Fast vibration correction of images with metal objects in CBCT

Abstract

The invention relates to vibration correction. There is provided a vibration artifact suppression method (100) comprising the steps of: a) reconstructing (110) a three-dimensional image of an object of interest based on projection data acquired with an X-ray imaging system, b) determining (120) whether the reconstructed three-dimensional image contains a metal object, and c) performing one of the following steps on the basis of the result of the determination: c1) in response to determining that the reconstructed three-dimensional image contains the metal object, performing (130) a vibration correction method on the basis of the metal object segmented in the reconstructed three-dimensional image; or c2) in response to determining that the reconstructed three-dimensional image does not contain the metal object, performing (140) a vibration correction method based on the object of interest segmented in the reconstructed three-dimensional image. By means of the vibration artifact suppression method, the number of iterations can be greatly reduced, and therefore the overall reconstruction time is remarkably shortened.

Description

Technical Field

[0001] The present invention relates to a vibration artifact suppression method, a vibration artifact suppression device, an X-ray imaging system, a computer program product, and a computer-readable medium. Background Art

[0002] Performing three-dimensional (3D) imaging using an interventional C-arm system is an area of increasing interest in many interventional procedures. For data acquisition, an electric movement of the C-arc is performed to move the tube and the detector around the region of interest. During this movement, projection data is acquired, which can be used together with knowledge about the position of the tube and the detector to reconstruct a 3D image.

[0003] In the geometric data derived from a calibration procedure, it can be observed that the C-arc vibrates during acquisition due to acceleration forces associated with the movement. If there is a deviation in the phase and / or amplitude of the vibration pattern between the calibration procedure and the interventional data acquisition, serious image artifacts may occur, significantly degrading the image quality. This may particularly affect mobile C-arm systems as their vibrations are much larger than those of fixed systems. Summary of the Invention

[0004] Therefore, there may be a need to improve vibration correction, for example, for X-ray imaging systems such as mobile C-arm systems.

[0005] The object of the present invention is solved by the subject matter of the independent claims, wherein further embodiments are incorporated in the dependent claims.

[0006] In a first aspect, a vibration artifact suppression method is provided. The method includes:

[0007] a) reconstructing a three-dimensional image of an object of interest based on projection data acquired by an X-ray imaging system;

[0008] b) determining whether the reconstructed three-dimensional image contains a metallic object, and

[0009] c) performing a vibration correction method based on an interest structure segmented in the reconstructed three-dimensional image, wherein the interest structure is selected based on the result of the determining step.

[0010] In other words, the present disclosure proposes a vibration correction method for an X-ray system (e.g., for a mobile C-arm system) to effectively reduce vibration artifacts.

[0011] In some examples, the vibration artifact suppression method disclosed herein includes an initial reconstruction, in which a specific reconstructed image structure is segmented. The segmented image structure is forward projected onto the initially acquired projections and registered with the corresponding structures in the projection data to estimate the vibration. Using the estimated vibration information thus determined, a new reconstruction with reduced vibration artifacts can be performed. If desired, the process can undergo multiple iterations in order to obtain sufficient image quality.

[0012] The image structure to be segmented is selected based on the result of determining the presence of a metal object. That is, in some cases where the reconstructed image contains a metal object, the image structure to be segmented includes the metal object, and step c) includes c1) performing a vibration correction method based on the segmented metal object. In this case, advantageously, the number of iterations can be lower, and this is also the case for mobile C-arm 3D imaging. This will be explained in detail below, particularly with respect to Figure 4 the images shown. Thus, in the presence of one or more metal objects, the one or more metal objects are segmented and used as a basis for vibration estimation.

[0013] In other cases, where the reconstructed image does not contain any metal objects, or only a limited amount of metal is present, for example, a bone structure is segmented instead of the metal and used as a basis for vibration estimation. That is, step c) thus includes c2) performing a vibration correction method based on the segmented bone structure.

[0014] This will be explained in detail below, particularly with respect to Figure 1 the examples shown.

