A method and system for correcting artifacts in computed tomography images based on the fbp algorithm

Abstract

The application provides a computer tomography image artifact correction method and system based on an FBP algorithm, relates to the image processing technical field of a CT scanning device of a medical instrument, and calculates a ring artifact correction table through water film scanning. By using the correction table, the problems of fine ring artifacts, ring dark band artifacts and ring bright band artifacts in the image reconstructed by the CT scanning device are solved.

Description

Technical Field

[0001] This invention relates to the field of image processing technology for medical device CT scanning equipment, specifically to a method for eliminating CT artifacts based on a correction table, and more particularly to a method and system for correcting computed tomography image artifacts based on the FBP algorithm. Background Technology

[0002] Medical imaging equipment (such as computed tomography (CT) equipment, C-arm, etc.) often produces concentric ring artifacts in reconstructed images, which can adversely affect image quality.

[0003] Chinese patent application CN110111318B discloses a method and system for detecting annular artifacts, comprising: acquiring an original image; mapping pixels in the original image to a polar coordinate image; determining a region to be protected in the polar coordinate image; smoothing at least one region in the polar coordinate image other than the region to be protected to obtain a smoothed image; generating a residual image based on the polar coordinate image and the smoothed image; and determining the position of the annular artifact in the original image based on the residual image. This correction method requires polar coordinate transformation first, and the operation steps are relatively complex. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for correcting artifacts in computed tomography images based on the FBP algorithm.

[0005] According to the present invention, a method and system for correcting artifacts in computed tomography images based on the FBP algorithm are provided, the scheme of which is as follows:

[0006] Firstly, a method for correcting artifacts in computed tomography images based on the FBP algorithm is provided, the method comprising:

[0007] Step S1: Obtain the projection data PhantomProj of the water film Phantom filled with distilled water in the container by CT scanning, and then obtain the projection data AirProj of the air.

[0008] Step S2: Read the projection data of the water film (PhantomProj) and the projection data of the air (AirProj), divide the projection data of the water film and the air to obtain the data phantomDivAirData, and adjust the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X] format;

[0009] Step S3: Perform Gaussian filtering on the data phantomDivAirData to obtain smooth water film projection data SmoothPhantomData. Obtain the difference SubPhantomData between the data phantomDivAirData and the water film projection data SmoothPhantomData.

[0010] Step S4: Obtain the unit artifact of each pixel by using the difference SubPhantomData and the water film projection data SmoothPhantomData. These unit artifacts are composed of OrgCorTable.

[0011] Step S5: Binarize the data phantomDivAirData to obtain the binarized and smoothed water film data Im2bwPhantomProj;

[0012] Step S6: Obtain the preliminary artifact correction table CorTable using the binarized water film data Im2bwPhantomProj and OrgCorTable;

[0013] Step S7: Average the preliminary artifact correction table CorTable on the Y-axis and Z-axis to obtain X averaged correction values. The X correction values ​​form a one-dimensional array MeanCorTable. Change the data format to float32 and output it as a ring artifact correction table in .dat format.

[0014] Step S8: Deploy the ring artifact correction table to the CT system for another scan. In the raw data preprocessing stage, before performing X-ray hardening correction, nonlinear correction and other preprocessing corrections, multiply the pixel value of each pixel on the detector channel corresponding to each frame by the value of the corresponding channel of the correction table, and then reconstruct it after other corrections to obtain the artifact-free water film image.

[0015] Preferably, the scanning parameters in step S1 are 120kVp and 200mAs.

[0016] Preferably, in step S2, the data phantomDivAirData format is adjusted to a three-dimensional matrix [Z,Y,X] format. The Z-axis of the data phantomDivAirData is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling.

[0017] Preferably, the deviation value SubPhantomData of the water film in the projection data in step S3 is calculated using the following formula:

[0018] SubPhantomData[z,y,x]=phantomDivAirData[z,y,x]-SmoothPhantomData[z,y,x].

[0019] Preferably, the OrgCorTable calculation formula for the unit artifact composition in step S4 is:

[0020] OrgCorTable[z,y,x]=SubPhantomData[z,y,x] / SmoothPhantomData[z,y,x].

[0021] Preferably, step S5 includes:

[0022] SmoothPhantomData[z,y,x]≤T represents the background region, while the region with values ​​greater than or equal to T represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows:

[0023]

[0024] T=max{SmoothPhantomData[z,y,x]} / 4

[0025] In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which is one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve.

