Zooming static ct system and image reconstruction method
By using a static CT system with variable focal length and a weighted filtering back projection algorithm, the problem of inaccurate reconstruction caused by unequal detector unit angles in traditional CT systems has been solved, achieving more efficient and accurate image reconstruction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TSINGHUA UNIVERSITY
- Filing Date
- 2022-12-13
- Publication Date
- 2026-06-23
AI Technical Summary
In traditional isometric detector CT systems, when the distance between the X-ray source and the detector changes, the angle subtended by each detector unit relative to the X-ray source is not equal, which makes it impossible to maintain time-shift invariance. This results in the inability to use FBP to achieve accurate reconstruction, reducing the applicability and reliability of the system.
A static CT system with variable focal length is used. It employs a cylindrical detector array arranged in an arc and an X-ray source array arranged in a preset shape. Combined with a data acquisition system, a control system, and an image processing system, it uses a weighted filtering back projection reconstruction algorithm to reconstruct images. The projection data is weighted, filtered, and back projected using three weighting factors to achieve accurate reconstruction.
This improved the efficiency and accuracy of image reconstruction, enhanced the applicability and reliability of the system, and solved the problem of reconstruction accuracy when the distance between the X-ray source and the detector changes.
Smart Images
Figure CN115998314B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computed tomography (CT) technology, and in particular to a static CT system with variable focal length and an image reconstruction method. Background Technology
[0002] In related technologies, the X-ray source of a traditional isoangular detector CT system is located at the center of the detector arc, and the focal length is fixed. Therefore, the angle subtended by each detector unit with respect to the X-ray source is equal, and its image reconstruction can also be achieved by using the FBP (Filter Back-Projection) algorithm.
[0003] In addition, such as Figure 1 The diagram shows a static CT system with an isoangular detector of equal focal length. In a static CT with a fixed focal length, the detector array forms a ring and remains stationary, and the X-ray source also forms a complete ring and remains stationary. The X-ray sources are distributed at equal angles, similar to a parent-child ring structure. Traditional fourth-generation CT is similar to this.
[0004] However, in related technologies, when the distance between the radiation source and the detector changes, the angle subtended by each detector unit relative to the radiation source is not equal, thus the time shift invariance cannot be maintained, and accurate reconstruction cannot be achieved using FBP. This reduces the applicability and reliability of the system and urgently needs to be addressed. Summary of the Invention
[0005] This application provides a static CT system with variable focal length and an image reconstruction method to solve the problems in related technologies where, when the distance between the X-ray source and the detector changes, the angles subtended by each detector unit relative to the X-ray source are not equal, thus failing to maintain time-shift invariance, making it impossible to achieve accurate reconstruction using FBP, and reducing the applicability and reliability of the system.
[0006] The first aspect of this application provides a static CT system with variable focal length, comprising: a cylindrical detector array arranged in an arc and an X-ray source array arranged in a preset shape, wherein the distance from the X-ray source to the detector in the X-ray source array is variable, the X-ray source array and the detector array remain stationary during scanning, and the X-ray source array acquires projection data at different angles by sequentially emitting beams; a data acquisition system for controlling the detector to acquire data; a control system for controlling the beam emission of the X-ray source and the data acquisition of the detector; and an image processing system for processing the acquired image projection data using an image reconstruction algorithm.
[0007] Optionally, in one embodiment of this application, the arc-arranged cylindrical detector array is composed of multiple detector units arranged at equal angles, or the multiple detector units are composed of modules arranged at equal angles; the X-ray source array with a preset shape is a smooth curve or a multi-segment broken line and is designed according to the target application scenario and the scanned object, wherein the shape is set in correspondence with the focal length of different X-ray sources; the image reconstruction algorithm is a weighted filtering back-projection reconstruction algorithm using three weighting factors to perform weighted filtering on the projection data, wherein the first weighting factor performs weighted correction on the original projection data before filtering to obtain pre-weighted corrected projection data; the second weighting factor performs weighted correction on the convolution kernel function to perform convolution with the pre-weighted corrected projection data using the weighted corrected convolution kernel function to obtain filtered projection data; the third weighting factor performs weighted correction on the filtered projection data to obtain final weighted filtered projection data, and the final weighted filtered projection data is used for back-projection reconstruction to obtain the final reconstructed image.
