Magnetic resonance SAR (Synthetic Aperture Radar) value monitoring method of mobile magnetic resonance equipment

Abstract

The invention discloses a magnetic resonance SAR value monitoring method for mobile magnetic resonance equipment. The monitoring method comprises the following steps: acquiring magnetic resonance SAR values at a plurality of time points in real time; judging whether the SAR values are greater than or equal to a first threshold value, and if the SAR values are smaller than the first threshold value, executing the following steps: fitting a plurality of SAR values according to a time sequence to form an SAR value curve graph, calculating a slope based on the SAR values of adjacent time points on the SAR value curve graph to determine a change trend of the SAR values, and controlling the magnetic resonance equipment to enter a pre-adjustment stage based on the change trend, and the SAR value is reduced by adjusting equipment parameters. And if not, executing the following steps: controlling the magnetic resonance equipment to stop running. According to the scheme provided by the invention, the judgment condition is added, the original unique judgment condition is expanded to a plurality of judgment conditions, and the expanded judgment conditions can pre-judge the change rule of the SAR value, so that the SAR value is prevented from rising to a certain degree to cause harm to human tissues.

Description

Technical Field

[0001] The present invention relates to the technical field of magnetic resonance, and particularly to a method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device. Background Art

[0002] Magnetic resonance imaging (MRI) is a high-tech imaging method based on the performance characteristics of hydrogen nuclei in organisms in a magnetic field. The physical basis of magnetic resonance imaging is the resonance phenomenon related to the magnetism of substances and magnetic fields, that is, the resonance characteristics exhibited by the interaction between radiofrequency waves and a nuclear system with both angular momentum and magnetic moment in an external magnetic field. In recent years, ultra-high-field magnetic resonance imaging devices have made rapid progress in magnetic resonance brain functional imaging, spectral imaging, white matter fiber bundle imaging, cardiac examinations, etc., due to their significant advantages such as better spatial and temporal resolutions and better signal-to-noise ratios.

[0003] When radiofrequency electromagnetic waves propagate in the human body during magnetic resonance imaging, the superposition of incident electromagnetic waves and transmitted electromagnetic waves will produce a standing wave effect, resulting in excessive absorption of radiofrequency energy in a local part of the human body, leading to a significant increase in the accumulation of the energy of radiofrequency pulses under high magnetic field strength in the human body, causing the tissue temperature to rise and generating a local heating or heat accumulation effect at the local part. The above phenomenon can be reflected by the specific absorption ratio (SAR). Therefore, how to monitor SAR is a crucial issue.

[0004] The patent document with the application number CN201610378133.1 records a method for detecting the SAR value, which specifically includes: in the pre-scanning stage, calculating the loaded loss parameter D through the forward radiofrequency power and backward radiofrequency power of the radiofrequency coil, and determining the ratio r of the radiofrequency absorption power of the body part to the forward radiofrequency power according to the loaded loss parameter D and the prior no-load loss parameter D0. Then, during the imaging process, only by obtaining the forward radiofrequency power can the radiofrequency absorption power of the body part be determined, which can effectively avoid the influence of the coupling between radiofrequency coils on the quality factor of the radiofrequency coil when the load is large, and the obtained SAR value is more accurate.

[0005] However, in this application document, only how to detect the SAR value is disclosed, and the problem of how to use the detected SAR value for the adjustment and control of the magnetic resonance device is not solved. Summary of the Invention

[0006] The present invention provides a method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device to solve the above problems existing in the prior art.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device, comprising:

[0009] S100, obtaining the magnetic resonance SAR values at multiple time points in real time;

[0010] S200, determining whether the SAR value is greater than or equal to a first threshold. If it is less than the first threshold, step S300 is executed; if it is greater than or equal to the first threshold, step S400 is executed;

[0011] S300, fitting the multiple SAR values in chronological order to form a SAR value curve graph, calculating the slope based on the SAR values at adjacent time points on the SAR value curve graph to determine the change trend of the SAR value, and controlling the magnetic resonance device to enter a pre-adjustment stage based on the change trend, and reducing the SAR value by adjusting the device parameters;

[0012] S400, controlling the magnetic resonance device to stop running.

[0013] Wherein, in S300, controlling the magnetic resonance device to enter a pre-adjustment stage based on the change trend includes:

[0014] Adjusting the main magnetic field strength and magnetic field distribution, and adjusting the distance between the radio frequency coil and the human body part. By reducing the main magnetic field strength, and adjusting the magnetic field distribution to reduce the intensity of the radio frequency field at the position with a high SAR value, and by increasing the distance between the radio frequency coil and the human body part to reduce the SAR value.

[0015] Wherein, S300 includes:

[0016] S301, obtaining the slope between the SAR values at two consecutive time points based on the SAR value curve graph. If both of the two consecutive slopes are greater than a set first slope threshold, adjusting the main magnetic field strength and magnetic field distribution to a second level, where the second level is a preset parameter setting for reducing the SAR value;

[0017] S302, if one of the two consecutive slopes is greater than the set first slope threshold, setting a fixed monitoring time period. During this monitoring time period, if any slope is greater than the set first slope threshold, adjusting the distance between the radio frequency coil and the human body part.

[0018] Wherein, S300 further includes:

[0019] S303, if the obtained slope is negative and the SAR value is lower than a preset safety threshold, dynamically adjusting the main magnetic field strength and magnetic field distribution to a first level according to the current human tissue characteristics, where the first level is a standard parameter setting optimized based on tissue characteristics;

[0020] S304. If the obtained slope is negative, adjust the distance between the RF coil and the human body part to the standard distance value, where the standard distance value is a preset safe distance.

[0021] Among them, S100 includes:

[0022] S101. Perform grid division on human tissues and record the position data of each grid.

[0023] S102. Obtain the corresponding SAR value for each grid.

[0024] S103. Dynamically record the changes in the SAR values of each grid.

[0025] S104. Screen the change data of the SAR values, eliminate the data points that exceed the preset range and the difference from the adjacent data points exceeds the preset threshold, and the remaining data forms the current magnetic resonance SAR value.

[0026] Among them, S101 includes:

[0027] S1011. Construct a surface model according to the human tissue morphology and divide the grid by the adaptive grid refinement technology.

[0028] S1012. Divide the grid based on the surface model and record the coordinates.

