109758230B discloses a neurosurgery navigation method and system based on augmented reality technology, including: S1, preoperative preparation: importing the patient's preoperative medical images, fusing images of multiple modalities; formulating a surgical plan; S2, automatic alignment: determining the world coordinate system; solving the spatial transformation relationship between the image coordinate system and the world coordinate system; S3, tracking guidance: mapping the surgical plan in the image space to the world coordinate system, and superimposing the surgical plan on the patient's head observed by the augmented reality glasses according to the real-time posture of the augmented reality glasses relative to the world coordinate system, and when the augmented reality glasses move, the surgical plan maintains an unchanged relative position to the patient's head.

[0006] However, in the process of implementing the technical solution of the present invention, the present invention finds that the above technology has at least the following technical problems:

[0007] In the existing technology, augmented reality navigation technology relies on real-time images during surgery. However, due to the complex surgical environment and light source, when the guide needle encounters resistance under the action of rotation, it will deform. When the actual trajectory is replanned according to the deformation of the rigid solid, there is a problem of low real-time performance of the data that surgical navigation relies on. Summary of the invention

[0008] The embodiments of the present invention provide a method and system for optimizing visualized channel data based on augmented reality technology, thereby solving the problem of low real-time performance of data relied on by surgical navigation in the prior art and improving the real-time performance of data relied on by surgical navigation.

[0009] The embodiment of the present invention provides a method for optimizing visualized channel data based on augmented reality technology, comprising the following steps: acquiring basic image data of an imaging device, acquiring intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device; analyzing the impact of intraoperative imaging on the patient based on the basic image data and the intraoperative imaging delay data to obtain a first real-time interference evaluation coefficient, analyzing the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain a second real-time interference evaluation coefficient, wherein the first real-time interference evaluation coefficient is used to quantify the impact of the patient's physiological changes on intraoperative imaging, and the second real-time interference evaluation coefficient is used to quantify the impact of the patient's physiological changes on intraoperative imaging. The impact of surgical environment factors on intraoperative imaging; the first real-time interference assessment coefficient and the second real-time interference assessment coefficient are respectively compared with the first threshold value and the second threshold value obtained from the preset database to determine whether to take primary intervention and early warning measures; when no primary intervention and early warning measures are taken, the intraoperative imaging real-time interference assessment coefficient is obtained according to the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, and the intraoperative imaging real-time interference assessment coefficient is compared with the real-time interference assessment threshold value obtained from the preset database to determine whether to take corresponding secondary intervention and early warning measures, and the intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

[0010] Optionally, the surgical data acquisition equipment includes a frame rate measurement tool, a network monitoring tool, a network bandwidth monitoring tool, a network delay monitoring tool, a magnetic resonance imager, a light intensity meter and a multi-parameter monitor; the basic image data includes image resolution and image refresh rate, the image resolution represents the number of pixels per inch in the image generated by the imaging device, and the image refresh rate represents the number of image frames updated per second on the imaging device screen; the intraoperative imaging delay data includes frame acquisition rate, frame loss rate, transmission bandwidth and transmission delay; the intraoperative imaging interference data includes magnetic field strength, ambient light intensity and signal-to-noise ratio.

[0011] Optionally, the process of analyzing the impact of intraoperative imaging on patients based on basic image data and intraoperative imaging delay data to obtain a first real-time interference assessment coefficient is as follows: A1, obtaining reference intraoperative imaging delay data from a preset database, the reference intraoperative imaging delay data including a reference frame acquisition rate range, a reference frame loss rate, a reference transmission bandwidth range and a reference transmission delay range, the reference frame acquisition rate range including a maximum frame acquisition rate and a minimum frame acquisition rate, the reference transmission delay range including a minimum transmission delay and a maximum transmission delay, and the reference transmission bandwidth range including a minimum transmission bandwidth and a maximum transmission bandwidth; A2, comparing the result of a hyperbolic sine operation on the image resolution with the result of a hyperbolic cosine operation on the image refresh rate The results are summed to obtain an evaluation influence factor, which represents the influence of the imaging device on the real-time performance of intraoperative imaging; A3, if the frame acquisition rate and the transmission delay are both within the corresponding reference frame acquisition rate range and the reference transmission delay range, and the frame loss rate is below the reference frame loss rate, and the transmission bandwidth is above the reference transmission bandwidth, then execute A4, otherwise the value of the first real-time interference evaluation coefficient is recorded as 1; A4, a ratio operation is performed on the intraoperative imaging delay data and the corresponding reference intraoperative imaging delay data, followed by a hyperbolic tangent operation to obtain a delay index, and the first real-time interference evaluation coefficient is obtained by performing an exponential operation on the evaluation influence factor and the delay index, and the delay index represents the influence of image delay during surgery on the real-time performance of intraoperative imaging.

[0012] Optionally, the process of analyzing the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain the second real-time interference evaluation coefficient is as follows: B1, obtaining reference intraoperative imaging interference data from a preset database, the reference intraoperative imaging interference data including a reference magnetic field strength, a reference ambient light intensity interval and a reference signal-to-noise ratio, the reference ambient light intensity interval including a minimum ambient light intensity and a maximum ambient light intensity; B2, summing the result of a hyperbolic sine operation on the image resolution and the result of a hyperbolic cosine operation on the image refresh rate to obtain an evaluation influence factor; B3, if the magnetic field strength If the intensity is above the reference magnetic field intensity and the ambient light intensity belongs to the reference ambient light intensity range, and the signal-to-noise ratio is below the reference signal-to-noise ratio, execute B4, otherwise the first real-time interference evaluation coefficient is recorded as 1; B4, perform a ratio operation on the intraoperative imaging interference data and the corresponding reference intraoperative imaging interference data and then perform a hyperbolic tangent operation to obtain an environmental index, and perform an exponential operation on the evaluation influencing factor and the environmental index to obtain a second real-time interference evaluation coefficient, the environmental index represents the impact of the operating room environment on the real-time performance of intraoperative imaging during surgery, and the numerical expression of the second real-time interference evaluation coefficient is as follows:

[0013]

[0014] TX = sinh(IF) + cosh(IR);

[0015] Where IF represents the image resolution, IR represents the image refresh rate, M represents the magnetic field strength, L represents the ambient light intensity, N represents the signal-to-noise ratio, M0 represents the reference magnetic field strength, and L represents the reference magnetic field strength. MIN Indicates the minimum ambient light intensity, L MAX represents the maximum ambient light intensity, N0 represents the reference signal-to-noise ratio, TX represents the evaluation impact factor, and SAC represents the second real-time interference evaluation coefficient.