[0008] Optionally, in one embodiment of this application, the weighted filtering back projection formula of the image reconstruction algorithm is:
[0009]
[0010] Where β is the rotation angle, and γ is the sector angle of the detector element relative to the center of the detector arc. It is obtained from the system scan at a rotation angle of β, a sector angle of γ relative to the center of the detector arc, and a detector element height of [missing information]. The projection data at time, f(x, y, z) is the reconstructed value at coordinates (x, y, z), γ m The maximum sector angle of the detector element relative to the center of the detector arc;
[0011] Where R is the radius of the detector arc, γ0 is the sector angle of the detector element corresponding to the ray traversed by the reconstructed pixel relative to the center of the detector arc, and L is:
[0012]
[0013] Where D is the distance from the ray source to the origin.
[0014] h(t) is a standard convolution kernel function, which is: Furthermore, using the SL filter, the discrete form is:
[0015]
[0016] Where cosη is the three-dimensional projection factor:
[0017]
[0018] J is the Jacobian determinant of the integral transform of the zoom system:
[0019] J=(Dcos(α)-Rk′(β)sin(α))g′(γ)
[0020] Where α is the sector angle of the detector unit relative to the X-ray source, k′(β) is the derivative of k(8), k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R from the detector to the center of the detector arc, and g′(Y) is the derivative of α=g(γ).
[0021] The sector angle γ of the detector with respect to the center of the arc of the detector has the following relationship with the sector angle α with respect to the radiation source:
[0022]
[0023] The three weighting factors are A(γ), B(γ0-γ), and C(γ0), respectively. A(γ) weights the projection data before filtering, B(γ0-γ) weights the filtering kernel function, and C(γ0) weights the projection data after filtering. The three weighting factors are expressed as follows:
[0024]
[0025]
[0026] Among them, P A (γ) and P B (γ) is the polynomial used for estimation.
[0027] Optionally, in one embodiment of this application, the polynomial P... A (γ) and P B (γ) can be:
[0028]
[0029]
[0030] A second aspect of this application provides an image reconstruction method using a static CT system with an isometric detector and variable focal length as described above. The method includes the following steps: a radiation source sequentially emits beams to acquire projection data at different angles; three weighting factors are calculated for each variable focal length system; based on the three weighting factors, the projection data is weighted, filtered, and backprojected to obtain a final reconstructed image. The weighted filtering and backprojection reconstruction includes: a first weighting factor weighting and correcting the original projection data before filtering to obtain pre-weighted corrected projection data; a second weighting factor weighting and correcting the convolution kernel function, and then convolving the pre-weighted corrected projection data with the weighted kernel function to obtain filtered projection data; a third weighting factor weighting and correcting the filtered projection data to obtain final weighted filtered projection data; and backprojection reconstruction of the filtered projection data to obtain the final reconstructed image.
[0031] Optionally, in one embodiment of this application, the weighted filtering back projection formula of the image reconstruction algorithm is:
[0032]
[0033] Where β is the rotation angle, and γ is the sector angle of the detector element relative to the center of the detector arc. It is obtained from the system scan at a rotation angle of β, a sector angle of γ relative to the center of the detector arc, and a detector element height of [missing information]. The projection data at time, f(x, y, z) is the reconstructed value at coordinates (x, y, z), γ m The maximum sector angle of the detector element relative to the center of the detector arc;
[0034] Where R is the radius of the detector arc, γ0 is the sector angle of the detector element corresponding to the ray traversed by the reconstructed pixel relative to the center of the detector arc, and L is:
[0035]
[0036] Where D is the distance from the ray source to the origin.
[0037] h(t) is a standard convolution kernel function, which is: Furthermore, using the SL filter, the discrete form is:
[0038]
[0039] Where cosη is the three-dimensional projection factor:
[0040]
[0041] J is the Jacobian determinant of the integral transform of the zoom system:
[0042] J=(Dcos(α)-Rk′(β)sin(α))g′(γ)
[0043] Where α is the sector angle of the detector unit relative to the X-ray source, k′(β) is the derivative of k(8), k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R from the detector to the center of the detector arc, and g′(Y) is the derivative of α=g(Y).