[0015] In an embodiment, step c1) further includes determining the amount of the metal object in the reconstructed three-dimensional image, and determining whether to perform a vibration correction method based on the metal object segmented in the reconstructed three-dimensional image based on the amount of the metal object.

[0016] In addition to determining whether the image contains metal, it can also be selected to check whether there is enough metal structure available for a robust vibration estimation. This can be achieved by verifying how many image slices include important parts of the metal structure. Other possible criteria can be the volume percentage of the metal or the volume percentage of the convex hull of the metal, since the distribution within the field of view (FOV) is an important aspect of robust vibration correction.

[0017] In an embodiment, the amount of the metal object is determined based on at least one of the following:

[0018] the number of image slices in the projection data that include the metal object;

[0019] the volume percentage of the metal object; or

[0020] The volume percentage of the convex hull of the metal object.

[0021] In an embodiment, the vibration correction method includes:

[0022] Segmenting the metal object in the reconstructed three-dimensional image;

[0023] Forward-projecting the segmented metal object onto the acquisition projections of the projection data;

[0024] Registering the forward-projected metal object with the metal object in the acquisition projections to estimate the vibration of the C-arm X-ray imaging system during acquisition of the projection data; and

[0025] Performing further reconstruction using the estimated vibration.

[0026] This will be explained in detail below, particularly with regard to Figure 2 the example shown.

[0027] According to an embodiment, the vibration correction method in step c2) includes:

[0028] Segmenting the bone structure in the reconstructed three-dimensional image;

[0029] Forward-projecting the segmented bone structure onto the acquisition projections of the projection data;

[0030] Registering the forward-projected bone structure with the corresponding bone structure in the acquisition projections to estimate the vibration of the C-arm X-ray imaging system during acquisition of the projection data; and

[0031] Performing further reconstruction using the estimated vibration.

[0032] This will be explained in detail below, particularly with regard to Figure 3 the example shown.

[0033] In some examples, the forward projection and reconstruction are performed iteratively.

[0034] In some examples, the segmented metal object or the segmented bone structure is forward-projected onto the acquisition projections with reduced resolution.

[0035] The computation time of iterative image reconstruction is generally determined by the forward projection operation and the back projection operation. By using acquisition projections with reduced resolution, the computation time can be significantly reduced.

[0036] In one embodiment, in step a), a three-dimensional image of the object of interest is reconstructed at a lower resolution than the final image reconstruction.

[0037] The initial reconstruction and all reconstructions within the vibration correction iteration can be performed at a lower resolution than the final image reconstruction to save computational time.

[0038] In a second aspect, there is provided a vibration artifact suppression device including a processor configured to perform the steps of the method according to any one of the preceding claims.

[0039] In a third aspect, there is provided an X-ray imaging system including:

[0040] A C-arm X-ray imaging system configured to acquire projection data of an object of interest; and a vibration artifact suppression device according to the second aspect and any associated examples.

[0041] In some embodiments, the C-arm X-ray imaging system is a mobile C-arm X-ray imaging system such as used in medical imaging.

[0042] In another aspect, there is provided a computer program product including instructions that, when executed by a processor, cause the processor to perform the steps of the method according to the third aspect and any associated examples.

[0043] In another aspect of the present invention, there is provided a computer-readable storage medium having stored thereon the computer program product.

[0044] It should be understood that all combinations of the foregoing concepts and additional concepts discussed in more detail below (as long as these concepts are not mutually inconsistent) are considered to be part of the inventive subject matter disclosed herein. In particular, all combinations of the claimed subject matter of this disclosure are considered to be part of the inventive subject matter disclosed herein.

[0045] With reference to the embodiments described below, these and other aspects of the present invention will become apparent and be elucidated. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In the drawings, like reference numerals generally refer to like parts in different views. Also, the drawings are not necessarily to scale, and emphasis is generally placed on illustrating the principles of the present invention.

[0047] Figure 1 A flowchart depicting an exemplary vibration artifact suppression method is shown.

[0048] Figure 2 A flowchart showing the steps of a vibration correction method based on segmented metal objects in a reconstructed image according to one embodiment is shown.