[0026] Preferably, step S6 includes:

[0027] The binarized Im2bwPhantomProj is multiplied by the OrgCorTable at corresponding positions, retaining only the valid data components containing the OrgCorTable, to obtain the preliminary artifact correction table CorTable, specifically represented by the following formula:

[0028] CorTable[z,y,x]=Im2bwPhantomPro[z,y,x]*OrgCorTable[z,y,x].

[0029] Preferably, in step S7, a loop is used to iterate through the values ​​of each vertical axis and each vertical axis to calculate the average value of the non-zero values ​​in the vertical axis and vertical axis. If a value of 0 is found in either the vertical axis or the vertical axis, it is skipped and not included in the calculation.

[0030] Secondly, a system for correcting artifacts in computed tomography images based on the FBP algorithm is provided, the system comprising:

[0031] Module M1: Obtains the projection data PhantomProj of the water film Phantom in the container filled with distilled water by CT scanning, and then obtains the projection data AirProj of the air.

[0032] Module M2: Reads the projection data of the water film (PhantomProj) and the projection data of the air (AirProj), divides the projection data of the water film and the air to obtain the data phantomDivAirData, and adjusts the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X] format;

[0033] Module M3: Performs Gaussian filtering on the data phantomDivAirData to obtain smooth water film projection data SmoothPhantomData, and obtains the difference SubPhantomData between the data phantomDivAirData and the water film projection data SmoothPhantomData.

[0034] Module M4: The unit artifacts of each pixel are obtained by using the difference SubPhantomData and the water film projection data SmoothPhantomData, and these unit artifacts are composed of OrgCorTable;

[0035] Module M5: Binarizes the data phantomDivAirData to obtain the binarized and smoothed water film data Im2bwPhantomProj;

[0036] Module M6: Obtain the preliminary artifact correction table CorTable from the binarized water film data Im2bwPhantomProj and OrgCorTable;

[0037] Module M7: Averages the initial artifact correction table CorTable on the Y and Z axes to obtain X averaged correction values. These X correction values ​​form a one-dimensional array MeanCorTable. The data format is changed to float32, and the output is a ring-shaped artifact correction table in .dat format.

[0038] Module M8: Deploy the ring artifact correction table to the CT system for rescanning. In the raw data preprocessing stage, before performing X-ray hardening correction, nonlinear correction, and other preprocessing corrections, multiply the pixel value of each pixel on the detector channel corresponding to each frame by the value of the corresponding channel of the correction table. After other corrections, reconstruct the image to obtain the artifact-free water film image.

[0039] Preferably, the scanning parameters in module M1 are 120kVp and 200mAs;

[0040] In module M2, the data phantomDivAirData format is adjusted to a three-dimensional matrix [Z,Y,X] format. The Z-axis of the data phantomDivAirData is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling.

[0041] The deviation value SubPhantomData of the water film in module M3 based on the projection data is calculated using the following formula:

[0042] SubPhantomData[z,y,x]=phantomDivAirData[z,y,x]-SmoothPhantomData[z,y,x];

[0043] The formula for calculating the OrgCorTable, which represents the unit artifacts in module M4, is as follows:

[0044] OrgCorTable[z,y,x]=SubPhantomData[z,y,x] / SmoothPhantomData[z,y,x];

[0045] The module M5 includes:

[0046] SmoothPhantomData[z,y,x]≤T represents the background region, while the region with values ​​greater than or equal to T represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows:

[0047]

[0048] T=max{SmoothPhantomData[z,y,x]} / 4

[0049] In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which is one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve.

[0050] The module M6 includes:

[0051] The binarized Im2bwPhantomProj is multiplied by the OrgCorTable at corresponding positions, retaining only the valid data components containing the OrgCorTable, to obtain the preliminary artifact correction table CorTable, specifically represented by the following formula:

[0052] CorTable[z,y,x]=Im2bwPhantomPro[z,y,x]*OrgCorTable[z,y,x];

[0053] In module M7, a loop is used to iterate through the values ​​of each vertical axis and each vertical axis, and the average value of the non-zero values ​​of the vertical axis and vertical axis is calculated. If a value of 0 is found in either the vertical axis or the vertical axis, it is skipped and not included in the calculation.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] By utilizing the projection data of water film and air from CT scans and performing some numerical calculations, an artifact correction table is obtained. After this correction table is debugged in the CT equipment code, it can maximize the resolution of various artifacts in the images reconstructed by CT scanning devices, including but not limited to fine ring artifacts, annular dark band artifacts, annular bright band artifacts, and other artifacts caused by insufficient detector X-ray hardening correction and changes in detector nonlinear performance. This enhances the quality of image reconstruction and improves economic efficiency at a low cost.