[0044] The sector angle γ of the detector with respect to the center of the arc of the detector has the following relationship with the sector angle α with respect to the radiation source:
[0045]
[0046] The three weighting factors are A(γ), B(γ0-γ), and C(γ0), respectively. A(γ) weights the projection data before filtering, B(γ0-γ) weights the filtering kernel function, and C(γ0) weights the projection data after filtering. The three weighting factors are expressed as follows:
[0047]
[0048]
[0049] Among them, P A (γ) and P B (γ) is the polynomial used for estimation.
[0050] Optionally, in one embodiment of this application, the polynomial P... A (γ) and P B (γ) can be:
[0051]
[0052]
[0053] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the image reconstruction method described above.
[0054] This application embodiment controls multiple X-ray sources in an X-ray source array to scan sequentially via a control system and a data acquisition system. This allows for the acquisition of projection data on a cylindrical detector array at different angles. Finally, an image processing system uses an image reconstruction algorithm to process the acquired image projection data, thereby optimizing system geometry, improving the efficiency and accuracy of image reconstruction, and enhancing the system's applicability and reliability. This solves the problems in related technologies where, as the distance between the X-ray source and the detector changes, the unequal angles subtended by each detector unit relative to the X-ray source prevent the maintenance of time-shift invariance, hindering accurate reconstruction using FBP and reducing the system's applicability and reliability.
[0055] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0056] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:
[0057] Figure 1 This is a schematic diagram of a static CT system with an isogonal detector of medium focal length, which is part of the relevant technology.
[0058] Figure 2 This is a schematic diagram of the structure of a static CT system with variable focal length according to an embodiment of this application;
[0059] Figure 3 This is a schematic diagram of a static CT system with variable focal length according to a specific embodiment of this application;
[0060] Figure 4 This is a three-dimensional structural diagram of a static CT system with variable focal length according to a specific embodiment of this application.
[0061] Figure 5 This is a schematic diagram showing the comparison of MTF (Modulation Transfer Function) curve results between the direct reconstruction method and the rearrangement method in a specific embodiment of this application.
[0062] Figure 6 A schematic diagram of the reconstruction result structure of a Shepp-Logan simulator of a variable focal length static CT system according to a specific embodiment of this application;
[0063] Figure 7 This is a schematic diagram of the reconstruction result of a high-contrast simulation of a static CT system with variable focal length according to a specific embodiment of this application.
[0064] Figure 8This is a flowchart of an image reconstruction method provided according to an embodiment of this application. Detailed Implementation
[0065] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.
[0066] The following is a schematic diagram of the structure of a static CT system with variable focal length according to an embodiment of this application, with reference to the accompanying drawings. Figure 2 This is a schematic diagram of the structure of a static CT system with variable focal length according to an embodiment of this application.
[0067] like Figure 2 As shown, the variable focal length static CT system 10 includes: a detector array 100, an X-ray source array 200, a data acquisition system 300, a control system 400, and an image processing system 500.
[0068] The array consists of a cylindrical detector array 100 arranged in an arc and an X-ray source array 200 arranged in a preset shape. The distance between the X-ray source and the detector in the X-ray source array 200 can be varied. The X-ray source array 200 and the detector array 100 remain stationary during scanning. The X-ray source array 200 acquires projection data at different angles by sequentially emitting beams.
[0069] In actual implementation, the embodiments of this application can set up a cylindrical detector array 100 arranged in an arc and an X-ray source array 200 arranged in a specific shape. The distance from the X-ray source to the detector in the X-ray source array 200 can be varied to improve the accuracy and comprehensiveness of the scan. The X-ray source array 200 and the detector array 100 remain stationary during scanning. The X-ray source array 200 emits beams sequentially to scan at different angles by relying on different X-ray sources, thereby achieving more flexible scanning sampling, that is, acquiring projection data at different angles, thereby improving the flexibility and applicability of scanning sampling.
[0070] It should be noted that the preset shape is set by those skilled in the art according to the actual situation, and no specific limitation is made here.
[0071] The data acquisition system 300 is used to control the detector to acquire data.
[0072] In some embodiments, the present application may provide a data acquisition system 300, which may control the detector array 100 to acquire projection data in order to improve the feasibility of image reconstruction.
[0073] Control system 400 controls the beam output of the X-ray source and the data acquisition by the detector.
