Cone beam CT scattering correction method and device, electronic equipment and storage medium

Abstract

The invention provides a cone beam CT scattering correction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring DR projections of two groups of workpieces acquired by acquisition equipment and a single DR projection of a scatter correction plate; generating a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; obtaining a discrete scattering signal set based on the first DR projection set and the second DR projection set; performing image processing on the single DR projection to obtain a hole area; based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with the CS theory, solving is carried out through an ADMM algorithm, and a complete scattering signal is reconstructed; and deducting the complete scattering signal in the first DR projection set to obtain a corrected DR projection. The method can improve the accuracy of scatter correction.

Description

Technical Field

[0001] The present application relates to the field of CT imaging technology, and in particular to a cone-beam CT scatter correction method, device, electronic device and storage medium. Background Art

[0002] In the process of X-ray imaging, workpieces such as aircraft engine turbine blades are inspected using computer tomography (CT). Due to their high density and complex geometry, turbine blades are prone to noise problems during scanning, resulting in artifacts in the reconstructed image. Scattering artifacts and projection superposition are important factors that restrict imaging quality. Most artifacts are caused by the Compton effect, which causes the photons received by the detector to include initial photons and scattered photons, resulting in a deviation between the measurement results and the actual intensity measurement results, reducing the image contrast, affecting the image quality, and blurring the boundary and internal structure information. Therefore, in order to improve image quality and obtain clearer image details, it is necessary to perform scattering correction on cone beam CT images.

[0003] Scattering correction plates are used to perform scattering correction of digital ray (DR) projection images. Currently, there are methods such as beam stop array method (BSA), beam hole array method (BHA) and beam stop grid method (BSG). Taking the BSA method as an example, the correction plate is made of a plexiglass plate, and evenly arranged lead blocks are embedded in it. The correction plate is placed in front of the detector. The light intensity detected at the position corresponding to the lead block on the detector is generated by scattered rays. The signal value at the centroid of the corresponding lead block is interpolated in two dimensions and extended to the entire plane to obtain a scattering intensity distribution map. The disadvantage of this method is that due to the occlusion of the correction plate, the detector receives less data, and only the signal at the centroid is selected for interpolation, resulting in a lower accuracy rate of the fitted scattering signal. Summary of the invention

[0004] In view of this, the present application provides a cone-beam CT scatter correction method, device, electronic device and storage medium, which can improve the accuracy of scatter correction.

[0005] To solve the above technical problems, the technical solution of this application is implemented as follows:

[0006] In one embodiment, a cone-beam CT scatter correction method is provided, the method comprising:

[0007] Acquire DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate;

[0008] Generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scatter signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is not added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added;

[0009] Performing image processing on the single DR projection to obtain a hole area;

[0010] Based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with CS theory, and the ADMM algorithm is used to solve the model and reconstruct the complete scattering signal;

[0011] The complete scatter signal is deducted from the first DR projection set to obtain a corrected DR projection.

[0012] Wherein, the acquisition device acquires DR projections of two groups of workpieces when there is no relative displacement of the workpiece positions and the scanning parameters are consistent.

[0013] The performing image processing on the single DR projection includes:

[0014] Binarization, contour extraction, contour tracking and circle fitting processing.

[0015] The L1 norm constraint model promotes sparsity by introducing the L1 norm constraint, so that the gradients of the complete scattering signal in the horizontal and vertical directions are equal to the corresponding sparse vectors respectively.

[0016] Wherein, the L1 norm constraint model is expressed as:

[0017]

[0018] st D h xp = 0, D v ·xq=0

[0019] Where x is a scattered signal in the complete scattered signal, x * is a scattered signal in the discrete scattered signal set, W = diag {ω i}∈R n×n is a diagonal weight matrix, ω i is a position matrix, and the position correction is used to represent the position information of the scatter correction plate; ω i When it is in the hole area, the value is 1, and when it is outside the hole area, the value is 0; D h and D vare the horizontal difference matrix and the vertical difference matrix, λ is the regularization parameter, and p and q are the sparse representation coefficients, which represent the sparse representation of the gradient in the horizontal and vertical directions, respectively.