[0029] Among them, S300 also includes:

[0030] S305. Monitor the change process of the increasing SAR value, set the stage where the SAR value rises from the second threshold to the third threshold as the rising stage, and set the stage where the SAR value rises from the third threshold to the first threshold as the mutation stage, where the second threshold < the third threshold < the first threshold.

[0031] S306. Record the time required for the rising stage as the first time period T1, and record the time required for the mutation stage as the second time period T2.

[0032] When , dynamically adjust the slope threshold for determining the SAR value change trend, where B is a set time condition value.

[0033] Among them, S306 includes:

[0034] S3061. Dynamically control the slope threshold by adjusting the set time condition value B.

[0035] S3062. Evaluate the descending rate of the SAR value by adjusting the set time condition value and the slope threshold.

[0036] S3063, screen out the optimal set time condition values and slope thresholds for different tissue sites based on the SAR value decline rate.

[0037] Among them, the value range of the set time condition value B is greater than 0 and less than 0.5 to ensure that the time difference between the rising stage and the mutation stage is sufficient to reflect the dynamic characteristics of the SAR value change.

[0038] Among them, S3062 includes:

[0039] Calculate the decline rate of the SAR value after adjusting the parameters. Based on the difference between the decline rate and the preset target rate, iteratively optimize the time condition value B and the slope threshold until the preset optimization condition is met.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] The present invention provides a method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device. The monitoring method includes: obtaining the magnetic resonance SAR values at multiple time points in real time; determining whether the SAR value is greater than or equal to the first threshold. If it is less than the first threshold, perform the following steps: fit the multiple SAR values in chronological order to form an SAR value curve graph, calculate the slope based on the SAR values at adjacent time points on the SAR value curve graph to determine the change trend of the SAR value, control the magnetic resonance device to enter the pre-adjustment stage based on the change trend, and reduce the SAR value by adjusting the device parameters. If it is greater than or equal to the first threshold, perform the following steps: control the magnetic resonance device to stop running. The solution provided by the present scheme adds judgment conditions, expands the original single judgment condition to multiple judgment conditions, and the expanded judgment conditions can pre-judge the change law of the SAR value, avoiding harm to human tissues caused by the SAR value rising to a certain extent.

[0042] Other features and advantages of the present invention will be described in the following description, and part of them will be obvious from the description, or understood by implementing the present invention.

[0043] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings are used to provide a further understanding of the present invention, and constitute a part of the description. They are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the drawings: [[ID=2,8]]

[0045] Figure 1 is a flowchart of a method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device in an embodiment of the present invention;

[0046] Figure 2A method flowchart for determining the changing trend of the SAR value in an embodiment of the present invention and controlling a magnetic resonance device to enter a pre-adjustment stage based on the changing trend;

[0047] Figure 3 A method flowchart for obtaining the value of the slope threshold of the changing trend of the SAR value in an embodiment of the present invention. Detailed implementation manners

[0048] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for explaining and illustrating the present invention, and are not used to limit the present invention.

[0049] An embodiment of the present invention provides a method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device. Please refer to Figure 1 , and the monitoring method includes:

[0050] S100, obtaining the magnetic resonance SAR values at multiple time points in real time;

[0051] S200, determining whether the SAR value is greater than or equal to a first threshold. If it is less than the first threshold, step S300 is executed; if it is greater than or equal to the first threshold, step S400 is executed;

[0052] S300, fitting the multiple SAR values in chronological order to form a SAR value curve graph, calculating the slope based on the SAR values at adjacent time points on the SAR value curve graph to determine the changing trend of the SAR value, and controlling the magnetic resonance device to enter a pre-adjustment stage based on the changing trend, and reducing the SAR value by adjusting the device parameters;

[0053] S400, controlling the magnetic resonance device to stop running.

[0054] The working principle of the above technical solution is as follows: Obtain the magnetic resonance SAR values at multiple time points in real time. In the monitoring process, it is first necessary to obtain the SAR values at multiple time points from the magnetic resonance device in real time, and this operation is the basis of the entire monitoring method. The system determines the acquisition method of the SAR values according to the pre-configured data acquisition template. The data acquisition template includes the distribution of acquisition time points and data format requirements to ensure that the acquired SAR values can fully reflect the operating status of the device. The acquisition device continuously monitors the SAR values through built-in sensors, and filters the raw data to remove interference signals. Subsequently, the system stores the processed SAR values in the temporary database in chronological order to form a continuous SAR value sequence. During the storage process, the system also marks the data for quick retrieval in subsequent steps. To improve the reliability of the data, the system obtains environmental parameters from the auxiliary monitoring module, such as the temperature and electromagnetic interference level around the device, and associates these parameters with the SAR values. The associated data is integrated into multiple groups of characterization data, and each group of characterization data includes the SAR value and the corresponding environmental parameters. The grouping rule of the characterization data is to separate the continuous data into independent units at a preset time interval, and this process ensures the traceability of the data.

[0055] Judge whether the SAR value is greater than or equal to the first threshold. After obtaining the SAR value sequence, the system needs to judge whether the SAR value reaches or exceeds the preset first threshold, and this judgment determines the subsequent operation direction. The system first retrieves the first threshold from the pre-configured threshold library, which is pre-constructed based on the device type and usage scenario and contains the safety limits under different operating modes. The SAR values collected in real time are compared with the first threshold one by one, and the comparison process is automatically completed by the system. If the SAR value is less than the first threshold, the system will start the pre-adjustment process to control the change of the SAR value by adjusting the device parameters. If the SAR value is greater than or equal to the first threshold, the system will immediately trigger the instruction to stop running. During the judgment process, the system also records the result of each comparison to form a judgment log for retrospective analysis when necessary. The execution of the judgment logic depends on the pre-set conditional branches to ensure that each situation can be accurately identified and processed.

