A method, device and medium for unconstrained CBCT system hardening correction

Abstract

The present invention discloses an unconstrained CBCT system hardening correction method, device, and medium. The method comprises: acquiring an air projection image and a projection image of a dedicated correction phantom; calculating a phantom multi-energy line integral image based on the air projection image and the projection image of the dedicated correction phantom; calculating forward projection geometric parameters based on the phantom multi-energy line integral image; forward projecting the dedicated correction phantom based on the forward projection geometric parameters to obtain a target image and target indicators; determining a mapping relationship from multi-energy projection to mono-energy projection based on the target image and the phantom multi-energy line integral image; and performing hardening correction on the multi-energy projection image based on the mapping relationship. The present invention has wide applicability and strong robustness and can be widely used in the field of computed tomography imaging technology.

Description

Technical Field

[0001] The present invention relates to the field of computer tomography technology, and in particular to an unconstrained CBCT system hardening correction method, device and medium. Background Art

[0002] Cone Beam Computed Tomography (CBCT) is widely used in medical fields such as oral diagnosis and image-guided radiotherapy. However, X-ray sources can only produce multi-energy radiation. When penetrating the imaging object, a large number of low-energy soft radiation is absorbed by the object, increasing the average beam energy and causing hardening artifacts in the reconstructed image.

[0003] The main methods for hardening correction in conventional CBCT systems include fitting and iterative methods. The fitting method generally collects and reconstructs uniform water phantom projections, obtains the three-dimensional contour of the object and performs forward projection, thereby obtaining a multi-energy fitting curve between the penetration path and the original projection. The newly collected projection data is then corrected to reconstruct a CBCT image free of hardening artifacts. The fitting method is limited by the accuracy of the forward projection, and its correction effect is less robust. The iterative method generally designs a simulated water phantom image free of hardening artifacts. The polynomial coefficients of the original projection combination are calculated through optimization methods to minimize the difference between the real reconstructed image and the simulated water phantom image. The optimized coefficients are applied to the newly collected projections to obtain the corrected CBCT reconstructed image. The iterative method has a better correction effect, but its setting of the objective function is relatively strict and it is easy to fall into a local solution.

[0004] Furthermore, the two mainstream hardening correction methods are only suitable for artifact correction of small objects or large field of view (FOV) CBCT systems. When the correction phantom is large or the CBCT FOV is small, the reconstructed image will be "truncated," and the complete object outline cannot be captured. This can lead to a significant difference between the beam's penetration path and its true path (or produce truncation artifacts that affect iterative optimization). Conventional hardening correction methods are constrained by the FOV and are difficult to implement in CBCT systems with small FOVs. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method, device, and medium for correcting CBCT system hardening with wide applicability and strong robustness.

[0006] One aspect of the present invention provides an unconstrained CBCT system hardening correction method, comprising:

[0007] Acquire air projection images and projection images of a dedicated calibration phantom;

[0008] Calculating a phantom multi-energy line integral image according to the air projection image and the projection image of the dedicated correction phantom;

[0009] Calculating forward projection geometric parameters according to the multi-energy line integral image of the phantom;

[0010] Performing forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators;

[0011] determining a mapping relationship from multi-energy projection to mono-energy projection according to the target image and the multi-energy line integral image of the phantom;

[0012] A hardening correction is performed on the multi-energy projection image according to the mapping relationship.

[0013] Optionally, the method further includes:

[0014] The hardening-corrected image is reconstructed by filtered back projection to obtain a CBCT reconstructed image without hardening artifacts.

[0015] Optionally, acquiring the air projection image and the projection image of the dedicated correction phantom includes:

[0016] Determining scanning parameters, wherein the scanning parameters include tube voltage, tube current, frame rate, and exposure time;

[0017] Performing a circular scan on the air according to the scanning parameters to obtain the air projection image;

[0018] Positioning the calibration phantom horizontally so that the top center point of the calibration phantom is located on the central axis of rotation of the device;

[0019] The calibration phantom is scanned to obtain a projection image of the dedicated calibration phantom.