[0016] Optionally, the specific steps of comparing the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold and the second threshold obtained from the preset database to determine whether to take the first-level intervention and early warning measures are as follows: S1, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, the image generated by the imaging device is compressed and transmitted through the UDP protocol, and environmental management measures are taken at the same time, otherwise S2 is executed; S2, if the first real-time interference assessment coefficient is not greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, environmental management measures are taken, otherwise S3 is executed; S3, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is not greater than the second threshold, the image generated by the imaging device is compressed and transmitted through the UDP protocol, otherwise no first-level intervention and early warning measures are taken.

[0017] Optionally, the specific contents of the environmental management measures are as follows: sending a command button to remind the medical staff in the operating room to enable electromagnetic compatibility equipment; sending a command button to remind the medical staff in the operating room to perform automatic exposure adjustment; sending a command button to remind the medical staff in the operating room to perform noise reduction processing, and the noise reduction processing includes enabling the power supply filter and the low-noise amplifier, the power supply filter is used to reduce the impact of power supply noise on the imaging device, and the low-noise amplifier is used to reduce noise interference during signal transmission; when it is detected that the second real-time interference evaluation coefficient is not greater than the second threshold, sending a command button to remind the medical staff in the operating room to perform environmental adjustment measures, and the environmental adjustment measures include choosing to turn off the electromagnetic compatibility equipment, the power supply filter and the low-noise amplifier, and disabling the automatic exposure adjustment algorithm.

[0018] Optionally, the process of deriving the real-time interference assessment coefficient for intraoperative imaging based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient is as follows: obtaining a real-time assessment weight from a preset database, wherein the real-time assessment weight includes a first weight and a second weight; obtaining the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, and summing the first real-time interference assessment coefficient and the second real-time interference assessment coefficient and the corresponding first weight and second weight to obtain a total independent interference value; multiplying the first real-time interference assessment coefficient and the second real-time interference assessment coefficient to obtain a comprehensive interference value; and obtaining the real-time interference assessment coefficient for intraoperative imaging based on the total independent interference value and the comprehensive interference value.

[0019] Optionally, the specific process of comparing the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold obtained from a preset database to determine whether to take corresponding secondary intervention and early warning measures is as follows: if the intraoperative imaging real-time interference assessment coefficient is greater than the real-time interference assessment threshold, no secondary intervention and early warning measures are taken; if the intraoperative imaging real-time interference assessment coefficient is not greater than the real-time interference assessment threshold, the current intraoperative imaging intervention and early warning are sent to the operating room medical staff through the surgical equipment instrument display screen and imaging interference reduction suggestions are provided.

[0020] Optionally, the imaging interference reduction suggestions include checking surgical instruments, checking electromagnetic equipment, checking reflected light and noise reminders; the checking surgical instruments means checking whether there are magnetic surgical instruments in the current operating room; the checking electromagnetic equipment is used to reduce the electromagnetic interference of electromagnetic equipment on imaging equipment; the checking reflected light is used to reduce the impact of reflected light on imaging quality.

[0021] The embodiment of the present invention provides a visual channel data optimization system based on augmented reality technology, including: a data acquisition module, an independent interference assessment module, a primary intervention and warning module, and a secondary intervention and warning module; wherein the data acquisition module is used to acquire basic image data of an imaging device, and acquire intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device; the independent interference assessment module is used to analyze the impact of intraoperative imaging on the patient based on the basic image data and the intraoperative imaging delay data to obtain a first real-time interference assessment coefficient, and to analyze the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain a second real-time interference assessment coefficient, wherein the first real-time interference assessment coefficient is used to quantify the impact of the patient's physiological changes on intraoperative imaging, and the The second real-time interference assessment coefficient is used to quantify the impact of surgical environment factors on intraoperative imaging; the first-level intervention and early warning module is used to compare the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold value and the second threshold value obtained from the preset database respectively to determine whether to take first-level intervention and early warning measures; the second-level intervention and early warning module is used to derive the intraoperative imaging real-time interference assessment coefficient based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient when no first-level intervention and early warning measures are taken, and compare the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold value obtained from the preset database to determine whether to take corresponding second-level intervention and early warning measures, and the intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

[0022] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0023] 1. Whether to take primary intervention and early warning measures is determined by the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient, and whether to take secondary intervention and early warning measures is determined by the intraoperative imaging real-time interference evaluation coefficient, thereby reducing interference with the data that surgical navigation relies on, thereby improving the real-time performance of the data that surgical navigation relies on, and effectively solving the problem of low real-time performance of the data that surgical navigation relies on in the prior art.

[0024] 2. By obtaining the reference intraoperative imaging interference data, the result of the hyperbolic sine operation on the image resolution and the result of the hyperbolic cosine operation on the image refresh rate are summed to obtain the evaluation influence factor. If the magnetic field strength is above the reference magnetic field strength and the ambient light intensity belongs to the reference ambient light intensity range, and the signal-to-noise ratio is below the reference signal-to-noise ratio, the intraoperative imaging interference data and the corresponding reference intraoperative imaging interference data are ratio-operated and then hyperbolic tangent-operated to obtain the environmental index. At the same time, the second real-time interference evaluation coefficient is obtained by performing an exponential operation on the evaluation influence factor and the environmental index. Otherwise, the first real-time interference evaluation coefficient is recorded as 1, so as to more accurately evaluate the interference of the operating room environment on imaging, thereby improving the real-time performance of the data that surgical navigation relies on.

[0025] 3. By obtaining the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, and summing them with the corresponding real-time assessment weights to obtain the independent interference total value, then multiplying the first real-time interference assessment coefficient and the second real-time interference assessment coefficient to obtain the comprehensive interference value, and based on the independent interference total value and the comprehensive interference value, the intraoperative imaging real-time interference assessment coefficient is obtained, so as to more comprehensively evaluate the real-time of the data that the surgical navigation relies on, and then realize timely measures to improve the real-time of the data that the surgical navigation relies on. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flowchart of a method for optimizing channel data visualization based on augmented reality technology provided by an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of changes in the real-time interference assessment coefficient of intraoperative imaging provided by an embodiment of the present invention;

[0028] Figure 3 A schematic diagram of the structure of a visual channel data optimization system based on augmented reality technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The embodiment of the present invention solves the problem of low real-time performance of data relied on by surgical navigation in the prior art by providing a method and system for optimizing visualized channel data based on augmented reality technology. The method obtains basic image data of an imaging device, and obtains intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device. First, a first real-time interference assessment coefficient is obtained based on the basic image data and the intraoperative imaging delay data, and then a second real-time interference assessment coefficient is obtained based on the basic image data and the intraoperative imaging interference data. Then, the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient are respectively compared with a first threshold and a second threshold to determine whether to take primary intervention and early warning measures. Then, when no primary intervention and early warning measures are taken, an intraoperative imaging real-time interference assessment coefficient is obtained according to the first real-time interference assessment coefficient and the second real-time interference assessment coefficient. Finally, the intraoperative imaging real-time interference assessment coefficient is compared with the real-time interference assessment threshold to determine whether to take corresponding secondary intervention and early warning measures, thereby improving the real-time performance of data relied on by surgical navigation.

