Method and system for correcting X-ray intensity fluctuation under CT tube voltage fluctuation

Abstract

The invention discloses a method and system for correcting X-ray intensity fluctuation under CT tube voltage fluctuation, and the method comprises the steps: scanning air data according to a pre-scanning condition, and calculating the intensity proportional relation of X-rays after filtration under different tube voltage values; establishing a mapping model of X-ray intensity proportion parameters based on the intensity proportion relation; acquiring a feedback value of the tube voltage under the current exposure in the process of scanning the patient in real time; determining a corresponding X-ray intensity proportion parameter from the mapping model based on the feedback value of the tube voltage; correcting the incident original X-ray light intensity of each channel based on the X-ray intensity proportion parameter; and X-ray attenuation values of the channels penetrating through the scanned object are calculated, and image reconstruction is carried out based on the attenuation values. When a patient is scanned, corresponding proportion parameters can be dynamically called, the attenuation value is calculated through the ratio of the corrected incident light intensity to the detected intensity, and the hardening effect correction and reconstruction algorithm is combined, so that the precision and stability of image reconstruction are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of X-ray intensity calculation, and in particular to a method and system for correcting X-ray intensity fluctuation under CT tube voltage fluctuation. Background Art

[0002] In computed tomography (CT) imaging, the attenuation calculation of X-rays passing through the scanned object is the core of image reconstruction, and the accuracy of the incident light intensity and the intensity after attenuation directly determines the image quality. The existing technology infers the incident light intensity of each channel by the X-ray intensity of the reference channel, assuming that the X-ray energy spectrum is fixed when the tube voltage is stable, and the intensity ratio relationship between each channel and the reference channel is constant. However, the fluctuation of the tube voltage in actual scanning will change the distribution of the X-ray energy spectrum, resulting in the intensity ratio relationship between each channel and the reference channel after filtering to fluctuate dynamically with the real-time change of the tube voltage. This fluctuation makes the fixed ratio relationship relied on by the traditional method invalid, especially when the sampling frequency of the high-voltage control device is high, the slight fluctuation of the tube voltage will cause a significant change in the average energy of the X-ray, which will cause the calculation error of the incident light intensity of each channel, and finally lead to the distortion of the attenuation value calculation and image artifacts. Therefore, how to correct the incident light intensity error caused by the tube voltage fluctuation, and then eliminate the dynamic deviation of the ratio relationship when calculating the attenuation value, and finally improve the image quality through hardening correction and reconstruction algorithm has a high research value. Summary of the invention

[0003] In view of this, the present invention proposes a method and system for correcting X-ray intensity fluctuation under CT tube voltage fluctuation, which can solve the problem of image accuracy degradation caused by unstable X-ray intensity ratio relationship caused by tube voltage fluctuation. The present invention provides the following technical solutions: A method for correcting X-ray intensity fluctuation under CT tube voltage fluctuation, the method comprising: Scan air data according to the pre-scanning conditions, and calculate the intensity ratio relationship of X-rays after filtration between each detector channel and the reference channel under different CT tube voltage values according to the air data; Based on the intensity ratio relationship, a mapping model is established, the mapping model including a mapping relationship between a CT tube voltage value and an X-ray intensity ratio parameter of each detection channel, and a mapping relationship between a CT tube voltage value and an X-ray intensity ratio parameter of each reference channel; During the patient scanning process, the feedback value of the tube voltage under the current exposure is obtained in real time; determining a corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage; Correcting the incident raw X-ray intensity of each detector channel based on the X-ray intensity ratio parameter; The X-ray attenuation value of each detector channel passing through the scanned object is calculated, and image reconstruction is performed based on the attenuation value.

