Energy spectrum cone beam artifact suppression method, device, equipment, medium and program product

Abstract

The present application relates to the field of medical imaging technology, and in particular to a method, apparatus, device, medium, and program product for suppressing energy spectrum cone beam artifacts, wherein the method comprises: acquiring high- and low-energy projection data and reconstructing high- and low-energy CT images; performing energy spectrum reconstruction on the high- and low-energy projection data to obtain a base material image to generate virtual monoenergetic images at two target energies, and performing cone beam artifact correction processing to obtain two corrected virtual monoenergetic images and a cone beam artifact error image; performing a linear weighted combination of the two corrected virtual monoenergetic images to obtain a corrected base material image and virtual monoenergetic images at other energies; and subtracting the cone beam artifact error images at corresponding equivalent energies from the high- and low-energy CT images to obtain corrected high- and low-energy CT images. Thus, the method solves the problems in the related art of cone beam artifacts generated by image reconstruction and the need to repeat the two-step method multiple times to correct the cone beam artifacts, resulting in cumbersome operations and increased time costs.

Description

Technical Field

[0001] The present application relates to the field of medical imaging technology, and in particular to a method, device, equipment, medium and program product for suppressing energy spectrum cone beam artifacts. Background Art

[0002] In the related art, wide-body cone-beam CT based on multi-row detectors and flat-panel detectors can use the FDK reconstruction algorithm to quickly and effectively reconstruct a three-dimensional image of an object by performing a single-circle scan around the object.

[0003] However, in related technologies, due to the lack of sampling space data, faults other than the center plane cannot be accurately reconstructed, especially at positions deviating from the center plane. The cone beam artifacts will become more serious with the increase of the scanning cone angle, and the cone beam artifacts need to be corrected by repeating the two-step method multiple times. The operation is cumbersome and very time-consuming, and needs to be improved urgently. Summary of the Invention

[0004] The present application provides a method, apparatus, device, medium and program product for suppressing energy spectrum cone beam artifacts to solve the problems in the related art, such as cone beam artifacts generated by image reconstruction and the need to repeat the two-step method for correction, which may lead to cumbersome operations and increased time costs.

[0005] The first aspect of the present application provides a method for suppressing energy spectrum cone beam artifacts, comprising the following steps: acquiring high- and low-energy projection data, and reconstructing the high- and low-energy projection data respectively to obtain high- and low-energy CT images; performing energy spectrum reconstruction on the high- and low-energy projection data to obtain base material images, so as to generate two virtual monoenergetic images at target energies based on the base material images, wherein the two target energies are the equivalent energies of the high- and low-energy CT images, respectively; performing cone beam artifact correction processing on the virtual monoenergetic images at the two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image; obtaining a corrected base material image and virtual monoenergetic images at other energies based on a linear weighted combination of the two corrected virtual monoenergetic images; and subtracting the cone beam artifact error images at the corresponding equivalent energies from the high- and low-energy CT images respectively to obtain high- and low-energy CT images after cone beam artifact correction.

[0006] Optionally, in one embodiment of the present application, the energy spectrum reconstruction of the high- and low-energy projection data to obtain the base material image includes: performing projection domain base material decomposition on the high- and low-energy projection data to obtain projection images of two base materials; and combining the projection images of the two base materials and the target reconstruction algorithm to obtain two base material images.

[0007] Optionally, in one embodiment of the present application, the energy spectrum reconstruction of the high and low energy projection data to obtain the base material image includes: based on the high and low energy projection data, using a target reconstruction algorithm to obtain reconstructed high and low energy CT images; and performing image domain base material decomposition on the reconstructed high and low energy CT images to obtain two base material images.

[0008] Optionally, in one embodiment of the present application, the cone beam artifact correction processing of the virtual monoenergetic images at the two target energies includes: preprocessing each virtual monoenergetic image to obtain a prior image; forward projecting and reconstructing the prior image to obtain a prior image containing cone beam artifacts, so as to calculate the difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image; and subtracting the cone beam artifact error estimation image from each virtual monoenergetic image to obtain the corrected virtual monoenergetic image.

