A magnetic resonance imaging method and system for an operating room

Abstract

The application relates to the technical field of intraoperative image navigation, in particular to a magnetic resonance imaging method and system for an operating room, which acquires a channel radio frequency signal amplitude of an intraoperative magnetic resonance receiving array signal, calculates a tissue region signal attenuation ratio, analyzes a local signal attenuation trend, and generates an intraoperative magnetic resonance signal attenuation feature. The application detects the signal amplitude, identifies an abnormal region, optimizes radio frequency signal uniformity, and reduces misjudgment of a low signal region. Gain correction values are dynamically adjusted, image resolution and signal stability are improved. Magnetic field gradient changes are analyzed, magnetic induction offset abnormal regions are screened, and the interference of surgical instruments on images is reduced. Magnetic field compensation values are calculated, pixel signal amplitudes are adjusted, magnetic induction distortion region signals are restored to be uniform, and spatial precision is improved. Image signal distribution is detected, signal uniformity is optimized, and image consistency is improved.

Description

Technical Field

[0001] This invention relates to the field of intraoperative image navigation technology, and more particularly to a magnetic resonance imaging method and system for use in the operating room. Background Technology

[0002] Intraoperative image navigation technology encompasses various techniques that provide real-time medical imaging support during surgery to assist surgeons in precise operations and ensure surgical safety and accuracy. The core of this technology involves image acquisition, data processing, surgical navigation, and interactive display, aiming to provide visualized information about intraoperative tissue structures through medical imaging technology. Common intraoperative image navigation technologies include ultrasound imaging, computed tomography (CT), and magnetic resonance imaging (MRI). Among these, MRI, due to its high soft tissue resolution and radiation-free characteristics, has become one of the most important technologies for intraoperative image navigation. To adapt to the operating room environment, intraoperative MRI systems typically employ low-field MRI equipment, combined with dedicated coil arrays, shielding devices, and rapid imaging techniques to reduce electromagnetic interference and improve image quality. Meanwhile, development trends in this technology include real-time transmission and processing of image data, image fusion for surgical path planning, and image-guided precision interventional therapy to enhance real-time visualization capabilities during surgery.

[0003] One type of magnetic resonance imaging (MRI) method for use in the operating room involves acquiring image data of the surgical area during surgery, processing and displaying it in real time to assist surgeons in accurately locating target tissues and adjusting surgical plans. This method primarily encompasses the application of low-field MRI equipment, optimized configuration of dedicated coil arrays, the use of electromagnetic shielding technology, and image reconstruction algorithms based on Fourier transform. Rapid scanning is performed using low-field MRI equipment, the signal-to-noise ratio is improved using dedicated coil arrays, and electromagnetic shielding technology reduces external interference in the operating room environment. Simultaneously, this method employs a high-speed data transmission protocol to achieve real-time transmission of image data, and uses an image reconstruction algorithm based on Fourier transform to process the acquired data to generate multi-modal fusion imaging results. Furthermore, this method incorporates augmented reality or virtual reality technology to provide interactive image display, allowing doctors to view intraoperative image data on a high-definition touchscreen, and utilizes artificial intelligence technology for lesion annotation and surgical path planning analysis.

[0004] Intraoperative MRI is affected by electromagnetic interference in the operating room environment, resulting in uneven signal attenuation and low-signal areas in the images. This leads to unclear tissue boundaries and affects accurate intraoperative identification. Traditional imaging relies on fixed gain adjustment strategies, which have limitations in compensating for signal attenuation areas and can easily cause uneven amplification of tissue signals, resulting in a decrease in overall image contrast. Magnetic field distortion affects the spatial accuracy of intraoperative imaging, especially when surgical instruments are close together. Sudden changes in the local magnetic field can interfere with pixel signals, causing image distortion and affecting surgical positioning. Traditional methods do not adaptively adjust to dynamic signal changes in intraoperative images, making images prone to signal distortion in the interference environment and reducing the temporal consistency of image data. The lag in image signal compensation strategies results in significant signal fluctuations in images during surgery, increasing the uncertainty of image information and affecting the surgeon's reliance on the images. Image signal equalization adjustment relies on fixed standards and fails to incorporate real-time signal distribution optimization, making it impossible for image data to remain consistent in non-uniform signal environments and reducing the reliability of intraoperative image data. Summary of the Invention

[0005] To address the technical problems existing in the prior art, embodiments of the present invention provide a magnetic resonance imaging method and system for use in an operating room. The technical solution is as follows:

[0006] A magnetic resonance imaging method for use in an operating room includes the following steps:

[0007] S1: Obtain the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculate the signal attenuation ratio of the tissue area, analyze the local signal attenuation trend, and generate intraoperative magnetic resonance signal attenuation characteristics.

[0008] S2: Based on the intraoperative magnetic resonance signal attenuation characteristics, obtain the signal intensity difference between adjacent tissues, calculate the channel signal contribution, optimize the gain correction value to adjust the radio frequency receiving coil signal gain, and generate intraoperative image gain adjustment parameters.

[0009] S3: Based on the intraoperative image gain adjustment parameters, calculate the magnitude of magnetic flux density change, analyze the distribution range of magnetic field abrupt change areas caused by surgical instrument interference, and generate intraoperative magnetic field distortion parameters.

[0010] S4: Based on the intraoperative magnetic field distortion parameters, extract the magnetic induction offset value of the image pixels, calculate the magnetic field compensation value, adjust the amplitude of the image pixel signals, and generate intraoperative image magnetic induction compensation data according to the image grayscale classification.

[0011] S5: Based on intraoperative image magnetic induction compensation data, obtain the distribution range of image signals, detect changes in grayscale contrast of tissue region images, compare the signal amplitude before and after compensation, adjust the signal in the region that deviates from the signal equalization benchmark, and generate the optimized results of intraoperative magnetic resonance imaging signals.

[0012] As a further aspect of the present invention, the intraoperative magnetic resonance signal attenuation characteristics include channel signal amplitude error distribution, tissue region signal attenuation ratio, and local signal attenuation trend; the intraoperative image gain adjustment parameters include channel signal contribution distribution, time series signal stability index, and gain correction value; the intraoperative magnetic field distortion parameters include magnetic field gradient change, magnetic flux density change amplitude, and magnetic field abrupt change region distribution range; the intraoperative image magnetic induction compensation data includes magnetic field change rate, image pixel magnetic induction offset value, and magnetic field compensation value; and the intraoperative magnetic resonance imaging signal optimization results include image signal distribution range, tissue region signal mean difference, and signal equalization adjustment benchmark.

[0013] As a further aspect of the present invention, the specific steps for obtaining the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculating the signal attenuation ratio of the tissue region, analyzing the local signal attenuation trend, and generating intraoperative magnetic resonance signal attenuation characteristics are as follows:

[0014] S101: Acquire intraoperative magnetic resonance receiving array signals, detect channel radio frequency signal amplitude, calculate amplitude deviation and normalize it, filter channel signals whose deviation exceeds the set amplitude deviation threshold range, and construct channel signal amplitude deviation dataset;

[0015] S102: Based on the channel signal amplitude deviation dataset, classify the channel signals according to the tissue region, calculate the attenuation ratio of the channel signal in each region, summarize the differences in attenuation ratios between tissue regions based on the regional mean, screen out abnormal signal regions whose attenuation ratios exceed the threshold of the regional mean, analyze the local signal attenuation changes, and establish a distribution set of signal attenuation ratios in tissue regions.