[0049] Figure 3 A flowchart showing the steps of a vibration correction method based on segmented objects of interest in a reconstructed image according to one embodiment is shown.

[0050] Figure 4 Images showing the results of iterative processing of vibration correction for bone structures and metal foreign bodies with different numbers of iterations are presented.

[0051] Figure 5 An exemplary X-ray imaging system is shown. DETAILED DESCRIPTION

[0052] Performing 3D imaging using an interventional C-arm system is an area of increasing interest in many interventional procedures. For data acquisition, an electric movement of the C-arc is performed to move the tube and detector around the region of interest. During this movement, projection data is acquired, which can be used, together with knowledge of the positions of the tube and detector, to reconstruct a 3D image. Knowledge of the positions of the tube and detector is obtained from a geometric calibration procedure, in which data acquisition is performed using precisely known geometric objects in the region of interest.

[0053] In the geometric data derived from the calibration procedure, it can be observed that the C-arc vibrates during acquisition due to acceleration forces associated with the movement. In addition, from repeated calibrations, it can be seen that for different acquisition runs, this vibration varies in amplitude and phase. If there is a deviation in the phase and / or amplitude of the vibration pattern between the calibration procedure and the interventional data acquisition, serious image artifacts may occur, significantly degrading the image quality (see Figure 4 , the left image in the top row).

[0054] To reduce these artifacts, vibration correction (VC) methods have been developed. The method starts with an initial reconstruction. In the initial reconstruction, certain image structures are segmented and forward projected onto the acquired projections. Then, the forward projected structures are registered with the corresponding structures in the originally acquired projections to estimate the vibration. A new reconstruction is performed using the estimated vibration, thereby reducing vibration artifacts.

[0055] Vibrations in a mobile C-arm system can be particularly large, much larger than in a fixed system, and thus the processing may have to be repeated iteratively (see Figure 4 , top row). That is, in the iterative process, the vibration correction reconstruction is repeatedly used to segment and forward project bone structures, which are in turn used to refine the vibration estimate in another registration step. In the example shown ( Figure 4 , top row), the process is repeated 4 times to achieve an acceptable level of artifact suppression. Thus, five image reconstructions, four forward projections, and four registrations must be performed, resulting in a long computation time for the reconstruction.

[0056] It has been found that for images containing metallic objects, if the metallic objects are segmented, forward projected, and used for registration, the number of iterations for vibration correction can be significantly reduced. This is of particular interest because for these datasets on top of vibration correction, metal artifact reduction (MAR) can be performed, which is also computationally very demanding. By using the vibration artifact suppression method disclosed herein, the number of iterations can be significantly reduced, thereby significantly accelerating the overall reconstruction time.

[0057] Figure 1 A flowchart depicting an exemplary vibration artifact suppression method 100 in accordance with an embodiment of the present disclosure is shown. The vibration artifact suppression method 100 can be implemented as a device, module, or related component in a set of logic instructions stored in a non-transitory machine or computer-readable storage medium such as random access memory (RAM), read-only memory (ROM), programmable ROM (PROM), firmware, flash memory, etc., stored in configurable logic such as, for example, programmable logic arrays (PLAs), field-programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), stored in fixed-function hardware logic using circuit technologies such as, for example, application-specific integrated circuits (ASICs), complementary metal oxide semiconductors (CMOS), or transistor-transistor logic (TTL) technologies, or stored in any combination thereof. For example, computer program code for performing the operations shown in method 200 can be written in any combination of one or more programming languages, including object-oriented programming languages such as JAVA, SMALLTALK, C++, Python, etc. and conventional procedural programming languages such as the "C" programming language or similar programming languages. For example, the exemplary method can be implemented as Figure 5 the apparatus 30 shown.

[0058] In step 110 (i.e., step a), the vibration artifact suppression method 100 includes the step of reconstructing a 3D image of an object of interest based on projection data acquired using an X-ray imaging system (e.g., a mobile C-arm system). The reconstructed image can also be referred to as an initial reconstructed image or an initial image. In some examples, the projection data can be obtained by performing a scan using the X-ray imaging system. In some other examples, the projection can be obtained by calling previously acquired projection data from a computer memory. The acquired projection data can be the native resolution of the X-ray detector of the X-ray imaging system.