[0020] After obtaining the corrected DR projection, the method further comprises:

[0021] The corrected DR projection is reconstructed using the FDK algorithm to obtain a scatter-corrected three-dimensional CT reconstructed model.

[0022] After obtaining the scatter-corrected three-dimensional CT reconstruction model, the method further comprises:

[0023] Slicing the three-dimensional CT reconstructed model to obtain slice images;

[0024] The scatter correction effect is analyzed based on the slice image.

[0025] In another embodiment, a cone-beam CT scatter correction device is provided, the device comprising:

[0026] An acquisition unit is configured to acquire two sets of DR projections of the workpieces acquired by the acquisition device and a single DR projection of the scatter correction plate;

[0027] A determination unit is configured to generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scatter signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is not added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added;

[0028] a processing unit configured to perform image processing on the single DR projection to obtain a hole area;

[0029] A reconstruction unit is configured to establish an L1 norm constraint model based on the discrete scattered signal set and the hole area in combination with the CS theory, and solve it through the ADMM algorithm to reconstruct the complete scattered signal;

[0030] The calculation unit is configured to perform subtraction of the complete scattered signal from the first DR projection set to obtain a corrected DR projection.

[0031] In another embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned cone-beam CT scatter correction method when executing the program.

[0032] In another embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the cone-beam CT scatter correction method as described above is implemented.

[0033] It can be seen from the above technical scheme that in the above embodiment, a discrete scattering signal set is obtained by projection of two groups of collected workpieces, and the hole area is obtained by a single DR projection of the scatter correction plate of the wipe; based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with CS theory, and the complete scattering signal is reconstructed by solving it through the ADMM algorithm; the complete scattering signal is deducted from the first DR projection set to obtain the corrected DR projection. This scheme can improve the accuracy of scattering correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 This is a schematic diagram of a cone-beam CT scatter correction process in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of a three-dimensional CT reconstruction model generation process in an embodiment of the present application;

[0037] Figure 3 This is a schematic diagram of the process of analyzing the scattering correction effect in the embodiment of the present application;

[0038] Figure 4 This is a schematic diagram of the structure of a cone-beam CT scatter correction device in an embodiment of the present application;

[0039] Figure 5 A schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe the order or precedence of the objects. It should be understood that the data used in this way can be interchangeable where appropriate, so that the implementation of the present invention described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0042] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0043] In the related art, a scatter correction plate is used to perform scatter correction on DR projection images. Currently, there are methods such as beam stop array (BSA), beam hole array (BHA) and beam stop grid (BSG). Taking the BSA method as an example, the correction plate is made of a plexiglass plate in which evenly arranged lead blocks are embedded. The correction plate is placed in front of the detector. The light intensity detected at the position corresponding to the lead block on the detector is generated by the scattered rays. The signal value at the center of mass of the corresponding lead block is two-dimensionally interpolated and expanded to the entire plane to obtain a scattering intensity distribution diagram.

[0044] For example, in the bicubic interpolation fitting scattering field used in related technologies, during the interpolation process, the pixel value of the target point (x, y) = (i + u, j + v) is obtained by weighted average of the 16 points closest to the origin in the matrix grid, where: i is the horizontal coordinate of the target point; j is the vertical coordinate of the target point; u is the distance from the target point on the horizontal coordinate; v is the distance from the target point on the vertical coordinate. At this time, it is necessary to use the Bicubic function to calculate the corresponding weights along the x and y directions respectively, and then perform the required interpolation calculation. When calculating, interpolate the vertical direction first, and then use this value to interpolate the horizontal direction after obtaining the vertical value.

[0045] The disadvantage of this method is that due to the obstruction of the correction plate, the detector receives less data, and only the signal at the centroid is selected for interpolation, resulting in low data utilization and reduced accuracy of the fitted scattering signal.