[0030] The technical solution in the embodiment of the present invention is to solve the problem of low real-time performance of the data relied on by the above-mentioned surgical navigation, and the overall idea is as follows:

[0031] Whether to take primary intervention and early warning measures is determined by the first real-time interference assessment coefficient, the second real-time interference assessment coefficient and the corresponding first and second thresholds, and whether to take secondary intervention and early warning measures is determined by the intraoperative imaging real-time interference assessment coefficient and the real-time interference assessment threshold, thereby achieving the effect of improving the real-time of data that surgical navigation relies on.

[0032] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0033] like Figure 1As shown, it is a flowchart of a method for optimizing visualized channel data based on augmented reality technology provided by an embodiment of the present invention, the method comprising the following steps: acquiring basic image data of an imaging device, acquiring intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device; analyzing the impact of intraoperative imaging on the patient based on the basic image data and the intraoperative imaging delay data to obtain a first real-time interference evaluation coefficient, analyzing the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain a second real-time interference evaluation coefficient, the first real-time interference evaluation coefficient is used to quantify the impact of the patient's physiological changes on intraoperative imaging, and the second real-time interference evaluation coefficient is used to quantify the impact of the patient's physiological changes on intraoperative imaging. Used to quantify the impact of surgical environment factors on intraoperative imaging; compare the first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold value and the second threshold value obtained from the preset database respectively to determine whether to take primary intervention and early warning measures; when no primary intervention and early warning measures are taken, the intraoperative imaging real-time interference assessment coefficient is obtained based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, and compare the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold value obtained from the preset database to determine whether to take corresponding secondary intervention and early warning measures. The intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

[0034] In this embodiment, through the layered warning mechanism, the medical staff in the operating room can take precautions and make adjustments before problems occur, ensuring that surgical imaging is not significantly affected by interference factors; the method provided by this embodiment effectively improves the real-time and accuracy of intraoperative imaging; by comprehensively considering network factors and surgical environment factors, the impact of these changes on intraoperative imaging is quantified, ensuring that the imaging quality matches the surgical requirements, and improving the real-time nature of the data that surgical navigation relies on.

[0035] Optionally, the surgical data acquisition equipment includes frame rate measurement tools, network monitoring tools, network bandwidth monitoring tools, network delay monitoring tools, magnetic resonance imaging devices, light intensity meters and multi-parameter monitors; basic image data include image resolution and image refresh rate, image resolution indicates the number of pixels per inch in the image generated by the imaging device, and image refresh rate indicates the number of image frames updated per second on the imaging device screen; intraoperative imaging delay data includes frame acquisition rate, frame loss rate, transmission bandwidth and transmission delay; intraoperative imaging interference data includes magnetic field strength, ambient light intensity and signal-to-noise ratio.

[0036] In this embodiment, the frame rate measurement tool directly reads the output signal of the imaging device (such as a magnetic resonance imager) and counts the number of image frames collected within a unit time (such as 1 second) to obtain the frame acquisition rate, which is usually expressed in frames per second (FPS); the network monitoring tool tracks the data packets or frames transmitted in the network and calculates the number of lost data packets to obtain the frame loss rate, which is usually expressed as a percentage. For example, if 1000 frames are sent and the receiving end only receives 950 frames, the frame loss rate is 5%; the network bandwidth monitoring tool monitors the data transmission speed in real time to obtain the transmission bandwidth during imaging data transmission. For example, a transmission bandwidth of 100 (Mbps) means that the network can transmit 100 megabits of data per second; the network delay monitoring tool can accurately calculate the transmission delay of imaging data transmission, that is, the time required for data to travel from the source to the receiving end, which is usually expressed in milliseconds (ms). For example, a delay of 20 (ms) This means that the round-trip time for data in the transmission network is 20 milliseconds; the magnetic resonance imaging device has an integrated magnetic field monitoring system that can display the magnetic field strength of the device in real time when it is running, for example, the magnetic field strength is 1.5 Tesla or 3.0 Tesla, which is usually determined according to the imaging requirements and device configuration; the light intensity meter is placed in the operating room or imaging environment, and the instrument will detect and display the ambient light intensity of the surrounding environment in real time, for example, the measured value is 500 (lux) or 1000 (lux); during the imaging or monitoring process, the multi-parameter monitor analyzes the collected signal and the noise part of the signal to calculate the signal-to-noise ratio (SNR). The signal-to-noise ratio is usually expressed in decibels (dB), such as 20 (dB) or 30 (dB). The higher the signal-to-noise ratio, the higher the signal quality; the above data can comprehensively evaluate the operating status of the imaging device use environment and the network environment, which helps to optimize the imaging quality and ensure the smooth progress of the surgical process.

[0037] Optionally, the process of analyzing the impact of intraoperative imaging on patients based on basic image data and intraoperative imaging delay data to obtain a first real-time interference assessment coefficient is as follows: A1, obtaining reference intraoperative imaging delay data from a preset database, the reference intraoperative imaging delay data including a reference frame acquisition rate range, a reference frame loss rate, a reference transmission bandwidth range and a reference transmission delay range, the reference frame acquisition rate range including a maximum frame acquisition rate and a minimum frame acquisition rate, the reference transmission delay range including a minimum transmission delay and a maximum transmission delay, and the reference transmission bandwidth range including a minimum transmission bandwidth and a maximum transmission bandwidth; A2, performing a hyperbolic sine operation on the image resolution and a hyperbolic cosine operation on the image refresh rate. A sum operation is performed to obtain an evaluation influence factor, which represents the influence of the imaging device on the real-time performance of intraoperative imaging; A3, if the frame acquisition rate and the transmission delay are both within the corresponding reference frame acquisition rate range and the reference transmission delay range, and the frame loss rate is below the reference frame loss rate, and the transmission bandwidth is above the reference transmission bandwidth, then execute A4, otherwise the value of the first real-time interference evaluation coefficient is recorded as 1; A4, a ratio operation is performed on the intraoperative imaging delay data and the corresponding reference intraoperative imaging delay data, followed by a hyperbolic tangent operation to obtain a delay index, and the first real-time interference evaluation coefficient is obtained by performing an exponential operation on the evaluation influence factor and the delay index, and the delay index represents the influence of image delay during surgery on the real-time performance of intraoperative imaging.