[0009] The second aspect of the present application provides an energy spectrum cone beam artifact suppression device, including: an acquisition module for acquiring high- and low-energy projection data, and reconstructing the high- and low-energy projection data respectively to obtain high- and low-energy CT images; a generation module for performing energy spectrum reconstruction on the high- and low-energy projection data to obtain a base material image, so as to generate two virtual monoenergetic images at target energies based on the base material image, wherein the two target energies are the equivalent energies of the high- and low-energy CT images, respectively; a processing module for performing cone beam artifact correction processing on the virtual monoenergetic images at the two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image; a first correction module for obtaining a corrected base material image and virtual monoenergetic images at other energies based on a linear weighted combination of the two corrected virtual monoenergetic images; and a second correction module for subtracting the cone beam artifact error images at the corresponding equivalent energies from the high- and low-energy CT images respectively to obtain high- and low-energy CT images after cone beam artifact correction.

[0010] Optionally, in one embodiment of the present application, the generation module includes: a first decomposition unit, used to perform projection domain basis material decomposition on the high and low energy projection data to obtain projection images of two basis materials; a first reconstruction unit, used to combine the projection images of the two basis materials and the target reconstruction algorithm to obtain two basis material images.

[0011] Optionally, in one embodiment of the present application, the generation module includes: a second reconstruction unit, used to obtain reconstructed high- and low-energy CT images based on the high- and low-energy projection data using a target reconstruction algorithm; a second decomposition unit, used to perform image domain basis material decomposition on the reconstructed high- and low-energy CT images to obtain two basis material images.

[0012] Optionally, in one embodiment of the present application, the processing module includes: a processing unit, used to preprocess each virtual monoenergetic image to obtain a prior image; a calculation unit, used to forward project and reconstruct the prior image to obtain a prior image containing cone beam artifacts, so as to calculate the difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image; and a correction unit, used to subtract the cone beam artifact error estimation image from each virtual monoenergetic image to obtain the corrected virtual monoenergetic image.

[0013] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the energy spectrum cone beam artifact suppression method as described in the above embodiment.

[0014] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, the above-mentioned energy spectrum cone beam artifact suppression method is implemented.

[0015] A fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned energy spectrum cone beam artifact suppression method.

[0016] The embodiment of the present application can obtain high- and low-energy CT images by reconstructing the acquired high- and low-energy projection data, and use the high- and low-energy projection data to perform energy spectrum reconstruction to obtain a base material image, thereby generating two virtual monoenergetic images at different target energies, and after performing cone beam artifact correction on these two virtual monoenergetic images, a linear weighted combination method is used to generate a corrected base material image and virtual monoenergetic images at other energies, and the cone beam artifact error image at the corresponding equivalent energy is subtracted from the high- and low-energy CT images to obtain high- and low-energy CT images after cone beam artifact correction, which can effectively suppress cone beam artifacts, significantly improve image uniformity and contrast, and can effectively save processing time and computing resources, thereby improving work efficiency. Thus, the problem in the related art that cone beam artifacts are generated during image reconstruction and cone beam artifacts need to be corrected by repeated two-step methods multiple times may result in cumbersome operations and increased time costs is solved.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 This is a flow chart of a method for suppressing energy spectrum cone beam artifacts according to an embodiment of the present application;

[0020] Figure 2 Flowchart of a method for suppressing energy spectrum cone beam artifacts according to one embodiment of the present application;

[0021] Figure 3 1 is a flowchart of cone beam artifact correction based on a two-step method according to one embodiment of the present application;

[0022] Figure 4 Schematic diagram of cone beam artifact correction results according to one embodiment of the present application;

[0023] Figure 5 This is a schematic diagram of result analysis according to one embodiment of the present application;

[0024] Figure 6 Schematic diagram of the structure of a device for suppressing energy spectrum cone beam artifacts according to an embodiment of the present application;