[0004] Optionally, the step of calling the pre-scanning condition to scan the air data to model and calculate the intensity ratio relationship of the X-rays of each detector channel and the reference channel at different tube voltage values includes: In the pre-scanning stage, call the pre-scanning condition to scan the air data and record the tube voltage feedback value kVData of each exposure and the X-ray intensity value AirDat0 of each detector channel; Preprocess the X-ray intensity value AirDat0 of the detector channel in the air data to obtain preprocessed data AirDat1; Calculate the ratio data AirDat2 of the X-ray intensity value of the reference channel to the preprocessed X-ray intensity value AirDat1 of each detector channel for each exposure; Divide the value range of the tube voltage feedback value kVData into multiple intervals with preset intervals, and statistically calculate the average intensity value MeanAirData of the ratio data AirDat2 in each interval; Calculate the intensity ratio relationship of the X-rays filtered by each detector channel and the reference channel in the interval of the corresponding tube voltage feedback value according to the average intensity value MeanAirData.

[0005] Optionally, the step of establishing a mapping model between the tube voltage value and the X-ray intensity ratio parameters of each detection channel and the reference channel based on the intensity ratio relationship includes: Normalize the intensity ratio relationship to obtain the correction parameters corresponding to each detector channel; Interpolate or average the correction parameters in each interval of the tube voltage feedback value to establish a piecewise mapping relationship between the tube voltage feedback value and the correction parameters; or perform polynomial fitting on the corresponding relationship between the intensity ratio relationship and the tube voltage feedback value to obtain a mathematical function representing the mapping relationship between the tube voltage feedback value and the correction parameters; Save the parameters of the piecewise mapping relationship or the fitting function and the corresponding interval of the tube voltage feedback value as a calibration model file.

[0006] Optionally, the step of determining the corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage includes: Compare the tube voltage feedback value obtained when scanning the patient with the pre-stored tube voltage range in the mapping model. If the tube voltage feedback value is less than the pre-stored minimum tube voltage value, take the minimum tube voltage value. If it is greater than the pre-stored maximum tube voltage value, take the maximum tube voltage value to determine the corrected real-time tube voltage feedback value; Obtain the real-time X-ray intensity ratio parameter according to the real-time tube voltage feedback value and the mapping model.

[0007] Optionally, obtaining the real-time X-ray intensity proportionality parameter according to the real-time feedback value of the tube voltage and the mapping model includes: If the mapping model is a piecewise mapping relationship, directly obtain the pre-stored proportionality parameter corresponding to the interval according to the segmentation interval to which the tube voltage feedback value belongs; or if the mapping model is a polynomial function, substitute the tube voltage feedback value into the mathematical function to calculate the corresponding X-ray intensity proportionality parameter.

[0008] Optionally, calculating the X-ray attenuation value passing through the object to be scanned for each channel and performing image reconstruction based on the attenuation value includes: Calculating the X-ray attenuation value for each channel through the corrected incident original X-ray intensity and the X-ray intensity after attenuation detected by the detector during the patient scan. The formula is: where I d is the X-ray intensity after attenuation detected by the detector, is the corrected incident original X-ray intensity; Performing X-ray hardening correction on the attenuation value μ s，c to eliminate the attenuation error caused by the hardening effect when high-energy X-rays penetrate the material; Recombining the corrected attenuation value μ s，c into the projection data format to match the input requirements of the image reconstruction algorithm; Applying a filtered back-projection algorithm or an iterative reconstruction algorithm to the recombined attenuation value to reconstruct and generate a CT image of the object to be scanned.

[0009] The present invention further discloses a correction system for X-ray intensity fluctuation under CT tube voltage fluctuation, including: An intensity proportionality relationship calculation module, configured to scan air data according to pre-scanning conditions, and calculate the intensity proportionality relationship of X-rays between each detector channel and a reference channel at different CT tube voltage values according to the air data; A mapping model construction module, configured to establish a mapping model based on the intensity proportionality relationship. The mapping model includes the mapping relationship between the CT tube voltage value and the X-ray intensity proportionality parameter of each detection channel, and the mapping relationship between the CT tube voltage value and the X-ray intensity proportionality parameter of each reference channel; A data acquisition module, configured to obtain the feedback value of the tube voltage under the current exposure in real time during the scanning of the patient; A proportionality parameter determination module, configured to determine the corresponding X-ray intensity proportionality parameter from the mapping model based on the feedback value of the tube voltage; An X-ray intensity correction module, configured to correct the incident original X-ray intensity of each detector channel based on the X-ray intensity proportionality parameter; An image reconstruction module is used to calculate the X-ray attenuation values of each detector channel passing through the object to be scanned, and perform image reconstruction based on the attenuation values.