[0056] If the SAR value is less than the first threshold, the pre-adjustment phase is executed: When the SAR value has not reached the first threshold, the system will enter the pre-adjustment phase, and adjust the device parameters by analyzing the changing trend of the SAR value to reduce the SAR value. First, the system fits the SAR values at multiple time points into a continuous SAR value curve in chronological order. The fitting process uses mathematical interpolation methods to ensure the smoothness and representativeness of the curve. Based on the SAR value curve, the system calculates the slope between adjacent time points, and the magnitude and direction of the slope reflect the changing trend of the SAR value. Subsequently, the system retrieves the corresponding parameter adjustment plan from the pre-adjustment strategy library according to the slope data. The pre-adjustment strategy library is constructed in advance by analyzing historical operation data and expert experience, and contains adjustment methods under different changing trends. After selecting the adjustment plan, the system automatically modifies the operation parameters of the magnetic resonance device, such as the intensity of the radio frequency pulse or the frequency of the scanning sequence. After the adjustment is completed, the system will continue to monitor the SAR value and fine-tune the adjustment plan according to the real-time feedback data. This loop adjustment process ensures that the SAR value is always within a controllable range. The construction of the pre-adjustment strategy library depends on the analysis of the operation data of the same type of device. First, the system groups the stored historical SAR value data according to the device model and usage environment, and then conducts trend analysis on each group of data to determine the parameter adjustment rules under different operating conditions.

[0057] If the SAR value is greater than or equal to the first threshold, control the magnetic resonance device to stop running: When the SAR value reaches or exceeds the first threshold, the system will immediately control the magnetic resonance device to stop running to ensure safety. First, the system sends a stop signal to the device, instructing all ongoing scanning operations to pause. After the stop signal is sent, the system activates the protection mechanism, such as disconnecting the power supply of the radio frequency source or pausing the generation of the magnetic field, to prevent the SAR value from continuing to rise. While the device is stopped, the system records the event details, including the time point when the stop was triggered and the SAR value data at that time. These records are stored in the fault database and notified to the operator through the alarm module. The alarm information will be presented visually to facilitate the operator to quickly understand the situation. After stopping the operation, the system will generate a reset guide, prompting the operator to check the device status and complete the necessary reset operations. During the reset process, the system will also verify whether the SAR value has returned to a safe level to ensure that the device can be restarted safely.

[0058] The beneficial effects of the above technical solutions are as follows: By obtaining the SAR values at multiple time points in real time and combining curve fitting and slope calculation, this method can accurately judge the changing trend of the SAR value before it reaches the first threshold, and enter the pre-adjustment phase in advance to reduce the SAR value when necessary. Compared with the traditional single-threshold judgment, this method adds a judgment condition of trend analysis, effectively avoiding the harm caused by the SAR value rising to a dangerous level to human tissues, and improving the safety of using mobile magnetic resonance devices.

[0059] In another embodiment of S300, controlling the magnetic resonance device to enter the pre-adjustment stage based on the change trend includes:

[0060] Adjust the main magnetic field strength and magnetic field distribution, and adjust the distance between the radio frequency coil and the human body part. By reducing the main magnetic field strength, and adjusting the magnetic field distribution to reduce the strength of the radio frequency field at the position with a high SAR value, and by increasing the distance between the radio frequency coil and the human body part to reduce the SAR value.

[0061] The working principle of the above technical solution is as follows: Before controlling the magnetic resonance device to enter the pre-adjustment stage based on the change trend, the system will adjust the operating parameters of the device according to the real-time monitoring data to ensure that the scanning process can adapt to the dynamically changing requirements. The specific steps of controlling the magnetic resonance device to enter the pre-adjustment stage based on the change trend are as follows. During the MRI scanning process, the system continuously collects real-time data, which includes the monitoring information of patient movement, the change of physiological parameters, and the estimated results of local SAR values. These information are obtained through built-in sensors and analysis algorithms. The system performs trend analysis on these real-time data, and judges whether it is necessary to adjust the device parameters by tracking the change patterns of the data. For example, when it is detected that the patient's position has shifted or the local SAR value shows an upward trend, the system will identify the necessity of adjustment. Once the analysis result indicates that the current parameters may not meet the scanning requirements, the system will enter the pre-adjustment stage. In this stage, the system calculates the adjustment schemes for magnetic field shimming and radio frequency transmission parameters using the current monitoring data. Specifically, the system will determine a new shimming current configuration according to the patient's current body position and the characteristics of the scanning area to optimize the uniformity of the main magnetic field, that is, the B0 field. This process involves adjusting the magnetic field distribution to reduce local non-uniformity. Then, the system will adjust the radio frequency transmission parameters, such as reshaping the distribution of the B1 field by changing the amplitude and phase of the radio frequency pulse, so as to reduce the strength of the radio frequency field in the area with a high SAR value, while ensuring that the signal strength is sufficient to support clear image generation. The calculation of these adjustment schemes depends on pre-configured mathematical models, which can derive suitable adjustment values based on real-time input data. After the calculation is completed, the system applies the new shimming current and radio frequency transmission parameters to the magnetic resonance device, and this application process is realized by controlling hardware modules, such as adjusting the settings of current drivers and radio frequency amplifiers. Subsequently, the scanning process continues to run, and the system will maintain the stability of the operation using the updated parameters.

[0062] When collecting real-time data, the system utilizes a variety of monitoring means. For example, it captures the patient's minute displacements through optical sensors or indirectly estimates the changing trend of the SAR value through temperature probes. These data are integrated into a dynamic data stream for subsequent analysis. When conducting trend analysis, the system adopts the method of time series analysis to continuously track the short-term and long-term changes of the data and compare them with preset thresholds to determine whether to trigger the entry into the pre-adjustment phase. In the pre-adjustment phase, the system not only calculates the adjustment values of the shim current and radio frequency parameters but also takes into account the characteristics of the patient's body shape and the scanned part. For example, different magnetic field distribution optimization strategies may be required for head scans and abdominal scans. To achieve the adjustment of the radio frequency field, the system dynamically selects different combinations of radio frequency coil elements and indirectly affects the interaction between the radio frequency field and the human body part by changing the output characteristics of each channel in a multi-channel transmission system. This way can achieve the purpose of reducing the SAR value without physically moving the coil. During the calculation of the adjustment value, the system also refers to the hardware limitations of the device to ensure that the new parameter configuration is within the feasible range, such as avoiding the current exceeding the maximum capacity of the driver or the radio frequency pulse exceeding the safety specifications. When applying the adjustment, the system will first perform a quick verification scan to confirm that the new parameter settings can take effect in actual operation. This verification process is completed by collecting a small amount of test data and analyzing its quality. Once the verification is passed, the system will seamlessly switch to the new parameter configuration and continue to execute the complete scan task.