[0020] Optionally, the method further includes:

[0021] Determining whether the calibration phantom is horizontally placed based on the projection image of the dedicated calibration phantom, and determining whether the top center point of the calibration phantom is located on the central axis of rotation of the device;

[0022] When the correction model fails to be placed horizontally, or the top center point of the correction model fails to be located on the central axis of rotation of the device, return to the step of horizontally positioning the correction model so that the correction model completes the horizontal placement and the top center point of the correction model is located on the central axis of rotation of the device.

[0023] Optionally, calculating forward projection geometric parameters according to the multi-energy line integral image of the phantom includes:

[0024] The forward projection geometric parameters are calculated using a nonlinear LM optimization iterative algorithm so that the contours of the forward projection image obtained according to the forward projection geometric parameters match those of the multi-energy line integral image.

[0025] Optionally, after the step of forward projecting the dedicated calibration phantom according to the forward projection geometric parameters, the method further includes:

[0026] forward projecting the complete digital model of the dedicated correction phantom according to the forward projection geometric parameters to calculate the ray penetration path projection;

[0027] Taking the image projected by the ray penetration path as the target image, and calculating the target index between the target image and the multi-energy line integral image;

[0028] When the value of the target indicator is less than or equal to a preset threshold, return to the step of calculating the forward projection geometric parameters using a nonlinear LM optimization iterative algorithm until the value of the target indicator is greater than the preset threshold.

[0029] Optionally, determining a mapping relationship from a multi-energy projection to a mono-energy projection according to the target image and the phantom multi-energy line integral image includes:

[0030] When the value of the target index is greater than a preset threshold, a target image obtained by projecting the current ray penetration path is output;

[0031] Polynomial iteration is performed on all pixel sets between the multi-energy line integral image and the target image to determine a mapping relationship from the multi-energy projection to the mono-energy projection.

[0032] Another embodiment of the present invention further provides an unconstrained CBCT system hardening correction device, comprising:

[0033] The first module is used to obtain an air projection image and a projection image of a dedicated calibration phantom;

[0034] A second module is configured to calculate a phantom multi-energy line integral image based on the air projection image and the projection image of the dedicated correction phantom;

[0035] A third module is used to calculate forward projection geometric parameters based on the multi-energy line integral image of the phantom;

[0036] A fourth module is configured to perform forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators;

[0037] A fifth module is configured to determine a mapping relationship from a multi-energy projection to a mono-energy projection based on the target image and the multi-energy line integral image of the phantom;

[0038] The sixth module is used to perform hardening correction on the multi-energy projection image according to the mapping relationship.

[0039] Another aspect of the present invention provides an electronic device including a processor and a memory;

[0040] The memory is used to store programs;

[0041] The processor executes the program to implement the method described above.

[0042] Another aspect of the present invention provides a computer-readable storage medium, wherein the storage medium stores a program, and the program is executed by a processor to implement the method described above.

[0043] The present invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the above method.

[0044] The embodiment of the present invention first obtains an air projection image and a projection image of a special correction phantom; then, based on the air projection image and the projection image of the special correction phantom, calculates the phantom multi-energy line integral image; based on the phantom multi-energy line integral image, calculates the forward projection geometric parameters; based on the forward projection geometric parameters, forward projects the special correction phantom to obtain a target image and target indicators; then, based on the target image and the phantom multi-energy line integral image, determines the mapping relationship from multi-energy projection to single-energy projection; finally, performs hardening correction on the multi-energy projection image according to the mapping relationship. The present invention can effectively solve the problem that a cone-beam imaging system with a small FOV cannot be corrected when the outer contour of the correction phantom cannot be fully reconstructed, and is also compatible with hardening correction of a large FOV. The design concept of the present invention is simple and easy to implement, has strong robustness, and has strong portability and practicality, and can effectively remove hardening artifacts and improve the accuracy of the CT value of the reconstructed image. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. 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 any creative work.