[0010] The present invention further discloses a computer-readable storage medium, characterized in that the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0011] The present invention further discloses an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that when the processor executes the program, the above-mentioned method is implemented.

[0012] The present invention further discloses a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, the above-mentioned method is implemented.

[0013] According to the technical solution of the present invention, by real-time monitoring of the tube voltage fluctuation and combining with the dynamic correction of pre-scan modeling, the problems of unstable X-ray energy spectrum distribution caused by tube voltage changes and misalignment of the filtered intensity ratio relationship between each detector channel and the reference channel in traditional CT imaging are effectively solved. By scanning air data in the pre-scan stage and statistically analyzing the intensity ratios of each channel to the reference channel in different tube voltage intervals in segments, a mapping model between the tube voltage and the correction parameters is established, so that during the patient scan, the corresponding ratio parameters can be dynamically retrieved according to the real-time feedback tube voltage value, thereby accurately correcting the incident light intensity error caused by tube voltage fluctuation, avoiding the attenuation value calculation deviation caused by the traditional method relying on a fixed ratio relationship. Finally, the attenuation value is calculated by the ratio of the corrected incident light intensity to the detected intensity, and combined with the hardening effect correction and the reconstruction algorithm, the accuracy and stability of image reconstruction are significantly improved. Especially in the scenario where the sampling frequency of the high-voltage control device is high and the tube voltage fluctuation range is large, through the parameter adaptation of segmented mapping or polynomial fitting, the dynamic consistency of the incident light intensity calculation of each channel can be continuously maintained, thereby eliminating the attenuation error caused by energy spectrum changes, reducing image artifacts, making the CT imaging result more real and reliable. At the same time, through the rapid invocation of the pre-stored correction model and the closed-loop control of real-time feedback, the correction process is simplified and the adaptability of the system to different tube voltage fluctuation ranges is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] For purposes of illustration and not limitation, the present invention is described in connection with the embodiments and drawings of the present invention, wherein: Figure 1 is a flowchart of the method for correcting the X-ray light intensity fluctuation under CT tube voltage fluctuation in the embodiment of the present invention; Figure 2 is a structural diagram of the system for correcting the X-ray light intensity fluctuation under CT tube voltage fluctuation in the embodiment of the present invention; Figure 3 It is a schematic structural diagram of an electronic device in an embodiment of the present invention. Specific Embodiment

[0015] In order to enable those skilled in the art of this technology to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0016] It should be noted that, without conflict, the embodiments of this application and the features in the embodiments can be combined with each other. The embodiments of this application will be described in detail below with reference to the drawings.