[0074] In actual implementation, the embodiments of this application can be equipped with a control system 400, which can control the beam output of the X-ray source array 200 and the data acquisition of the detector array 100, thereby improving the accuracy and comprehensiveness of the projection data.
[0075] In some embodiments, the control system 400 can precisely control the focal length of the detector array 100 and the X-ray source array 200 at different angles to accurately calculate the required weights, thereby improving the efficiency and accuracy of the reconstructed image and increasing the resolution of the reconstruction result.
[0076] Image processing system 500 uses image reconstruction algorithms to process the acquired image projection data.
[0077] In some embodiments, the present application may provide an image processing system 500. The image processing system 500 may use the image reconstruction algorithm in the following steps to process the acquired image projection data, thereby improving the efficiency and accuracy of the reconstructed image and enhancing the applicability of the system.
[0078] Optionally, in one embodiment of this application, the cylindrical detector array 100 arranged in an arc is composed of multiple detector units arranged at equal angles, or is composed of multiple detector units forming modules and the modules arranged at equal angles; the X-ray source array 200 with a preset shape is a smooth curve or a multi-segment broken line and is designed according to the target application scenario and the scanned object, wherein the shape is set corresponding to the focal length of different X-ray sources; the image reconstruction algorithm is a weighted filtering back projection reconstruction algorithm using three weighting factors to perform weighted filtering on the projection data, wherein the first weighting factor performs weighted correction on the original projection data before filtering to obtain pre-weighted corrected projection data; the second weighting factor performs weighted correction on the convolution kernel function to perform convolution with the pre-weighted corrected projection data using the weighted corrected convolution kernel function to obtain filtered projection data; the third weighting factor performs weighted correction on the filtered projection data to obtain the final weighted filtered projection data, and the final weighted filtered projection data is used for back projection reconstruction to obtain the final reconstructed image.
[0079] As one possible implementation, the cylindrical detector array 100 arranged in an arc in this embodiment can be composed of multiple detector units arranged at equal angles, or multiple detector units can be composed of modules and arranged at equal angles. The X-ray source array 200 can be a smooth curve or a multi-segment broken line and is designed according to the target application scenario and the object being scanned. The shape of the X-ray source array 200 is set to correspond to the focal length of different X-ray sources, thereby improving the flexibility and applicability of scanning sampling.
[0080] For example, such as Figure 3 and Figure 4 The image shown is a static CT imaging structure with variable focal length proposed in an embodiment of this application, wherein... Figure 3 This is a schematic diagram of a variable focal length static CT system according to a specific embodiment of this application. In the variable focal length static CT system, the detector array forms a ring and remains stationary, while the X-ray source also forms a ring and remains stationary. The X-ray source array can be of any shape, such as... Figure 3 The left image shows a smooth curve for the ray source array, while the right image shows a polygon.
[0081] Figure 4 This is a three-dimensional schematic diagram of a static CT system with variable focal length according to a specific embodiment of this application, where S is the X-ray source, O is the center of the detector array, and the arrangement of the X-ray source array is not limited to an arc shape, but can be any trajectory.
[0082] Depend on Figure 3 and Figure 4 As can be seen, since the focal length is variable, the angle subtended by each detector with respect to the X-ray source is not necessarily equal. Therefore, the FDK imaging formula of isoangular fan-beam CT cannot be directly used. The fan angle γ of the detector with respect to the center of the detector arc and the fan angle α with respect to the X-ray source have the following relationship:
[0083]
[0084] Where k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R between detectors of each other.
[0085] Depend on Figure 3 and Figure 4 It can be seen that in a CT system with variable focal length, k is related to the scanning angle.
[0086] For example, such as Figure 5 As shown, Figure 5 To compare the MTF curves reconstructed directly using the embodiments of this application with those reconstructed using conventional rearrangement, direct FBP reconstruction cannot be used when k=0.8 at a fixed focal length.
[0087] Furthermore, in the embodiments of this application, the weighted filtering back projection formula of the image reconstruction algorithm is:
[0088]
[0089] Where β is the rotation angle, and γ is the sector angle of the detector element relative to the center of the detector arc. It is obtained from the system scan at a rotation angle of β, a sector angle of γ relative to the center of the detector arc, and a detector element height of [missing information]. The projection data at time, f(x, y, z) is the reconstructed value at coordinates (x, y, z), γ m γ0 is the maximum sector angle of the detector unit relative to the center of the detector arc, R is the radius of the detector arc, and γ0 is the sector angle of the detector unit relative to the center of the detector arc corresponding to the ray traversed by the reconstructed pixel.