[0059] In some examples, downsampled projection data can be used and an image resolution of an initial image commensurate with the downsampled projection data can be used to generate the initial image. Any known downsampling method can be used to implement downsampling of the projection data. In some examples, fine-resolution pixels can be grouped into pixel groups corresponding to the coarse-resolution pixels of the downsampled data, and then the values of the corresponding pixel groups of the fine-resolution pixels are averaged or summed to generate the values of the coarse-resolution pixels. In some examples, interpolation, extrapolation, and / or integration from a fine-resolution grid to a coarse-resolution grid can be used to resample the fine-resolution pixels onto a grid or other pixel pattern for the coarse-resolution pixels.

[0060] Any known reconstruction method can be used to generate the initial reconstructed image. Examples of reconstruction methods for reconstructing a 3D image of an object of interest can include, but are not limited to, filtered back projection (FBP), Feldkamp-Davis-Kress (FDK) reconstruction method, an IR method using an objective function having, for example, a least squares or penalized weighted least squares data fidelity term and a regularization term.

[0061] In step 120, i.e., step b), the vibration artifact suppression method 100 includes a step of determining whether the reconstructed three-dimensional image contains a metal object. A metal object can also be referred to as a metallic foreign object. The initial image can be judged whether it contains a metal object in different ways.

[0062] In some examples, if the image values are quantitatively correct Hounsfield unit (HU) values, then whether the initial image contains a metal can be judged based on the number of voxel values exceeding a defined threshold. This is because HU values exhibit a significant difference between anatomical structures and metallic foreign objects. For example, the HU values of bones can be in the range of +300 to +1900. Metallic foreign objects generally have higher HU values. For example, copper has +14000 HU, silver has +17000 HU, steel has +20000 HU, and gold has +30000 HU. Therefore, a HU threshold can be defined to distinguish metallic foreign objects from anatomical structures.

[0063] In some examples, if the image values are not quantitatively correct HU values, then whether the initial image contains a metal can be judged based on the histogram of the initial image. An image histogram is a gray value distribution showing the occurrence frequency of each gray value. Histogram analysis is based on the assumption that the gray values of anatomical structures and metal objects are distinguishable. This may result in two peaks appearing on the histogram. These peaks usually overlap, but the minimum value between them can be detected so as to separate the two objects, for example, using a linear support vector machine. It should be understood that other AI-based (e.g., neural network) or non-AI-based methods can be used to separate the two objects based on the histogram of the initial image or the image itself.

[0064] In some examples, it can be determined whether the initial image contains metal based on user input (e.g., via a graphical user interface (GUI)).

[0065] Optionally, step 120 may further include the following steps: determining the amount of metal objects in the reconstructed three-dimensional image, and determining whether to perform a vibration correction method based on the metal objects segmented in the reconstructed three-dimensional image based on the amount of metal objects. In other words, in addition to determining whether the image contains metal, it can also be verified whether there is sufficient metal structure for robust estimation of vibration.

[0066] In some examples, the amount of metal objects can be determined based on the number of image slices including metal objects in the projection data. For example, step 120 may further include checking how many image slices include important parts of the metal structure. A threshold can be set for the number of image slices. If the number of image slices including important parts of the metal structure is equal to or greater than the threshold, it can be determined to perform a vibration correction method based on the metal objects segmented in the reconstructed three-dimensional image.

[0067] In some examples, the amount of metal objects can be determined based on the volume percentage of the metal objects and / or the volume percentage of the convex hull of the metal objects, because the distribution within the field of view (FOV) is an important aspect of robust vibration correction.

[0068] If it is determined that the reconstructed three-dimensional image contains metal objects, the vibration artifact suppression method 100 proceeds from step 120 to step 130, i.e., step c1), and performs a vibration correction method based on the metal objects segmented in the reconstructed image. For example, if there are no metal objects, or the amount of metal is below the threshold, the vibration artifact suppression method 100 proceeds from step 120 to step 140, i.e., step c2), and performs a vibration correction method based on other image structures (e.g., bone structures) segmented in the reconstructed image.