[0046] In view of the above problems, a cone-beam CT scatter correction method is disclosed in an embodiment of the present application. A discrete scatter signal set is obtained by projecting two sets of collected workpieces, and a hole area is obtained by a single DR projection of the collected scatter correction plate. Based on the discrete scatter signal set and the hole area, an L1 norm constraint model is established in combination with the compressed sensing (CS) theory, and the complete scatter signal is reconstructed by solving the alternating direction method of multipliers (ADMM) algorithm. The complete scatter signal is deducted from the first DR projection set to obtain a corrected DR projection. This solution can improve the accuracy of scatter correction.

[0047] The following is a description of the cone-beam CT scatter correction process implemented in an embodiment of the present application in conjunction with the accompanying drawings.

[0048] See also Figure 1 , Figure 1 This is a schematic diagram of a cone beam CT scatter correction process in an embodiment of the present application. The specific steps are:

[0049] Step 101: acquiring DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate.

[0050] The acquisition device acquires two sets of DR projections of the workpiece when there is no relative displacement of the workpiece position and the scanning parameters are consistent. The first set of DR projections acquired is the DR projections acquired when the scatter correction plate is not added, and the second set of DR projections acquired is the DR projections acquired when the scatter correction plate is added.

[0051] Step 102, generating a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtaining a discrete scattering signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece without adding a scattering correction plate; and the second DR projection set is a set of DR projections obtained by scanning the workpiece with adding a scattering correction plate.

[0052] Step 103: perform image processing on a single DR projection to obtain a hole area.

[0053] Image processing of a single DR projection, including:

[0054] The single DR projection is subjected to binarization, contour extraction, contour tracking and circle fitting.

[0055] Step 104, based on the discrete scattered signal set and the hole area, an L1 norm constraint model is established in combination with the CS theory, and the ADMM algorithm is used to solve the model to reconstruct the complete scattered signal.

[0056] The complete scattering signal here refers to the scattering signal of the complete image.

[0057] Step 105 , subtract the complete scattered signal from the first DR projection set to obtain a corrected DR projection.

[0058] In this embodiment, a discrete scattering signal set is obtained by projecting two sets of collected workpieces, and a hole area is obtained by a single DR projection of the scatter correction plate of the wipe; based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with CS theory, and the complete scattering signal is reconstructed by solving it through the ADMM algorithm; the complete scattering signal is deducted from the first DR projection set to obtain the corrected DR projection. This solution can improve the accuracy of scattering correction.

[0059] In another example of this embodiment, the L1 norm constraint model promotes sparsity by introducing the L1 norm constraint, so that the gradients of the complete scattered signal in the horizontal and vertical directions are respectively equal to the corresponding sparse vectors.

[0060] Among them, the L1 norm constraint model is expressed as:

[0061]

[0062] st D h xp = 0, D v ·xq=0

[0063] Where x is a scattered signal in the complete scattered signal, x * is a scattered signal in the discrete scattered signal set, W = diag{ω i}∈R n×n is a diagonal weight matrix, R n×n represents a real number matrix, n is the number of sampling points of the x signal, ω i is the position matrix, and the position correction is used to represent the position information of the scatter correction plate; ω i When it is in the hole area, the value is 1, and when it is outside the hole area, the value is 0; D h and D v are the horizontal difference matrix and the vertical difference matrix, λ is the regularization parameter, and p and q are the sparse representation coefficients, which represent the sparse representation of the gradient in the horizontal and vertical directions, respectively.

[0064] See also Figure 2 , Figure 2 This is a schematic diagram of a 3D CT reconstruction model generation process in an embodiment of the present application. The specific steps are:

[0065] Step 201 : acquiring DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate.