[0025] Figure 7 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0027] The following describes the energy spectrum cone beam artifact suppression method, apparatus, device, medium, and program product of the embodiments of the present application with reference to the accompanying drawings. In response to the problem in the related art mentioned in the background art above that cone beam artifacts are generated by image reconstruction and cone beam artifacts need to be corrected by repeating a two-step method multiple times, which may lead to cumbersome operations and increased time costs, the present application provides an energy spectrum cone beam artifact suppression method. In this method, high- and low-energy CT images can be obtained by reconstructing the acquired high- and low-energy projection data, and the high- and low-energy projection data are used to perform energy spectrum reconstruction to obtain a base material image, thereby generating two virtual monoenergetic images at different target energies. After cone beam artifact correction is performed on these two virtual monoenergetic images, a linear weighted combination method is used to generate the corrected base material image and virtual monoenergetic images at other energies. The cone beam artifact error images at the corresponding equivalent energy are subtracted from the high- and low-energy CT images to obtain high- and low-energy CT images after cone beam artifact correction. This method can effectively suppress cone beam artifacts, significantly improve image uniformity and contrast, and effectively save processing time and computing resources, thereby improving work efficiency. This solves the problem in related technologies that cone beam artifacts are generated due to image reconstruction and the cone beam artifacts need to be corrected by repeating the two-step method multiple times, which may lead to cumbersome operations and increased time costs.

[0028] Specifically, Figure 1 A schematic flow chart of a method for suppressing energy spectrum cone beam artifacts provided in an embodiment of the present application.

[0029] like Figure 1 As shown, the energy spectrum cone beam artifact suppression method includes the following steps:

[0030] In step S101 , high-energy and low-energy projection data are acquired, and the high-energy and low-energy projection data are reconstructed respectively to obtain high-energy and low-energy CT images.

[0031] It is understood that high- and low-energy projection data refer to ray projection data collected at higher and lower energy levels;

[0032] Specifically, in the dual-energy CT technology, the embodiment of the present application can obtain high- and low-energy projection data, and reconstruct the high- and low-energy projection data separately to obtain high- and low-energy CT images, wherein the obtained high- and low-energy projection data can be expressed as:

[0033]

[0034]

[0035] Among them, P1, P2, S1(E), and S2(E) represent the low-energy projection, high-energy projection, and the corresponding equivalent energy spectrum, respectively. E1 and E2 represent the equivalent energy of the low-energy spectrum and the high-energy spectrum; μ1(E), μ2(E), ρ1, and ρ2 represent the mass attenuation coefficient and density distribution of the two base materials at energy E, respectively.

[0036] It is worth noting that in the dual-energy imaging in the embodiments of the present application, if it is based on dual-source dual-detector technology, the system should include two groups of ray sources and detectors that generally interact with each other perpendicularly; if it is based on double-layer detector technology, the detectors in the system should be double-layer detectors; if it is based on fast kilovolt switching technology, the ray sources in the system should have fast kilovolt switching capabilities, and other technologies can be deduced by analogy.

[0037] The embodiments of the present application can more accurately distinguish the characteristics of different tissues by acquiring high- and low-energy projection data, and can perform more precise quantitative analysis by reconstructing high- and low-energy CT images, thereby improving the contrast and clarity of high- and low-energy CT images.

[0038] In step S102, energy spectrum reconstruction is performed on the high-energy and low-energy projection data to obtain a base material image, so as to generate virtual monoenergetic images at two target energies according to the base material image, wherein the two target energies are equivalent energies of the high-energy and low-energy CT images, respectively.

[0039] It can be understood that the base material image refers to the density distribution map of different base materials obtained by material decomposition, and the virtual monoenergetic image refers to an image that can show the attenuation of the material under the target energy. The two target energies can be selected as the energy efficiency energies E1 and E2 corresponding to the low-energy spectrum and the high-energy spectrum.

[0040] Optionally, in one embodiment of the present application, energy spectrum reconstruction is performed on high and low energy projection data to obtain a base material image, including: performing projection domain base material decomposition on the high and low energy projection data to obtain projection images of two base materials; combining the projection images of the two base materials and the target reconstruction algorithm to obtain two base material images.

[0041] Optionally, in one embodiment of the present application, energy spectrum reconstruction is performed on high and low energy projection data to obtain base material images, including: based on the high and low energy projection data, using a target reconstruction algorithm to obtain reconstructed high and low energy CT images; performing image domain base material decomposition on the reconstructed high and low energy CT images to obtain two base material images.

[0042] It is understandable that the target reconstruction algorithm refers to a mathematical algorithm used to reconstruct a cross-sectional image of a target object from original projection data, such as FDK (Feldkamp-Davis-Kress) or similar reconstruction algorithms such as T-FDK.