[0063] The SAR value refers to the specific absorption rate, which is an index to measure the rate of radio frequency energy absorption by human tissues and needs to be strictly controlled in magnetic resonance imaging to ensure safety. Shim refers to the process of making the main magnetic field more uniform by adjusting the current, and this operation can reduce the distortion phenomenon in the image.

[0064] The beneficial effects of the above technical solution are as follows: In the pre-adjustment phase, by specifically adjusting the main magnetic field strength, magnetic field distribution, and the distance between the radio frequency coil and the human body part, it is possible to optimize and intervene in response to the specific reasons for the increase in the SAR value. Reducing the main magnetic field strength and adjusting the magnetic field distribution reduce the intensity of the radio frequency field in the high-SAR value area, and increasing the distance between the radio frequency coil and the human body part further reduces the SAR value. This multi-parameter collaborative adjustment strategy significantly improves the efficiency and pertinence of reducing the SAR value.

[0065] In another embodiment, please refer to Figure 2 , S300 includes:

[0066] S301, obtaining the slope between the SAR values at two consecutive time points based on the SAR value curve graph. If both of the two consecutive slopes are greater than the set first slope threshold, adjust the main magnetic field strength and magnetic field distribution to the second level, where the second level is the preset parameter setting for reducing the SAR value;

[0067] In S302, if one of two consecutive slopes is greater than the set first slope threshold, set a fixed monitoring time period. During this monitoring time period, if any slope is greater than the set first slope threshold, adjust the distance between the radio frequency coil and the human body part.

[0068] The working principle of the above technical solution is as follows: By monitoring and analyzing the SAR value (Specific Absorption Rate, an index to measure the absorption of radio frequency energy by human tissues) in real time, key parameters in the magnetic resonance imaging device are dynamically adjusted to ensure operation safety and scanning efficiency. The whole process relies on the acquisition and analysis of SAR value data and parameter adjustment based on the analysis results, forming a complete closed-loop control scheme.

[0069] The SAR value data is obtained by communicating with the SAR monitoring module inside the magnetic resonance imaging device. The system first extracts the real-time SAR value from the monitoring module. These data are recorded in the form of a time series, reflecting the absorption of radio frequency energy by human tissues during the scanning process. Then, the system constructs a curve graph of the SAR value changing with time based on these data for subsequent trend analysis and calculation.

[0070] In the data processing stage, the system groups and samples the SAR value curve at a preset time sampling interval, and calculates the slope of the SAR value between every two consecutive time points. The slope, as an index of the SAR value change rate, can reflect its rising or falling trend. To ensure the accuracy of the analysis, the sampling interval can be flexibly configured according to the device operating state or environmental requirements. Usually, it is set to a shorter time range to capture rapid changes, or a longer time range to smooth out noise interference. The number of sampling groups is at least two to facilitate the comparison of consecutive slopes.

[0071] Based on the calculated slopes, the system constructs an analysis data set that contains the slope values of consecutive time intervals. The analysis data set is used to judge the change trend of the SAR value and trigger the corresponding adjustment mechanism. Specifically, the system makes a conditional judgment on the slope values and takes different operation steps according to different situations.

[0072] If the analysis data set shows that the slopes of two consecutive time intervals are both greater than the preset first slope threshold, the system will adjust the main magnetic field strength and magnetic field distribution. The specific operation is to control the superconducting magnet and gradient coil in the magnetic resonance device to switch the main magnetic field strength and magnetic field distribution to the preset second-level parameter settings. This parameter combination is pre-designed to effectively reduce the energy requirement of the radio frequency pulse and optimize the uniformity of the magnetic field distribution at the same time.

[0073] If the analysis of the dataset shows that only one of the slopes of two consecutive time intervals is greater than the first slope threshold, the system will set a fixed monitoring time period. During this period, the system continuously samples the SAR value curve and calculates the slope. If any slope is found to exceed the first slope threshold, the system will adjust the distance between the RF coil and the human body part. Specifically, it controls the mechanical positioning device of the RF coil or the moving mechanism of the patient bed to increase the physical distance between the two, thereby reducing the deposition of the RF field in human tissues.

[0074] To enhance the adaptability of the system, additional environmental parameters can be added when constructing the analysis dataset, such as temperature data during device operation or data on changes in the patient's body position. These parameters can provide more context information for slope analysis and further optimize the accuracy of adjustment decisions. In addition, after each parameter adjustment, the system will continue to collect new SAR value data and repeat the above sampling, analysis, and adjustment processes to form a dynamic feedback mechanism.

[0075] Among them, the SAR value (Specific Absorption Rate) is an index to measure the rate at which human tissues absorb RF energy and is usually related to the intensity of RF pulses in magnetic resonance imaging. The main magnetic field refers to the static magnetic field generated by a superconducting magnet in a magnetic resonance device, which is used to align the hydrogen nuclei in the human body. The RF coil is a component that emits and receives RF signals and directly affects the distribution of SAR values. The gradient coil is used to generate a gradient magnetic field for spatial positioning.

[0076] The beneficial effects of the above technical solution are as follows: By analyzing the slopes of two consecutive time points in the SAR value curve graph and taking different adjustment measures according to the comparison result between the slope and the first slope threshold, this method realizes the refined monitoring of the SAR value change trend. When the consecutive slopes both exceed the standard, the main magnetic field parameters are adjusted. When only one slope exceeds the standard, dynamic monitoring and adjustment of the RF coil distance are performed. This hierarchical response mechanism improves the sensitivity of the system to SAR value changes and the accuracy of intervention measures.

[0077] In another embodiment, S300 further includes:

[0078] S303, if the obtained slope is negative and the SAR value is lower than the preset safety threshold, then dynamically adjust the main magnetic field strength and magnetic field distribution to the first level according to the current human tissue characteristics, where the first level is the standard parameter setting optimized based on tissue characteristics;

[0079] S304, if the obtained slope is negative, then adjust the distance between the RF coil and the human body part to the standard distance value, where the standard distance value is the preset safe distance.