[0046] Figure 1 A schematic diagram of a dedicated calibration phantom provided in an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of an application environment provided by an embodiment of the present invention;

[0048] Figure 3 This is an overall flow chart of the calibration method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0050] In view of the problems existing in the prior art, the present invention provides an unconstrained CBCT system hardening correction method.

[0051] include:

[0052] Acquire air projection images and projection images of a dedicated calibration phantom;

[0053] Calculating a phantom multi-energy line integral image according to the air projection image and the projection image of the dedicated correction phantom;

[0054] Calculating forward projection geometric parameters according to the multi-energy line integral image of the phantom;

[0055] Performing forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators;

[0056] determining a mapping relationship from multi-energy projection to mono-energy projection according to the target image and the multi-energy line integral image of the phantom;

[0057] A hardening correction is performed on the multi-energy projection image according to the mapping relationship.

[0058] Optionally, the method further includes:

[0059] The hardening-corrected image is reconstructed by filtered back projection to obtain a CBCT reconstructed image without hardening artifacts.

[0060] It should be noted that this embodiment performs polynomial iteration on all pixel sets of the target image and the phantom's multi-energy line integral image to obtain a mapping relationship from multi-energy projections to mono-energy projections, thereby obtaining polynomial fitting coefficients, also known as correction coefficients. The correction coefficients are applied to other subsequently acquired data to correct the multi-energy projections, thereby reconstructing a CBCT image free of hardening artifacts.

[0061] Optionally, acquiring the air projection image and the projection image of the dedicated correction phantom includes:

[0062] Determining scanning parameters, wherein the scanning parameters include tube voltage, tube current, frame rate, and exposure time;

[0063] Performing a circular scan on the air according to the scanning parameters to obtain the air projection image;

[0064] Positioning the calibration phantom horizontally so that the top center point of the calibration phantom is located on the central axis of rotation of the device;

[0065] The calibration phantom is scanned to obtain a projection image of the dedicated calibration phantom.

[0066] Optionally, the method further includes:

[0067] Determining whether the calibration phantom is horizontally placed based on the projection image of the dedicated calibration phantom, and determining whether the top center point of the calibration phantom is located on the central axis of rotation of the device;

[0068] When the correction model fails to be placed horizontally, or the top center point of the correction model fails to be located on the central axis of rotation of the device, return to the step of horizontally positioning the correction model so that the correction model completes the horizontal placement and the top center point of the correction model is located on the central axis of rotation of the device.

[0069] Optionally, calculating forward projection geometric parameters according to the multi-energy line integral image of the phantom includes:

[0070] The forward projection geometric parameters are calculated using a nonlinear LM optimization iterative algorithm so that the contours of the forward projection image obtained according to the forward projection geometric parameters match those of the multi-energy line integral image.

[0071] Optionally, after the step of forward projecting the dedicated calibration phantom according to the forward projection geometric parameters, the method further includes:

[0072] forward projecting the complete digital model of the dedicated correction phantom according to the forward projection geometric parameters to calculate the ray penetration path projection;

[0073] Taking the image projected by the ray penetration path as the target image, and calculating the target index between the target image and the multi-energy line integral image;

[0074] When the value of the target indicator is less than or equal to a preset threshold, return to the step of calculating the forward projection geometric parameters using a nonlinear LM optimization iterative algorithm until the value of the target indicator is greater than the preset threshold.

[0075] It should be noted that the forward projection algorithm adopted in this embodiment is the RayCast algorithm.

[0076] The optimized geometric parameters of this embodiment include but are not limited to: the distance SID between the ray source and the detector, the distance AID between the rotation center and the detector, the acquisition angle G, the detector offset distance D, the digital model translation (Mx, My, Mz) and the rotation (Ax, Ay, Az).

[0077] The optimization method selected in this embodiment is the nonlinear LM (Levenberg-Marquardt) algorithm, and the iterative loss function is the structural similarity (SSIM).