[0038] The numerical expression of the first real-time interference evaluation coefficient is as follows:

[0039]

[0040] TX = sinh(IF) + cosh(IR);

[0041] In the formula, IF represents the image resolution, IR represents the image refresh rate, R represents the frame acquisition rate, and R MAX Indicates the maximum frame acquisition rate, R MIN represents the minimum frame acquisition rate, H represents the frame loss rate, H0 represents the reference frame loss rate, P represents the transmission bandwidth, P MIN Indicates the minimum transmission bandwidth, P MAX represents the maximum transmission bandwidth, A represents the transmission delay, and A MIN Indicates the minimum transmission delay, A MAX represents the maximum transmission delay, TX represents the evaluation impact factor, and FAC represents the first real-time interference evaluation coefficient.

[0042] In this embodiment, the algorithm combines basic image data, intraoperative imaging delay data and reference intraoperative imaging delay data to comprehensively analyze the impact on intraoperative imaging to obtain a first real-time interference assessment coefficient. When the frame acquisition rate is higher, the frame loss rate is lower, the transmission bandwidth is larger and the transmission delay is larger, the corresponding first real-time interference assessment coefficient is larger, indicating that the current network factors are less conducive to the real-time performance of intraoperative imaging, and it is necessary to monitor the intraoperative imaging delay data in real time to ensure that changes in the imaging equipment during the operation are detected in time, and to ensure the synchronization of imaging quality and operation. By comprehensively quantifying multiple interference factors, the real-time performance and stability of intraoperative imaging can be effectively improved, providing a higher guarantee for the smooth progress of surgical operations.

[0043] Specifically, the reference frame acquisition rate range is obtained from a preset database. In a specific embodiment, the reference frame acquisition rate range is obtained by referring to the equipment technical manual provided by the imaging device. For example, referring to the equipment technical manual provided by the ultrasonic imaging device (model XYZ-500), the reference frame acquisition rate range is 10-60 (frames / second).

[0044] Specifically, the reference frame loss rate is obtained from a preset database. In a specific embodiment, the reference frame loss rate is obtained by referring to the equipment technical manual provided by the imaging device. For example, referring to the equipment technical manual provided by the ultrasonic imaging device (model XYZ-500) to obtain that the allowable frame loss rate does not exceed 0.01%, then the reference frame loss rate is 0.01%.

[0045] Specifically, the reference transmission bandwidth range is obtained from a preset database. In a specific embodiment, the reference transmission bandwidth range is obtained by referring to the equipment technical manual provided by the imaging device. For example, referring to the equipment technical manual provided by the ultrasonic imaging device (model XYZ-500), it can be obtained that the transmission bandwidth required by the ultrasonic imaging device (model XYZ-500) is 50 (Mbps) to 200 (Mbps), and the reference transmission bandwidth range is 50 (Mbps) to 200 (Mbps).

[0046] Specifically, the reference transmission delay range is obtained from a preset database. In a specific embodiment, the reference transmission delay range is obtained by referring to the equipment technical manual provided by the imaging device. For example, referring to the equipment technical manual provided by the ultrasonic imaging device (model XYZ-500) can obtain that the expected transmission delay range is 20-50 milliseconds, and the reference transmission delay range is 20-50 (milliseconds).

[0047] Optionally, the process of analyzing the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain the second real-time interference evaluation coefficient is as follows: B1, obtaining reference intraoperative imaging interference data from a preset database, the reference intraoperative imaging interference data including a reference magnetic field strength, a reference ambient light intensity range and a reference signal-to-noise ratio, the reference ambient light intensity range including a minimum ambient light intensity and a maximum ambient light intensity; B2, summing the result of a hyperbolic sine operation on the image resolution and the result of a hyperbolic cosine operation on the image refresh rate to obtain an evaluation influence factor; B3, if the magnetic field strength If the reference magnetic field intensity is above the reference ambient light intensity range and the signal-to-noise ratio is below the reference signal-to-noise ratio, execute B4, otherwise the first real-time interference evaluation coefficient is recorded as 1; B4, perform a ratio operation on the intraoperative imaging interference data and the corresponding reference intraoperative imaging interference data and then perform a hyperbolic tangent operation to obtain an environmental index, and perform an exponential operation on the evaluation influencing factor and the environmental index to obtain a second real-time interference evaluation coefficient. The environmental index represents the impact of the operating room environment on the real-time performance of intraoperative imaging during surgery. The numerical expression of the second real-time interference evaluation coefficient is as follows:

[0048]

[0049] TX = sinh(IF) + cosh(IR);

[0050] Where IF represents the image resolution, IR represents the image refresh rate, M represents the magnetic field strength, L represents the ambient light intensity, N represents the signal-to-noise ratio, M0 represents the reference magnetic field strength, and L represents the reference magnetic field strength. MIN Indicates the minimum ambient light intensity, L MAX represents the maximum ambient light intensity, N0 represents the reference signal-to-noise ratio, TX represents the evaluation impact factor, and SAC represents the second real-time interference evaluation coefficient.

[0051] In this embodiment, the algorithm combines basic image data, intraoperative imaging interference data and reference intraoperative imaging interference data for comprehensive analysis to obtain a second real-time interference evaluation coefficient, wherein, when the magnetic field intensity is smaller, the ambient light intensity is greater and the signal-to-noise ratio is smaller, the second real-time interference evaluation coefficient is larger, indicating that the operating room environment has a greater interference with intraoperative imaging. Therefore, it is necessary to monitor relevant data of the operating room environment, thereby improving the stability and reliability of real-time evaluation of intraoperative imaging, and helping operating room medical staff to adjust imaging equipment or operating procedures in real time during surgery, thereby reducing the impact of imaging quality fluctuations on surgical accuracy; and mathematically modeling environmental factors and imaging real-time, so that interference evaluation is not limited to a single factor, but can take into account the comprehensive impact of the entire operating room environment, which helps to identify the interference of environmental factors such as light intensity changes and magnetic field fluctuations on imaging real-time, thereby affecting the real-time of the surgical navigation system.

[0052] Specifically, the reference magnetic field strength is obtained from a preset database. In a specific embodiment, the reference magnetic field strength is obtained by consulting the technical documents provided by the imaging device, for example, consulting the technical documents provided by the MRI device (model GE Signa Explorer 1.5T MRI) to obtain a reference magnetic field strength of 1.5 Tesla.