[0016] S103: Based on the signal attenuation ratio distribution set of the tissue region, analyze the attenuation trend of adjacent channel signals within the abnormal region, calculate the gradient change of local signal attenuation, summarize the signal attenuation fluctuation range of each tissue region according to the change rate of local signal attenuation, and generate intraoperative magnetic resonance signal attenuation characteristics.

[0017] As a further aspect of the present invention, for calculating the gradient change G of local signal attenuation Cm The formula used is:

[0018]

[0019] Among them, G Cm A represents the local gradient change of the channel signal within the current region. Cm A represents the amplitude of the magnetic resonance signal in the m-th channel. Cm:1 D represents the amplitude of the magnetic resonance signal in the (m+1)th adjacent channel. CM represents the physical distance between adjacent channels, M represents the number of channels within the abnormal region, and A represents the number of channels within the abnormal region. RM A represents the median of all channel signals within the region. RA C represents the mean of all channel signals within the region. S4 This represents a decimal number with stable computational properties.

[0020] As a further aspect of the present invention, the specific steps for obtaining the signal intensity difference between adjacent tissues based on the intraoperative magnetic resonance signal attenuation characteristics, calculating the channel signal contribution, optimizing the gain correction value to adjust the radio frequency receiving coil signal gain, and generating intraoperative image gain adjustment parameters are as follows:

[0021] S201: Based on the intraoperative magnetic resonance signal attenuation characteristics, calculate the amplitude difference of the channel signal in adjacent tissue regions, statistically analyze the signal intensity changes between each tissue, filter out regions where the amplitude difference exceeds the amplitude difference threshold, and obtain the signal intensity difference value between adjacent tissues.

[0022] S202: Based on the signal intensity difference between adjacent tissues, detect the stability of multi-channel signals in the time series, calculate the range of signal amplitude change at each time point, analyze the temporal fluctuation trend of channel signals, and compare the signal contribution at adjacent time points to obtain the channel signal contribution ratio.

[0023] S203: Based on the channel signal contribution ratio, adjust the RF receiving coil signal gain, compare the channel signal amplitude error with the regional signal change, calculate the adjustment range after gain correction, and optimize the gain parameters to obtain the intraoperative image gain adjustment parameters.

[0024] As a further aspect of the present invention, the adjustment magnitude G after the calculation gain correction is... adj The formula used is:

[0025]

[0026] Among them, G init η represents the initial gain value set by the factory, η represents the gain adjustment coefficient, and CR TG,t G represents the gain contribution ratio. j G represents the current gain value of channel j, N represents the total number of channels, and G represents the current gain value of channel j. OAV This represents the average global gain calculated after optimization.

[0027] As a further aspect of the present invention, based on the intraoperative image gain adjustment parameters, the specific steps for calculating the magnitude of magnetic flux density change, analyzing the distribution range of magnetic field abrupt change regions caused by surgical instrument interference, and generating intraoperative magnetic field distortion parameters are as follows:

[0028] S301: Based on the intraoperative image gain adjustment parameters, calculate the change in magnetic field gradient in each region, extract the magnetic field strength in each region with reference to spatial coordinate information, analyze the fluctuation range of magnetic field strength in each region, and obtain the magnitude of magnetic field strength change.

[0029] S302: Based on the magnitude of the magnetic field strength change, filter out regions where the magnetic field strength change exceeds a preset magnetic field strength change threshold, analyze the trend of magnetic flux density change, compare the rate of magnetic flux change in each region, calculate the magnetic flux change gradient of the magnetic field region where the rate of change exceeds a preset rate of change threshold, and obtain the abnormal magnetic field strength interval.

[0030] S303: Based on the abnormal magnetic field intensity range, analyze the magnetic field mutation points caused by surgical instrument interference, detect the distribution range of the abnormal magnetic field intensity range, calculate the spatial coverage of the abnormal range, and obtain the intraoperative magnetic field distortion parameters.

[0031] As a further aspect of the present invention, based on the intraoperative magnetic field distortion parameters, the specific steps for extracting the magnetic induction offset value of image pixels, calculating the magnetic field compensation value, adjusting the amplitude of image pixel signals, and generating intraoperative image magnetic induction compensation data according to image grayscale grading are as follows:

[0032] S401: Based on the intraoperative magnetic field distortion parameters, call the magnetic flux change rate of each region, calculate the magnetic induction offset value of the image pixels, mark the region where the offset value exceeds the preset magnetic induction offset value threshold as the magnetic field change region, and obtain magnetic induction offset abnormal data.

[0033] S402: Based on the magnetic induction offset anomaly data, obtain the distribution range of the magnetic field change region, calculate the magnetic field compensation value of each magnetic field change region, adjust the amplitude of the image pixel signal, correct the compensation amplitude of the pixel signal according to the magnetic field gradient direction, and obtain the magnetic field compensation amplitude.

[0034] S403: Based on the magnetic field compensation amplitude, the pixels are classified according to the image grayscale value, the magnetic induction change trend of each grayscale level is analyzed, the image signal balance is statistically analyzed, and intraoperative image magnetic induction compensation data is obtained.

[0035] As a further aspect of the present invention, the specific steps for obtaining the image signal distribution range based on intraoperative image magnetic induction compensation data, detecting changes in grayscale contrast of tissue region images, comparing signal amplitudes before and after compensation, adjusting regional signals that deviate from the signal equalization benchmark, and generating optimized intraoperative magnetic resonance imaging signal results are as follows:

[0036] S501: Based on the intraoperative image magnetic induction compensation data, obtain the distribution range of intraoperative image signals, detect the contrast change of image grayscale in each tissue area, compare the image signal amplitude before and after compensation, and obtain image signal distribution parameters.

[0037] S502: Based on the image signal distribution parameters, calculate the signal mean difference of each tissue region, call the intraoperative image gain adjustment parameters to set the signal equalization adjustment benchmark, compare the intraoperative image signal distribution range, filter the regions that deviate from the signal equalization adjustment benchmark, calculate the amplitude offset of the image signal in the deviated region, and obtain the signal equalization adjustment amplitude.

[0038] S503: Adjust the amplitude of the image signal in the off-region according to the signal equalization adjustment amplitude, optimize the image signal equalization of each region, statistically analyze the distribution trend after signal adjustment, evaluate the degree of conformity between the signal amplitude and the equalization adjustment benchmark, and obtain the intraoperative magnetic resonance imaging signal optimization result.

[0039] A magnetic resonance imaging system for use in an operating room, the system comprising:

[0040] The signal attenuation detection module acquires the intraoperative magnetic resonance receiving array signal, detects the channel radio frequency signal amplitude, calculates the signal attenuation ratio of the tissue area, screens abnormal areas, analyzes the local signal attenuation trend, and generates intraoperative magnetic resonance signal attenuation characteristics.

[0041] Based on the intraoperative magnetic resonance signal attenuation characteristics, the gain adjustment module calculates the signal intensity difference between adjacent tissues, detects the stability of multi-channel signals, calculates the channel signal contribution, optimizes the gain correction value, adjusts the signal gain of the radio frequency receiving coil, and generates intraoperative image gain adjustment parameters.

[0042] The magnetic field distortion monitoring module obtains the change in magnetic field gradient based on the intraoperative image gain adjustment parameters, calculates the change in magnetic flux density in each region, screens regions with abnormal magnetic field strength, analyzes magnetic field mutation points caused by surgical instrument interference, calculates the spatial coverage of mutation points, summarizes the degree of influence of magnetic field disturbance, extracts signal offset features of mutation regions, detects the time series distribution of magnetic field fluctuations, and generates intraoperative magnetic field distortion parameters.