[0069] Figure 2 A flowchart depicting one implementation of step 130 is shown.

[0070] In step 210 of step 130, the metal objects in the reconstructed 3D image are segmented. In some examples, simple thresholding with a fixed threshold (for images with correct HU values) or an estimated threshold (e.g., based on the histogram of the image) can be used to segment the metal objects. In some examples, AI-based segmentation of metal objects can be implemented, e.g., based on U-Net.

[0071] In step 220 of step 130, once the metal object is segmented, the segmented metal object is forward projected onto the acquisition projection. In some examples, the segmented metal object can be forward projected onto an acquisition projection with reduced resolution, e.g., onto a low-resolution grid.

[0072] In step 230 of step 130, the forward projected metal object is registered with the metal object in the acquisition projection to estimate the vibration of the X-ray imaging system during acquisition of the projection data. This can be done by standard means already available for vibration correction based on, e.g., bone structures.

[0073] In step 240 of step 130, further reconstruction is performed using the estimated vibration, thereby reducing vibration artifacts.

[0074] To improve this situation, steps 210 to 240 can be iteratively repeated.

[0075] Figure 3 A flowchart depicting one implementation of step 140 is shown.

[0076] In step 310 of step 140, an object of interest (e.g., a bone structure) in the reconstructed 3D image is segmented. In some examples, simple thresholding with a fixed threshold (for an image with correct HU values) or an estimated threshold (e.g., based on the histogram of the image) can be used to segment the structure of interest for performing vibration correction, e.g., for bone structures. In some examples, AI-based segmentation of the structure of interest can be performed, e.g., based on U-Net.

[0077] In step 320 of step 140, once the relevant structure(s) have been segmented, the segmented structure is forward projected onto the acquisition projection. In some examples, the segmented structure can be forward projected onto an acquisition projection with reduced resolution, e.g., onto a low-resolution grid.

[0078] In step 330 of step 140, the forward projected structure is registered with the corresponding structure in the original acquired projection to estimate the vibration of the X-ray imaging system during acquisition of the projection data.

[0079] In step 340 of step 140, further reconstruction is performed using the estimated vibration, thereby reducing vibration artifacts.

[0080] To improve this situation, steps 310 to 340 can be iteratively repeated.

[0081] Figure 4 Images are shown of the bone structure and metal foreign object processed with different numbers of iterations of vibration correction (from left to right). Figure 4The image shown includes metallic foreign objects. Figure 4 The top row of Figure 4 shows vibration correction based only on bone structure, while Figure 4 the bottom row of Figure 4 shows vibration correction based on metallic structure. It can be seen that Figure 4 if vibration correction is based on metallic structure, vibration artifacts (such as the one indicated by the white arrow in the upper left image) are suppressed more quickly.

[0082] Figure 5 FIG. shows an exemplary X-ray imaging system 50 according to some embodiments of the present disclosure. Examples of X-ray imaging systems can include, but are not limited to, C-arm systems, computed tomography (CT) systems, digital radiography (DXR) systems, and image-guided therapy (IGT) systems. In some examples, the C-arm system can be a mobile C-arm system. The following discussion of the X-ray system 50 is merely an example of such an implementation and is not intended to be limiting in terms of modality.

[0083] The X-ray imaging system 50 includes an image acquisition device 10, a reconstruction device 20, and a vibration artifact suppression device 30.

[0084] The image acquisition device 10 includes an X-ray detector 16 opposite an X-ray source 12. The image acquisition device 10 is configured to scan an object of interest 14 to generate projection data including one or more image slices, i.e., raw images, each image slice representing a specific thickness of the object scanned at a specific projection angle.

[0085] The reconstruction device 20 is configured to receive the projection data that can be obtained by scanning using the X-ray system 10 and determine an initial reconstructed image. Any known reconstruction method can be used to generate the initial reconstructed image. Examples of reconstruction methods for reconstructing a 3D image of an object of interest can include, but are not limited to, filtered back projection (FBP), Feldkamp-Davis-Kress (FDK) reconstruction method, IR methods using an objective function having, for example, a least squares or penalized weighted least squares data fidelity term and a regularization term. The reconstruction device 20 then provides the initial reconstructed image to the vibration artifact suppression device 30.