[0080] The working principle of the above technical solution is as follows: First, real-time SAR value data is obtained through a SAR monitoring system integrated with an MRI device. The SAR monitoring system calculates the current SAR value by using the power and duration of the radiofrequency pulse and combining the characteristics of human tissues. To analyze the change trend of the SAR value, these data need to be systematically processed. The processing process includes grouping and sampling the SAR value data at a preset time sampling interval. The time sampling interval can be flexibly configured according to the imaging requirements, usually ranging from as short as 1 minute to as long as 2 hours. The number of sampled groups is at least two or more to ensure that the change trend can be captured. Next, the change slope of the SAR value over time is calculated for each group of data. The slope calculation can be completed through statistical methods, such as using linear regression to determine the change direction of the SAR value. A positive slope means that the SAR value increases over time, while a negative slope indicates that the SAR value decreases over time. After calculating the slope, an analysis data set is constructed based on the slope of each group of data and the current SAR value. To make the analysis more comprehensive, other relevant parameters can be added to the analysis data set, such as the type of human tissue, the characteristics of the imaging sequence, and the parameter data representing the current time. These additional parameters help to more accurately reflect the change context of the SAR value. In addition, to facilitate subsequent processing, the data can be resampled to optimize the accuracy of the analysis.

[0081] Subsequently, according to the analysis results, the corresponding parameter set is retrieved from a pre-configured MRI device parameter library. The MRI device parameter library is previously constructed by professionals based on the analysis of a large amount of imaging data and human tissue characteristics. The parameter library contains multiple parameter sets, and each parameter set corresponds to a specific SAR value change trend and tissue characteristics. For example, if the analysis data set shows that the slope is negative and the SAR value is lower than the preset safety threshold, the parameter set that matches this condition is retrieved from the parameter library. When retrieving the parameter set, the characteristics of the imaging site or the patient's physiological state can be further considered to ensure that the selected parameter set is more in line with the actual requirements. The design of the parameter library ensures that each analysis data set can find the associated parameter set, thus providing accurate guidance for subsequent configuration. To improve the flexibility of retrieval, the parameter library can also be updated regularly to incorporate new imaging scenarios and tissue characteristic data.

[0082] Finally, according to the parameter set retrieved from the parameter library, the configuration of the MRI device is adjusted. According to the instructions of the parameter set, first, the main magnetic field strength and magnetic field distribution are adjusted. If the analysis result shows that the slope is negative and the SAR value is lower than the preset safety threshold, then according to the current human tissue characteristics, the main magnetic field strength and magnetic field distribution are adjusted to the standard parameter settings optimized based on tissue characteristics. This adjustment is achieved by controlling the current and distribution pattern of the magnetic field generation unit. Secondly, the distance between the radiofrequency coil and the human body part is adjusted. If the slope is negative, the distance is set to the preset safe distance value. During the adjustment process, the radiofrequency coil can be accurately moved through the mechanical positioning system to ensure that the spacing between it and the imaging part meets the standard requirements. In addition, the characteristics of the radiofrequency pulse can also be adjusted according to the parameter set, such as changing the amplitude and duration of the pulse, to further optimize the distribution of the SAR value. The parameters of the gradient magnetic field also need to be adjusted, such as modifying the working mode of the gradient coil to adapt to the new configuration requirements. Through these steps, the parameters of the MRI device are dynamically adjusted to adapt to the change trend of the SAR value.

[0083] The beneficial effects of the above technical solution are as follows: In the case where the SAR value decreases and the slope is negative, this method dynamically optimizes the main magnetic field strength and magnetic field distribution to the first level according to the human tissue characteristics, and at the same time adjusts the distance of the radiofrequency coil to the standard value. This strategy not only ensures that the SAR value remains within the safe range, but also maximizes the magnetic resonance imaging quality under the premise of safety, while maintaining the stable operation of the device, thus enhancing the practicality of the system.

[0084] In another embodiment, S100 includes:

[0085] S101, divide the human tissue into grids and record the position data of each grid;

[0086] S102, obtain the corresponding SAR value for each grid;

[0087] S103, dynamically record the change of the SAR value of each grid;

[0088] S104, screen the change data of the SAR value, remove the data points that exceed the preset range and the difference from the adjacent data points exceeds the preset threshold, and the remaining data forms the current magnetic resonance SAR value.

[0089] The working principle of the above technical solution is as follows: In an MRI system, human tissue is precisely divided into uniform cubic grid cells by establishing a three-dimensional spatial coordinate system. Each grid cell has unique spatial coordinate information. The system uses an electromagnetic field sensor array to collect real-time electromagnetic field intensity data at each grid cell location and converts the collected raw data into standardized SAR values. The system establishes a real-time data acquisition channel to continuously monitor the SAR values of each grid cell, forming a time series data stream. The system uses an adaptive filtering algorithm to analyze the collected SAR value sequence. If a grid cell's SAR value suddenly changes beyond a safety threshold, the system marks the data point as an outlier. The system uses spatial correlation analysis to compare the SAR value trend of the outlier data point with that of the surrounding grid cells. If a data point is found to be significantly different from its surroundings, the system removes it from the data set. The system then performs spatial interpolation on the filtered data to reconstruct a complete SAR value distribution map, forming the final human tissue electromagnetic field distribution data.

[0090] The beneficial effects of this technical solution are as follows: by gridding human tissue and dynamically recording the SAR value changes at each grid, this method significantly improves the spatial resolution and data accuracy of SAR measurements. Furthermore, by filtering out abnormal data, the reliability of SAR data is ensured. This combination of gridding and data optimization effectively reduces noise interference and improves the accuracy of SAR monitoring.

[0091] In another embodiment, S101 includes:

[0092] S1011, constructing a surface model based on human tissue morphology and dividing the mesh using adaptive mesh refinement technology;

[0093] S1012, dividing the mesh based on the surface model and recording the coordinates.

[0094] Specifically, it includes: constructing a surface model according to the morphology of human tissue, and refining the surface model by inserting new nodes;

[0095] Create multiple connection matrices to configure stiffness matrices and load vectors;

[0096] According to the mapping relationship between the surface model and the human tissue morphology, the mapped coordinates are input into the boundary conditions, the stiffness matrix and the load vector are calculated, and the solution of the equation is obtained. The solution of the equation is the result of meshing.

[0097] It should be noted that the above equation is as follows:

[0098]

[0099] Among them, u(x,y) represents the function of the spline surface, x and y represent the x and y axis coordinates respectively, and g B represents the input boundary condition, and N B (x,y) represents the basis function supported on the boundary, and N A (x,y) represents the basis function not supported on the boundary, and n eq <n nq ,n eq the first integer, n nq the second integer, d represents the vector between the stiffness matrix and the load vector; g B represents the coefficient of N B (x,y). A represents the number of the global basis function, and B represents the number of the local basis function.

