Image artifact correction method, system and device, computer equipment and storage medium

Abstract

The invention relates to an image artifact correction method, system and device, computer equipment and a storage medium. The method comprises the following steps: acquiring target scanning data corresponding to a region of interest; the target scanning data comprises data in a reconstruction view field range and data in a scanning view field range; performing image reconstruction on the region of interest according to the data in the reconstruction view field range to obtain a target reconstruction scanning image; and for an area between the scanning visual field range and the reconstruction visual field range, if the tissue scanning value is smaller than a preset tissue threshold value, performing scleroossification correction on the target reconstruction scanning image to obtain a target correction scanning image. By the adoption of the method, image reconstruction and osteosclerosis correction can be combined, under the condition that it is judged that no object (such as bone tissue) exists outside the target visual field, the image is reconstructed and osteosclerosis correction is conducted directly through data in the current scanning visual field range, the time of one-time filtering back projection can be saved, and the efficiency of image reconstruction and osteosclerosis correction is improved. And the image reconstruction efficiency of the region of interest is improved.

Description

Technical Field

[0001] The present application relates to the field of medical imaging technology, and in particular to an image artifact correction method, system, apparatus, computer equipment, storage medium, and computer program product. Background Art

[0002] With the development of computer technology, computed tomography (CT) technology has emerged. This technology uses precisely collimated X-ray beams, gamma rays, ultrasound, etc., together with highly sensitive detectors to perform cross-sectional scans around the area of ​​interest one after another. It has the characteristics of fast scanning time and clear images. However, during the scanning process, bones will cause X-ray hardening artifacts, generally known as osteosclerosis artifacts. In order to eliminate the influence of this artifact, osteosclerosis correction is required.

[0003] Traditional techniques typically require imaging within the maximum reconstruction field of view to avoid bones outside the field of view, resulting in poor correction results. However, this requires multiple filtered back-projection reconstructions: one for the target field of view and the remaining for the maximum field of view. This increases the computational complexity of reconstruction and results in inefficient reconstruction of the region of interest. Summary of the Invention

[0004] Based on this, it is necessary to provide an image artifact correction method, apparatus, computer equipment, computer-readable storage medium and computer program product that can improve the image reconstruction efficiency of the region of interest in order to address the above technical problems.

[0005] In a first aspect, the present application provides a method for correcting image artifacts. The method comprises:

[0006] Acquire target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstructed field of view and data within a scan field of view;

[0007] Performing image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0008] For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

[0009] In a second aspect, the present application also provides an image artifact correction system. The system includes: a scanning device and a computer;

[0010] The scanning device is used to scan the region of interest;

[0011] The computer is used to obtain target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstruction field of view and data within a scanning field of view;

[0012] The computer is further configured to perform image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0013] The computer is further configured to perform sclerosis correction on the target reconstructed scan image to obtain a target corrected scan image if the tissue scan value of the area between the scanning field of view and the reconstruction field of view is less than a preset tissue threshold.

[0014] In a third aspect, the present application further provides an image artifact correction device. The device comprises:

[0015] A scanning data acquisition module, configured to acquire target scanning data corresponding to the region of interest; the target scanning data includes data within the reconstruction field of view and data within the scanning field of view;

[0016] An image reconstruction module is used to reconstruct the image of the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0017] The sclerosis correction module is used to perform sclerosis correction on the target reconstructed scan image when the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstruction field of view is less than a preset tissue threshold to obtain a target corrected scan image.

[0018] In a fourth aspect, the present application further provides a computer device. The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0019] Acquire target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstructed field of view and data within a scan field of view;

[0020] Performing image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0021] For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

[0022] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0023] Acquire target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstructed field of view and data within a scan field of view;

[0024] Performing image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0025] For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

[0026] In a sixth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0027] Acquire target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstructed field of view and data within a scan field of view;

[0028] Performing image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0029] For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

[0030] The above-mentioned image artifact correction method, device, computer equipment, storage medium and computer program product obtain target scanning data corresponding to the region of interest; the target scanning data includes data within the reconstruction field of view and data within the scanning field of view; based on the data within the reconstruction field of view, the image of the region of interest is reconstructed to obtain a target reconstructed scan image; for the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, the target reconstructed scan image is corrected for ossification to obtain a target corrected scan image.