[0086] The vibration artifact suppression device 30 is configured to perform a vibration artifact suppression method as disclosed herein, such as Figure 1 the method shown, to obtain a reconstructed image with reduced vibration artifacts.

[0087] Typically, the vibration artifact suppression device 30 may include various physical and / or logical components for transmitting and manipulating information, which may be implemented as hardware components (e.g., computing devices, processors, logic devices), executable computer program instructions to be executed by various hardware components (e.g., firmware, software), or any combination thereof, as required by a given set of design parameters or performance constraints. Although Figure 5 a limited number of components may be shown by way of example, it will be understood that more or fewer components may be employed for a given implementation.

[0088] In some embodiments, the vibration artifact suppression device 30 may be embodied as a device or apparatus such as a server, workstation, or mobile device, or may be embodied in such device or apparatus. The apparatus 10 may include one or more microprocessors or computer processors that execute appropriate software. For example, the vibration artifact suppression device 30 may have a processing unit that may be implemented by one or more of these processors. The software may have been downloaded and / or stored in a corresponding memory, such as volatile memory like RAM or non-volatile memory like flash memory. The software may include instructions that configure one or more processors to perform the functions described herein.

[0089] It should be noted that the vibration artifact suppression device 30 may be implemented with or without a processor, and may also be implemented as a combination of dedicated hardware for performing some functions and a processor for performing other functions (e.g., one or more programmed microprocessors and associated circuitry). For example, the vibration artifact suppression device 30 may be implemented in the form of programmable logic in a device or apparatus, such as a field programmable gate array (FPGA). Generally, each functional unit of the apparatus may be implemented in the form of a circuit.

[0090] In some embodiments, the vibration artifact suppression device 30 may also be implemented in a distributed manner. For example, some or all units of the apparatus 10 may be arranged as separate modules in a distributed architecture and connected in a suitable communication network, such as a 3rd Generation Partnership Project (3GPP) network, Long Term Evolution (LTE) network, Internet, LAN (Local Area Network), wireless LAN (Local Area Network), WAN (Wide Area Network), etc.

[0091] Although Figure 5 the reconstruction device 20 and the vibration artifact suppression device 30 may be shown by way of example as two separate devices, in some other examples, the vibration artifact suppression device 30 may reside in the reconstruction device 20, such as running as software.

[0092] In another exemplary embodiment of the present invention, there is provided a computer program or a computer program unit, characterized in that it is adapted to execute the method steps of the method according to one of the foregoing embodiments on a suitable system.

[0093] Therefore, the computer program unit can be stored on a computer unit, which can also be part of an embodiment of the present invention. The computing unit can be adapted to execute or cause the execution of the steps of the above method. In addition, it can be adapted to operate the components of the above device. The computing unit can be adapted to automatically operate and / or execute the commands of the user. The computer program can be loaded into the working memory of the data processor. Therefore, the data processor can be equipped to execute the method of the present invention.

[0094] This exemplary embodiment of the present invention covers computer programs that use the present invention from the very beginning and computer programs that turn existing programs into programs using the present invention by means of up-to-date programs.

[0095] In addition, the computer program element may be able to provide all the necessary steps to implement the process of the exemplary embodiment of the method as described above.

[0096] According to another exemplary embodiment of the present invention, there is provided a computer-readable medium such as a CD-ROM, wherein the computer-readable medium has a computer program unit stored thereon, which is described in the previous part.

[0097] The computer program can be stored and / or distributed on a suitable medium, such as an optical storage medium or a solid-state medium provided together with or as part of other hardware, but can also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0098] However, the computer program can also be presented via a network such as the World Wide Web and can be downloaded from such a network into the working memory of the data processor. According to another exemplary embodiment of the present invention, there is provided a medium for making a computer program unit available for download, the computer program unit being arranged to execute the method according to one of the foregoing embodiments of the present invention.