[0043] Based on the intraoperative magnetic field distortion parameters, the magnetic induction compensation module extracts the magnetic field change rate, detects the magnetic induction offset value of image pixels, filters abnormal magnetic induction offset areas, calculates the magnetic field compensation value, adjusts the amplitude of image pixel signals, and generates intraoperative image magnetic induction compensation data according to image grayscale levels.

[0044] Based on the intraoperative image magnetic induction compensation data, the image signal optimization module obtains the image signal distribution range, detects changes in grayscale contrast of tissue region images, compares the signal amplitude before and after compensation, adjusts the signal in the region that deviates from the signal equalization benchmark, and generates the intraoperative magnetic resonance imaging signal optimization result.

[0045] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0046] This invention identifies abnormal regions by detecting signal amplitude, optimizes radio frequency signal equalization, and reduces misjudgments in low-signal areas. It dynamically adjusts gain correction values ​​to improve image resolution and signal stability. Analyzing magnetic field gradient changes filters out abnormal magnetic induction offset regions, reducing interference from surgical instruments on the image. Calculating magnetic field compensation values ​​adjusts pixel signal amplitude to restore signal equalization in magnetically distorted areas, improving spatial accuracy. Detecting image signal distribution optimizes signal equalization, improving image consistency. Dynamic gain adjustment optimizes image contrast, reduces noise interference, and local magnetic field compensation reduces equipment magnetic induction interference, ensuring image spatial accuracy and enhancing real-time visualization capabilities of intraoperative images. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart of the method of the present invention;

[0049] Figure 2 This is a detailed flowchart of step S1 of the present invention;

[0050] Figure 3 This is a detailed flowchart of step S2 of the present invention;

[0051] Figure 4 This is a detailed flowchart of step S3 of the present invention;

[0052] Figure 5 This is a detailed flowchart of step S4 of the present invention;

[0053] Figure 6 This is a detailed flowchart of step S5 of the present invention;

[0054] Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0055] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0056] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0057] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0058] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0059] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0060] Please see Figure 1 The present invention provides a technical solution: a magnetic resonance imaging method for use in an operating room, comprising the following steps:

[0061] S1: Obtain the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculate the signal attenuation ratio of the tissue area, analyze the local signal attenuation trend, and generate intraoperative magnetic resonance signal attenuation characteristics.

[0062] S2: Based on the intraoperative magnetic resonance signal attenuation characteristics, the signal intensity difference between adjacent tissues is obtained, the channel signal contribution is calculated, the gain correction value is optimized to adjust the signal gain of the radio frequency receiving coil, and intraoperative image gain adjustment parameters are generated.

[0063] S3: Based on the intraoperative image gain adjustment parameters, calculate the magnitude of magnetic flux density change, analyze the distribution range of magnetic field abrupt change areas caused by surgical instrument interference, and generate intraoperative magnetic field distortion parameters.

[0064] S4: Based on the intraoperative magnetic field distortion parameters, extract the magnetic induction offset value of the image pixels, calculate the magnetic field compensation value, adjust the amplitude of the image pixel signals, and generate intraoperative image magnetic induction compensation data according to the image gray level.

[0065] S5: Based on intraoperative image magnetic induction compensation data, obtain the distribution range of image signals, detect changes in grayscale contrast of tissue region images, compare the signal amplitude before and after compensation, adjust the signal in the region that deviates from the signal equalization benchmark, and generate the optimized results of intraoperative magnetic resonance imaging signals.

[0066] Intraoperative magnetic resonance signal attenuation characteristics include channel signal amplitude error distribution, tissue region signal attenuation ratio, and local signal attenuation trend. Intraoperative image gain adjustment parameters include channel signal contribution distribution, time series signal stability index, and gain correction value. Intraoperative magnetic field distortion parameters include magnetic field gradient change, magnetic flux density change amplitude, and magnetic field abrupt change region distribution range. Intraoperative image magnetic induction compensation data include magnetic field change rate, image pixel magnetic induction offset value, and magnetic field compensation value. Intraoperative magnetic resonance imaging signal optimization results include image signal distribution range, tissue region signal mean difference, and signal equalization adjustment benchmark.

[0067] Please see Figure 2 The specific steps for obtaining the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculating the signal attenuation ratio of the tissue region, analyzing the local signal attenuation trend, and generating intraoperative magnetic resonance signal attenuation characteristics are as follows:

[0068] S101: Acquire intraoperative magnetic resonance receiving array signals, detect channel radio frequency signal amplitude, calculate amplitude deviation and normalize it, filter channel signals whose deviation exceeds the set amplitude deviation threshold range, and construct channel signal amplitude deviation dataset;

[0069] Intraoperative acquisition of MRI receiver array signals requires the separate acquisition of MRI signals through multiple radio frequency (RF) channels. Simultaneous processing of the RF signals from each channel is then performed at the receiving end. First, amplitude detection is performed on the RF signals received from all channels, and the amplitude value of each channel's RF signal is calculated. Assume the amplitude of a certain channel's signal is A. Ci The reference amplitude value is A GB Then calculate the deviation value D of the signal amplitude of this channel. Ci The optimized calculation method is as follows:

[0070]

[0071] The amplitude deviation value is normalized, and the normalized deviation value D′ is obtained. Ci The calculation is as follows:

[0072]

[0073] Among them, A GB The setting is based on the average value of all channel signals. This value is used to calculate the deviation of the channel signal relative to the overall level. The calculation method is as follows:

[0074]

[0075] In a certain magnetic resonance imaging (MRI) system test, assuming the signal amplitudes of the six channels are A... C1 =5.5mV, A C2 =4.8mV, A C3 =5.1mV, A C4 =4.9mV, A C5 =5.2mV, A C6 = 5.0mV, then the reference value is calculated as follows:

[0076]

[0077] T DA The (amplitude deviation threshold) is set based on a range of 10% to 20% of the global signal mean, and its calculation method is as follows:

[0078] T DA =α×A GB , 0.1≤α≤0.2;

[0079] If we take α = 0.12, then calculate T. DA The values ​​are as follows:

[0080] T DA =0.12 × 5.08 = 0.61 mV;

[0081] C S1 and C S2 As a small-value constant, it is mainly used to avoid extreme cases when dividing by zero or squaring. It is usually taken as 0.01mV, and the specific value is determined by the minimum quantization error of the experimental equipment.

[0082] Subsequently, the normalized deviation value D′ was calculated. Ci If a certain channel signal A C1 =5.5mV, then calculate D C1 And determine whether it exceeds T. DA If the range is exceeded, it is marked as an abnormal signal. Finally, all the filtered abnormal channel signals constitute the channel signal amplitude deviation dataset.

[0083] S102: Based on the channel signal amplitude deviation dataset, classify channel signals according to tissue regions, calculate the attenuation ratio of channel signals in each region, summarize the differences in attenuation ratios between tissue regions based on the regional mean, screen out abnormal signal regions whose attenuation ratios exceed the threshold of the regional mean, analyze local signal attenuation changes, and establish a distribution set of signal attenuation ratios in tissue regions.