[0078] Optionally, determining a mapping relationship from a multi-energy projection to a mono-energy projection according to the target image and the phantom multi-energy line integral image includes:

[0079] When the value of the target index is greater than a preset threshold, a target image obtained by projecting the current ray penetration path is output;

[0080] Polynomial iteration is performed on all pixel sets between the multi-energy line integral image and the target image to determine a mapping relationship from the multi-energy projection to the mono-energy projection.

[0081] It should be noted that, in this embodiment, the polynomial fitting is performed to remove distorted pixels at the edge of the image, and the fitting order is a quartic polynomial.

[0082] An embodiment of the present invention further provides an unconstrained CBCT system hardening correction device, comprising:

[0083] The first module is used to obtain an air projection image and a projection image of a dedicated calibration phantom;

[0084] A second module is configured to calculate a phantom multi-energy line integral image based on the air projection image and the projection image of the dedicated correction phantom;

[0085] A third module is used to calculate forward projection geometric parameters based on the multi-energy line integral image of the phantom;

[0086] A fourth module is configured to perform forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators;

[0087] A fifth module is configured to determine a mapping relationship from a multi-energy projection to a mono-energy projection based on the target image and the multi-energy line integral image of the phantom;

[0088] The sixth module is used to perform hardening correction on the multi-energy projection image according to the mapping relationship.

[0089] An embodiment of the present invention further provides an electronic device, including a processor and a memory;

[0090] The memory is used to store programs;

[0091] The processor executes the program to implement the method described above.

[0092] An embodiment of the present invention further provides a computer-readable storage medium, wherein the storage medium stores a program, and the program is executed by a processor to implement the method described above.

[0093] The present invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the above method.

[0094] The specific implementation process of the present invention is described in detail below with reference to the accompanying drawings:

[0095] Figure 2 The cone-beam computed tomography system designed for this invention features a small detector and a large imaged object. Conventional imaging methods often result in significant object truncation. The application of detector biasing technology effectively expands the FOV and minimizes the truncation of the imaged object.

[0096] Figure 3 The flow chart of the correction method provided by the present invention is applied to Figure 2 The cone-beam computed tomography system in FIG. 1 is used as an example to illustrate the method, which includes the following steps:

[0097] S100: Level the loading platform of the scanning device. The digital level indicator shows that the angle deviation should be less than 0.5 degrees. Use the laser light device to indicate the center position of the rotating axis of the scanning device. Figure 1The special correction phantom shown is cylindrical in shape, with a diameter of 20mm and a height of 25mm, and is filled with PMMA. A layer of circular and evenly distributed positioning columns is nested on the upper part of the special correction phantom. The positioning columns are made of aluminum, with a height of 8cm and a diameter of 5mm. Before collecting the phantom, the positioning columns need to be inserted into the holes of the cylindrical phantom with an insertion depth of 5cm. The positioning columns are used in subsequent steps to determine whether the outer contour of the forward projection matches the multi-energy line integral image of the special phantom. Place the phantom on a leveled stage, and adjust the position of the correction phantom so that its top center point coincides with the rotation center point indicated by the vertical laser. Perform image acquisition on the special correction phantom, remove the phantom, and then collect images of the air to obtain the air projection image p1 and the correction phantom projection image p2 at each acquisition angle. According to the Lambert-Beer law, the multi-energy line integral image can be obtained.

[0098] In this step, the equipment's laser indicator must accurately indicate the center of rotation and the phantom must be level. Perform a 360-degree circular scan of the phantom and observe the projected image in the imaging software for significant tilt or positional offset. If the projected image is severely tilted or significantly offset, further leveling of the scanning equipment is required, and the laser indicator must be correctly indicating the center of rotation and the phantom must be positioned near the center of rotation.