[0017] Refer to Figure 1 , this embodiment discloses a correction method for X-ray intensity fluctuation under CT tube voltage fluctuation. The method includes the following steps: S100: Scan air data according to pre-scanning conditions to model and calculate the intensity ratio relationship of X-rays in each detector channel and the reference channel at different tube voltage values based on the air data. In the pre-scanning stage, the system first configures the pre-scanning conditions, and then starts the air scan to eliminate the attenuation effect of the object being scanned on the X-rays. Specifically, during the scan, at the start of each exposure, the tube voltage feedback value kVData output by the high-voltage control device is read in real time (for example, the preset tube voltage for the current exposure is 120 kV, and the actual tube voltage value is 120.5 kV), and the X-ray intensity values AirData0 detected by all detector channels during this exposure are recorded. When performing multi-turn cyclic scanning, the above process is repeated, and all exposure data is collected through multiple exposures to ensure coverage of the tube voltage fluctuation range. For example, the recorded kVData range is from 115.0 kV to 125.0 kV. After obtaining the exposure data, outliers (such as discrete points caused by detector failures) in the X-ray intensity values AirData0 are interpolated or replaced. For example, the bad point data is filled with the average value of adjacent channels. At the same time, air correction is performed to eliminate the influence of air background noise. The formula is: AirData1 s，c = AirData0 s，c - AirBaCkground s，c , where, AirBackground s，cis the pre-calibrated air background noise value, s is the number of channel rows, and c is the channel number. Further, calculate the ratio data AirDat2 of the X-ray intensity value of the reference channel for each exposure to the X-ray intensity value AirDat1 of each detector channel, that is, calculate the ratio of each channel to the reference channel based on the intensity of the reference channel to eliminate the proportional change caused by the tube current fluctuation. The calculation formula is: where RefC s is the intensity after preprocessing of the reference channel for the s-th exposure. Exemplarily, if the intensity of the reference channel for a certain exposure is 1000 counts and the AirData1 of channel 1 is 1150 counts, then AirData2 is 1000 / 1150≈0.8696. Divide the maximum value (such as 140.0 kV) and the minimum value (such as 80.0 kV) of all the recorded kVData values into intervals with a step size of 0.2 kV. Statistically analyze all the AirData2 data within each interval, and calculate the average ratio of each channel. The calculation formula is: where is the set of all exposure indices within the k-th tube voltage interval, and N k is the number of valid exposures within interval k. Exemplarily, within the interval 120.0 kV to 120.2 kV, if the average value of AirData2 of a certain channel is 0.92, then record the average ratio of this channel within this interval as 0.92. For each tube voltage interval k, the filtered intensity proportional relationship of channel c is defined as: Based on this, save the proportional relationship Ratio k,c for all intervals k as a correction table according to the tube voltage range.

[0018] S200: Based on the intensity proportional relationship, establish a mapping model. This mapping model includes the mapping relationship between the CT tube voltage value and the X-ray intensity proportional parameter of each detection channel, and the mapping relationship between the CT tube voltage value and the X-ray intensity proportional parameter of each reference channel. After calculating the average ratio of each channel, for each tube voltage interval k and channel c, calculate the correction parameter CorrectParamk.c. The formula is: According to the corresponding relationship between the correction parameter CorrectParam k,c and the tube voltage value, select one of the following two methods to establish a mapping model: Polynomial fitting method: Take the central voltage value of interval k, such as the average voltage of the k-th interval, as the independent variable x, and take the correction parameter CorrectParam k,c as the dependent variable y. Perform a fitting operation on all the (x, y) data points of channel c for all intervals k. Exemplarily: y = a2x 2 +a1x + a0, where a0, a1, and a2 are the coefficients obtained by fitting.

[0019] Piecewise mapping method: directly save the center voltage value of each interval k and the corresponding correction parameter CorrectParam k .c as discrete mapping pairs.

[0020] Save the above mapping model parameters independently by channel.

[0021] S300: Real-time obtain the feedback value of the tube voltage under the current exposure during the process of scanning the patient.

[0022] During the patient scanning stage, the feedback value of the tube voltage of the current exposure is obtained in real time, and its precise synchronization with the detector data is ensured. Specifically, a voltage sensor is built into the high-voltage generator of the CT device to monitor the actual output value of the tube voltage in real time. The system communicates with the high-voltage control device through a digital interface to obtain the feedback value of the tube voltage for each exposure. At the beginning of each exposure, the system sends an exposure trigger signal to the high-voltage control device to trigger the X-ray tube to discharge; the high-voltage device immediately returns the actual value of the current tube voltage after the discharge is completed, ensuring strict correspondence with the X-ray intensity data collected by the detector. During each exposure cycle, the actual value of the current tube voltage is read through the interface. According to the correction table saved in the pre-scan stage, the preset tube voltage range is extracted, and the feedback value of the tube voltage obtained during the patient scanning is compared with the pre-stored tube voltage range in the mapping model. If the feedback value of the tube voltage is less than the pre-stored minimum tube voltage value, the minimum tube voltage value is taken; if it is greater than the pre-stored maximum tube voltage value, the maximum tube voltage value is taken to determine the real-time feedback value of the corrected tube voltage. Finally, according to the real-time feedback value of the tube voltage and the mapping model in step S200, the real-time X-ray intensity ratio parameter is obtained.