[0031] By acquiring the target scan data corresponding to the region of interest and processing the target scan data using the data within the reconstruction field of view, a target reconstructed scan image is obtained. During the processing, by detecting that the interval tissue scan value is less than the preset tissue threshold, the target reconstructed scan image is corrected for ossification to highlight and accurately present the bone structure of the area, and finally a target corrected scan image is obtained. This entire process combines image reconstruction and ossification correction, selects the range for field of view reconstruction, and directly uses the data within the current scanning field of view to reconstruct the image and perform bone sclerosis correction when it is determined that there is no object (such as bone tissue) outside the target field of view. This can save the time of one filtered back projection and improve the image reconstruction efficiency of the region of interest. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A diagram illustrating an application environment of an image artifact correction method according to an embodiment;

[0033] Figure 2 is a schematic flow chart of an image artifact correction method in one embodiment;

[0034] Figure 3 A schematic flow chart of a method for obtaining interval tissue scanning values ​​in one embodiment;

[0035] Figure 4 1 is a flow chart of a method for obtaining a detector interval channel range in one embodiment;

[0036] Figure 5 A schematic flow chart of a method for obtaining interval tissue scanning values ​​in another embodiment;

[0037] Figure 6 Schematic diagram of a flow chart of a method for obtaining interval tissue scanning values ​​in another embodiment;

[0038] Figure 7 Schematic diagram of a flow chart of a method for obtaining a target correction scan image in one embodiment;

[0039] Figure 8 1 is a flow chart of a method for obtaining actual visual field information in one embodiment;

[0040] Figure 9 is a flow chart of a method for obtaining actual visual field information in another embodiment;

[0041] Figure 10 Schematic diagram of a flow chart of a method for adjusting visual field information in one embodiment;

[0042] Figure 11 A schematic diagram of a CT scan in one embodiment;

[0043] Figure 12A schematic diagram of the detector channel range corresponding to projection data and its reconstructed field of view in one embodiment;

[0044] Figure 13 A schematic diagram of determining whether to reconstruct an object outside the field of view in one embodiment;

[0045] Figure 14 A logic block diagram for determining whether an object exists outside the field of view of data reconstructed in one embodiment;

[0046] Figure 15 A logic block diagram of an image reconstruction process for bone sclerosis correction in one embodiment;

[0047] Figure 16 is a structural block diagram of an image artifact correction device in one embodiment;

[0048] Figure 17 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail 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] The image artifact correction method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the scanning device 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The scanning device 102 scans the area of ​​interest of the target object, and the server 104 obtains the target scanning data corresponding to the area of ​​interest from the scanning device 102; the target scanning data includes data within the reconstruction field of view and data within the scanning field of view; according to the data within the reconstruction field of view, the image of the area of ​​interest is reconstructed to obtain a target reconstructed scan image; for the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than the preset tissue threshold, the target reconstructed scan image is corrected for bone sclerosis to obtain a target corrected scan image. Among them, the server 104 can be implemented as an independent server or a server cluster consisting of multiple servers.

[0051] In one embodiment, Figure 2 As shown, a method for correcting image artifacts is provided. Figure 1 The following steps are used as an example to illustrate the server in the example:

[0052] Step 202: Acquire target scanning data corresponding to the region of interest.

[0053] The region of interest may be a region of the target object that needs to be scanned, which may or may not have abnormalities, and the target object may be a person, an animal, or a plant.

[0054] The target scan data may be scan data obtained by scanning the region of interest of the target object, wherein the target scan data includes data within the reconstruction field of view and data within the scanning field of view. The reconstruction field of view is the range of the target scan data for scanning the region of interest, while the scanning field of view is the entire field of view of the target scan data for scanning the region of interest. Generally, the area corresponding to the data within the scanning field of view is larger than the area corresponding to the data within the reconstruction field of view. Figure 11 As shown, Figure 11 The scanning field of view refers to the scanning field of view obtained during the scanning process, while the reconstruction field of view refers to the reconstruction field of view that needs to be reconstructed based on the scanned object; Figure 11 The detector and aperture of the scanning device are also included in the , and the scan object (region of interest) can also be Figure 11 see.