[0090] Where L is:
[0091]
[0092] Where D is the distance from the ray source to the origin.
[0093] h(t) is the standard convolution kernel function, and the convolution kernel function is: Furthermore, using the SL filter, the discrete form is:
[0094]
[0095] Where cosη is the three-dimensional projection factor:
[0096]
[0097] J is the Jacobian determinant of the integral transform of the zoom system:
[0098] J=(Dcos(α)-Rk′(β)sin(α))g′(γ)
[0099] Where α is the sector angle of the detector unit relative to the X-ray source, k′(β) is the derivative of k(β), k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R from the detector to the center of the detector arc, and g′(Y) is the derivative of α=g(γ).
[0100] Furthermore, the three weighting factors are A(γ), B(γ0-γ), and C(γ0), respectively. A(γ) weights the unfiltered projected data, B(γ0-γ) weights the filtering kernel function, and C(γ0) weights the filtered projected data. The three weighting factors are expressed as follows:
[0101]
[0102]
[0103] Among them, P A (γ) and P B (γ) is the polynomial used for estimation.
[0104] Among them, polynomial P A (γ) and P B (γ) can be:
[0105]
[0106]
[0107] Therefore, the embodiments of this application can achieve weighted adjustment of the projection data before filtering, weighted adjustment of the convolution kernel function, and weighted adjustment of the projection data after filtering by using three weighting factors, and achieve accurate approximation of the time-varying part of the generalized isogonal detector architecture by using geometric polynomials.
[0108] For example, such as Figure 6 As shown, in a variable focal length isoangular detector system, embodiments of this application can use the proposed reconstruction algorithm to obtain a profile of the Shepp-Logan simulator, wherein the profile is... Figure 6 The white dashed line in the middle left image.
[0109] For example, such as Figure 7 As shown, in a variable focal length isometric detector system, embodiments of this application can use the proposed reconstruction algorithm to obtain a profile of a high-contrast simulated object, wherein the profile is... Figure 7 The white circle in the middle left image shows the cross-section.
[0110] In summary, the embodiments of this application can use a three-weight correction factor and a geometric correction factor to achieve weighted adjustment of the projection data before filtering, weighted adjustment of the convolution kernel function, and weighted adjustment of the projection data after filtering when filtering the projection data, and then perform back-projection reconstruction to obtain the final reconstructed image, thereby effectively improving the efficiency and accuracy of the reconstructed image, increasing the resolution of the reconstruction result, and improving the applicability and reliability of the system.
[0111] The variable focal length static CT system proposed in this application can sequentially scan using multiple X-ray sources arranged in a specific shape in an X-ray source array. The center of a cylindrical detector array arranged in an arc is set as the X-ray source array to acquire projection data at different angles. A data acquisition system controls the detectors to acquire data, and a control system controls the beam output of the X-ray sources and the data acquisition by the detectors. Finally, an image processing system uses an image reconstruction algorithm to process the acquired image projection data, thereby optimizing the system geometry, improving the efficiency and accuracy of reconstructed images, and enhancing the system's applicability and reliability. This solves the problems in related technologies where, when the distance between the X-ray source and the detector changes, the angle subtended by each detector unit relative to the X-ray source is not equal, thus failing to maintain time-shift invariance, making accurate reconstruction impossible using FBP, and reducing the system's applicability and reliability.
[0112] in, Figure 8 This is a schematic flowchart of an image reconstruction method provided in an embodiment of this application.
[0113] like Figure 8 As shown, the image reconstruction method includes the following steps:
[0114] In step S801, the X-ray source emits beams sequentially to acquire projection data at different angles;
[0115] In step S802, the three weighting factors under the corresponding zoom distance system are calculated;
[0116] In step S803, the projection data is weighted, filtered, and backprojected for reconstruction based on three weighting factors to obtain the final reconstructed image. The weighted filtering backprojection reconstruction includes: the first weighting factor weights and corrects the original projection data before filtering to obtain pre-weighted corrected projection data; the second weighting factor weights and corrects the convolution kernel function, and then convolves the pre-weighted corrected projection data with the weighted kernel function to obtain filtered projection data; the third weighting factor weights and corrects the filtered projection data to obtain the final weighted filtered projection data; and the filtered projection data is then backprojected for reconstruction to obtain the final reconstructed image.