[0043] Specifically, the embodiment of the present application can be based on the obtained high and low energy projection data {P i}, and solve the nonlinear equations according to formula (1) to obtain the projection images of the two base materials, and then use the FDK reconstruction algorithm to reconstruct the density distribution of different base materials to obtain the density distribution images of different base materials, that is, the base material images. Alternatively, the embodiment of the present application can be based on the high and low energy projection data {P i}, the FDK reconstruction algorithm is used to obtain the reconstructed high- and low-energy CT images, and then the reconstructed high- and low-energy CT images are decomposed in the image domain to obtain two basis material images.

[0044] Furthermore, the embodiment of the present application can generate virtual monoenergetic images of different base materials at two energies based on the density distribution image and the linear attenuation coefficient. In the embodiment of the present application, the density images of the base materials can be weighted added according to a calculation expression to obtain virtual monoenergetic images of the scanned object at energies E1 and E2. The calculation expression can be specifically as follows:

[0045]

[0046]

[0047] Where μ(E,r) represents the linear attenuation coefficient of the object at position r and energy E.

[0048] It is worth noting that the embodiment of the present application performs weighted addition of the density images of the base materials, where the weights are determined by the attenuation coefficients of different base materials at the target energy, and two different energy points are selected, usually a higher energy and a lower energy, to cover a wider energy spectrum range.

[0049] The present embodiment performs energy spectrum reconstruction on high- and low-energy projection data to obtain a base material image, which helps reduce artifacts. The base material image provides material information, providing an information foundation for the subsequent generation of a virtual monoenergetic image. Generating virtual monoenergetic images at two target energies based on the base material image facilitates analysis of the different contrast and noise characteristics of virtual monoenergetic images (VMIs) at different energies, helps reduce artifact intensity in surrounding areas, and improves image quality, flexibility, and accuracy in clinical applications.

[0050] In step S103 , cone beam artifact correction processing is performed on the virtual monoenergetic images at the two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image.

[0051] Optionally, in one embodiment of the present application, cone beam artifact correction processing is performed on virtual monoenergetic images at two target energies, including: preprocessing each virtual monoenergetic image to obtain a prior image; forward projecting and reconstructing the prior image to obtain a prior image containing cone beam artifacts, so as to calculate the difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image; and subtracting the cone beam artifact error estimation image from each virtual monoenergetic image to obtain a corrected virtual monoenergetic image.

[0052] It can be understood that preprocessing includes but is not limited to threshold segmentation, noise reduction and other processing.

[0053] Specifically, combined Figure 2 As shown, taking dual-energy CT imaging as an example, cone beam artifact correction processing for virtual single-energy images at two target energies can be performed as follows:

[0054] Step S1: Decompose the material in the projection domain using the collected energy spectrum data to obtain a base material image and give the base material image a virtual monoenergetic image at two energies, where the energy is selected to be the equivalent energy E1 and E2 of the high and low energy spectra.

[0055] Step S2: performing a two-step cone beam artifact correction process on the virtual monoenergetic images at the two energies to obtain corrected virtual monoenergetic images.

[0056] Among them, combined Figure 3 As shown in the figure, for a single reconstructed 3D image, cone beam artifact correction can be achieved by a two-step method for cranial imaging. The specific method can be as follows:

[0057] (1) Perform threshold segmentation and other processing (M(·)) on the initial image (denoted by f) to divide the image into air, soft tissue, and bone. Set the air to 0, the soft tissue to a suitable constant, and the bone to be processed or not. The processed image is denoted as M(f);

[0058] (2) Perform forward projection P(·) and FDK reconstruction operation R(·) on the processed image to obtain the image R(P(M(f));

[0059] (3) Smoothing the image M(f) by S(·) to make its resolution roughly match R(P(M(f))) and subtracting the two to obtain the estimated image f of the cone beam artifact a =R(P(M(f))-S(M(f);

[0060] (4) Subtract the artifact estimation image from the initial image to obtain the cone beam artifact corrected image f c =ff a .

[0061] The embodiment of the present application performs cone beam artifact correction processing on virtual monoenergetic images at two target energies, which helps to reduce artifact interference, improve image clarity and accuracy, and facilitate quantitative analysis, greatly saving time and computing resources.

[0062] In step S104, a corrected base material image and virtual monoenergetic images at other energies are obtained according to a linear weighted combination of the two corrected virtual monoenergetic images.