[0055] Specifically, a control terminal of scanning device 102 sends a command to the scanning device to scan a region of interest of the target object. Scanning device 102 scans the region of interest according to the command, obtaining target scan data. Server 104 communicates with scanning device 102 to obtain the target scan data corresponding to the region of interest of the target object from scanning device 102 and stores it in a storage space of server 104. When the target scan data needs to be processed, the target scan data is input to the central processing unit of server 104.

[0056] Step 204 : reconstructing the image of the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image.

[0057] The target reconstructed scan image may be an image reconstructed using target scan data within the reconstruction field of view.

[0058] Specifically, within the reconstruction field of view, the data within the reconstruction field of view is processed and corrected to ensure accuracy and completeness. An image reconstruction algorithm is then used to reconstruct the region of interest from the processed data within the reconstruction field of view into a reconstructed scanned image of the target. This algorithm incorporates filtering, interpolation, and other image processing techniques to maximize the restoration of the target's shape, structure, or features.

[0059] Step 206 : For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

[0060] Among them, the tissue scanning value can be the value obtained by accumulating the tissue scanning values ​​of the detector channel between the data within the scanning field of view and the data within the reconstruction field of view according to different acquisition angles, wherein the tissue scanning value is the scanning value corresponding to any detector channel within the detector interval channel range.

[0061] Among them, the preset tissue threshold can be a constraint condition for the interval tissue scanning value. If the interval tissue scanning value is less than the preset tissue threshold, it means that there is no object in the interval between the data within the scanning field of view and the data within the reconstruction field of view. If the interval tissue scanning value is greater than the preset tissue threshold, it means that there is an object in the interval between the data within the scanning field of view and the data within the reconstruction field of view.

[0062] The target corrected scan image may be a scan image that has been further corrected for sclerosis based on the target reconstructed scan image.

[0063] Specifically, when the tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstruction field of view is less than the preset tissue threshold, a bone extraction algorithm is usually applied to perform ossification correction on the target reconstructed scan image to highlight the bone structure in the image. This involves preprocessing steps such as filtering and edge detection of the image to emphasize the contrast of the bone part. Then, the extracted bone information is used for correction processing, which may include adjusting the grayscale level, contrast or further geometric correction of the image to ensure that the bone structure is accurately expressed in the image. Finally, through this ossification correction process, the target corrected scan image is obtained, in which the bone structure is clearer and more prominent, providing more accurate information for fields such as medical imaging.

[0064] In the above-mentioned image artifact correction method, target scanning data corresponding to the region of interest is obtained; the target scanning data includes data within the reconstruction field of view and data within the scanning field of view; based on the data within the reconstruction field of view, the image of the region of interest is reconstructed to obtain a target reconstructed scan image; for the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than the preset tissue threshold, the target reconstructed scan image is corrected for ossification to obtain a target corrected scan image.

[0065] By acquiring the target scan data corresponding to the region of interest and processing the target scan data using the data within the reconstructed field of view, a target reconstructed scan image is obtained. During the processing, by detecting that the interval tissue scan value is less than the preset tissue threshold, the target reconstructed scan image is corrected for ossification to highlight and accurately present the bone structure of the area, and finally a target corrected scan image is obtained. This entire process combines image reconstruction and ossification correction, selects the range for field of view reconstruction, and directly uses the data within the current scanning field of view to reconstruct the image and perform bone sclerosis correction when it is determined that there is no object (such as bone tissue) outside the target field of view. This can save the time of one filtered back projection and improve the image reconstruction efficiency of the region of interest.

[0066] In one embodiment, Figure 3 As shown, after the step of reconstructing the image of the region of interest based on the data within the reconstruction field of view to obtain the target reconstructed scan image, the method further includes:

[0067] Step 302 : Determine a field of view interval corresponding to the data within the scanning field of view and the data within the reconstruction field of view.

[0068] The field of view interval may be a difference between the range of data within the scanning field of view and the range of data within the reconstruction field of view on the target object.