[0053] Specifically, the reference ambient light intensity interval is obtained from a preset database. In a specific embodiment, the reference ambient light intensity interval is obtained according to industry standards. For example, the light intensity in an operating room is generally required to be between 1000 and 10,000 lux, depending on the type of surgery. Therefore, the reference ambient light intensity interval is [1000, 10000].

[0054] Specifically, the reference signal-to-noise ratio is obtained from a preset database. In a specific embodiment, the reference signal-to-noise ratio is obtained by consulting the technical documents provided by the imaging device, for example, consulting the technical documents provided by the MRI device (model Siemens Magnetom Vida 3TMRI) to obtain that the allowable signal-to-noise ratio does not exceed 25 (dB), and the reference signal-to-noise ratio is 25 (dB).

[0055] Optionally, the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient are respectively compared with the first threshold and the second threshold obtained from the preset database to determine whether to take the first-level intervention and early warning measures. The specific steps are as follows: S1, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, the image generated by the imaging device is compressed and transmitted through the UDP protocol, and environmental management measures are taken at the same time, otherwise S2 is executed; S2, if the first real-time interference assessment coefficient is not greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, environmental management measures are taken, otherwise S3 is executed; S3, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is not greater than the second threshold, the image generated by the imaging device is compressed and transmitted through the UDP protocol, otherwise no first-level intervention and early warning measures are taken.

[0056] In this embodiment, the UDP protocol (User Datagram Protocol) is a simple, connectionless transport layer protocol. The use of the UDP protocol can reduce transmission delays. The image generated by the imaging device is compressed using an image compression algorithm. The image compression algorithm is used to reduce the amount of image data for faster storage or transmission. It is mainly divided into lossy compression and lossless compression. By compressing image data, using a low-latency transmission protocol (UDP) and environmental management measures, the overall delay of the imaging device can be effectively reduced and the real-time performance of the image can be improved.

[0057] Specifically, the first threshold is obtained from a preset database. In a specific embodiment, the first threshold is obtained by substituting the historical intraoperative imaging delay data of the corresponding surgical type into the numerical expression of the first real-time interference assessment coefficient to obtain a data set, and statistically obtaining the numerical value of the corresponding percentile of the data set, then the numerical value is recorded as the first threshold, and the percentile is obtained through a mapping set of surgical types and percentiles. For example, in the data set of the first real-time interference assessment coefficient obtained from the historical intraoperative imaging delay data of 500 spinal surgeries, if the corresponding percentile of the spinal surgery in the query mapping set is 95%, and it is statistically obtained that 95% of the first real-time interference assessment coefficients in the data set are below 0.35, then 0.35 is recorded as the first threshold corresponding to the first real-time interference assessment coefficient when performing spinal surgery.

[0058] Specifically, the second threshold is obtained from a preset database. In a specific embodiment, the first threshold is obtained by substituting the historical intraoperative imaging interference data of the corresponding surgical type into the numerical expression of the second real-time interference evaluation coefficient to obtain a data set, and statistically obtaining the numerical value of the corresponding percentile of the data set, then the numerical value is recorded as the second threshold, and the percentile is obtained through a mapping set of surgical types and percentiles. For example, in the data set of the second real-time interference evaluation coefficient obtained from the historical intraoperative imaging interference data of 500 spinal surgeries, if the corresponding percentile of the spinal surgery in the query mapping set is 99%, and it is statistically obtained that 99% of the second real-time interference evaluation coefficients in the data set are below 0.55, then 0.55 is recorded as the first threshold corresponding to the second real-time interference evaluation coefficient when performing spinal surgery.

[0059] Optionally, the specific contents of the environmental management measures are as follows: sending a command button to remind the medical staff in the operating room to enable electromagnetic compatibility equipment, which is used to reduce the electromagnetic radiation of electronic equipment in the operating room; sending a command button to remind the medical staff in the operating room to perform automatic exposure adjustment, which is used to enable the surgical equipment to automatically adjust the exposure parameters when the ambient light intensity changes to ensure that the intraoperative image is always clear and stable; sending a command button to remind the medical staff in the operating room to perform noise reduction processing, which includes enabling power supply filters and low-noise amplifiers, which are used to reduce the impact of power supply noise on imaging equipment, and low-noise amplifiers are used to reduce noise interference during signal transmission; when it is detected that the second real-time interference evaluation coefficient is not greater than the second threshold, the command button is sent to remind the medical staff in the operating room that the interference of operating room environmental factors on the real-time of intraoperative imaging has been reduced and to take environmental adjustment measures, which include choosing to turn off electromagnetic compatibility equipment, power supply filters and low-noise amplifiers and deactivating the automatic exposure adjustment algorithm.

[0060] In this embodiment, by reminding medical staff to enable electromagnetic compatibility equipment, the interference of electromagnetic radiation generated by other electronic equipment (such as monitors, vital signs monitors, etc.) in the operating room to the imaging equipment can be reduced, and image distortion or signal loss caused by electromagnetic radiation can be reduced; the exposure setting of the imaging device can be dynamically adjusted through automatic exposure adjustment to ensure that the imaging clarity is not affected by changes in ambient light, avoid overexposure or underexposure of the image, and ensure that the intraoperative image is always stable; the power supply filter can reduce the electrical noise (such as voltage fluctuations, harmonic interference) of the power supply system in the operating room, thereby reducing the impact on the power supply of the imaging device, ensuring the stability of image acquisition and processing, and reducing image fluctuations or distortion caused by power supply noise; the low-noise amplifier can effectively suppress noise interference in signal transmission, especially in the process from the imaging device to the processing unit, which helps to maintain the purity of the signal, reduce the impact of noise on image quality, and ensure the clarity and reliability of the image data; the method provided by the embodiment of the present invention ensures that the interference of the operating room environment on the imaging device is minimized, and the real-time and stability of the image during surgical navigation is improved.

[0061] Optionally, the process of deriving the real-time interference assessment coefficient of intraoperative imaging according to the first real-time interference assessment coefficient and the second real-time interference assessment coefficient is as follows: obtaining the real-time assessment weight from a preset database, the real-time assessment weight including the first weight and the second weight; obtaining the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, summing the first real-time interference assessment coefficient and the second real-time interference assessment coefficient and the corresponding first weight and second weight to obtain an independent interference total value, the independent interference total value represents the overall reflection of the network factors and environmental factors affecting the real-time of intraoperative imaging; multiplying the first real-time interference assessment coefficient and the second real-time interference assessment coefficient to obtain a comprehensive interference value, the comprehensive interference value is used to reflect the joint influence of network factors and environmental factors on the real-time of intraoperative imaging; obtaining the real-time interference assessment coefficient of intraoperative imaging based on the independent interference total value and the comprehensive interference value, the numerical expression of the real-time interference assessment coefficient of intraoperative imaging is as follows:

[0062]

[0063] Wherein, FAC represents the first real-time interference assessment coefficient, SAC represents the second real-time interference assessment coefficient, α represents the first weight, β represents the second weight, ORC represents the intraoperative imaging real-time interference assessment coefficient, and e represents a natural constant.