[0084] Based on the channel signal amplitude deviation dataset, all channel signals are classified according to tissue regions. The channel signals of each tissue region are assigned based on the amplitude of the received magnetic resonance signal. The attenuation ratio of the channel signals in each tissue region is calculated. Let the tissue region R be... k The set of channel signal amplitudes in the data is {A} Rj +, the attenuation ratio RDR of the region k The optimized calculation is as follows:

[0085]

[0086] Among them, A RA The (regional average signal) is calculated using the average of all channel signals within the region. It is used to measure the signal level of a local area, and the calculation method is as follows:

[0087]

[0088] T AR The (attenuation ratio threshold) is set to a value range of 5%-10% of the global reference signal mean, and the calculation method is as follows:

[0089] T AR =β×A GB , 0.05≤β≤0.1;

[0090] If we take β = 0.08, then calculate T. AR The values ​​are as follows:

[0091] T AR =0.08 × 5.08 = 0.41,

[0092] If the attenuation ratio RDR of a certain region k If the value of 0.11 exceeds the set threshold, the area is marked as an abnormal signal area. Further analysis is conducted on the local attenuation changes of the signal within the area, and a distribution set of signal attenuation ratios in the tissue region is established.

[0093] S103: Based on the distribution set of signal attenuation ratio in tissue regions, analyze the attenuation trend of adjacent channels within abnormal regions, calculate the gradient change of local signal attenuation, summarize the signal attenuation fluctuation range in each tissue region according to the rate of change of local signal attenuation, and generate intraoperative magnetic resonance signal attenuation characteristics.

[0094] Based on the signal attenuation ratio distribution set of the tissue region, the attenuation trend of adjacent channels within the abnormal region is analyzed, and the gradient change of local signal attenuation is calculated. The gradient change G Cm The optimized calculation is as follows:

[0095]

[0096] Among them, A RM (Medium-range signal) is the median of the signal amplitude within that region, calculated as follows:

[0097] A RM =median(A Rj );

[0098] T GR The gradient change threshold is set to a value range of 7% to 12% of the signal mean within the local area, and the calculation method is as follows:

[0099] T GR =γ×A RA ,0.07≤γ≤0.12;

[0100] If we take γ = 0.1, then calculate T. GR The values ​​are as follows:

[0101] T GR =0.1 × 4.7 = 0.47;

[0102] If it exceeds the set threshold T GR If the signal is abnormally attenuated, the region is identified as an abnormal attenuation region, and the intraoperative magnetic resonance signal attenuation characteristics are ultimately generated.

[0103] Please see Figure 3 The specific steps for generating intraoperative image gain adjustment parameters, based on the intraoperative magnetic resonance signal attenuation characteristics to obtain the signal intensity difference between adjacent tissues, calculate the channel signal contribution, optimize the gain correction value to adjust the radio frequency receiving coil signal gain, are as follows:

[0104] S201: Based on the intraoperative magnetic resonance signal attenuation characteristics, calculate the amplitude difference of the channel signal in adjacent tissue regions, statistically analyze the signal intensity changes between each tissue, filter out regions where the amplitude difference exceeds the amplitude difference threshold, and obtain the signal intensity difference value between adjacent tissues.

[0105] Based on the intraoperative MRI signal attenuation characteristics, the amplitude of channel signals in adjacent tissue regions is calculated. First, all channel signals in each tissue region are partitioned and categorized according to the physical location and signal amplitude of the channels. The set of channel signal amplitudes for each region is defined as follows: Then, the amplitude difference of the channel signals in adjacent regions is calculated, and the average amplitude value of each region is selected. and the average amplitude value of adjacent regions Calculate the amplitude difference ΔA k as follows:

[0106]

[0107] Assume region R k signal mean Adjacent region R k:1 signal mean The channel signals within the region are 5.1, 5.2, 5.3, 5.4, and 5.5 mV, respectively, and the stability constant C is... S6R =0.02, then:

[0108]

[0109] Then set the amplitude difference threshold T. DAR as follows:

[0110]

[0111] Assuming λ = 0.1, the mean of the global reference signal A GBS =5.0mV, the number of adjacent regions K=3, and the mean values ​​of each region are 5.4, 4.7, and 5.1mV respectively, then

[0112]

[0113] If ΔA k =0.66mV exceeds T DAR If the signal strength is 0.63mV, then this region is selected as a region with abnormal signal strength changes.

[0114] S202: Based on the difference in signal intensity between adjacent tissues, detect the stability of multi-channel signals in the time series, calculate the range of signal amplitude change at each time point, analyze the temporal fluctuation trend of channel signals, and compare the signal contribution at adjacent time points to obtain the channel signal contribution ratio.

[0115] Based on the signal intensity differences between adjacent tissues, the stability of multi-channel signals over time is detected. First, the channel signal amplitude at each time point is obtained and arranged in chronological order. Let A be the set of channel signal amplitudes at the t-th time point. t ={A t,j +, then calculate the range of signal amplitude variation ΔA at each time point. t The calculation is as follows:

[0116]

[0117] Then, the signal contribution ratio CR is calculated. TS,t as follows:

[0118]

[0119] Assuming time point t=1, the maximum value of the channel signal A t,max =5.4mV, minimum value A t,min =4.9mV, mean The channel signals are 5.2, 5.1, 4.9, and 5.0 mV, respectively, and the stability constant C is... S7T =0.02, then

[0120]

[0121] set up C S8G =0.02, calculate the contribution ratio:

[0122]

[0123] Let the contribution ratio threshold T be set. DT =0.08, due to CR TS,1 =0.088 exceeds T DT If so, the signal contribution at that time point is determined to be abnormal.

[0124] S203: Based on the channel signal contribution ratio, adjust the RF receiving coil signal gain, compare the channel signal amplitude error with the regional signal change, calculate the adjustment amplitude after gain correction, and optimize the gain parameters to obtain the intraoperative image gain adjustment parameters.

[0125] Based on the channel signal contribution ratio, adjust the RF receiving coil signal gain and calculate the adjustment magnitude G after gain correction. adj as follows:

[0126]

[0127] Assume G init =10dB, gain contribution ratio CR TG,t =0.2, with channel gains of 9.8, 10.2, 10.1, and 9.9 dB respectively. The average gain after optimization is G. OAV =10.0dB, gain adjustment factor η=0.8, then

[0128]

[0129] Finally, the optimized intraoperative image gain adjustment parameter G OAV Gain optimization for intraoperative magnetic resonance imaging.

[0130] Please see Figure 4 Based on intraoperative image gain adjustment parameters, the following steps are taken to calculate the magnitude of magnetic flux density change, analyze the distribution range of magnetic field abrupt change regions caused by surgical instrument interference, and generate intraoperative magnetic field distortion parameters:

[0131] S301: Based on the intraoperative image gain adjustment parameters, calculate the change in magnetic field gradient in each region, extract the magnetic field strength in each region with reference to spatial coordinate information, analyze the fluctuation range of magnetic field strength in each region, and obtain the magnitude of magnetic field strength change.