[0069] Specifically, since the range of data within the scanning field of view is larger than the range of data within the reconstruction field of view, the range of data within the scanning field of view is subtracted from the range of data within the reconstruction field of view, and the interval between the two is the field of view interval, where the field of view interval includes at least one detector channel of a scanning device.

[0070] Step 304: Calculate the corresponding detector interval channel range in the field of view interval.

[0071] The detector interval channel range can be the range information of each detector channel in the field of view interval. Figure 12 Schematic diagram of the detector channel range corresponding to the projection data and its reconstructed field of view.

[0072] Specifically, each detector channel in the field of view interval is traversed to obtain the position information of each detector channel. According to the position information of each detector channel, the detector channels corresponding to the two endpoints of the field of view interval are determined. Finally, according to the position information of the detector channels of the endpoints, the corresponding detector interval channel range in the field of view interval is calculated.

[0073] Step 306 : Accumulate the tissue scanning values ​​according to the detector interval channel range to obtain the interval tissue scanning value.

[0074] Specifically, according to the detector interval channel range, the tissue scan values (detector signal values) corresponding to each detector channel in the range are read, and the tissue scan values corresponding to each detector channel in the detector interval channel range are accumulated in the manner of the ray beam (i.e., the sampling angle) to obtain the interval tissue scan value.

[0075] In this embodiment, by traversing each detector channel in the field of view interval, the endpoints of the field of view interval can be obtained, and the corresponding detector interval channel range is further calculated. Finally, by accumulating the tissue scan values of these detector channels in the manner of the ray beam, the tissue scan value in the interval is obtained, which helps to more accurately analyze and diagnose the structure and lesions in the medical image, and improves the accuracy and reliability of image reconstruction, and provides a more reliable basis for medical diagnosis.

[0076] In one embodiment, as shown in Figure 4 the corresponding detector interval channel range in the field of view interval is calculated, including:

[0077] Step 402, the detector field of view channel range corresponding to all detector channels in the data in the scan field of view range is calculated.

[0078] The detector field of view channel range can be a detector range corresponding to a detector channel in the range of data in the scan field of view range.

[0079] Specifically, each detector channel in the data in the scan field of view range is traversed to obtain the position information of each detector channel, the detector channels corresponding to the two endpoints of the data in the scan field of view range are determined according to the position information of each detector channel, and finally the corresponding detector field of view channel range in the data in the scan field of view range is calculated according to the position information of the detector channels of the endpoints.

[0080] Step 404, the detector reconstruction channel range corresponding to all detector channels in the data in the reconstruction field of view range is calculated.

[0081] The detector reconstruction channel range can be a detector range corresponding to a detector channel in the range of data in the reconstruction field of view range.

[0082] Specifically, each detector channel in the data in the reconstruction field of view range is traversed to obtain the position information of each detector channel, the detector channels corresponding to the two endpoints of the data in the reconstruction field of view range are determined according to the position information of each detector channel, and finally the corresponding detector field of view channel range in the data in the reconstruction field of view range is calculated according to the position information of the detector channels of the endpoints.

[0083] Step 406, the detector interval channel range is obtained according to the detector field of view channel range and the detector reconstruction channel range.

[0084] Specifically, since the detector field of view channel range is greater than and includes the detector reconstruction channel range, for example, the detector field of view channel range is [n1, nk], while the detector reconstruction channel range is [n1, nj], and the value of k is greater than j, the detector reconstruction channel range is a subset of the detector field of view channel range. Subtracting the detector reconstruction channel range from the detector field of view channel range yields the detector interval channel range.

[0085] In this embodiment, by traversing each detector channel in the data within the reconstructed field of view, their position information can be obtained, and the specific detector channels corresponding to the two endpoints of the data within the reconstructed field of view are determined based on this position information. Subsequently, by calculating the position information of the endpoint detector channels, the corresponding detector field of view channel range in the data within the reconstructed field of view is obtained. In this process, the importance of the detector field of view channel range is emphasized, which is greater than and includes the detector reconstruction channel range. The existence of this difference can accurately determine the detector interval channel range, and by subtracting the detector reconstruction channel range from the detector field of view channel range, it helps to more accurately locate and analyze the structural information in the medical image. This processing method helps to improve the accuracy and reliability of image reconstruction and provides a more accurate data basis for medical diagnosis.