[0064] In this embodiment, the algorithm combines the first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the real-time assessment weight for comprehensive analysis to obtain the intraoperative imaging real-time interference assessment coefficient. The first real-time interference assessment coefficient and the second real-time interference assessment coefficient are negatively correlated with the intraoperative imaging real-time interference assessment coefficient. Specifically, Figure 2 As shown, Figure 2 A schematic diagram of a change in the real-time interference evaluation coefficient of intraoperative imaging provided by an embodiment of the present invention, from Figure 2 It can be seen that with the increase of the first real-time interference assessment coefficient and the second real-time interference assessment coefficient, the image shows a downward trend, the intraoperative imaging real-time interference assessment coefficient gradually decreases, and approaches 0, further proving that the first real-time interference assessment coefficient and the second real-time interference assessment coefficient are negatively correlated with the intraoperative imaging real-time interference assessment coefficient; through the method provided by the embodiment of the present invention, the independent and common influences of the network and the environment are integrated to judge the degree of real-time interference of intraoperative imaging, which helps to comprehensively reflect the impact on the real-time performance of imaging and helps to evaluate the interference level of imaging.

[0065] Specifically, by combining the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient, and assuming that the first weight is 0.7 and the second weight is 0.3, a data change table of the intraoperative imaging real-time interference evaluation coefficient is obtained, as shown in Table 1:

[0066] Table 1 Data changes of real-time interference evaluation coefficient of intraoperative imaging

[0067]

[0068] It can be seen from Table 1 that with the increase of the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient, the real-time interference evaluation coefficient of intraoperative imaging gradually decreases. For example, in the second and fourth rows of data in the table, the first real-time interference evaluation coefficient increases from 0.8 in the second row to 1.1 in the fourth row, but the second real-time interference evaluation coefficient is still 0.6, and the real-time interference evaluation coefficient of intraoperative imaging decreases from 0.11 in the second row to 0.07 in the fourth row; for another example, in the second and fifth rows of data in the table, the second real-time interference evaluation coefficient increases from 0.6 in the second row to 1.2 in the fourth row, but the first real-time interference evaluation coefficient is still 0.8, and the real-time interference evaluation coefficient of intraoperative imaging decreases from 0.11 in the second row to 0.06 in the fourth row; it can be seen that ensuring the accuracy and real-time performance of intraoperative imaging by analyzing the changes in the network and environment is conducive to assisting medical staff in the operating room to better complete surgical operations.

[0069] Specifically, the first weight is the weight corresponding to the first real-time interference assessment coefficient in the preset database, which represents the numerical value of the influence degree of the first real-time interference assessment coefficient on the real-time interference assessment coefficient of intraoperative imaging. When used, the weight corresponding to the first real-time interference assessment coefficient can be directly obtained from the preset database, and the corresponding relationship can be a pre-set mapping relationship. For example, the first real-time interference assessment coefficient corresponding to the intraoperative imaging delay data and the weight corresponding to the real-time interference assessment coefficient of intraoperative imaging preset in the preset database form a mapping set, and the real-time first real-time interference assessment coefficient is input into the mapping set to obtain the corresponding weight, wherein the mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1], and the sum of the second weight and the first weight is 1.

[0070] Optionally, the specific process of comparing the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold obtained from a preset database to determine whether to take corresponding secondary intervention and early warning measures is as follows: if the intraoperative imaging real-time interference assessment coefficient is greater than the real-time interference assessment threshold, no secondary intervention and early warning measures are taken; if the intraoperative imaging real-time interference assessment coefficient is not greater than the real-time interference assessment threshold, secondary intervention and early warning measures are taken, and the current intraoperative imaging intervention and early warning are sent to the operating room medical staff through the surgical equipment instrument display screen to inform the operating room medical staff that the real-time of the current guide needle trajectory path is reduced, and provide suggestions for reducing imaging interference.

[0071] In this embodiment, once the secondary intervention and early warning measures are triggered, medical staff will receive a reminder through the device display screen, informing them of the reduced imaging quality and providing suggestions for reducing interference; the embodiment of the present invention can evaluate and respond to imaging interference in real time and automatically determine whether early warning measures need to be taken, thereby reducing human intervention. At the same time, early warning information is directly fed back to the medical staff in the operating room to facilitate rapid response, and imaging interference is reduced by timely adjustment, thereby ensuring surgical imaging accuracy and surgical safety.

[0072] Specifically, the real-time interference assessment threshold is obtained from a preset database. In a specific embodiment, the real-time interference assessment threshold is obtained by substituting the historical intraoperative imaging delay data of the corresponding surgical type into the numerical expression of the first real-time interference assessment coefficient and the historical intraoperative imaging interference data into the numerical expression of the second real-time interference assessment coefficient to obtain two independent data sets, and then substituting the two independent data sets into the numerical expression of the intraoperative imaging real-time interference assessment coefficient to obtain a comprehensive data set, and statistically obtaining the numerical value of the percentile corresponding to the comprehensive data set, then the numerical value is recorded as the real-time interference assessment threshold, and the percentile is obtained through the mapping set of surgical types and percentiles. For example, a comprehensive data set of intraoperative imaging real-time interference assessment coefficients is obtained through two independent data sets of historical intraoperative data of 500 spinal surgeries. If the corresponding percentile of the spinal surgery in the query mapping set is 99%, and the statistics show that 99% of the intraoperative imaging real-time interference assessment coefficients in the comprehensive data set are above 0.45, then 0.45 is recorded as the real-time interference assessment threshold corresponding to the intraoperative imaging real-time interference assessment coefficient when performing spinal surgery.

[0073] Optionally, suggestions for reducing imaging interference include checking surgical instruments, checking electromagnetic equipment, checking reflected light and noise reminders; checking surgical instruments means checking whether there are magnetic surgical instruments in the current operating room, and if so, moving the magnetic surgical instruments away from the imaging equipment; checking electromagnetic equipment is used to reduce electromagnetic interference of electromagnetic equipment on imaging equipment; checking reflected light is used to reduce the impact of reflected light on imaging quality; noise reminders indicate prompting medical workers in the operating room to keep quiet to reduce the impact of noise interference on imaging.