[0056] Other beneficial effects of the present invention will be explained in detail through the introduction of specific technical features and technical solutions in specific embodiments. Those skilled in the art should be able to understand the beneficial technical effects brought about by these technical features and technical solutions through the introduction of these technical features and technical solutions. Attached Figure Description

[0057] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0058] Figure 1 This is a flowchart of the present invention;

[0059] Figure 2 The image below is the original projection data of the water film PhantomProj at z=0. All images below are projection images with the vertical axis z=0, i.e., the first frame.

[0060] Figure 3 The projection image of phantomDivAirData is obtained by dividing the projection data of the water film and the air.

[0061] Figure 4 This is the projected image of the binarized phantomDivAirData;

[0062] Figure 5 This is the value of phantomDivAirData when z is 0 and y is 16, which is the 832nd value in row 16 of frame 0;

[0063] Figure 6 The graph is a comparison of the binarized Im2bwPhantomProj image before and after median filtering, which is the binarized image of the 16th row of the 0th layer.

[0064] Figure 7 The final correction coefficient value is MeanCorTable;

[0065] Figure 8 This is a comparison image before and after artifact removal. Detailed Implementation

[0066] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0067] This invention provides a method for correcting artifacts in computed tomography images based on the FBP algorithm. It can automatically calculate an artifact correction table based on the projection data of the offset water film, and then correct the CT image according to the correction table, thereby ensuring the quality of image reconstruction. (Refer to...) Figure 1 As shown, the method specifically includes:

[0068] Step S1: A 20cm water film (Phantom) filled with distilled water in an acrylic container was scanned using CT. Projection data (PhantomProj) of the water film was obtained, followed by projection data (AirProj) of the air. The scanning parameters were 120kVp and 200mAs. The reconstructed projection data of the water film contained noticeable annular artifacts, annular dark band artifacts, annular bright band artifacts, and other artifacts caused by insufficient detector X-ray hardening correction and changes in detector nonlinear performance.

[0069] Step S2: Read the projection data of the water film (PhantomProj) and the projection data of the air (AirProj). Divide the projection data of the water film and the air to obtain the data phantomDivAirData. Adjust the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X] format. The Z-axis of this data is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling.

[0070] Step S3: Perform Gaussian filtering on phantomDivAirData to obtain smooth water film projection data SmoothPhantomData. Then, subtract SmoothPhantomData from phantomDivAirData to obtain the deviation value SubPhantomData of the water film in the projection data. The calculation formula is as follows:

[0071] SubPhantomData[z,y,x]=phantomDivAirData[z,y,x]-SmoothPhantomData[z,y,x].

[0072] Step S4: Divide SubPhantomData and SmoothPhantomData at the corresponding data points to obtain the "unit artifact" for each pixel. These "unit artifacts" form OrgCorTable.

[0073] The calculation formula is:

[0074] OrgCorTable[z,y,x]=SubPhantomData[z,y,x] / SmoothPhantomData[z,y,x].

[0075] Step S5: Binarize phantomDivAirData. The binarization threshold is one-quarter of the maximum value of phantomDivAirData, to obtain the binarized and smoothed water film data Im2bwPhantomProj.

[0076] SmoothPhantomData[z,y,x]≤T represents the background region, while the region with values ​​greater than or equal to T represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows:

[0077]

[0078] T=max{SmoothPhantomData[z,y,x]} / 4

[0079] In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which has been experimentally determined to be one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve.

[0080] Step S6: Multiply the binarized Im2bwPhantomProj with OrgCorTable at the corresponding positions, retaining only the valid data components containing OrgCorTable, to obtain the preliminary artifact correction table CorTable.

[0081] The specific formula is as follows:

[0082] CorTable[z,y,x]=Im2bwPhantomPro[z,y,x]*OrgCorTable[z,y,x].

[0083] This step is to ensure that the value of the correction table is also 0, so as to reduce the error caused by the 0 value in the projection data.