[0063] Specifically, combined Figure 2 As shown, taking dual-energy CT imaging as an example, cone beam artifact correction processing can be performed as follows:

[0064] Step S3: The two corrected virtual monoenergetic images are decomposed again to obtain two basis material images. Virtual monoenergetic images at other energies can be obtained by linear combination of basis materials. The virtual monoenergetic images obtained in this way can correct cone beam artifacts.

[0065] In the actual implementation process, according to formula (2), it can be seen in the embodiment of the present application that the virtual monoenergetic images at different energies are all linear combinations of the base material images, and the virtual monoenergetic images are also linearly correlated. The forward projection and reconstruction operations of the correction process in the two-step method also maintain the linear consistency of the input and output. Therefore, the embodiment of the present application can perform correction operations only on the virtual monoenergetic images at two energies to achieve cone beam artifact correction for other energies.

[0066] In addition, combined Figure 4 As shown, the embodiment of the present application can simply and efficiently implement cone beam artifact correction of virtual monoenergetic images within a range of energy. In this case, several regions of interest are selected in the image for numerical statistics. The results are as follows: Figure 5 As shown in the figure, the quantitative analysis of the results shows that the uniformity of the image is greatly improved after correction.

[0067] In step S105 , the cone beam artifact error images at corresponding equivalent energies are subtracted from the high and low energy CT images, respectively, to obtain the high and low energy CT images after cone beam artifact correction.

[0068] Specifically, combined Figure 2 As shown, taking dual-energy CT imaging as an example, cone beam artifact correction processing can be performed as follows:

[0069] Step S4: For the high- and low-energy CT images directly reconstructed from the high- and low-energy projection data, the artifact estimates obtained in the correction process in step S2 can be directly used as the artifact estimates in the high- and low-energy CT images and subtracted from them to obtain the corrected high- and low-energy CT images.

[0070] The embodiment of the present application only needs to correct the images of two selected energy points, and the images of the remaining energy points can be generated by linear combination, which significantly reduces the number of repeated corrections and the time required, effectively improves the efficiency of correction, and can further optimize the image quality. The corrected high- and low-energy CT images are helpful to identify and quantify specific types of substances, such as calcifications, metal implants, fat, bones and soft tissues. The low-energy CT images can enhance the contrast of soft tissues, and the high-energy CT images can reduce noise, effectively improving the image quality and providing technical support for diagnosis and treatment.

[0071] According to the energy spectrum cone beam artifact suppression method proposed in the embodiment of the present application, high and low energy CT images can be obtained by reconstructing the acquired high and low energy projection data, and the high and low energy projection data are used to perform energy spectrum reconstruction to obtain a base material image, thereby generating two virtual monoenergetic images at different target energies. After the two virtual monoenergetic images are subjected to cone beam artifact correction, a linear weighted combination method is used to generate the corrected base material image and the virtual monoenergetic image at other energies. The cone beam artifact error image at the corresponding equivalent energy is subtracted from the high and low energy CT images to obtain the high and low energy CT images after cone beam artifact correction. This can effectively suppress cone beam artifacts, significantly improve image uniformity and contrast, and effectively save processing time and computing resources, thereby improving work efficiency. Thus, the problem in the related art that cone beam artifacts are generated due to image reconstruction, and the cone beam artifacts need to be corrected by repeating the two-step method multiple times, which may lead to cumbersome operations and increased time costs, is solved.

[0072] Next, the energy spectrum cone beam artifact suppression device proposed according to the embodiment of the present application is described with reference to the accompanying drawings.

[0073] Figure 6 Schematic diagram of a block diagram of an energy spectrum cone beam artifact suppression device according to an embodiment of the present application.

[0074] like Figure 6 As shown, the energy spectrum cone-beam artifact suppression device 10 includes: an acquisition module 100 , a generation module 200 , a processing module 300 , a first correction module 400 and a second correction module 500 .

[0075] Specifically, the acquisition module 100 is used to acquire high-energy and low-energy projection data, and reconstruct the high-energy and low-energy projection data respectively to obtain high-energy and low-energy CT images;

[0076] A generation module 200 is configured to perform energy spectrum reconstruction on the high-energy and low-energy projection data to obtain a base material image, and to generate virtual monoenergetic images at two target energies based on the base material image, wherein the two target energies are equivalent energies of the high-energy and low-energy CT images, respectively;

[0077] The processing module 300 is configured to perform cone beam artifact correction on the virtual monoenergetic images at two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image.