[0100] The working principle of the above technical solution is as follows: Before constructing the surface model according to the human tissue morphology, the morphological features of the tissue are extracted based on the medical image data. The specific steps of morphological feature extraction are as follows: perform feature recognition on the medical image data according to the pre-configured feature extraction algorithm to obtain multiple sets of morphological feature data; arrange the multiple sets of morphological feature data in order to form a feature data set, and retrieve the corresponding surface construction parameter set from the pre-configured morphology library according to the feature data set; set the corresponding parameters in the surface model construction process according to each parameter value in the surface construction parameter set; among them, each set of morphological feature data includes: parameters representing the surface curvature of the tissue, parameters representing the boundary features of the tissue, parameters representing the internal structure of the tissue, parameters representing the tissue density, etc.; the grouping rule of the morphological feature data is to divide the data at a preset spatial interval to form individual groups.

[0101] Among them, the construction of the morphology library is to analyze the image data of the whole life cycle of human tissues in the same anatomical position of the same type; first, group the stored image data of the whole life cycle of human tissues according to the tissue identification parameter set and the position parameter set of the set anatomical position; among them, the parameters in the identification parameter set include: parameters representing data such as tissue size, shape, texture, etc.; the parameters in the position parameter set include: parameters representing spatial coordinates, parameters representing the relationship between adjacent tissues, etc.; perform spatial association on the image data of the whole life cycle of each tissue in the same group, and correspond the image data of each spatial region to the standard feature template; determine the average value of the difference between the morphological features of the image data and the standard morphological features under the same anatomical position and the same tissue features, and query the pre-configured corresponding table of morphological differences and construction parameters according to the difference to determine the corresponding parameter values; in this way, a construction item in the morphology library is obtained; the spatial association is carried out based on the spatial position, for example, using the pre-configured first spatial interval (which can be configured as any value between 0.1 mm and 1 cm) for spatial association.

[0102] After completing the morphological feature extraction, a surface model is constructed based on the extracted morphological features, and the mesh is divided by an adaptive mesh refinement technique. The specific steps for constructing the surface model are as follows: The morphological feature data is surface-fitted according to a pre-configured surface generation algorithm to obtain an initial surface model; the initial surface model is corresponded to the pre-configured mesh division rules to determine the initial parameters of mesh division; the surface model is preliminarily meshed according to the initial parameters to obtain an initial mesh; the quality of the initial mesh is evaluated to determine the area that needs to be refined; the area that needs to be refined is mesh-refined according to the pre-configured refinement rules to obtain the refined mesh; among them, the specific operations of mesh refinement include: locally encrypting the area that needs to be refined to increase the mesh density; smoothing the encrypted mesh to ensure the mesh quality; performing topological optimization on the smoothed mesh to ensure the continuity of the mesh.

[0103] During the mesh division process, the coordinate information of each mesh node is also recorded. The specific steps for coordinate recording are as follows: The mesh nodes are coordinate-transformed according to a pre-configured coordinate system to obtain standard coordinates; the standard coordinates are associated with the topological relationship of the mesh nodes to form a coordinate data set; the corresponding coordinate correction parameters are retrieved from a pre-configured coordinate library according to the coordinate data set; the coordinate data set is corrected according to the coordinate correction parameters to obtain the final coordinate data; among them, the coordinate library is constructed by analyzing the coordinate data of the same organizational structure of the same type to ensure the accuracy and consistency of the coordinate data.

[0104] The beneficial effects of the above technical solution are: An adaptive mesh refinement technique is used to construct a human tissue surface model and divide the mesh. This method can more accurately reflect the complex morphology and anatomical features of human tissues. This high-precision mesh division method improves the adaptability and accuracy of SAR value calculation, providing a more reliable data basis for subsequent monitoring and adjustment.

[0105] In another embodiment, S300 further includes:

[0106] S305, monitoring the change process of the increasing SAR value, setting the stage where the SAR value rises from the second threshold to the third threshold as the rising stage, and setting the stage where the SAR value rises from the third threshold to the first threshold as the mutation stage, where the second threshold < the third threshold < the first threshold;

[0107] S306, recording the time required for the rising stage as the first time period T1, and recording the time required for the mutation stage as the second time period T2;

[0108] When , the slope threshold for determining the SAR value change trend is dynamically adjusted, where B is a set time condition value.

[0109] The working principle of the above technical solution is as follows: Monitor the changing process of the increase in the SAR value. Set the stage where the SAR value rises from the second threshold to the third threshold as the rising stage, and set the stage where the SAR value rises from the third threshold to the first threshold as the mutation stage, where the second threshold < the third threshold < the first threshold; Record the time required for the rising stage as the first time period T1, and record the time required for the mutation stage as the second time period T2; When (T1 - T2) / (T1 + T2) ≥ B, dynamically adjust the slope threshold for determining the SAR value change trend, where B is the set time condition value.

[0110] Among them, determining the SAR value change trend is the basis for dynamic threshold adjustment. The specific determination steps are as follows:

[0111] Based on the historical data of the SAR value, construct a time series curve; The time series curve is a functional relationship of the SAR value changing with time;

[0112] Divide the time series curve into multiple consecutive time windows; The time window is a time period with a preset fixed length;

[0113] Calculate the average change rate of the SAR value within each time window; The average change rate is the ratio of the increment of the SAR value within the time window to the length of the time window;

[0114] Extract the time window with the largest average change rate, and use this time window as the reference interval for the SAR value change trend;

[0115] In addition, with the current time window as the center, determine a sliding interval that includes multiple time windows before and after; Map the SAR value data within the sliding interval to a two-dimensional coordinate system to determine each data point;

[0116] Extract the points whose distance from the center point of the time window is less than or equal to the preset distance threshold and construct a trend determination parameter set; According to the pre-configured trend determination library, determine the trend coefficient; According to the trend coefficient and the average change rate of each time window, determine the current SAR value change trend;

[0117] Among them, the trend coefficient in the trend determination library is corresponding and associated with the trend determination parameter set; And the parameters of the trend determination parameter set are the distance values from each extracted data point to the center point of the time window; And the more the number of parameters of the trend determination parameter set, the more accurate the determined trend coefficient, and the smaller the value of each parameter, the more accurate the determined trend coefficient.