[0066] Before the acquisition device acquires DR projections, the scanning parameters of the acquisition device need to be set:

[0067] According to the scanning target, such as the workpiece, the size selects the effective imaging range, the acquisition DR projection grayscale range can be set to 0-65535, the scanning voltage V can be set to 430KV, the scanning current I can be set to 1600μA, the source to the detector distance FDD can be set to 1158mm, the source to the center of the turntable, that is, the source to the workpiece distance FDD can be 500mm. The setting of the above specific parameters is an example, and the specific implementation is limited according to the specific scanning equipment and the relevant conditions of the stage where the workpiece is located, and this is not limited in the embodiment of the present application.

[0068] When performing two complete scans on the workpiece, it is necessary to ensure that there is no relative displacement of the workpiece position and that the scanning parameters set above are the same. The first time, the workpiece to be measured is directly placed on the stage, and no equipment is added between the radiation source, the workpiece to be measured, and the detector, that is, no scatter correction plate is added, and a set of DR projections is obtained. This set of projections is a DR projection containing scattered signals and real signals. A scatter correction plate is added between the workpiece to be measured and the detector, and a second scan is performed to obtain a set of projection DR projections.

[0069] In specific implementation, the scatter correction plate can use a BHA scatter correction plate. The BHA scatter correction plate is processed from a lead plate with uniform texture. Holes are penetrated in the lead plate at specific intervals. The rays scan the workpiece through the holes, and the remaining signals are absorbed by the lead plate.

[0070] Step 202, generating a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtaining a discrete scattering signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece without adding a scattering correction plate; and the second DR projection set is a set of DR projections obtained by scanning the workpiece with adding a scattering correction plate.

[0071] When performing DR projection acquisition, 360° DR projections can be acquired at equal intervals to directly form a first DR projection set and a second DR projection set; or 360° DR projections can be acquired continuously, and then DR projections of preset values ​​are sampled at equal intervals to form a first DR projection set and a second DR projection set.

[0072] When obtaining a discrete scattered signal set based on the first DR projection set and the second DR projection set, the corresponding projections in the first DR projection set and the second DR projection set are subtracted to obtain the discrete scattered signal set, which is specifically implemented as follows:

[0073] The DR projection in the first DR projection set is a DR projection of the aliased scattered signal and the real signal according to Lambert-Beer law:

[0074] I 1 =I 0 exp(-μl) (1)

[0075] The initial intensity of X-rays is I 0 , after passing through the workpiece, the strength becomes I 1 , μ represents the attenuation coefficient of the workpiece, and l is the thickness of the workpiece that the ray passes through. At the detector position, due to the existence of the scattered signal S, the actual received signal strength C 1 for:

[0076] C 1 =I 1 +S 1 (2)

[0077] For the second scan, since the lead plate has a certain thickness, the scattered rays entering the hole will be absorbed by the hole wall of the lead plate. Therefore, the signal intensity at the hole position on the detector is regarded as the discrete distribution of the real signal intensity, that is, C 2 =I 1 , subtracting the signal intensities collected from the two scans, we can get the corresponding discrete scattering signal:

[0078] S 1 =C 1 -C 2 (3)

[0079] The discrete scattered signal set is composed of multiple obtained discrete scattered signals.

[0080] Step 203: perform image processing on a single DR projection to obtain a hole area.

[0081] Image processing is performed on a single DR projection, specifically:

[0082] The single DR projection is subjected to binarization, contour extraction, contour tracking, circle fitting and other processing.

[0083] Step 204: Based on the discrete scattered signal set and the hole area, an L1 norm constraint model is established in combination with the CS theory, and the ADMM algorithm is used to solve the model and reconstruct the complete scattered signal.

[0084] For discrete scattering signals, CS theory is introduced to replace the traditional interpolation algorithm. By establishing an L1 norm constraint model, the scattering signal is reconstructed using the CS framework.