[0132] Based on intraoperative image gain adjustment parameters, the calculation results of intraoperative magnetic field gradient changes are obtained. First, spatial coordinate information is extracted, with each coordinate point corresponding to a magnetic field strength value. The magnetic field strength data comes from the signal amplitude of the intraoperative magnetic resonance imaging (MRI) image, which is affected by the intraoperative image gain adjustment parameters. Combined with the baseline magnetic field strength data obtained during equipment calibration, the magnetic field strength value of each region is determined. The magnetic field strength of each region is defined as the average value of all magnetic field measurement points within it. The extracted magnetic field strength data are arranged in a spatial coordinate system, and the magnetic field strength gradient is calculated according to the coordinate changes. The calculation method for the change in magnetic field strength gradient is to calculate the difference in magnetic field strength between adjacent coordinate points and divide it by the spatial distance between the two points. Let the coordinate point (x... i ,y i ,z i The magnetic field strength at point () is B M,i Adjacent coordinate points (x i:1 ,y i:1 ,z i:1 The magnetic field strength at point () is B M,i:1 Calculate the change in magnetic field gradient B grad,i as follows:

[0133]

[0134] Among them, B ref This represents the baseline magnetic field strength, and its value is set based on the average stable magnetic field strength measured during equipment calibration. This value is usually the result of magnetic field measurement during the preoperative equipment self-test process and is finely adjusted according to changes in the intraoperative environment. The setting method is as follows:

[0135]

[0136] If the magnetic field strength values ​​measured during equipment calibration are 49.8, 50.1, 49.9, 50.0, and 50.2 mT respectively, then calculate B. ref as follows:

[0137]

[0138] G MRI This represents the intraoperative image gain adjustment parameter, which is set based on the ratio of the device's factory default gain parameter to the current image signal gain. This value is used to correct intraoperative magnetic field measurement data, and the setting method is as follows:

[0139]

[0140] Among them, A MRI A represents the current image gain value. ref The default gain for the device is set at the factory. If A MRI=12.0dB, A ref =10.0dB, then calculate G MRI as follows:

[0141]

[0142] Assume the magnetic field strength B at the measurement point (x1, y1, z1) = (0, 0, 0) is... M,1 =50.5mT, magnetic field strength B at adjacent measurement point (x2,y2,z2)=(2,2,1) M,2 =52.3mT, then the change in magnetic field gradient is calculated as follows:

[0143]

[0144] Based on the intraoperative image gain adjustment parameters, the change in magnetic field gradient in each region was calculated, and the fluctuation range of magnetic field strength was analyzed to obtain the magnitude of magnetic field strength change.

[0145] S302: Based on the magnitude of magnetic field strength change, filter out regions where the magnetic field strength change exceeds the preset magnetic field strength change threshold, analyze the trend of magnetic flux density change, compare the rate of magnetic flux change in each region, calculate the magnetic flux change gradient of the magnetic field region where the rate of change exceeds the preset rate of change threshold, and obtain the abnormal magnetic field strength interval.

[0146] Based on the magnitude of the magnetic field strength change, filters are selected where the magnetic field strength change exceeds the magnetic field strength change threshold T. BM The region, T BM The setting is based on the average magnetic field strength B under undisturbed conditions. ref Multiply by an adjustment factor α, where α ranges from 0.1 to 0.2, and this value varies with the stability of the magnetic field. If the standard deviation σ of the magnetic field measurement points... B If the value is large, then α should be set to a higher value to enhance the screening accuracy. The setting method is as follows:

[0147] T BM =α×B ref , 0.1≤α≤0.2;

[0148] If the standard deviation σ of the magnetic field data measured by the device B =7.0mT, reference magnetic field strength B ref =50.0mT, then calculate α and obtain T. BM as follows:

[0149]

[0150] T BM =0.14 × 50.0 = 7.0 mT;

[0151] Calculate the rate of change of magnetic flux density S Φ,t It also filters out magnetic field regions that exceed a rate of change threshold, which is set as follows:

[0152] S Φ,th =β×S Φ,avg ;

[0153] Among them, S Φ,th S represents the threshold of the rate of change of magnetic flux density. Φ,avg Let S be the average rate of change of magnetic flux density at all measurement points, with β ranging from 1.2 to 1.5, increasing with the range of magnetic field variation. Φ,avg =1.0Wb / s, β=1.3, then:

[0154] S Φ,th =1.3 × 1.0 = 1.3 Wb / s;

[0155] Assuming the measured magnetic flux density in a certain region is Φ1 = 4.8 Wb at time t = 1 s and Φ2 = 6.0 Wb at time t+1 = 1.5 s, the rate of change of magnetic flux density is calculated as follows:

[0156]

[0157] Assuming the magnetic field strength variation in this region is ΔB = 7.5 mT, the magnetic flux gradient is calculated as follows:

[0158]

[0159] Finally, based on the calculated gradient of magnetic flux change... Obtain the abnormal range of magnetic field strength.

[0160] S303: Based on the abnormal magnetic field intensity range, analyze the magnetic field mutation points caused by surgical instrument interference, detect the distribution range of the abnormal magnetic field intensity range, calculate the spatial coverage of the abnormal range, and obtain the intraoperative magnetic field distortion parameters.

[0161] Based on the abnormal magnetic field intensity range, we analyze the magnetic field abrupt change points caused by surgical instrument interference, extract magnetic field measurement points within the abnormal magnetic field intensity range, calculate the rate of change of magnetic field intensity at all measurement points, and determine whether there are any magnetic field abrupt change points. The criterion for determining a magnetic field abrupt change point is that the rate of change of magnetic field intensity exceeds the abrupt change threshold T. jump The setting method is as follows:

[0162] T jump =γ×B ref ;

[0163] Wherein, γ ranges from 0.04 to 0.08, varying with the level of magnetic field interference in the equipment environment. If B ref=50.0mT, γ=0.05, then calculate T. jump as follows:

[0164] T jump =0.05 × 50.0 = 2.5 mT / ms;

[0165] Calculate the spatial coverage C of the abnormal interval MF C MF The setting is based on the volume ratio of the abnormal magnetic field region and the total measurement space volume V. total The imaging range of the magnetic resonance imaging (MRI) device is determined, and the setting method is as follows:

[0166]

[0167] If the volume V of the abnormal magnetic field region abn =12cm³, total measured volume V total =100cm3, then calculate C MF as follows:

[0168]

[0169] Finally, the parameters of intraoperative magnetic field distortion were calculated.

[0170] Please see Figure 5 Based on intraoperative magnetic field distortion parameters, the magnetic induction offset values ​​of image pixels are extracted, magnetic field compensation values ​​are calculated, and the amplitude of image pixel signals is adjusted. The specific steps for generating intraoperative image magnetic induction compensation data according to image grayscale levels are as follows:

[0171] S401: Based on the intraoperative magnetic field distortion parameters, call the magnetic flux change rate of each region, calculate the magnetic induction offset value of the image pixels, mark the region where the offset value exceeds the preset magnetic induction offset value threshold as the magnetic field change region, and obtain magnetic induction offset abnormal data.

[0172] Based on intraoperative magnetic field distortion parameters, the magnetic flux change rate of each region is called to calculate the magnetic induction offset value of image pixels. The spatial coordinate information of each pixel is extracted, correlated with its corresponding magnetic field strength, and combined with the magnetic flux density change rate to obtain the magnetic induction offset of that pixel. Let the magnetic flux density change rate corresponding to pixel P(x,y) be S. Φ,px The magnetic field gradient is B G,P The change in magnetic field strength is ΔB px The pixel signal amplitude change rate is S P,rate If the time interval is Δt, then the magnetic induction offset value B shift,P The calculation is as follows:

[0173]

[0174] Assume the rate of change of magnetic flux density at a pixel is S Φ,px = 2.2 Wb / s, magnetic field gradient is B G,P =1.5mT / m, the change in magnetic field strength is ΔB px =0.8mT, the pixel signal amplitude change rate is S P,rate =0.4, and the time interval is Δt =0.5s, then the magnetic induction offset value is calculated as follows:

[0175]

[0176] Among them, the magnetic induction offset threshold T BS The setting is based on the mean magnetic induction offset B of all pixels in the image. shift,avg Multiply by an adjustment factor γ, where γ ranges from 0.2 to 0.4, and its value increases as the range of the magnetic field gradient increases. The calculation method is as follows:

[0177] T BS =γ×B shift,avg , 0.2≤γ≤0.4;

[0178] If the mean magnetic displacement of all pixels in the image is B shift,avg =0.9T, standard deviation of magnetic induction offset σ Bshift =0.27T, then calculate γ and obtain T. BS as follows:

[0179]

[0180] T BS =0.3 × 0.9 = 0.27T;

[0181] Filter out all magnetic induction offset values ​​B shift,P Greater than T BS The pixels are used to mark the area as a region of magnetic field abrupt change, and finally, magnetic induction offset anomaly data is obtained.