[0084] Step S7: Average the initial artifact correction table CorTable on the Y and Z axes to obtain X averaged correction values. These X correction values ​​form a one-dimensional array MeanCorTable. Change the data format to float32 and output it as a .dat format annular artifact correction table. In this step S7, a loop iterates through the values ​​of each vertical axis and calculates the average of the non-zero values ​​on that axis. If a value on either the vertical or y-axis is 0, it is skipped and not included in the calculation.

[0085] Step S8: Deploy the ring artifact correction table to the CT system and scan again. In the raw data preprocessing stage, before performing X-ray hardening correction, nonlinear correction and other preprocessing corrections, multiply the pixel value of each detector channel corresponding to each frame by the value of the corresponding channel of the correction table, and then reconstruct after other corrections to obtain the water film image after artifact removal.

[0086] Reference Figure 2 The image shown is a projection data image of the first water film. All other images below are image data of the first layer of the water film. Figure 2 It can be seen that the background noise of this water film is relatively high. (Refer to...) Figure 3 The image shown is the first projection data image after the water film separates from the air phase. Figure 3 It can be seen that this image numerical calculation can eliminate the grid pattern caused by the edges of the detector elements. (Refer to...) Figure 4 As shown, this is the binarized projection image of SmoothPhantomData, derived from... Figure 4 This value can eliminate the values ​​at the edge of the water film, removing the influence caused by these values. (Refer to...) Figure 5 The image shows the 832 values ​​in row 16 of frame 0 of phantomDivAirData, generated by... Figure 5 It can be seen that the projected data of the water film contains a considerable amount of "burrs". (Refer to...) Figure 6 The image shown is a graph of the binarized Im2bwPhantomProj image at layer 0, row 16. Figure a is the binarized image before median filtering, and Figure b is the binarized graph after median filtering. Median filtering removes values ​​with large fluctuations at the water film edge. (Refer to...) Figure 7 The image shows the final correction coefficient value MeanCorTable obtained after averaging. This value is output and debugged in the CT image reconstruction code. After successful debugging, the water film phantom is rescanned according to the original scanning parameters. (Refer to...) Figure 8 As shown, the images are comparisons before and after artifact removal. Figure a is the water film tomographic image before removing the ring artifacts, and Figure b is the water film tomographic image after removing the artifacts. It can be seen that the ring artifacts have been greatly improved.

[0087] This invention also provides a system for correcting computed tomography (CT) image artifacts based on the FBP algorithm. This system can be implemented by executing the steps of the FBP algorithm-based CT image artifact correction method. Therefore, those skilled in the art can understand the FBP algorithm-based CT image artifact correction method as a preferred embodiment of the FBP algorithm-based CT image artifact correction system. The system specifically includes:

[0088] Module M1: Obtains the projection data PhantomProj of the water film Phantom in the container filled with distilled water by CT scanning, and then obtains the projection data AirProj of the air.

[0089] Module M2: Reads the projection data of the water film (PhantomProj) and the projection data of the air (AirProj), divides the projection data of the water film and the air to obtain the data phantomDivAirData, and adjusts the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X].

[0090] Module M3: Performs Gaussian filtering on the phantomDivAirData to obtain smooth water film projection data SmoothPhantomData. The difference between the phantomDivAirData and the water film projection data SmoothPhantomData is obtained as SubPhantomData.

[0091] Module M4: The unit artifacts of each pixel are obtained by using the difference SubPhantomData and the water film projection data SmoothPhantomData. These unit artifacts are composed of OrgCorTable.

[0092] Module M5: Binarizes the data phantomDivAirData to obtain the binarized and smoothed water film data Im2bwPhantomProj.

[0093] Module M6: Obtain the preliminary artifact correction table CorTable using the binarized water film data Im2bwPhantomProj and OrgCorTable.

[0094] Module M7: Averages the initial artifact correction table CorTable on the Y and Z axes to obtain X averaged correction values. These X correction values ​​form a one-dimensional array MeanCorTable. The data format is changed to float32, and the output is a ring-shaped artifact correction table in .dat format.

[0095] Module M8: Deploys the ring artifact correction table to the CT system for rescanning. During the raw data preprocessing stage, before performing X-ray hardening correction, nonlinear correction, and other preprocessing corrections, multiplies the pixel value of each detector channel corresponding to each frame by the value of the corresponding channel of the correction table. After other corrections, it is reconstructed to obtain the artifact-free water film image.