[0023] Exemplarily, assume that the s = 500th exposure is performed during the patient scanning stage. After triggering the exposure, the system sends a trigger signal to the high-voltage device; the high-voltage device returns the tube voltage feedback value: 122.1 kV; the correction table range is [115.0 kV, 125.0 kV], and it is determined that the tube voltage feedback value is within the range; the tube voltage feedback value is passed to the correction module for querying the correction parameter in the mapping model; the detector channel data and the tube voltage feedback value are marked as the same exposure event.

[0024] Through the technical solution of step S300, the real-time and accurate acquisition of the tube voltage feedback value is realized, and the error problem caused by the traditional method relying on the preset tube voltage value is solved. It ensures the strict synchronization of the real-time tube voltage feedback value and the patient scanning data, provides a reliable input for subsequent dynamic correction, and finally improves the uniformity and consistency of CT images.

[0025] S400: Determine the corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage.

[0026] Before the start of the scan during the patient scan phase, the system loads the calibration model file generated during the pre-scan phase, including: polynomial coefficients or piecewise interval parameters, and records the pre-stored tube voltage range for all channels. First, determine the value of the tube voltage feedback value, that is, if the tube voltage feedback value is less than the pre-stored minimum tube voltage value, take the minimum tube voltage value; if it is greater than the pre-stored maximum tube voltage value, take the maximum tube voltage value. Determine the correction parameter for the interval according to the type of the calibration model, that is, the X-ray intensity ratio parameter.

[0027] For piecewise mapping, first perform interval positioning, that is, calculate the interval index corresponding to the real-time tube voltage. The calculation formula is: where kV_corrected is the effective value of the real-time tube voltage feedback value after boundary processing, kVMin is the minimum tube voltage value recorded during the pre-scan phase, and interval_step is the tube voltage segmentation interval. Further determine the interval range based on the calculated interval index. Read the correction parameter corresponding to the interval from the calibration table according to the interval range.

[0028] For polynomial fitting, first calculate the correction parameter using the pre-stored polynomial coefficients. The calculation formula is: CorrectParam c = a0 + a1 × kV_corrected + a2 × kV_corrected 2 .

[0029] After calculating the correction parameter, bind it to the detector data of the current exposure to form a calibration input.

[0030] S500: Correct the incident original X-ray intensity of each channel based on the X-ray intensity ratio parameter. During the patient scan phase, the correction parameter CorrectParam c obtained through the real-time tube voltage feedback value, combined with the reference channel intensity and the filter material parameters, dynamically corrects the incident original X-ray intensity of each channel. Specifically, perform bad pixel correction and air correction on the patient scan data to obtain the pre-processed detection intensity I d , that is, the X-ray intensity after attenuating through the scanned patient. Record the intensity RefC s of the pre-processed reference channel of the current exposure. Calculate the corrected incident original light intensity of the c-th channel according to the correction parameter The calculation formula is: where μ filter is the attenuation coefficient of the filter material at the current tube voltage, L ref is the path length of the reference channel passing through the filter material, and L s，c is the path length of the S-th row and the c-th channel passing through the filter material.

[0031] S600: Calculate the X-ray attenuation values of each channel passing through the object to be scanned, and perform image reconstruction based on the attenuation values.

[0032] Among them, the calculation formula for the X-ray attenuation value is: After calculating the attenuation value, correct it. Among them, b0, b1, and b2 are pre-stored hardening correction coefficients. The corrected attenuation value μ corrected，s，c is reorganized into a projection matrix P(θ, r) according to the scan angle and the detector position. Among them, θ is the scan angle, and r is the position index of the detector channel, and at the same time, ensure that the projection data format is consistent with the input requirements of the reconstruction algorithm.