[0099] S110: Use the Ray Cast algorithm to forward project the complete digital model of the dedicated calibration phantom and calculate the ray penetration path The calculation formula of forward projection can be described as follows:

[0100]

[0101] Where Q(r) represents the state value of the object at a distance r from the ray source. If there is matter at r, Q takes the value of 1, otherwise it takes the value of 0. dr is the differential element of ray r in the penetration direction, which can be expressed in Cartesian coordinates as

[0102] To match the forward projected image The multi-energy line integral image A is implemented by iterative nonlinear LM optimization algorithm. The geometric parameters optimized in this embodiment include: the distance SID between the ray source and the detector, the distance AID between the rotation center and the detector, the acquisition angle G, the detector offset distance μ0, the digital model translation (Mx, My, Mz) and the rotation (Ax, Ay, Az). The initial values ​​of the geometric parameters to be optimized are set to SID = 450mm, AID = 200mm, G = 90 degrees, μ0 = 35mm, (Mx, My, Mz) = (0, 0, 0), (Ax, Ay, Az) = (0, 0, 0). In order to achieve efficient optimization, the structural similarity function (SSIM) is used as the loss function of LM in this embodiment, and the matching process can be described by the following optimization formula:

[0103]

[0104] Among them, μ A 、 Represent the multi-energy line integral image A and the penetration path image respectively The mean of . Represents image A and penetration path image The variance of . Represents image A and image 1. c2 are constants. Their purpose is to avoid instability when the denominator is close to 0. In the embodiment, c1=2.5 and c2=7.5 are taken. The calculation formula can be described by the following formula:

[0105]

[0106]

[0107]

[0108]

[0109]

[0110] The penetration path image calculated by the forward projection The more similar the outer contour is to the multi-energy line integral image A, the larger the SSIM value is, and the optimal output image is B. Multiple angles can be selected for forward projection optimization to increase the accuracy of the matching.

[0111] S120: Perform polynomial iteration on all pixel sets of images A and B to obtain the mapping relationship from multi-energy projection to mono-energy projection. During the polynomial fitting, distorted pixels at the image edges are removed to reduce fitting deviation. The fitting order is a quartic polynomial, so there are four parameters to be optimized. Assuming the parameters to be fitted are a1, a2, a3, and a4, the iterative process can be described by the following formula:

[0112]

[0113]

[0114] S130: Performing hardening correction on the newly acquired multi-energy projection image according to the mapping relationship obtained by the above iteration, and performing filtered back projection reconstruction on the corrected image to obtain a CBCT reconstructed image without hardening artifacts.

[0115] In summary, this invention effectively addresses the problem of cone-beam imaging systems with small FOVs being unable to perform corrections without fully reconstructing the phantom's external contours, while also being compatible with hardening correction for larger FOVs. The invention boasts a simple and easy-to-implement design, strong robustness, portability, and practicality, effectively removing hardening artifacts and improving the CT accuracy of reconstructed images.

[0116] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0117] Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise indicated, one or more of the functions and / or features described may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It will also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the ordinary skill of an engineer. Therefore, a person skilled in the art using ordinary skill will be able to implement the present invention set forth in the claims without undue experimentation. It will also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0118] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0119] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the 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 (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0120] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0121] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0122] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations 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 any one or more embodiments or examples.

[0123] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0124] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. An unconstrained CBCT system hardening correction method, characterized in that: include: Acquire air projection images and projection images of a dedicated calibration phantom; Calculating a phantom multi-energy line integral image according to the air projection image and the projection image of the dedicated correction phantom; Calculating forward projection geometric parameters according to the multi-energy line integral image of the phantom; The step of calculating the forward projection geometric parameters based on the multi-energy line integral image of the phantom includes: Using a nonlinear LM optimization iterative algorithm to calculate the forward projection geometric parameters, so that the forward projection image obtained according to the forward projection geometric parameters matches the contour of the phantom multi-energy line integral image; Performing forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators; Wherein, after the step of forward projecting the dedicated calibration phantom according to the forward projection geometric parameters, the method further includes: forward projecting the complete digital model of the dedicated correction phantom according to the forward projection geometric parameters to calculate the ray penetration path projection; Taking the image projected by the ray penetration path as the target image, and calculating the target index between the target image and the multi-energy line integral image of the phantom; When the value of the target indicator is less than or equal to a preset threshold, returning to the step of calculating the forward projection geometric parameters using a nonlinear LM optimization iterative algorithm until the value of the target indicator is greater than the preset threshold; determining a mapping relationship from multi-energy projection to mono-energy projection according to the target image and the multi-energy line integral image of the phantom; A hardening correction is performed on the multi-energy projection image according to the mapping relationship.