[0096] Specifically, the scan parameters in module M1 are 120kVp and 200mAs;

[0097] In module M2, the phantomDivAirData data format is adjusted to a three-dimensional matrix [Z,Y,X] format. The Z-axis of the phantomDivAirData data is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling.

[0098] The deviation value of the water film in the projection data, SubPhantomData, in module M3 is calculated using the following formula:

[0099] SubPhantomData[z,y,x]=phantomDivAirData[z,y,x]-SmoothPhantomData[z,y,x];

[0100] The formula for calculating the OrgCorTable, which represents the unit artifacts in module M4, is as follows:

[0101] OrgCorTable[z,y,x]=SubPhantomData[z,y,x] / SmoothPhantomData[z,y,x];

[0102] Module M5 specifically includes: SmoothPhantomData[z,y,x]≤T represents the background region, and otherwise represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows:

[0103]

[0104] T=max{SmoothPhantomData[z,y,x]} / 4

[0105] In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which is one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve.

[0106] Module M6 specifically includes: multiplying the binarized Im2bwPhantomProj with OrgCorTable at corresponding positions, retaining only the valid data components containing OrgCorTable, to obtain the preliminary artifact correction table CorTable, with the specific formula as follows:

[0107] CorTable[z,y,x]=Im2bwPhantomPro[z,y,x]*OrgCorTable[z,y,x];

[0108] In module M7, a loop is used to iterate through the values ​​of each vertical axis and each vertical axis, and the average value of the non-zero values ​​of the vertical axis and vertical axis is calculated. If a value of 0 is found in either the vertical axis or the vertical axis, it is skipped and not included in the calculation.

[0109] This invention provides a method and system for correcting artifacts in computed tomography images based on the FBP algorithm. After performing some numerical calculations using the projection data of the water film in CT scans, an artifact correction table is obtained. After this correction table is debugged in the code of the CT device, it can effectively solve various artifact problems in the images reconstructed by the CT scanning device, including but not limited to fine ring artifacts, annular dark band artifacts, annular bright band artifacts, and other artifacts caused by insufficient detector X-ray hardening correction and changes in detector nonlinear performance.

[0110] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0111] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for correcting artifacts in computed tomography images based on the FBP algorithm, characterized in that, include: Step S1: Obtain the projection data PhantomProj of the water film Phantom in the container filled with distilled water by CT scanning, and then obtain the projection data AirProj of the air. Step S2: Read the projection data of the water film (PhantomProj) and the projection data of the air (AirProj), divide the projection data of the water film and the air to obtain the data phantomDivAirData, and adjust the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X] format; Step S3: Perform Gaussian filtering on the data phantomDivAirData to obtain smooth water film projection data SmoothPhantomData. Obtain the difference SubPhantomData between the data phantomDivAirData and the water film projection data SmoothPhantomData. Step S4: Obtain the unit artifact of each pixel by using the difference SubPhantomData and the water film projection data SmoothPhantomData. These unit artifacts are composed of OrgCorTable. Step S5: Binarize the data phantomDivAirData to obtain the binarized and smoothed water film data Im2bwPhantomProj; Step S6: Obtain the preliminary artifact correction table CorTable using the binarized water film data Im2bwPhantomProj and OrgCorTable; Step S7: Average the preliminary artifact correction table CorTable on the Y-axis and Z-axis to obtain X averaged correction values. The X correction values ​​form a one-dimensional array MeanCorTable. Change the data format to float32 and output it as a ring artifact correction table in .dat format. Step S8: Deploy the ring artifact correction table to the CT system and scan again. In the raw data preprocessing stage, before performing X-ray hardening correction and nonlinear correction, multiply the pixel value of each pixel on the detector channel corresponding to each frame by the value of the corresponding channel of the correction table, and then reconstruct after correction to obtain the water film image after artifact removal. Step S5 includes: SmoothPhantomData[z,y,x]≤T represents the background region, while the region with values ​​greater than or equal to T represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows: In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which is one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve. Step S6 includes: The binarized Im2bwPhantomProj is multiplied by the OrgCorTable at corresponding positions, retaining only the valid data components containing the OrgCorTable, to obtain the preliminary artifact correction table CorTable, specifically represented by the following formula: 。 2. The method for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 1, characterized in that, The scanning parameters in step S1 are 120 kVp and 200 mAs.