[0085] The L1 norm constraint model is expressed as:

[0086]

[0087] Among them, x is a scattered signal in the complete scattered signal, that is, the signal to be solved, x * is a scattered signal in the discrete scattered signal set, that is, S 1 , then the complete scattered signal can be obtained for a discrete scattered signal set; W = diag{ω i}∈R n×n is a diagonal weight matrix, R n×n represents a real number matrix, n is the number of sampling points of the x signal, ω i is the position matrix, and the position correction is used to represent the position information of the scatter correction plate; ω i When it is in the hole area, the value is 1, and when it is outside the hole area, the value is 0; D h and D v are the horizontal difference matrix and the vertical difference matrix, λ is the regularization parameter, p and q are the sparse representation coefficients, which represent the sparse representation of the gradients in the horizontal and vertical directions respectively; st represents the constraint condition.

[0088] The L1-norm constraint model promotes sparsity by introducing the L1-norm constraint, which makes the gradient of the complete scattering signal in the horizontal and vertical directions equal to the corresponding sparse vectors, respectively, which helps to recover the reconstructed scattering signal from limited measurements.

[0089] In order to deal with the norm constraint problem introduced in formula (4), this application uses the ADMM algorithm to solve. In the process of applying the ADMM algorithm, the augmented Lagrangian function is introduced to formalize the objective function. Formula (4) can be expressed as:

[0090]

[0091] where u p ,u q is the equality constraint D h xp = 0, D v The dual variable xq=0, ρ is an adjustable parameter, and the algorithm minimizes x, p, q, u respectively. p ,u q , specifically, at the kth iteration, the steps are:

[0092]

[0093] At this point, the solution of equation (4) is completed, and a scattered signal in the complete scattered signal corresponding to a scattered signal in each discrete scattered signal set can be obtained, thereby obtaining the complete scattered signal.

[0094] Step 205 , subtract the complete scattered signal from the first DR projection set to obtain a corrected DR projection.

[0095] Step 206: Reconstruct the corrected DR projection using the FDK algorithm to obtain a scatter-corrected three-dimensional CT reconstructed model.

[0096] The FDK (Feldkamp-Davis-Kress) algorithm is an algorithm widely used in 3D image reconstruction. The algorithm is based on Radon transform and Fourier slice theorem, and reconstructs images from projection data through filtered back projection. The FDK algorithm is particularly suitable for cone-beam CT imaging, which can process a large amount of projection data and reconstruct high-quality 3D images.

[0097] In this embodiment, based on the scatter correction plate and combined with the CS theory, a suitable sampling matrix is ​​designed through the discrete signals collected by the correction plate, and finally the established L1 norm constraint model is solved by the ADMM algorithm to obtain a complete scattering signal. A scattering field reconstruction technical process based on the scatter correction plate and the ADMM algorithm under the CS theory is established, which improves the data utilization rate of the DR projection collected by adding the correction plate, improves the accuracy of the scatter correction, and then obtains a high-quality three-dimensional CT reconstructed model based on the corrected DR projection.

[0098] See also Figure 3 , Figure 3 This is a schematic diagram of the process of analyzing the scatter correction effect in the embodiment of this application. The specific steps are:

[0099] Step 301 : acquiring DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate.

[0100] The acquisition device acquires DR projections of two groups of workpieces when there is no relative displacement of the workpiece positions and the scanning parameters are consistent.

[0101] Step 302, generating a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtaining a discrete scattering signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece without adding a scattering correction plate; and the second DR projection set is a set of DR projections obtained by scanning the workpiece with adding a scattering correction plate.

[0102] Step 303: perform image processing on a single DR projection to obtain a hole area.

[0103] Image processing of a single DR projection, including:

[0104] The single DR projection is subjected to binarization, contour extraction, contour tracking and circle fitting.

[0105] Step 304: Based on the discrete scattered signal set and the hole area, an L1 norm constraint model is established in combination with the CS theory, and the ADMM algorithm is used to solve the model and reconstruct the complete scattered signal.

[0106] Step 305 , subtract the complete scattered signal from the first DR projection set to obtain a corrected DR projection.

[0107] Step 306: Reconstruct the corrected DR projection using the FDK algorithm to obtain a scatter-corrected three-dimensional CT reconstructed model.

[0108] Step 307: Slice the 3D CT reconstructed model to obtain slice images.