[0078] A first correction module 400 is configured to obtain a corrected base material image and virtual monoenergetic images at other energies based on a linear weighted combination of the two corrected virtual monoenergetic images;

[0079] The second correction module 500 is used to subtract the cone beam artifact error images at corresponding equivalent energies from the high and low energy CT images, respectively, to obtain high and low energy CT images after cone beam artifact correction.

[0080] Optionally, in one embodiment of the present application, the generation module 200 includes: a first decomposition unit and a first reconstruction unit.

[0081] The first decomposition unit is used to perform projection domain basis material decomposition on the high and low energy projection data to obtain projection images of two basis materials;

[0082] The first reconstruction unit is configured to obtain two base material images by combining the projection images of the two base materials and a target reconstruction algorithm.

[0083] Optionally, in one embodiment of the present application, the generation module 200 includes: a second reconstruction unit and a second decomposition unit.

[0084] The second reconstruction unit is configured to obtain reconstructed high- and low-energy CT images using a target reconstruction algorithm based on the high- and low-energy projection data;

[0085] The second decomposition unit is used to perform image domain basis material decomposition on the reconstructed high-energy and low-energy CT images to obtain two basis material images.

[0086] Optionally, in one embodiment of the present application, the processing module 300 includes: a processing unit, a calculation unit, and a correction unit.

[0087] The processing unit is used to pre-process each virtual monoenergetic image to obtain a priori image;

[0088] a computing unit, configured to forward project and reconstruct the prior image to obtain a prior image containing cone beam artifacts, and to calculate a difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image;

[0089] The correction unit is used to subtract the cone beam artifact error estimation image from each virtual monoenergetic image to obtain a corrected virtual monoenergetic image.

[0090] It should be noted that the above explanations of the embodiment of the energy spectrum cone-beam artifact suppression method are also applicable to the energy spectrum cone-beam artifact suppression device of this embodiment, and will not be repeated here.

[0091] According to the energy spectrum cone beam artifact suppression device proposed in the embodiment of the present application, high and low energy CT images can be obtained by reconstructing the acquired high and low energy projection data, and the high and low energy projection data are used to perform energy spectrum reconstruction to obtain a base material image, thereby generating two virtual monoenergetic images at different target energies. After the two virtual monoenergetic images are subjected to cone beam artifact correction, a linear weighted combination method is used to generate the corrected base material image and the virtual monoenergetic image at other energies, and the cone beam artifact error image at the corresponding equivalent energy is subtracted from the high and low energy CT images to obtain the high and low energy CT images after cone beam artifact correction. This can effectively suppress cone beam artifacts, significantly improve image uniformity and contrast, and effectively save processing time and computing resources, thereby improving work efficiency. Thus, the problem in the related art that cone beam artifacts are generated due to image reconstruction and the cone beam artifacts need to be corrected by repeating the two-step method multiple times may lead to cumbersome operations and increased time costs is solved.

[0092] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0093] A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .

[0094] When the processor 702 executes the program, the energy spectrum cone-beam artifact suppression method provided in the above embodiment is implemented.

[0095] Furthermore, the electronic device further includes:

[0096] The communication interface 703 is used for communication between the memory 701 and the processor 702 .

[0097] The memory 701 is used to store computer programs that can be run on the processor 702 .

[0098] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0099] If the memory 701, processor 702, and communication interface 703 are implemented independently, the communication interface 703, memory 701, and processor 702 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0100] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.

[0101] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0102] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned energy spectrum cone beam artifact suppression method when executed by a processor.

[0103] An embodiment of the present application further provides a computer program product, which can run computer instructions. When the computer instructions are executed by a processor, the above energy spectrum cone beam artifact suppression method is implemented.

[0104] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0105] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0106] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing a custom logical function or process step, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed in a different order than shown or discussed, including performing functions in a substantially simultaneous manner or in a reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0107] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced 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. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, 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 can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0108] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, it can be implemented using any one or a combination of the following technologies known in the art: 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.