[0118] Monitor the change process of the increase in SAR value. Set the stage where the SAR value rises from the second threshold to the third threshold as the rising stage, and set the stage where the SAR value rises from the third threshold to the first threshold as the mutation stage, where the second threshold < the third threshold < the first threshold; record the time required for the rising stage as the first time period T1, and record the time required for the mutation stage as the second time period T2; when (T1 - T2) / (T1 + T2) ≥ B, dynamically adjust the slope threshold for determining the change trend of the SAR value, where B is the set time condition value.

[0119] The beneficial effects of the above technical solution are as follows: By dividing the SAR value increase process into a rising stage and a mutation stage, and dynamically adjusting the slope threshold in combination with the analysis of time periods T1 and T2, this method can capture the change law of the SAR value more meticulously. When (T1 - T2) / (T1 + T2) ≥ B, the system can timely identify potential mutation trends and optimize the judgment criteria, thereby enhancing the early warning ability for the mutation risk of the SAR value and strengthening the safety guarantee of the device.

[0120] In another embodiment, S306 includes:

[0121] S3061, dynamically control the slope threshold by adjusting the set time condition value B;

[0122] S3062, evaluate the decreasing rate of the SAR value by adjusting the set time condition value and the slope threshold;

[0123] S3063, screen out the optimal set time condition value and slope threshold for different tissue parts based on the decreasing rate of the SAR value.

[0124] The working principle of the above technical solution is as follows: In the SAR value dynamic adjustment system, the system first obtains the SAR value sequence within the current time window, and this sequence contains SAR value data at multiple consecutive time points. The system forms a change rate sequence by calculating the change rate of the SAR value between adjacent time points in real time through the sliding time window method. The system dynamically adjusts the calculation range of the slope threshold according to the preset time condition value B, where the time condition value B determines the size of the time window participating in the slope calculation. When calculating the slope threshold, the system processes the SAR value changes in different time periods in a weighted average manner, and the weight coefficient is inversely proportional to the time distance.

[0125] When the system evaluates the SAR value decline rate, it combines the time condition value and the slope threshold as key parameters for combined analysis. The system establishes a multi-dimensional parameter space and searches for the optimal parameter combination in this space. The system uses an iterative optimization method. After each adjustment of the parameters, it recalculates the SAR value decline rate and records the evaluation results of the parameter combination. The system establishes an evaluation function in the parameter space, which comprehensively considers the stability and response speed of the SAR value decline. The system uses the gradient descent algorithm to find the parameter combination that optimizes the evaluation function in the parameter space.

[0126] When the system screens for the optimal parameters, it establishes independent parameter optimization models for different tissue parts. The system first classifies the tissue parts and establishes feature vectors according to tissue characteristics. The system establishes a parameter optimization space for each tissue category and searches for the optimal combination of time condition value and slope threshold in this space. The system uses an adaptive learning algorithm to dynamically adjust the parameter optimization strategy according to historical data. During the parameter optimization process, the system considers the physiological characteristics and environmental factors of the tissue parts and establishes a multi-dimensional evaluation system. The system uses cross-validation to ensure the generalization ability of the parameter combination. After the parameter optimization is completed, the system stores the optimal parameter combination in the parameter library for subsequent use. During the operation of the system, it monitors the parameter effects in real time and makes dynamic adjustments according to the monitoring results.

[0127] The beneficial effects of the above technical solution are as follows: By dynamically adjusting the time condition value B and the slope threshold, the SAR value decline rate is evaluated and the optimal parameter settings for different tissue parts are screened. This iterative optimization mechanism realizes the adaptive adjustment of the monitoring strategy, which not only improves the applicability of the system to different tissue characteristics but also further enhances the efficiency and flexibility of reducing the SAR value.

[0128] In another embodiment, the set value range of the time condition value B is greater than 0 and less than 0.5 to ensure that the time difference between the rising stage and the mutation stage is sufficient to reflect the dynamic characteristics of the SAR value change.

[0129] The working principle of the above technical solution is as follows: In the SAR value dynamic monitoring system, the system first establishes a constraint mechanism for the time window parameter B, which ensures that the value of the time window parameter B is within the effective range. The system establishes a parameter constraint function to limit the value of the time window parameter B within a specific interval, which is jointly determined by the lower limit value and the upper limit value preset by the system. The system introduces a non-linear mapping relationship in the parameter constraint function to map the original parameter space into the effective interval. The system converts the time window parameter B into a standardized parameter value through parameter normalization processing.

[0130] During the parameter constraint process, the system adopts a dynamic boundary adjustment strategy to adaptively adjust the parameter boundary according to the variation characteristics of the SAR value. The system evaluates the influence degree of different parameter values on the variation characteristics of the SAR value by establishing a parameter sensitivity analysis model. In the parameter sensitivity analysis, the system introduces multi-dimensional evaluation indicators, including time response characteristics, signal stability, etc. The system searches for the optimal parameter value by establishing a parameter optimization objective function under the premise of meeting the constraint conditions. During the parameter optimization process, the system adopts an iterative search algorithm to gradually approach the optimal solution. The system ensures that the optimized parameters meet the system requirements by establishing a parameter effectiveness verification mechanism. During the parameter verification process, the system introduces a multi-scenario test strategy to verify the applicability of the parameters under different conditions. The system dynamically adjusts the parameter value according to the system operation state by establishing a parameter adaptive adjustment mechanism. During the parameter adjustment process, the system considers the comprehensive influence of historical data and real-time data to ensure the rationality of parameter adjustment.

[0131] The smaller the conditional value B, the better, and preferably it can be a negative value, indicating that the T2 time period is infinitely long. In this way, the mutation stage is infinitely stretched, indicating that adjusting the parameters of the magnetic resonance is effective. Therefore, through this method, the set slope threshold can be ensured to be accurate.

[0132] The beneficial effects of the above technical solution are as follows: by limiting the time conditional value B within the range greater than 0 and less than 0.5, this method ensures the effectiveness of the time difference between the rising stage and the mutation stage, and can scientifically reflect the dynamic characteristics of the SAR value change.

[0133] In another embodiment, S3062 includes:

[0134] Calculate the descent rate of the SAR value after adjusting the parameters. Based on the difference between the descent rate and the preset target rate, iteratively optimize the time conditional value B and the slope threshold until the preset optimization conditions are met.