[0117] Optionally, in one embodiment of this application, the weighted filtering back projection formula of the image reconstruction algorithm is:
[0118]
[0119] Where β is the rotation angle, and γ is the sector angle of the detector element relative to the center of the detector arc. It is obtained from the system scan at a rotation angle of β, a sector angle of γ relative to the center of the detector arc, and a detector element height of [missing information]. The projection data at time, f(x, y, z) is the reconstructed value at coordinates (x, y, z), γ m The maximum sector angle of the detector element relative to the center of the detector arc;
[0120] Where R is the radius of the detector arc, γ0 is the sector angle of the detector element corresponding to the ray traversed by the reconstructed pixel relative to the center of the detector arc, and L is:
[0121]
[0122] Where D is the distance from the ray source to the origin.
[0123] h(t) is the standard convolution kernel function, and the convolution kernel function is: Furthermore, using the SL filter, the discrete form is:
[0124]
[0125] Where cosη is the three-dimensional projection factor:
[0126]
[0127] J is the Jacobian determinant of the integral transform of the zoom system:
[0128] J=(Dcos(α)-Rk′(β)sin(α))g′(γ)
[0129] Where α is the sector angle of the detector unit relative to the X-ray source, k′(β) is the derivative of k(β), k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R from the detector to the center of the detector arc, and g′(Y) is the derivative of α=g(γ).
[0130] The sector angle γ of the detector about the center of the detector arc has the following relationship with the sector angle α about the X-ray source:
[0131]
[0132] The three weighting factors are A(γ), B(γ0-γ), and C(γ0), respectively. A(γ) weights the unfiltered projected data, B(γ0-γ) weights the filtering kernel function, and C(γ0) weights the filtered projected data. The three weighting factors are expressed as follows:
[0133]
[0134]
[0135] Among them, P A (γ) and P B(γ) is the polynomial used for estimation.
[0136] Optionally, in one embodiment of this application, the polynomial P... A (γ) and P B (γ) can be:
[0137]
[0138]
[0139] The image reconstruction method proposed in this application involves sequentially scanning multiple X-ray sources in an X-ray source array arranged in a specific shape. The center of a cylindrical detector array arranged in an arc is set as the X-ray source array to acquire projection data at different angles. A data acquisition system controls the detector to acquire data, and a control system controls the beam output of the X-ray sources and the data acquisition by the detectors. Finally, an image processing system uses an image reconstruction algorithm to process the acquired image projection data, thereby optimizing the system geometry, improving the efficiency and accuracy of image reconstruction, and enhancing the system's applicability and reliability. This solves the problems in related technologies where, when the distance between the X-ray source and the detector changes, the angle subtended by each detector unit relative to the X-ray source is not equal, thus failing to maintain time-shift invariance, making accurate reconstruction impossible using FBP, and reducing the system's applicability and reliability.
[0140] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the image reconstruction method described above.
[0141] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0142] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0143] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.
[0144] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0145] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0146] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0147] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0148] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.
Claims
1. A static CT system with variable focal length, characterized in that, include: The array consists of a cylindrical detector array arranged in an arc and an X-ray source array arranged in a preset shape. The distance from the X-ray source to the detector in the X-ray source array can be varied. The X-ray source array and the detector array remain stationary during scanning. The X-ray source array acquires projection data at different angles by sequentially emitting beams. A data acquisition system is used to control the detector to acquire data; A control system that controls the beam output of the X-ray source and the data acquisition by the detector; An image processing system that uses an image reconstruction algorithm to process the acquired image projection data; The circular arc-shaped cylindrical detector array is composed of multiple detector units arranged at equal angles, or is composed of multiple detector units forming modules and the modules arranged at equal angles. The X-ray source array with the preset shape is a smooth curve or a multi-segment broken line and is designed and composed according to the target application scenario and the object being scanned. The shape is set to correspond to the focal length of different X-ray sources. The image reconstruction algorithm is a weighted filtering backprojection reconstruction algorithm using three weighting factors to perform weighted filtering on the projection data. The first weighting factor weights and corrects the original projection data before filtering, resulting in pre-weighted corrected projection data. The second weighting factor weights and corrects the convolution kernel function, so that the pre-weighted corrected projection data is convolved with the weighted kernel function to obtain filtered projection data. The third weighting factor weights and corrects the filtered projection data to obtain final weighted filtered projection data. This final weighted filtered projection data is then used for backprojection reconstruction to obtain the final reconstructed image.