[0109] Step 308: Analyze the scatter correction effect based on the slice image.

[0110] The scatter correction effect is analyzed based on the slice image. If the correction effect does not meet expectations, the parameters involved in the scatter correction process can be readjusted.

[0111] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present disclosure, and will not be described in detail here.

[0112] Based on the same inventive concept, the present application also provides a cone-beam CT scatter correction device. Figure 4 , Figure 4 This is a schematic diagram of the structure of a cone-beam CT scatter correction device in an embodiment of the present application. The device includes:

[0113] An acquisition unit 401 is configured to acquire two groups of DR projections of workpieces acquired by an acquisition device, and a single DR projection of a scatter correction plate;

[0114] The determining unit 402 is configured to generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scatter signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when no scatter correction plate is added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added;

[0115] The processing unit 403 is configured to perform image processing on a single DR projection to obtain a hole area;

[0116] The reconstruction unit 404 is configured to establish an L1 norm constraint model based on the discrete scattered signal set and the hole area in combination with the CS theory, and solve it through the ADMM algorithm to reconstruct the complete scattered signal;

[0117] The calculation unit 405 is configured to perform subtraction of the complete scattered signal in the first DR projection set to obtain a corrected DR projection.

[0118] In another embodiment,

[0119] The acquisition device acquires DR projections of two groups of workpieces when there is no relative displacement of the workpiece positions and the scanning parameters are consistent.

[0120] In another embodiment,

[0121] The processing unit 403 is specifically used to perform binarization, contour extraction, contour tracking and circle fitting processing on a single DR projection.

[0122] In another embodiment, the L1 norm constraint model promotes sparsity by introducing an L1 norm constraint so that the gradients of the complete scattered signal in the horizontal and vertical directions are respectively equal to the corresponding sparse vectors.

[0123] In another embodiment, the L1 norm constraint model is expressed as:

[0124]

[0125] st D h xp = 0, D v ·xq=0

[0126] Where x is a scattered signal in the complete scattered signal, x * is a scattered signal in the discrete scattered signal set, W = diag{ω i}∈R n×n is a diagonal weight matrix, ω i is the position matrix, and the position correction is used to represent the position information of the scatter correction plate; ω i When it is in the hole area, the value is 1, and when it is outside the hole area, the value is 0; D h and D v are the horizontal difference matrix and the vertical difference matrix, λ is the regularization parameter, and p and q are the sparse representation coefficients, which represent the sparse representation of the gradient in the horizontal and vertical directions, respectively.

[0127] In another embodiment, the apparatus further comprises:

[0128] The modeling unit 406 is configured to perform reconstruction on the corrected DR projections using the FDK algorithm to obtain a scatter-corrected three-dimensional CT reconstructed model.

[0129] In another embodiment, the apparatus further comprises:

[0130] The analyzing unit 407 is configured to perform slicing on the three-dimensional CT reconstructed model to obtain slice images; and analyze the scatter correction effect based on the slice images.

[0131] The units in the above-mentioned embodiments may be integrated into one body or deployed separately; they may be combined into one unit or further divided into multiple sub-units.

[0132] In another embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the cone-beam CT scatter correction method can be implemented.

[0133] In another embodiment, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, a cone-beam CT scatter correction method can be implemented.

[0134] Figure 5 Schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. Figure 5 As shown, the electronic device may include: a processor (Processor) 510, a communication interface (Communications Interface) 520, a memory (Memory) 530 and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the following method:

[0135] Acquire DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate;

[0136] Generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scatter signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is not added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added;

[0137] Performing image processing on the single DR projection to obtain a hole area;

[0138] Based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with CS theory, and the ADMM algorithm is used to solve the model and reconstruct the complete scattering signal;

[0139] The complete scatter signal is deducted from the first DR projection set to obtain a corrected DR projection.