[0086] In one embodiment, Figure 5 As shown, according to the detector interval channel range, the tissue scanning values ​​are accumulated to obtain the interval tissue scanning value, including:

[0087] Step 502: Determine each detector interval channel in the field of view interval according to the detector interval channel range.

[0088] The detector interval channel may be a detector channel located within the detector interval channel range.

[0089] Specifically, the information within the detector interval channel range is traversed, wherein the information includes characteristic information of each detector channel within the detector interval channel range, and by reading the characteristic information, each detector channel within the detector interval channel range is obtained, and as each detector interval channel, each detector interval channel has ray beam information.

[0090] Step 504 , accumulating the tissue scanning values ​​of each detector interval channel to obtain an interval tissue scanning value.

[0091] Specifically, information from each beam is used as a constraint and applied to each detector channel. This involves weighting or otherwise combining the tissue scan values ​​from each detector channel to ensure that beam information from different directions is accounted for. Subsequently, the tissue scan values ​​from each detector channel are accumulated to obtain the tissue scan value for that channel. This process integrates information from various directions and, using the beam as a constraint, yields a cumulative tissue scan value for that channel.

[0092] In this embodiment, when traversing the information within the detector channel range, the characteristic information of each detector channel is included. By reading this information, each specific channel within the detector channel range is obtained, and beam information is assigned to each channel. This beam information is used as a constraint and applied to each detector channel range. This involves weighting or otherwise combining the tissue scan values ​​in each channel to ensure comprehensive consideration of beam information from different directions. Subsequently, the tissue scan values ​​in each detector channel range are accumulated to achieve the sum of the tissue scan values ​​for that range. This integration process, by combining information from various directions and using beam constraints, effectively accumulates tissue scan values ​​for the corresponding range, thereby enhancing the detailed analysis and accurate reconstruction of medical imaging data.

[0093] In one embodiment, Figure 6 As shown, with each beam as a constraint information condition, the tissue scanning values ​​of each detector interval channel are accumulated to obtain the interval tissue scanning value, including:

[0094] Step 602: Determine the cumulative model corresponding to the tissue scanning value of each detector interval channel.

[0095] The cumulative model may be a model that adds up the scan values ​​of various tissues according to actual needs.

[0096] Specifically, the information from each beam is applied as a constraint to the corresponding detector bin channel. This involves adjusting the tissue scan values ​​in each channel based on the direction, intensity, or other characteristics of the different beams. Next, by comprehensively considering all constraints, an accumulation model corresponding to the tissue scan values ​​in each detector bin channel is determined. This model involves weighted accumulation of the scan values ​​in each channel to reflect the relative importance of each constraint.

[0097] Step 604 , accumulate the tissue scan values ​​according to the accumulation model to obtain interval tissue scan values.

[0098] Specifically, a defined accumulation model is used to perform weighted accumulation of the tissue scan values. This involves summing the tissue scan values ​​of each channel according to the weights specified in the accumulation model. By summing each tissue scan value according to the weights, an interval tissue scan value is obtained. The accumulation model comprehensively considers multi-directional information under various constraints to obtain more comprehensive and accurate interval tissue scan values. The final accumulation result reflects the tissue characteristics of the target area when scanned in various directions, providing more complete information for subsequent analysis and application.

[0099] In this embodiment, by applying each beam of radiation information as a constraint to the corresponding detector interval channel, fine adjustment of the tissue scanning value in each channel is achieved, taking into account the direction, intensity and other characteristics of different beams of radiation. Subsequently, by integrating all the constraints, the cumulative model corresponding to the tissue scanning value of each detector interval channel is determined. This model takes into account the relative importance of each constraint and reflects the comprehensive influence of multi-directional information by weighted accumulation of the scanning values ​​in each channel. Using the determined cumulative model, the tissue scanning values ​​of the interval are correspondingly weighted and accumulated to obtain the tissue scanning value of the interval. This accumulation process provides more comprehensive and accurate interval tissue scanning values ​​while integrating the multi-directional information of each constraint. The final accumulation result reflects the tissue characteristics of the target area in all directions, providing a richer information basis for subsequent analysis and application.