[0074] In this embodiment, various physical and environmental factors that may affect the imaging equipment in the operating room are comprehensively covered by checking and adjusting magnetic surgical instruments, electromagnetic equipment, reflected light and noise interference; these measures optimize the working environment of the imaging equipment by reducing electromagnetic, optical and acoustic interference, thereby ensuring the real-time, clarity and accuracy of intraoperative images.

[0075] like Figure 3As shown, it is a structural schematic diagram of a visual channel data optimization system based on augmented reality technology provided by an embodiment of the present invention. A visual channel data optimization system based on augmented reality technology provided by an embodiment of the present invention includes: a data acquisition module, an independent interference assessment module, a primary intervention and warning module, and a secondary intervention and warning module; wherein the data acquisition module is used to obtain basic image data of an imaging device, and obtain intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device; the independent interference assessment module is used to analyze the impact of intraoperative imaging on patients based on the basic image data and the intraoperative imaging delay data to obtain a first real-time interference assessment coefficient, and analyze the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain a second real-time interference assessment coefficient, and the first real-time interference assessment coefficient Used to quantify the impact of patient physiological changes on intraoperative imaging, and the second real-time interference assessment coefficient is used to quantify the impact of surgical environment factors on intraoperative imaging; the first-level intervention and early warning module is used to compare the first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold and the second threshold obtained from the preset database, respectively, to determine whether to take first-level intervention and early warning measures; the second-level intervention and early warning module is used to derive the intraoperative imaging real-time interference assessment coefficient based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient when no first-level intervention and early warning measures are taken, and compare the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold obtained from the preset database to determine whether to take corresponding second-level intervention and early warning measures, and the intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

[0076] In this embodiment, the system monitors interference factors of intraoperative imaging in real time to avoid the negative impact of imaging delays or interference on the operation; and through a graded warning mechanism, it helps doctors make timely adjustments to reduce surgical risks; at the same time, the system comprehensively evaluates the patient's physiological changes and surgical environment to ensure accurate imaging and assist doctors in completing surgical operations more accurately.

[0077] To summarize, the first real-time interference assessment coefficient and the second real-time interference assessment coefficient are obtained to determine whether to take primary intervention and early warning measures, and the intraoperative imaging real-time interference assessment coefficient is used to determine whether to take secondary intervention and early warning measures, thereby reducing interference with the data that surgical navigation relies on, thereby improving the real-time performance of the data that surgical navigation relies on, and effectively solving the problem of low real-time performance of the data that surgical navigation relies on in the prior art.

[0078] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0082] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0083] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing visual channel data based on augmented reality technology, characterized in that: The following steps are involved: Acquire basic image data of the imaging device, and acquire intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through a surgical data acquisition device; A first real-time interference assessment coefficient is obtained by analyzing the impact of intraoperative imaging on patients based on basic image data and intraoperative imaging delay data, and a second real-time interference assessment coefficient is obtained by analyzing the impact of intraoperative imaging environment based on basic image data and intraoperative imaging interference data. The first real-time interference assessment coefficient is used to quantify the impact of patient physiological changes on intraoperative imaging, and the second real-time interference assessment coefficient is used to quantify the impact of surgical environment factors on intraoperative imaging; Compare the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold value and the second threshold value obtained from the preset database to determine whether to take the first-level intervention and early warning measures; When no primary intervention and early warning measures are taken, an intraoperative imaging real-time interference assessment coefficient is obtained based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient. The intraoperative imaging real-time interference assessment coefficient is compared with a real-time interference assessment threshold obtained from a preset database to determine whether to take corresponding secondary intervention and early warning measures. The intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

2. According to claim 1, the method for optimizing channel data based on visualization of augmented reality technology is characterized in that: The surgical data acquisition equipment includes a frame rate measurement tool, a network monitoring tool, a network bandwidth monitoring tool, a network delay monitoring tool, a magnetic resonance imager, a light intensity meter and a multi-parameter monitor; The basic image data includes image resolution and image refresh rate, wherein the image resolution represents the number of pixels per inch in an image generated by an imaging device, and the image refresh rate represents the number of image frames updated per second on the screen of the imaging device; The intraoperative imaging delay data includes frame acquisition rate, frame loss rate, transmission bandwidth and transmission delay; The intraoperative imaging interference data includes magnetic field strength, ambient light intensity and signal-to-noise ratio.

3. According to claim 2, the method for optimizing channel data based on visualization of augmented reality technology is characterized in that: The process of analyzing the impact of intraoperative imaging on patients based on the basic image data and intraoperative imaging delay data to obtain the first real-time interference assessment coefficient is specifically as follows: A1, obtaining reference intraoperative imaging delay data from a preset database, wherein the reference intraoperative imaging delay data includes a reference frame acquisition rate range, a reference frame loss rate, a reference transmission bandwidth range, and a reference transmission delay range, wherein the reference frame acquisition rate range includes a maximum frame acquisition rate value and a minimum frame acquisition rate value, wherein the reference transmission delay range includes a minimum transmission delay value and a maximum transmission delay value, and wherein the reference transmission bandwidth range includes a minimum transmission bandwidth value and a maximum transmission bandwidth value; A2, performing a sum operation on the result of a hyperbolic sine operation on the image resolution and the result of a hyperbolic cosine operation on the image refresh rate to obtain an evaluation impact factor, wherein the evaluation impact factor represents the impact of the imaging device on the real-time performance of intraoperative imaging; A3: If the frame acquisition rate and the transmission delay are both within the corresponding reference frame acquisition rate range and the reference transmission delay range, and the frame loss rate is below the reference frame loss rate, and the transmission bandwidth is above the reference transmission bandwidth, then execute A4; otherwise, the value of the first real-time interference assessment coefficient is recorded as 1; A4, performing a ratio operation on the intraoperative imaging delay data and the corresponding reference intraoperative imaging delay data and then performing a hyperbolic tangent operation to obtain a delay index, and performing an exponential operation on the evaluation influence factor and the delay index to obtain a first real-time interference evaluation coefficient, wherein the delay index represents the influence of image delay during surgery on the real-time performance of intraoperative imaging.