[0182] S402: Based on the magnetic induction offset anomaly data, obtain the distribution range of the magnetic field change area, calculate the magnetic field compensation value of each magnetic field change area, adjust the amplitude of the image pixel signal, correct the compensation amplitude of the pixel signal according to the magnetic field gradient direction, and obtain the magnetic field compensation amplitude.

[0183] Based on the magnetic induction offset anomaly data, the distribution range of magnetic field mutation regions is obtained. All pixels marked as magnetic field mutations are extracted, the boundary range of the magnetic field mutation regions is calculated, the mean magnetic induction offset within each region is obtained, and the magnetic field compensation value for each magnetic field mutation region is calculated. The magnetic field compensation value is set based on the difference between the mean magnetic induction offset value within the region and the reference magnetic induction offset value. Let the reference magnetic induction offset value be B. shift,ref=0.9T, then a certain mutation region R k The magnetic field compensation value C inside B,comp,k The calculation is as follows:

[0184]

[0185] Among them, the reference magnetic induction offset value B required for calculating the magnetic field compensation value. shift,ref The value is based on the average stable magnetic field strength of the equipment's magnetic resonance environment. This value is derived from the magnetic field measurement results during the preoperative equipment self-test process, and is set as follows:

[0186]

[0187] If the measured values ​​of magnetic induction offset during the equipment self-test process are 0.88, 0.91, 0.87, 0.92, and 0.90T respectively, then calculate B. shift,ref as follows:

[0188]

[0189] Assume the mean magnetic induction shift within a certain abrupt magnetic field change region R1 is B. shift,avg,1 = 1.2T, magnetic field gradient is B G,1 =1.5mT / m, the change in magnetic field strength is ΔB1 = 0.8mT, and the rate of change of pixel signal amplitude is S P,rate,1 =0.4, then the magnetic field compensation value is calculated as follows:

[0190]

[0191] Finally, the magnetic field compensation amplitude is obtained.

[0192] S403: Based on the magnetic field compensation amplitude, the pixels are classified according to the image grayscale value, the magnetic induction change trend of each grayscale level is analyzed, the image signal balance is statistically analyzed, and intraoperative image magnetic induction compensation data is obtained.

[0193] Based on the magnetic field compensation amplitude, pixels are classified according to their image grayscale values. The grayscale value distribution of the image pixels is extracted, and the grayscale levels of the image signal are calculated. Let N be the number of grayscale levels. G With 256 levels, the range of each gray level is calculated as follows:

[0194]

[0195] Assuming the maximum grayscale value G of the image pixel max =255, minimum grayscale value G min =0, let the gray values ​​of the four gray levels be 1020, 980, 995, and 1010, and calculate the gray mean G. avg as follows:

[0196]

[0197] Among them, image signal equalization E G The setting is based on the variance of the number of pixels at each grayscale level, and its calculation method is as follows:

[0198]

[0199] Among them, P i P represents the number of pixels within gray level i. avg The mean value P represents the average number of pixels across all gray levels of the image. Let the number of pixels for the 256 gray levels be 1020, 980, 995, and 1010, respectively. avg The calculation is as follows:

[0200]

[0201] The balance of the statistical image signals was analyzed, and finally, intraoperative image magnetic induction compensation data was obtained.

[0202] Please see Figure 6 The specific steps for obtaining the signal distribution range of intraoperative magnetic resonance imaging based on intraoperative image magnetic induction compensation data, detecting changes in grayscale contrast of tissue regions, comparing signal amplitudes before and after compensation, adjusting signals in regions deviating from the signal equalization benchmark, and generating optimized intraoperative magnetic resonance imaging signal results are as follows:

[0203] S501: Based on intraoperative image magnetic induction compensation data, obtain the distribution range of intraoperative image signals, detect the contrast change of image grayscale in each tissue area, compare the image signal amplitude before and after compensation, and obtain image signal distribution parameters.

[0204] Based on intraoperative magnetic induction compensation data, the distribution range of intraoperative image signals was obtained. After extracting the image data, an image grayscale matrix was established according to the image coordinate system, with each pixel corresponding to a grayscale value. The number of pixels at different grayscale levels was counted, and the grayscale distribution of the image signal across the entire image range was calculated. Let the image grayscale range be G. min and G max Let G be the minimum and maximum gray values ​​in the image, calculate the distribution of gray levels, analyze the gray-level contrast changes in each tissue region, obtain the gray-level difference value of each region, and let G be the maximum gray value in a certain region. max,R The minimum grayscale value is G min,R The grayscale contrast of this region is calculated as follows:

[0205]

[0206] Among them, C RLet R represent the grayscale contrast of region R. To avoid extremely small values ​​where the denominator is zero, let's assume the maximum grayscale value in a certain tissue region R1 is 220 and the minimum grayscale value is 80. Then, the grayscale contrast is calculated as follows:

[0207]

[0208] Image grayscale contrast setting reference value C baseline It is calculated based on the mean of the global grayscale contrast of the image, and the calculation method is as follows:

[0209]

[0210] If the grayscale contrast values ​​for the five regions are set to 0.45, 0.47, 0.44, 0.46, and 0.48 respectively, then calculate C. baseline as follows:

[0211]

[0212] Compare the image signal amplitudes before and after compensation. Let the mean gray level before compensation be G. avg,before The mean gray level after compensation is G. avg,after The rate of change of the mean grayscale value is calculated as follows:

[0213]

[0214] If the average grayscale value before compensation is 120 and the average grayscale value after compensation is 135, then...

[0215]

[0216] The image signal distribution parameters are calculated, including grayscale contrast variation and signal amplitude variation.

[0217] S502: Based on the image signal distribution parameters, calculate the signal mean difference of each tissue region, call the intraoperative image gain adjustment parameters to set the signal equalization adjustment benchmark, compare the intraoperative image signal distribution range, filter the regions that deviate from the signal equalization adjustment benchmark, calculate the amplitude offset of the image signal in the deviated regions, and obtain the signal equalization adjustment amplitude.

[0218] Based on image signal distribution parameters, the signal mean difference for each tissue region is calculated, the image signal mean of each tissue region is extracted, and the difference between it and the global image signal mean is calculated. Let a certain region R... k The average value of the image signal is The mean value of the global image signal is G global,avg The differences in the mean of the signals are calculated as follows:

[0219]

[0220] Suppose the average image signal value for a certain area is 140, and the average image signal value for the entire region is 130, then

[0221] ΔG eq,k =|140-130|=10;

[0222] Call the intraoperative image gain adjustment parameters and set the signal equalization adjustment reference G. eq,baseline The signal is set to the global image signal average, and the signal equalization adjustment range T is set. G,eq The signal equalization adjustment range is calculated based on the standard deviation of the image signal mean, as follows:

[0223]

[0224] Where α ranges from 0.05 to 0.15, and the mean values ​​of the image signals for the five regions are 125, 135, 130, 140, and 128, respectively, and the mean value of the global image signal is G. global,avg The calculation is as follows:

[0225]

[0226] Calculate the standard deviation σ G,global :

[0227]

[0228] T G,eq =0.1 × 131.6 = 13.16;

[0229] Filter areas that deviate from the signal equalization adjustment benchmark. If the mean image signal of a certain area is different from the G... eq,baseline The deviation is greater than T G,eq If the area is found to be off-target, then the amplitude offset of the image signal in the off-target area is calculated. Assuming the signal mean of a certain area is 140 and the equalization adjustment reference is 130, then...