[0099] It must be noted that the embodiments of the present invention are described with reference to different subjects. In particular, some embodiments are described with reference to method-type claims, while other embodiments are described with reference to device-type claims. However, those skilled in the art will understand from the above and following descriptions that, unless otherwise stated, any combination between features related to different subjects is also considered to be disclosed in this application, in addition to any combination of features belonging to one type of subject. However, all features can be combined together to provide a synergistic effect, rather than just a simple addition of features.

[0100] Although the present invention has been described in detail in the drawings and the foregoing description, such description and illustration are to be considered illustrative or exemplary and not restrictive. The present invention is not limited to the disclosed embodiments. Other variations of the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the dependent claims.

[0101] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.

Claims

1. A method (100) for suppressing vibration artifacts, comprising: a) Reconstructing (110) a three-dimensional image of an object of interest based on projection data acquired by an X-ray imaging system; b) Determining (120) whether the reconstructed three-dimensional image contains a metallic object, and c) Performing (130, 140) a vibration correction method based on an interest structure segmented in the reconstructed three-dimensional image, wherein the interest structure is selected based on the result of the determining step.

2. The vibration artifact suppression method according to claim 1, wherein, The interest structure is the metallic object, and step c) comprises: c1) Performing (130) the vibration correction method based on the metallic object.

3. The vibration artifact suppression method according to claim 2, Among them, Step c1) further comprises determining the amount of the metallic object in the reconstructed three-dimensional image, and determining whether to perform the vibration correction method based on the metallic object segmented in the reconstructed three-dimensional image based on the amount of the metallic object.

4. The vibration artifact suppression method according to claim 3, Among them, The amount of the metallic object is determined based on at least one of the following: The number of image slices including the metallic object in the projection data; The volume percentage of the metallic object; or The volume percentage of the convex hull of the metallic object.

5. The vibration artifact suppression method according to any one of the preceding claims 2 to 4, Among them, The vibration correction method in step c1) comprises: Segmenting (210) the metallic object in the reconstructed three-dimensional image; Forward-projecting (220) the segmented metallic object onto the acquisition projections of the projection data; Registering (230) the forward-projected metallic object with the metallic object in the acquisition projections to estimate the vibration of the X-ray imaging system during acquisition of the projection data; and Performing (240) further reconstruction using the estimated vibration.

6. The vibration artifact suppression method according to claim 1, wherein, The interest structure is a bone structure, and step c) comprises: c2) Performing (140) the vibration correction method based on the bone structure segmented in the reconstructed three-dimensional image.

7. The vibration artifact suppression method according to claim 6, Among them, The vibration correction method in step c2) comprises: Segmenting (310) the bone structure in the reconstructed three-dimensional image; Forward-projecting (320) the segmented bone structure onto the acquisition projections of the projection data; Registering (330) the forward-projected bone structure with the corresponding bone structure in the acquisition projections to estimate the vibration of the X-ray imaging system during acquisition of the projection data; and Performing further reconstruction using the estimated vibration.

8. The vibration artifact suppression method according to claim 5 or 7, Among them, The forward projection and reconstruction are performed iteratively.

9. The vibration artifact suppression method according to any one of claims 5 to 8, Among them, The segmented metallic object or the bone structure is forward-projected onto acquisition projections with reduced resolution.

10. The vibration artifact suppression method according to any one of the preceding claims, Among them, In step a), the three-dimensional image of the object of interest is reconstructed at a lower resolution than the final image reconstruction.

11. A vibration artifact suppression device (30) comprising a processor configured to perform the steps of the method according to any one of the preceding claims.

12. An X-ray imaging system (50) comprising: An X-ray imaging system configured to acquire projection data of an object of interest; And The vibration artifact suppression device according to claim 11.

13. The X-ray imaging system according to claim 12, Among them, Wherein the X-ray imaging system is a mobile C-arm X-ray imaging system.

14. A computer program product comprising instructions that, when executed by a processor, cause the processor to perform the steps of the method according to any one of claims 1 to 10.

15. A computer-readable storage medium having stored thereon the computer program product according to claim 14.

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