[0135] The working principle of the above technical solution is as follows: in the SAR value optimization system, the system first establishes a SAR value descent rate calculation model. This model constructs a time series analysis framework by collecting SAR value data at consecutive time points. The system introduces a sliding window mechanism in the time series analysis and calculates the instantaneous descent rate of the SAR value through the variation characteristics of the data points within the window. The system establishes a rate calculation function and uses the ratio of the difference between the SAR values at adjacent time points to the time interval as the quantization index of the descent rate. During the rate calculation process, the system adopts a weighted average strategy to assign different weight coefficients to the data at different time points to reflect the difference in data importance.

[0136] During the rate optimization process of the system, a target rate matching mechanism is established. This mechanism generates a rate deviation signal by comparing the difference between the actual descent rate and the preset target rate. The system converts the rate deviation signal into adjustment amounts for the time condition value B and the slope threshold by establishing a parameter adjustment function. During the parameter adjustment process, the system introduces an adaptive step size control strategy to dynamically adjust the amplitude of parameter changes according to the magnitude of the rate deviation. The system applies the adjusted parameter values to the SAR value calculation model by establishing a parameter update rule and recalculates the descent rate. During the parameter iteration process, the system adopts a convergence judgment mechanism to terminate the iteration process when the rate deviation is less than the preset threshold. The system ensures that the optimized parameters meet the system requirements by establishing a parameter validity verification mechanism. During the parameter verification process, the system introduces multi-dimensional evaluation indicators, including rate stability, parameter sensitivity, etc. The system dynamically adjusts the parameter values according to the system operating state by establishing a parameter adaptive adjustment mechanism. During the parameter adjustment process, the system considers the combined influence of historical data and real-time data to ensure the rationality of parameter adjustment.

[0137] The beneficial effects of the above technical solution are as follows: By calculating the descent rate of the SAR value after parameter adjustment and iteratively optimizing the time condition value B and the slope threshold based on the difference from the target rate, this method can continuously improve the monitoring strategy. This adaptive optimization process ensures that the SAR value quickly drops to a safe level after adjustment, significantly improving the response speed and security of the system.

[0138] 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.

Claims

1. A method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device, characterized in that, Including: S100, obtaining real-time magnetic resonance SAR values at multiple time points; S200, determining whether the SAR value is greater than or equal to a first threshold. If it is less than the first threshold, step S300 is executed. If it is greater than or equal to the first threshold, step S400 is executed; S300, fitting multiple SAR values in chronological order to form a SAR value curve graph, calculating the slope based on the SAR values at adjacent time points on the SAR value curve graph to determine the change trend of the SAR value, and controlling the magnetic resonance device to enter a pre-adjustment stage based on the change trend, and reducing the SAR value by adjusting device parameters; S400, controlling the magnetic resonance device to stop running.

2. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 1, characterized in that, In S300, controlling the magnetic resonance device to enter a pre-adjustment stage based on the change trend includes: Adjusting the main magnetic field intensity and magnetic field distribution, and adjusting the distance between the radio frequency coil and the human body part. By reducing the main magnetic field intensity, and adjusting the magnetic field distribution to reduce the intensity of the radio frequency field at the position with a high SAR value, and by increasing the distance between the radio frequency coil and the human body part to reduce the SAR value.

3. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 1, characterized in that, S300 includes: S301, obtaining the slope between the SAR values at two consecutive time points based on the SAR value curve graph. If both of the two consecutive slopes are greater than a set first slope threshold, adjusting the main magnetic field intensity and magnetic field distribution to a second level, where the second level is a preset parameter setting for reducing the SAR value; S302, if one of the two consecutive slopes is greater than the set first slope threshold, setting a fixed monitoring time period. During this monitoring time period, if any slope is greater than the set first slope threshold, adjusting the distance between the radio frequency coil and the human body part.

4. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 1, characterized in that, S300 further includes: S303, if the obtained slope is negative and the SAR value is lower than a preset safety threshold, dynamically adjusting the main magnetic field intensity and magnetic field distribution to a first level, where the first level is a standard parameter setting optimized based on tissue characteristics; S304, if the obtained slope is negative, adjusting the distance between the radio frequency coil and the human body part to a standard distance value, where the standard distance value is a preset safe distance.

5. The method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device according to claim 1, characterized in that, S100 includes: S101, dividing the human tissue into grids and recording the position data of each grid; S102, obtaining the corresponding SAR value for each grid; S103, dynamically recording the change of the SAR value of each grid; S104, screening the change data of the SAR value, removing the data points that exceed the preset range and the difference from the adjacent data points exceeds the preset threshold, and the remaining data forms the current magnetic resonance SAR value.

6. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 5, characterized in that, S101 includes: S1011, constructing a surface model according to the human tissue morphology and dividing the grids by an adaptive grid refinement technique; S1012, dividing the grids based on the surface model and recording the coordinates.

7. The method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device according to claim 1, characterized in that, S300 further includes: S305, monitoring the change process of the increasing SAR value, setting the stage where the SAR value rises from a second threshold to a third threshold as the rising stage, and setting the stage where the SAR value rises from the third threshold to the first threshold as the mutation stage; S306, recording the time required for the rising stage as a first time period T1, and recording the time required for the mutation stage as a second time period T2; When it is the case, dynamically adjust the slope threshold for determining the SAR value change trend, where B is the set time condition value.

8. The method for monitoring the magnetic resonance SAR value of a mobile magnetic resonance device according to claim 7, characterized in that, S306 includes: S3061, dynamically control the slope threshold by adjusting the set time condition value B; S3062, evaluate the decreasing rate of the SAR value by adjusting the set time condition value and the slope threshold; S3063, screen out the optimal set time condition value and slope threshold for different tissue parts based on the decreasing rate of the SAR value.

9. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 7, wherein, The value range of the set time condition value B is greater than 0 and less than 0.5 to ensure that the time difference between the rising stage and the mutation stage is sufficient to reflect the dynamic characteristics of the SAR value change.

10. The method for monitoring the magnetic resonance SAR value of the mobile magnetic resonance device according to claim 8, characterized in that, S3062 includes: Calculate the decreasing rate of the SAR value after adjusting the parameters, and iteratively optimize the time condition value B and the slope threshold based on the difference between the decreasing rate and the preset target rate until the preset optimization condition is met.

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