[0033] Apply the Ram-Lak filter to the projection data P(θ, r) to perform a filtering operation: Among them, is the Fourier transform. The filtered projection data is back-projected into the reconstruction space to generate a reconstructed CT image:

[0034] In summary, the correction method for the X-ray intensity fluctuation caused by the CT tube voltage fluctuation proposed in this embodiment establishes the filtered intensity ratio relationship between each detector channel and the reference channel under different tube voltages through pre-scanning air data, and constructs a mapping model of the tube voltage and the correction parameter based on this (including piecewise mapping or polynomial fitting). During the patient scan, the tube voltage feedback value is obtained in real time, and the corresponding correction parameter is dynamically determined to correct the incident light intensity of each channel. Combining the hardening effect correction and the filtered back-projection / iterative reconstruction algorithm, it effectively solves the problem of attenuation value calculation error caused by the energy spectrum change and the inaccurate ratio relationship due to the tube voltage fluctuation in the traditional method, significantly improves the image uniformity, signal-to-noise ratio and reconstruction accuracy, and at the same time supports multi-hardware adaptation and real-time processing, ensuring that it can still be quickly corrected through the pre-stored model in the scenario where the high-voltage device has a high sampling frequency or a large fluctuation amplitude. Finally, it realizes the reconstruction of high-resolution and low-artifact CT images to meet the requirements of conventional and low-dose scans.

[0035] Reference Figure 2 , this embodiment further discloses a correction system for the X-ray intensity fluctuation under the CT tube voltage fluctuation, including: The intensity ratio calculation module 21 is used to call the pre-scanning conditions to scan the air data, and model and calculate the intensity ratio relationship of the X-rays of each detector channel and the reference channel at different tube voltage values after filtration, including: in the pre-scanning stage, calling the pre-scanning conditions to scan the air data and recording the tube voltage feedback value kVData and the X-ray intensity value AirDat0 of each detector channel for each exposure; preprocessing the X-ray intensity value AirDat0 of the detector channel in the air data to obtain preprocessed data AirDat1; calculating the ratio data AirDat2 of the X-ray intensity value of the reference channel to the preprocessed X-ray intensity value AirDat1 of each detector channel for each exposure; dividing the value range of the tube voltage feedback value kVData into multiple intervals with preset intervals, and statistically calculating the average intensity value MeanAirData of the ratio data AirDat2 in each interval; calculating the intensity ratio relationship of the X-rays after filtration between each detector channel and the reference channel in the interval corresponding to the tube voltage feedback value according to the average intensity value MeanAirData, and saving the ratio relationship as a tube voltage fluctuation correction table according to the interval for subsequent correction calls; The mapping model construction module 22 is used to establish a mapping model between the tube voltage value and the X-ray intensity ratio parameter of each detection channel and the reference channel based on the intensity ratio relationship, including: normalizing the intensity ratio relationship to obtain the correction parameter corresponding to each detector channel; performing interpolation or averaging on the correction parameters in each interval of the tube voltage feedback value to establish a piecewise mapping relationship between the tube voltage feedback value and the correction parameter; or performing polynomial fitting on the corresponding relationship between the intensity ratio relationship and the tube voltage feedback value to obtain a mathematical function representing the mapping relationship between the tube voltage feedback value and the correction parameter; saving the parameters of the piecewise mapping relationship or the fitting function and the corresponding interval of the tube voltage feedback value as a correction model file; The data acquisition module 23 is used to obtain the feedback value of the tube voltage at the current exposure in real time during the scanning of the patient. A proportional parameter determination module 24, configured to determine a corresponding X-ray intensity proportional parameter from the mapping model based on the feedback value of the tube voltage, including: importing the tube voltage fluctuation correction table according to a preset scanning condition; comparing the feedback value of the tube voltage obtained during scanning of a patient with the pre-stored tube voltage range in the mapping model, if the feedback value of the tube voltage is less than the pre-stored minimum tube voltage value, then taking the minimum tube voltage value, and if it is greater than the pre-stored maximum tube voltage value, then taking the maximum tube voltage value, to determine a corrected real-time feedback value of the tube voltage; obtaining a real-time X-ray intensity proportional parameter according to the real-time feedback value of the tube voltage and the mapping model, including: if the mapping model is a piecewise mapping relationship, then directly taking the pre-stored proportional parameter corresponding to the section interval according to the section interval to which the tube voltage feedback value belongs; or if the mapping model is a polynomial function, then substituting the tube voltage feedback value into the mathematical function to calculate a corresponding X-ray intensity proportional parameter; An optical intensity correction module 25, configured to correct the incident original X-ray optical intensity of each channel based on the X-ray intensity proportional parameter; An image reconstruction module 26, configured to calculate the X-ray attenuation value of each channel passing through the object to be scanned, and perform image reconstruction based on the attenuation value, including: calculating the X-ray attenuation value of each channel through the corrected incident original X-ray optical intensity and the X-ray intensity after attenuation detected by a detector during patient scanning, and the formula is: Wherein, I d is the X-ray intensity after attenuation detected by the detector, is the corrected incident original X-ray optical intensity; performing X-ray hardening correction on the attenuation value μ s，c to eliminate the attenuation error caused by the hardening effect when high-energy X-rays penetrate materials; recombining the corrected attenuation value μ s，c into a projection data format to match the input requirements of the image reconstruction algorithm; applying a filtered backprojection algorithm or an iterative reconstruction algorithm to the recombined projection data to reconstruct and generate a CT image of the object to be scanned.