[0230] ΔG offset =|140-130|=10;

[0231] Finally, the signal equalization adjustment amplitude is obtained.

[0232] S503: Adjust the amplitude of the image signal in the off-center area according to the signal equalization adjustment amplitude, optimize the image signal equalization of each area, statistically analyze the distribution trend after signal adjustment, evaluate the degree of conformity between the signal amplitude and the equalization adjustment benchmark, and obtain the intraoperative magnetic resonance imaging signal optimization results.

[0233] Based on the signal equalization adjustment amplitude, the amplitude of the image signal in the off-center area is adjusted. Let the amplitude of the original image signal in a certain area be S. orig,k The signal adjustment amount is Sadj,k The equilibrium adjustment range is G. adj,k The adjusted signal amplitude is calculated as follows:

[0234] S eq,new,k =S orig,k -G adj,k ;

[0235] Optimize the image signal equalization of each region, statistically analyze the distribution trend after signal adjustment, calculate the signal equalization error, and let the global mean after signal adjustment be G. eq,new,avg The equilibrium error is calculated as follows:

[0236]

[0237] Finally, the degree of conformity between the signal amplitude and the equalization adjustment benchmark was evaluated to obtain the optimized results of the intraoperative magnetic resonance imaging signal.

[0238] Please see Figure 7 A magnetic resonance imaging system for use in an operating room, the system comprising:

[0239] The signal attenuation detection module acquires the intraoperative magnetic resonance receiving array signal, detects the channel radio frequency signal amplitude, calculates the signal attenuation ratio of the tissue area, screens abnormal areas, analyzes the local signal attenuation trend, and generates intraoperative magnetic resonance signal attenuation characteristics.

[0240] The gain adjustment module calculates the signal intensity difference between adjacent tissues based on the intraoperative magnetic resonance signal attenuation characteristics, detects the stability of multi-channel signals, calculates the channel signal contribution, optimizes the gain correction value, adjusts the signal gain of the radio frequency receiving coil, and generates intraoperative image gain adjustment parameters.

[0241] The magnetic field distortion monitoring module obtains the change in magnetic field gradient based on intraoperative image gain adjustment parameters, calculates the change amplitude of magnetic flux density in each region, screens areas with abnormal magnetic field strength, analyzes magnetic field mutation points caused by surgical instrument interference, calculates the spatial coverage of mutation points, summarizes the degree of influence of magnetic field disturbance, extracts signal offset features of mutation areas, detects the time series distribution of magnetic field fluctuations, and generates intraoperative magnetic field distortion parameters.

[0242] The magnetic induction compensation module extracts the rate of change of the magnetic field based on the intraoperative magnetic field distortion parameters, detects the magnetic induction offset value of the image pixels, filters the abnormal magnetic induction offset areas, calculates the magnetic field compensation value, adjusts the amplitude of the image pixel signal, and generates intraoperative image magnetic induction compensation data according to the image gray level.

[0243] The image signal optimization module obtains the image signal distribution range based on intraoperative image magnetic induction compensation data, detects changes in grayscale contrast of tissue region images, compares the signal amplitude before and after compensation, adjusts the signal in the region that deviates from the signal equalization benchmark, and generates the intraoperative magnetic resonance imaging signal optimization result.

[0244] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A magnetic resonance imaging method for use in an operating room, characterized in that, Includes the following steps: S1: Obtain the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculate the signal attenuation ratio of the tissue area, analyze the local signal attenuation trend, and generate intraoperative magnetic resonance signal attenuation characteristics. S2: Based on the intraoperative magnetic resonance signal attenuation characteristics, obtain the signal intensity difference between adjacent tissues, calculate the channel signal contribution, optimize the gain correction value to adjust the radio frequency receiving coil signal gain, and generate intraoperative image gain adjustment parameters. S3: Based on the intraoperative image gain adjustment parameters, calculate the magnitude of magnetic flux density change, analyze the distribution range of magnetic field abrupt change areas caused by surgical instrument interference, and generate intraoperative magnetic field distortion parameters. S4: Based on the intraoperative magnetic field distortion parameters, extract the magnetic induction offset value of the image pixels, calculate the magnetic field compensation value, adjust the amplitude of the image pixel signals, and generate intraoperative image magnetic induction compensation data according to the image grayscale classification. S5: Based on intraoperative image magnetic induction compensation data, obtain the distribution range of image signals, detect changes in grayscale contrast of tissue region images, compare the signal amplitude before and after compensation, adjust the signal in the region that deviates from the signal equalization benchmark, and generate the optimized results of intraoperative magnetic resonance imaging signals.

2. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: The intraoperative magnetic resonance signal attenuation characteristics include channel signal amplitude error distribution, tissue region signal attenuation ratio, and local signal attenuation trend. The intraoperative image gain adjustment parameters include channel signal contribution distribution, time series signal stability index, and gain correction value. The intraoperative magnetic field distortion parameters include magnetic field gradient change, magnetic flux density change amplitude, and magnetic field abrupt change region distribution range. The intraoperative image magnetic induction compensation data includes magnetic field change rate, image pixel magnetic induction offset value, and magnetic field compensation value. The intraoperative magnetic resonance imaging signal optimization results include image signal distribution range, tissue region signal mean difference, and signal equalization adjustment benchmark.

3. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: The specific steps for acquiring the channel radio frequency signal amplitude of the intraoperative magnetic resonance receiving array signal, calculating the signal attenuation ratio of the tissue region, analyzing the local signal attenuation trend, and generating intraoperative magnetic resonance signal attenuation characteristics are as follows: S101: Acquire intraoperative magnetic resonance receiving array signals, detect channel radio frequency signal amplitude, calculate amplitude deviation and normalize it, filter channel signals whose deviation exceeds the set amplitude deviation threshold range, and construct channel signal amplitude deviation dataset; S102: Based on the channel signal amplitude deviation dataset, classify the channel signals according to the tissue region, calculate the attenuation ratio of the channel signal in each region, summarize the differences in attenuation ratios between tissue regions based on the regional mean, screen out abnormal signal regions whose attenuation ratios exceed the threshold of the regional mean, analyze the local signal attenuation changes, and establish a distribution set of signal attenuation ratios in tissue regions. S103: Based on the signal attenuation ratio distribution set of the tissue region, analyze the attenuation trend of adjacent channel signals within the abnormal region, calculate the gradient change of local signal attenuation, summarize the signal attenuation fluctuation range of each tissue region according to the change rate of local signal attenuation, and generate intraoperative magnetic resonance signal attenuation characteristics.

4. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: For calculating the gradient change G of local signal attenuation Cm The formula used is: Among them, G Cm A represents the local gradient change of the channel signal within the current region. Cm A represents the amplitude of the magnetic resonance signal in the m-th channel. Cm+1 D represents the amplitude of the magnetic resonance signal in the (m+1)th adjacent channel. C M represents the physical distance between adjacent channels, M represents the number of channels within the abnormal region, and A represents the number of channels within the abnormal region. RM A represents the median of all channel signals within the region. RA C represents the mean of all channel signals within the region. S4 This represents a decimal number with stable computational properties.

5. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: The specific steps for obtaining signal intensity differences between adjacent tissues based on the intraoperative magnetic resonance signal attenuation characteristics, calculating channel signal contribution, optimizing gain correction values ​​to adjust the radio frequency receiving coil signal gain, and generating intraoperative image gain adjustment parameters are as follows: S201: Based on the intraoperative magnetic resonance signal attenuation characteristics, calculate the amplitude difference of the channel signal in adjacent tissue regions, statistically analyze the signal intensity changes between each tissue, filter out regions where the amplitude difference exceeds the amplitude difference threshold, and obtain the signal intensity difference value between adjacent tissues. S202: Based on the signal intensity difference between adjacent tissues, detect the stability of multi-channel signals in the time series, calculate the range of signal amplitude change at each time point, analyze the temporal fluctuation trend of channel signals, and compare the signal contribution at adjacent time points to obtain the channel signal contribution ratio. S203: Based on the channel signal contribution ratio, adjust the RF receiving coil signal gain, compare the channel signal amplitude error with the regional signal change, calculate the adjustment range after gain correction, and optimize the gain parameters to obtain the intraoperative image gain adjustment parameters.

6. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: The adjustment magnitude G after calculating the gain correction adj The formula used is: Among them, G init η represents the initial gain value set by the factory, η represents the gain adjustment coefficient, and CR TG,t G represents the gain contribution ratio. j G represents the current gain value of channel j, N represents the total number of channels, and G represents the current gain value of channel j. OAV This represents the average global gain calculated after optimization.

7. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: Based on the intraoperative image gain adjustment parameters, the specific steps for calculating the magnitude of magnetic flux density change, analyzing the distribution range of magnetic field abrupt changes caused by surgical instrument interference, and generating intraoperative magnetic field distortion parameters are as follows: S301: Based on the intraoperative image gain adjustment parameters, calculate the change in magnetic field gradient in each region, extract the magnetic field strength in each region with reference to spatial coordinate information, analyze the fluctuation range of magnetic field strength in each region, and obtain the magnitude of magnetic field strength change. S302: Based on the magnitude of the magnetic field strength change, filter out regions where the magnetic field strength change exceeds a preset magnetic field strength change threshold, analyze the trend of magnetic flux density change, compare the rate of magnetic flux change in each region, calculate the magnetic flux change gradient of the magnetic field region where the rate of change exceeds a preset rate of change threshold, and obtain the abnormal magnetic field strength interval. S303: Based on the abnormal magnetic field intensity range, analyze the magnetic field mutation points caused by surgical instrument interference, detect the distribution range of the abnormal magnetic field intensity range, calculate the spatial coverage of the abnormal range, and obtain the intraoperative magnetic field distortion parameters.

8. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: Based on the intraoperative magnetic field distortion parameters, the following are the specific steps for extracting the magnetic induction offset value of image pixels, calculating the magnetic field compensation value, adjusting the image pixel signal amplitude, and generating intraoperative image magnetic induction compensation data according to image grayscale levels: S401: Based on the intraoperative magnetic field distortion parameters, call the magnetic flux change rate of each region, calculate the magnetic induction offset value of the image pixels, mark the region where the offset value exceeds the preset magnetic induction offset value threshold as the magnetic field change region, and obtain magnetic induction offset abnormal data. S402: Based on the magnetic induction offset anomaly data, obtain the distribution range of the magnetic field change region, calculate the magnetic field compensation value of each magnetic field change region, adjust the amplitude of the image pixel signal, correct the compensation amplitude of the pixel signal according to the magnetic field gradient direction, and obtain the magnetic field compensation amplitude. S403: Based on the magnetic field compensation amplitude, the pixels are classified according to the image grayscale value, the magnetic induction change trend of each grayscale level is analyzed, the image signal balance is statistically analyzed, and intraoperative image magnetic induction compensation data is obtained.

9. The magnetic resonance imaging method for use in an operating room according to claim 1, characterized in that: The specific steps for obtaining the image signal distribution range based on intraoperative magnetic resonance imaging (MRI) compensation data, detecting changes in grayscale contrast in tissue regions, comparing signal amplitudes before and after compensation, adjusting signals in regions deviating from the signal equalization benchmark, and generating optimized intraoperative MRI signal results are as follows: S501: Based on the intraoperative image magnetic induction compensation data, obtain the distribution range of intraoperative image signals, detect the contrast change of image grayscale in each tissue area, compare the image signal amplitude before and after compensation, and obtain image signal distribution parameters. S502: Based on the image signal distribution parameters, calculate the signal mean difference of each tissue region, call the intraoperative image gain adjustment parameters to set the signal equalization adjustment benchmark, compare the intraoperative image signal distribution range, filter the regions that deviate from the signal equalization adjustment benchmark, calculate the amplitude offset of the image signal in the deviated region, and obtain the signal equalization adjustment amplitude. S503: Adjust the amplitude of the image signal in the off-region according to the signal equalization adjustment amplitude, optimize the image signal equalization of each region, statistically analyze the distribution trend after signal adjustment, evaluate the degree of conformity between the signal amplitude and the equalization adjustment benchmark, and obtain the intraoperative magnetic resonance imaging signal optimization result.

10. A magnetic resonance imaging system for use in an operating room, characterized in that, The system comprises: [The method for magnetic resonance imaging in an operating room is performed according to any one of claims 1-9] The signal attenuation detection module acquires the intraoperative magnetic resonance receiving array signal, detects the channel radio frequency signal amplitude, calculates the signal attenuation ratio of the tissue area, screens abnormal areas, analyzes the local signal attenuation trend, and generates intraoperative magnetic resonance signal attenuation characteristics. Based on the intraoperative magnetic resonance signal attenuation characteristics, the gain adjustment module calculates the signal intensity difference between adjacent tissues, detects the stability of multi-channel signals, calculates the channel signal contribution, optimizes the gain correction value, adjusts the signal gain of the radio frequency receiving coil, and generates intraoperative image gain adjustment parameters. The magnetic field distortion monitoring module obtains the change in magnetic field gradient based on the intraoperative image gain adjustment parameters, calculates the change in magnetic flux density in each region, screens regions with abnormal magnetic field strength, analyzes magnetic field mutation points caused by surgical instrument interference, calculates the spatial coverage of mutation points, summarizes the degree of influence of magnetic field disturbance, extracts signal offset features of mutation regions, detects the time series distribution of magnetic field fluctuations, and generates intraoperative magnetic field distortion parameters. Based on the intraoperative magnetic field distortion parameters, the magnetic induction compensation module extracts the magnetic field change rate, detects the magnetic induction offset value of image pixels, filters abnormal magnetic induction offset areas, calculates the magnetic field compensation value, adjusts the amplitude of image pixel signals, and generates intraoperative image magnetic induction compensation data according to image grayscale levels. Based on the intraoperative image magnetic induction compensation data, the image signal optimization module obtains the image signal distribution range, detects changes in grayscale contrast of tissue region images, compares the signal amplitude before and after compensation, adjusts the signal in the region that deviates from the signal equalization benchmark, and generates the intraoperative magnetic resonance imaging signal optimization result.

Images