2. The system according to claim 1, characterized in that, The weighted filtering back projection formula of the image reconstruction algorithm is: in, It is the rotation angle. It is the sector angle of the detector element relative to the center of the detector arc. The results were obtained from a system scan at a rotation angle of... The sector angle of the detector element relative to the center of the detector arc is... The height of the detector unit is Projection data at that time, The coordinates are The reconstruction value, The maximum sector angle of the detector element relative to the center of the detector arc; Where R is the radius of the detector's arc. L is the sector angle of the detector unit corresponding to the ray traversed by the reconstructed pixel relative to the center of the detector arc, where L is: Where D is the distance from the ray source to the origin; It is a standard convolution kernel function, the convolution kernel function is And using the SL filter, the discrete form is: in, It is a three-dimensional projection factor: J is the Jacobian determinant of the integral transform of the zoom system: in, It is the sector angle of the detector unit relative to the X-ray source. yes The derivative of is given by , where k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R between detectors of each other. yes The derivative function; The sector angle of the detector with respect to the center of the detector arc With respect to the fan angle of the radiation source The following relationship exists: The three weighting factors are as follows: , , , Weight the unfiltered projection data. Weighting the filter kernel function The filtered projection data is weighted, where the three weighting factors are represented as follows: in, and It is a polynomial used for estimation.
3. The system according to claim 2, characterized in that, in, The polynomial and yes: 。 4. An image reconstruction method, characterized in that, Using the static CT system with variable focal length as described in any one of claims 1-3, wherein the image reconstruction method includes the following steps: The X-ray source emits beams sequentially to acquire projection data at different angles; Calculate the three weighting factors for the corresponding zoom distance system; Based on the three weighting factors, the projection data is weighted, filtered, and backprojected to obtain the final reconstructed image. The weighted filtering and backprojection reconstruction includes: the first weighting factor weights and corrects the original projection data before filtering to obtain pre-weighted corrected projection data; the second weighting factor weights and corrects the convolution kernel function, and then convolves the pre-weighted corrected projection data with the weighted and corrected convolution kernel function to obtain filtered projection data; the third weighting factor weights and corrects the filtered projection data to obtain final weighted filtered projection data; and the filtered projection data is then backprojected to obtain the final reconstructed image.
5. The method according to claim 4, characterized in that, The weighted filtering back projection formula of the image reconstruction algorithm is: in, It is the rotation angle. It is the sector angle of the detector element relative to the center of the detector arc. The results were obtained from a system scan at a rotation angle of... The sector angle of the detector element relative to the center of the detector arc is... The height of the detector unit is Projection data at that time, The coordinates are The reconstruction value, The maximum sector angle of the detector element relative to the center of the detector arc; Where R is the radius of the detector's arc. L is the sector angle of the detector unit corresponding to the ray traversed by the reconstructed pixel relative to the center of the detector arc, where L is: Where D is the distance from the ray source to the origin. It is a standard convolution kernel function, the convolution kernel function is And using the SL filter, the discrete form is: in, It is a three-dimensional projection factor: J is the Jacobian determinant of the integral transform of the zoom system: in, It is the sector angle of the detector unit relative to the X-ray source. yes The derivative of is given by , where k is the ratio of the distance from the X-ray source to the center of the detector arc to the distance R between detectors of each other. yes The derivative function; The sector angle of the detector with respect to the center of the detector arc With respect to the fan angle of the radiation source The following relationship exists: The three weighting factors are as follows: , , , Weight the unfiltered projection data. Weighting the filter kernel function The filtered projection data is weighted, where the three weighting factors are represented as follows: in, and It is a polynomial used for estimation.
6. The method according to claim 5, characterized in that, in, The polynomial and yes: 。 7. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the image reconstruction method as described in any one of claims 4-6.