3. The method for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 1, characterized in that, In step S2, the data phantomDivAirData format is adjusted to a three-dimensional matrix [Z,Y,X] format. The Z-axis of the data phantomDivAirData is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling.

4. The method for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 1, characterized in that, The deviation value SubPhantomData of the water film in the projection data in step S3 is calculated using the following formula: 。 5. The method for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 1, characterized in that, The formula for calculating the OrgCorTable composed of unit artifacts in step S4 is as follows: 。 6. The method for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 1, characterized in that, In step S7, a loop is used to iterate through the values ​​of each vertical axis and each vertical axis to calculate the average value of the non-zero values ​​in the vertical axis and vertical axis. If a value of 0 is found in either the vertical axis or the vertical axis, it is skipped and not included in the calculation.

7. A system for correcting artifacts in computed tomography images based on the FBP algorithm, characterized in that, include: Module M1: Obtains the projection data PhantomProj of the water film Phantom in the container filled with distilled water by CT scanning, and then obtains the projection data AirProj of the air. Module M2: Reads the projection data of the water film (PhantomProj) and the projection data of the air (AirProj), divides the projection data of the water film and the air to obtain the data phantomDivAirData, and adjusts the format of the data phantomDivAirData to a three-dimensional matrix [Z,Y,X] format; Module M3: Performs Gaussian filtering on the data phantomDivAirData to obtain smooth water film projection data SmoothPhantomData, and obtains the difference SubPhantomData between the data phantomDivAirData and the water film projection data SmoothPhantomData. Module M4: The unit artifacts of each pixel are obtained by using the difference SubPhantomData and the water film projection data SmoothPhantomData, and these unit artifacts are composed of OrgCorTable; Module M5: Binarizes the data phantomDivAirData to obtain the binarized and smoothed water film data Im2bwPhantomProj; Module M6: Obtain the preliminary artifact correction table CorTable from the binarized water film data Im2bwPhantomProj and OrgCorTable; Module M7: Averages the initial artifact correction table CorTable on the Y and Z axes to obtain X averaged correction values. These X correction values ​​form a one-dimensional array MeanCorTable. The data format is changed to float32, and the output is a ring-shaped artifact correction table in .dat format. Module M8: Deploy the ring artifact correction table to the CT system for rescanning. In the raw data preprocessing stage, before performing X-ray hardening correction and nonlinear correction, multiply the pixel value of each pixel on the detector channel corresponding to each frame by the value of the corresponding channel of the correction table, and then reconstruct the image after correction to obtain the artifact-free water film image. The module M5 includes: SmoothPhantomData[z,y,x]≤T represents the background region, while the region with values ​​greater than or equal to T represents the selected water film region. T is an abbreviation for ThresholdValue, and the specific formula is as follows: In the formula, Im2bwPhantomProj[z,y,x] is the smoothed binarized water film projection data; the horizontal axis x, the vertical axis y, and the vertical axis z are the positions of the data in the three directions; T is the binarization threshold, which is one-quarter of the maximum value of the SmoothPhantomData data. After binarizing phantomDivAirData, median filtering is then applied to obtain a smoothed binarized curve. The module M6 includes: The binarized Im2bwPhantomProj is multiplied by the OrgCorTable at corresponding positions, retaining only the valid data components containing the OrgCorTable, to obtain the preliminary artifact correction table CorTable, specifically represented by the following formula: 。 8. The system for correcting artifacts in computed tomography images based on the FBP algorithm according to claim 7, characterized in that, The scanning parameters in module M1 are 120 kVp and 200 mAs. In module M2, the data phantomDivAirData format is adjusted to a three-dimensional matrix [Z,Y,X] format. The Z-axis of the data phantomDivAirData is determined by the CT single-loop sampling rate, the Y-axis is determined by the number of detector rows, and the X-axis is determined by the number of CT detectors or the detector axis sampling width after resampling. The deviation value SubPhantomData of the water film in module M3 based on the projection data is calculated using the following formula: ； The formula for calculating the OrgCorTable, which represents the unit artifacts in module M4, is as follows: ； In module M7, a loop is used to iterate through the values ​​of each vertical axis and each vertical axis, and the average value of the non-zero values ​​of the vertical axis and vertical axis is calculated. If a value of 0 is found in either the vertical axis or the vertical axis, it is skipped and not included in the calculation.

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