4. According to claim 2, the method for optimizing channel data based on visualization of augmented reality technology is characterized in that: The process of analyzing the impact of the intraoperative imaging environment based on the basic image data and the intraoperative imaging interference data to obtain the second real-time interference evaluation coefficient is specifically as follows: B1, obtaining reference intraoperative imaging interference data from a preset database, wherein the reference intraoperative imaging interference data includes a reference magnetic field intensity, a reference ambient light intensity interval, and a reference signal-to-noise ratio, wherein the reference ambient light intensity interval includes a minimum ambient light intensity and a maximum ambient light intensity; B2, summing the result of the hyperbolic sine operation on the image resolution and the result of the hyperbolic cosine operation on the image refresh rate to obtain the evaluation impact factor; B3, if the magnetic field strength is above the reference magnetic field strength and the ambient light intensity belongs to the reference ambient light intensity range, and the signal-to-noise ratio is below the reference signal-to-noise ratio, then execute B4, otherwise the first real-time interference assessment coefficient is recorded as 1; B4, performing a ratio operation on the intraoperative imaging interference data and the corresponding reference intraoperative imaging interference data and then performing a hyperbolic tangent operation to obtain an environmental index, and performing an exponential operation on the evaluation influencing factor and the environmental index to obtain a second real-time interference evaluation coefficient, wherein the environmental index represents the influence of the operating room environment on the real-time performance of intraoperative imaging during surgery, and the numerical expression of the second real-time interference evaluation coefficient is as follows: TX = sinh(IF) + cosh(IR); Where IF represents the image resolution, IR represents the image refresh rate, M represents the magnetic field strength, L represents the ambient light intensity, N represents the signal-to-noise ratio, M0 represents the reference magnetic field strength, and L represents the reference magnetic field strength. MIN Indicates the minimum ambient light intensity, L MAX represents the maximum ambient light intensity, N0 represents the reference signal-to-noise ratio, TX represents the evaluation impact factor, and SAC represents the second real-time interference evaluation coefficient.

5. According to claim 4, the method for optimizing channel data based on visualization of augmented reality technology is characterized in that: The specific steps of comparing the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold value and the second threshold value obtained from the preset database to determine whether to take the first-level intervention and early warning measures are as follows: S1, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, compress the image generated by the imaging device and transmit it through the UDP protocol, and take environmental management measures, otherwise execute S2; S2, if the first real-time interference assessment coefficient is not greater than the first threshold and the second real-time interference assessment coefficient is greater than the second threshold, then take environmental management measures, otherwise execute S3; S3, if the first real-time interference assessment coefficient is greater than the first threshold and the second real-time interference assessment coefficient is not greater than the second threshold, the image generated by the imaging device is compressed and transmitted through the UDP protocol, otherwise no first-level intervention and warning measures are taken.

6. The method for optimizing channel data visualization based on augmented reality technology according to claim 5, characterized in that: The specific contents of the environmental management measures are as follows: Send command button to remind medical staff in operating room to enable electromagnetic compatibility equipment; Send command button to remind medical staff in operating room to make automatic exposure adjustment; The sending command button reminds the medical staff in the operating room to perform noise reduction processing, wherein the noise reduction processing includes enabling a power filter and a low noise amplifier, wherein the power filter is used to reduce the influence of power noise on the imaging device, and the low noise amplifier is used to reduce noise interference during signal transmission; When it is detected that the second real-time interference evaluation coefficient is not greater than the second threshold, a command button is sent to remind the medical staff in the operating room to take environmental adjustment measures, which include choosing to turn off electromagnetic compatibility equipment, power supply filters and low-noise amplifiers, and disabling automatic exposure adjustment algorithms.

7. The method for optimizing channel data based on visualization of augmented reality technology according to claim 1, characterized in that: The process of obtaining the intraoperative imaging real-time interference evaluation coefficient according to the first real-time interference evaluation coefficient and the second real-time interference evaluation coefficient is specifically as follows: Acquire a real-time evaluation weight from a preset database, wherein the real-time evaluation weight includes a first weight and a second weight; Obtaining a first real-time interference assessment coefficient and a second real-time interference assessment coefficient, and performing a sum operation on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient and the corresponding first weight and second weight to obtain an independent interference total value; Performing a product operation on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient to obtain a comprehensive interference value; The interference assessment coefficient of intraoperative imaging real-time performance was obtained based on the total independent interference value and the comprehensive interference value.

8. The method for optimizing channel data visualization based on augmented reality technology according to claim 7, characterized in that: The specific process of comparing the intraoperative imaging real-time interference assessment coefficient with the real-time interference assessment threshold obtained from the preset database to determine whether to take corresponding secondary intervention and early warning measures is as follows: If the intraoperative imaging real-time interference assessment coefficient is greater than the real-time interference assessment threshold, no secondary intervention and warning measures will be taken; If the intraoperative imaging real-time interference assessment coefficient is not greater than the real-time interference assessment threshold, the current intraoperative imaging intervention and warning are sent to the operating room medical staff through the surgical equipment instrument display screen and imaging interference reduction suggestions are provided.

9. The method for optimizing channel data based on visualization of augmented reality technology according to claim 8, characterized in that: The imaging interference reduction suggestions include checking surgical instruments, checking electromagnetic equipment, checking reflected light and noise reminders; The checking of surgical instruments means checking whether there are magnetic surgical instruments in the current operating room; The inspection electromagnetic device is used to reduce the electromagnetic interference of the electromagnetic device on the imaging device; The inspection reflected light is used to reduce the influence of the reflected light on the imaging quality.

10. A visual channel data optimization system based on augmented reality technology, characterized in that: include: Data collection module, independent interference assessment module, primary intervention and early warning module, and secondary intervention and early warning module; Wherein, the data acquisition module is used to obtain basic image data of the imaging device, and obtain intraoperative imaging delay data and intraoperative imaging interference data corresponding to the surgical process through the surgical data acquisition device; The independent interference assessment module is used to analyze the impact of intraoperative imaging on patients based on basic image data and intraoperative imaging delay data to obtain a first real-time interference assessment coefficient, and to analyze the impact of intraoperative imaging environment based on basic image data and intraoperative imaging interference data to obtain a second real-time interference assessment coefficient, wherein the first real-time interference assessment coefficient is used to quantify the impact of patient physiological changes on intraoperative imaging, and the second real-time interference assessment coefficient is used to quantify the impact of surgical environment factors on intraoperative imaging; The first level intervention and warning module is used to compare the obtained first real-time interference assessment coefficient and the second real-time interference assessment coefficient with the first threshold and the second threshold obtained from the preset database to determine whether to take the first level intervention and warning measures; The secondary intervention and early warning module is used to derive an intraoperative imaging real-time interference assessment coefficient based on the first real-time interference assessment coefficient and the second real-time interference assessment coefficient when no primary intervention and early warning measures are taken, and compare the intraoperative imaging real-time interference assessment coefficient with a real-time interference assessment threshold obtained from a preset database to determine whether to take corresponding secondary intervention and early warning measures. The intraoperative imaging real-time interference assessment coefficient is used to comprehensively quantify the impact of intraoperative changes on intraoperative imaging.

Images