2. The unconstrained CBCT system hardening correction method according to claim 1, characterized in that: The method further comprises: The hardening-corrected image is reconstructed by filtered back projection to obtain a CBCT reconstructed image without hardening artifacts.

3. The unconstrained CBCT system hardening correction method according to claim 1, characterized in that: The step of acquiring the air projection image and the projection image of the dedicated correction phantom includes: Determining scanning parameters, wherein the scanning parameters include tube voltage, tube current, frame rate, and exposure time; Performing a circular scan on the air according to the scanning parameters to obtain the air projection image; Positioning the calibration phantom horizontally so that the top center point of the calibration phantom is located on the central axis of rotation of the device; The calibration phantom is scanned to obtain a projection image of the dedicated calibration phantom.

4. The unconstrained CBCT system hardening correction method according to claim 3, characterized in that: The method further comprises: Determining whether the calibration phantom is horizontally placed based on the projection image of the dedicated calibration phantom, and determining whether the top center point of the calibration phantom is located on the central axis of rotation of the device; When the correction model fails to be placed horizontally, or the top center point of the correction model fails to be located on the central axis of rotation of the device, return to the step of horizontally positioning the correction model so that the correction model completes the horizontal placement and the top center point of the correction model is located on the central axis of rotation of the device.

5. The unconstrained CBCT system hardening correction method according to claim 1, characterized in that: The determining, based on the target image and the phantom multi-energy line integral image, a mapping relationship from a multi-energy projection to a mono-energy projection includes: When the value of the target index is greater than a preset threshold, a target image obtained by projecting the current ray penetration path is output; Polynomial iteration is performed on all pixel sets between the phantom multi-energy line integral image and the target image to determine a mapping relationship from the multi-energy projection to the mono-energy projection.

6. An unconstrained CBCT system hardening correction device, characterized in that: include: The first module is used to obtain an air projection image and a projection image of a dedicated calibration phantom; A second module is configured to calculate a phantom multi-energy line integral image based on the air projection image and the projection image of the dedicated correction phantom; A third module is used to calculate forward projection geometric parameters based on the multi-energy line integral image of the phantom; The step of calculating the forward projection geometric parameters based on the multi-energy line integral image of the phantom includes: Using a nonlinear LM optimization iterative algorithm to calculate the forward projection geometric parameters, so that the forward projection image obtained according to the forward projection geometric parameters matches the contour of the phantom multi-energy line integral image; A fourth module is configured to perform forward projection on the dedicated calibration phantom according to the forward projection geometric parameters to obtain a target image and target indicators; The device further includes a module for performing the following steps after the fourth module completes the step of forward projecting the dedicated calibration phantom: forward projecting the complete digital model of the dedicated correction phantom according to the forward projection geometric parameters to calculate the ray penetration path projection; Taking the image projected by the ray penetration path as the target image, and calculating the target index between the target image and the multi-energy line integral image of the phantom; When the value of the target indicator is less than or equal to a preset threshold, returning to the step of calculating the forward projection geometric parameters using a nonlinear LM optimization iterative algorithm until the value of the target indicator is greater than the preset threshold; A fifth module is configured to determine a mapping relationship from a multi-energy projection to a mono-energy projection based on the target image and the multi-energy line integral image of the phantom; The sixth module is used to perform hardening correction on the multi-energy projection image according to the mapping relationship.

7. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The storage medium stores a program, and the program is executed by a processor to implement the method according to any one of claims 1 to 5.

Images