[0109] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0110] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0111] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for suppressing energy spectrum cone beam artifacts, characterized in that: The following steps are involved: Acquiring high-energy and low-energy projection data, and reconstructing the high-energy and low-energy projection data respectively to obtain high-energy and low-energy CT images; Performing energy spectrum reconstruction on the high-energy and low-energy projection data to obtain a base material image, and generating virtual monoenergetic images at two target energies according to the base material image, wherein the two target energies are equivalent energies of the high-energy and low-energy CT images, respectively; performing cone beam artifact correction processing on the virtual monoenergetic images at the two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image; Obtaining a corrected base material image and virtual monoenergetic images at other energies according to a linear weighted combination of the two corrected virtual monoenergetic images; The cone beam artifact error images at corresponding equivalent energies are subtracted from the high and low energy CT images respectively to obtain high and low energy CT images after cone beam artifact correction.

2. The method according to claim 1, characterized in that The reconstructing the energy spectrum of the high and low energy projection data to obtain a base material image includes: Performing projection domain-based material decomposition on the high-energy and low-energy projection data to obtain projection images of two base materials; The projection images of the two base materials are combined with a target reconstruction algorithm to obtain two base material images.

3. The method according to claim 1, characterized in that The reconstructing the energy spectrum of the high and low energy projection data to obtain a base material image includes: Based on the high and low energy projection data, a target reconstruction algorithm is used to obtain reconstructed high and low energy CT images; The reconstructed high-energy and low-energy CT images are subjected to image domain basis material decomposition to obtain two basis material images.

4. The method according to claim 1, wherein The performing cone beam artifact correction processing on the virtual monoenergetic images at the two target energies includes: Preprocess each virtual monoenergetic image to obtain a priori image; forward projecting and reconstructing the prior image to obtain a prior image containing cone beam artifacts, and calculating a difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image; The cone beam artifact error estimation image is subtracted from each virtual monoenergetic image to obtain the corrected virtual monoenergetic image.

5. A device for suppressing energy spectrum cone beam artifacts, characterized in that: include: an acquisition module, configured to acquire high-energy and low-energy projection data, and reconstruct the high-energy and low-energy projection data respectively to obtain high-energy and low-energy CT images; a generating module, configured to perform energy spectrum reconstruction on the high-energy and low-energy projection data to obtain a base material image, and to generate virtual monoenergetic images at two target energies based on the base material image, wherein the two target energies are equivalent energies of the high-energy and low-energy CT images, respectively; a processing module, configured to perform cone beam artifact correction processing on the virtual monoenergetic images at the two target energies to obtain two corrected virtual monoenergetic images and a cone beam artifact error image; A first correction module is configured to obtain a corrected base material image and virtual monoenergetic images at other energies based on a linear weighted combination of the two corrected virtual monoenergetic images; The second correction module is used to subtract the cone beam artifact error image at the corresponding equivalent energy from the high-energy and low-energy CT images, respectively, to obtain the high-energy and low-energy CT images after cone beam artifact correction.

6. The device according to claim 5, characterized in that The generation module includes: A first decomposition unit is configured to perform projection domain-based material decomposition on the high-energy and low-energy projection data to obtain projection images of two base materials; The first reconstruction unit is configured to obtain two base material images by combining the projection images of the two base materials with a target reconstruction algorithm.

7. The device according to claim 5, characterized in that The generation module includes: a second reconstruction unit, configured to obtain reconstructed high- and low-energy CT images using a target reconstruction algorithm based on the high- and low-energy projection data; The second decomposition unit is used to perform image domain basis material decomposition on the reconstructed high-energy and low-energy CT images to obtain two basis material images.

8. The device according to claim 5, characterized in that The processing module includes: A processing unit, configured to pre-process each virtual monoenergetic image to obtain a priori image; a computing unit, configured to forward project and reconstruct the prior image to obtain a prior image containing cone beam artifacts, and to calculate a difference between the prior image and the prior image containing cone beam artifacts to obtain a cone beam artifact error estimation image; A correction unit is configured to subtract the cone beam artifact error estimation image from each virtual monoenergetic image to obtain the corrected virtual monoenergetic image.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the energy spectrum cone beam artifact suppression method according to any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the energy spectrum cone beam artifact suppression method according to any one of claims 1 to 4.

11. A computer program product comprising a computer program, characterized in that The computer program is executed to implement the energy spectrum cone-beam artifact suppression method according to any one of claims 1 to 4.

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