[0036] Figure 3 The figure is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. As Figure 3 shown, the electronic device 50 includes: a processor 501 (processor), a memory 502 (memory), and a bus 503; Among them, the processor 501 and the memory 502 communicate with each other through the bus 503; the processor 501 is configured to call program instructions in the memory 502 to execute the methods provided by the above-mentioned method embodiments.

[0037] This embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute the methods provided by the above-described method embodiments.

[0038] Those of ordinary skill in the art will understand that all or part of the steps of implementing the above method embodiments can be accomplished by hardware associated with program instructions. The foregoing program can be stored in a computer-readable storage medium, and when executed, includes the steps of the above method embodiments; and the foregoing storage medium includes: ROM, RAM, magnetic disk, or optical disk, etc., all storage media that can store program code.

[0039] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

[0040] From the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, also by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0041] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A correction method for X-ray intensity fluctuation under CT tube voltage fluctuation, characterized in that, The method includes: Scanning air data according to pre-scanning conditions, and calculating the intensity ratio relationship of X-rays of each detector channel and a reference channel at different CT tube voltage values based on the air data; Based on the intensity ratio relationship, establishing a mapping model, which includes the mapping relationship between the CT tube voltage value and the X-ray intensity ratio parameter of each detection channel, and the mapping relationship between the CT tube voltage value and the X-ray intensity ratio parameter of each reference channel; During the process of scanning a patient, obtaining the feedback value of the tube voltage under the current exposure in real time; Determining the corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage; Correcting the incident original X-ray light intensity of each detector channel based on the X-ray intensity ratio parameter; Calculating the X-ray attenuation value of each detector channel passing through the object to be scanned, and performing image reconstruction based on the attenuation value.

2. The correction method for X-ray intensity fluctuation under CT tube voltage fluctuation according to claim 1, characterized in that, The step of calling pre-scanning conditions to scan air data for modeling and calculating the intensity ratio relationship of X-rays of each detector channel and a reference channel at different tube voltage values includes: In the pre-scanning stage, calling pre-scanning conditions to scan air data and recording the tube voltage feedback value kVData of each exposure and the X-ray intensity value AirDat0 of each detector channel; Preprocessing the X-ray intensity value AirDat0 of the detector channel in the air data to obtain preprocessed data AirDat1; Calculating the ratio data AirDat2 of the X-ray intensity value of the reference channel of each exposure to the preprocessed X-ray intensity value AirDat1 of each detector channel; Dividing the value range of the tube voltage feedback value kVData into multiple intervals with preset intervals, and statistically calculating the average intensity value MeanAirData of the ratio data AirDat2 in each interval; Calculating the intensity ratio relationship of X-rays after filtration of each detector channel and the reference channel in the interval corresponding to the tube voltage feedback value based on the average intensity value MeanAirData.