[0140] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0141] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0143] The flow chart and block diagram in the accompanying drawings of the present application show the possible architecture, function and operation of the system, method and computer program product according to the various embodiments disclosed in the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the box can also occur in the order of the standards in different figures. For example, the boxes represented by two connections can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims disclosed in this application may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in this application. In particular, without departing from the spirit and teachings of this application, the features described in the various embodiments and / or claims of this application may be combined and / or combined in a variety of ways, and all of these combinations and / or combinations fall within the scope disclosed in this application.

[0145] Specific embodiments are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas, and is not used to limit the present application. For those skilled in the art, changes can be made in the specific implementation methods and application scopes according to the ideas, spirits and principles of the present invention, and any modifications, equivalent substitutions, improvements, etc. made therein should be included in the scope of protection of this application.

Claims

1. A cone-beam CT scatter correction method, characterized in that: The method comprises: Acquire DR projections of two groups of workpieces acquired by an acquisition device and a single DR projection of a scatter correction plate; Generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scattering signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is not added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added; Performing image processing on the single DR projection to obtain a hole area; Based on the discrete scattering signal set and the hole area, an L1 norm constraint model is established in combination with CS theory, and the ADMM algorithm is used to solve the model and reconstruct the complete scattering signal; The complete scatter signal is deducted from the first DR projection set to obtain a corrected DR projection.

2. The method according to claim 1, characterized in that The acquisition device acquires DR projections of two groups of workpieces when there is no relative displacement of the workpiece positions and the scanning parameters are consistent.

3. The method according to claim 1, characterized in that: The performing image processing on the single DR projection comprises: Binarization, contour extraction, contour tracking and circle fitting processing.

4. The method according to claim 1, characterized in that: The L1 norm constraint model promotes sparsity by introducing the L1 norm constraint, so that the gradients of the complete scattered signal in the horizontal and vertical directions are equal to the corresponding sparse vectors, respectively.

5. The method according to claim 4, characterized in that The L1 norm constraint model is expressed as: Where x is a scattered signal in the complete scattered signal, x * is a scattered signal in the discrete scattered signal set, W = diag {ω i }∈R n×n is a diagonal weight matrix, R n×n represents a real number matrix, n is the number of sampling points of the x signal, ω i is a position matrix, and the position correction is used to represent the position information of the scatter correction plate; ω i When it is in the hole area, the value is 1, and when it is outside the hole area, the value is 0; D h and D v are the horizontal difference matrix and the vertical difference matrix, λ is the regularization parameter, and p and q are the sparse representation coefficients, which represent the sparse representation of the gradient in the horizontal and vertical directions, respectively.

6. The method according to any one of claims 1 to 5, characterized in that: After obtaining the corrected DR projection, the method further comprises: The corrected DR projection is reconstructed using the FDK algorithm to obtain a scatter-corrected three-dimensional CT reconstructed model.

7. The method according to claim 6, characterized in that After obtaining the scatter-corrected three-dimensional CT reconstruction model, the method further comprises: Slicing the three-dimensional CT reconstructed model to obtain slice images; The scatter correction effect is analyzed based on the slice image.

8. A cone-beam CT scatter correction device, characterized in that: The device comprises: An acquisition unit is configured to acquire two sets of DR projections of the workpieces acquired by the acquisition device and a single DR projection of the scatter correction plate; A determination unit is configured to generate a first DR projection set and a second DR projection set based on the DR projections of the two groups of workpieces; and obtain a discrete scatter signal set based on the first DR projection set and the second DR projection set; wherein the first DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is not added; and the second DR projection set is a set of DR projections obtained by scanning the workpiece when the scatter correction plate is added; a processing unit configured to perform image processing on the single DR projection to obtain a hole area; A reconstruction unit is configured to establish an L1 norm constraint model based on the discrete scattered signal set and the hole area in combination with the CS theory, and solve it through the ADMM algorithm to reconstruct the complete scattered signal; The calculation unit is configured to perform subtraction of the complete scattered signal from the first DR projection set to obtain a corrected DR projection.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method described in any one of claims 1 to 7 is implemented.

Images