3. The correction method for X-ray intensity fluctuation under CT tube voltage fluctuation according to claim 2, characterized in that The step of establishing a mapping model between the tube voltage value and the X-ray intensity ratio parameter of each detection channel and the reference channel based on the intensity ratio relationship includes: Normalizing the intensity ratio relationship to obtain the correction parameter corresponding to each detector channel; Performing interpolation or averaging processing on the correction parameters in each interval of the tube voltage feedback value to establish a piecewise mapping relationship between the tube voltage feedback value and the correction parameter; or Performing polynomial fitting on the corresponding relationship between the intensity ratio relationship and the tube voltage feedback value to obtain a mathematical function representing the mapping relationship between the tube voltage feedback value and the correction parameter; Saving the parameters of the piecewise mapping relationship or the fitting function and the corresponding interval of the tube voltage feedback value as a calibration model file.

4. The correction method for X-ray intensity fluctuation under CT tube voltage fluctuation according to claim 3, characterized in that, The step of determining the corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage includes: Compare the tube voltage feedback value obtained when scanning the patient with the pre-stored tube voltage range in the mapping model. If the tube voltage feedback value is less than the pre-stored minimum tube voltage value, take the minimum tube voltage value; if it is greater than the pre-stored maximum tube voltage value, take the maximum tube voltage value to determine the corrected real-time feedback value of the tube voltage; Obtain the real-time X-ray intensity ratio parameter according to the real-time feedback value of the tube voltage and the mapping model.

5. The correction method for the X-ray intensity fluctuation under the CT tube voltage fluctuation according to claim 4, wherein The obtaining the real-time X-ray intensity ratio parameter according to the real-time feedback value of the tube voltage and the mapping model includes: If the mapping model is a piecewise mapping relationship, directly take the pre-stored ratio parameter corresponding to the interval according to the piecewise interval to which the tube voltage feedback value belongs; or If the mapping model is a polynomial function, substitute the tube voltage feedback value into the mathematical function to calculate the corresponding X-ray intensity ratio parameter.

6. The correction method for X-ray intensity fluctuation under CT tube voltage fluctuation according to claim 1, characterized in that, The calculating the X-ray attenuation value of each channel passing through the object to be scanned and performing image reconstruction based on the attenuation value includes: Calculate the X-ray attenuation value of each channel based on the corrected incident original X-ray intensity and the X-ray intensity after attenuation detected by the detector during patient scanning. The formula is: Where, I d is the X-ray intensity after attenuation detected by the detector, is the corrected incident original X-ray intensity; For the attenuation value μ s,c perform X-ray hardening correction to eliminate the attenuation error caused by the hardening effect when high-energy X-rays penetrate the material; Recombine the corrected attenuation value μ s,c into a projection data format to match the input requirements of the image reconstruction algorithm; Apply a filtered back-projection algorithm or an iterative reconstruction algorithm to the recombined attenuation value to reconstruct the CT image of the object to be scanned.

7. A correction system for X-ray intensity fluctuation under CT tube voltage fluctuation, characterized in that, Include: An intensity ratio relationship calculation module for scanning air data according to pre-scanning conditions and calculating the intensity ratio relationship of the X-rays of each detector channel and the reference channel after filtering under different CT tube voltage values according to the air data; A mapping model construction module for establishing a mapping model based on the intensity ratio relationship, where the mapping model includes the mapping relationship between the CT tube voltage value and the X-ray intensity ratio parameter of each detection channel, and the mapping relationship between the CT tube voltage value and the X-ray intensity ratio parameter of each reference channel; A data acquisition module for obtaining the feedback value of the tube voltage under the current exposure in real time during the scanning of the patient; A ratio parameter determination module for determining the corresponding X-ray intensity ratio parameter from the mapping model based on the feedback value of the tube voltage; An optical intensity correction module for correcting the incident original X-ray intensity of each detector channel based on the X-ray intensity ratio parameter; An image reconstruction module for calculating the X-ray attenuation value of each detector channel passing through the object to be scanned and performing image reconstruction based on the attenuation value.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of claims 1-6 above is implemented.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the method described in any one of claims 1-6 above is implemented.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, the method described in any one of claims 1-6 above is implemented.

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