[0100] In one embodiment, Figure 7 As shown, the method further includes:

[0101] Step 702 : When the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstructed field of view is greater than a preset tissue threshold, the data within the scanning field of view is expanded to obtain expanded field of view information.

[0102] The extended field of view information may be a new scanning range obtained by expanding the data within the original scanning field of view.

[0103] Specifically, if the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstruction field of view is greater than the preset tissue threshold, Figure 13To determine whether there are objects outside the reconstructed field of view (FOV), the data between the scanned FOV and the reconstructed FOV indicates that there are objects within the FOV interval. The data within the scanned FOV is expanded to include information from the surrounding area, providing a broader and more detailed FOV. This expanded FOV information compensates for any missing or insufficient information in the original scanned FOV, enabling the generation of expanded data that satisfies a more complete FOV if the tissue scan value within that interval exceeds a preset threshold.

[0104] Step 704 : Scan the region of interest according to the extended field of view information to obtain extended scan data.

[0105] The extended scan data may be scan data obtained by scanning an expanded region of interest of the target object.

[0106] Specifically, a control terminal of scanning device 102 sends a command to the scanning device to scan a region of interest of the target object and a command to expand the field of view. Scanning device 102 scans the region of interest according to the command, obtaining extended scan data. Server 104 communicates with scanning device 102 to obtain the extended scan data corresponding to the region of interest of the target object from scanning device 102 and stores it in a storage space of server 104. When the extended scan data needs to be processed, the target scan data is input to the central processing unit of server 104.

[0107] Step 706 : reconstruct the extended scan data according to the extended field of view information to obtain an extended reconstructed scan image.

[0108] The extended reconstructed scan image is an image reconstructed using the scan data in the extended field of view information.

[0109] Specifically, the extended scan data is processed and corrected within the extended field of view, using the extended field of view as a constraint to ensure accuracy and completeness. An image reconstruction algorithm is then used to reconstruct the processed extended scan data into an extended reconstructed scan image. This algorithm incorporates filtering, interpolation, and other image processing techniques to maximize the restoration of the target's shape, structure, or features.

[0110] Step 708 : Perform sclerosis correction based on the extended reconstructed scan image and the target reconstructed scan image to obtain a target corrected scan image.

[0111] Specifically, the extended reconstructed scan image is combined with the target reconstructed scan image. This involves the alignment and matching of images to ensure that the two are spatially consistent. Then, a bone correction operation is performed on the merged scan image, which includes applying a bone extraction algorithm or other related technologies to highlight and adjust the bone structure in the image. The purpose of bone correction is to ensure that the bone features of the target area are clearly and accurately expressed in the image. Through this process, a target corrected scan image is obtained, which incorporates the expanded information and undergoes bone correction, making the image more consistent with the actual structure and providing more accurate image information for fields such as medical imaging. Figure 14 As shown, it is a logic block diagram for reconstructing whether there is an object outside the data within the field of view.

[0112] In this embodiment, if the interval tissue scan value corresponding to the data within the scanning field of view and the data within the reconstruction field of view exceeds the preset tissue threshold, that is, there is a possibility of missing an object, the system will expand the data within the scanning field of view. At this time, the information of the surrounding area is introduced into the scanning field of view to generate a wider and more detailed extended field of view information to make up for the information that may be missing or insufficient in the original scanning field of view. Then, the processed extended scan data is reconstructed into an extended reconstructed scan image using an image reconstruction algorithm, which includes filtering, interpolation and other processing. The extended reconstructed scan image is combined with the target scan image, and image alignment and matching are used to ensure that they are spatially consistent. Subsequently, a sclerosis correction operation is performed to emphasize and adjust the bone structure in the image to ensure that the bone features of the target area are clearly and accurately expressed. Finally, a corrected target scan image is obtained, which can integrate extended information, so that the sclerosis correction makes the image closer to the actual structure and provides more accurate image information for the field of medical imaging.

[0113] In one embodiment, Figure 8 As shown, after performing sclerosis correction based on the extended reconstructed scan image and the target reconstructed scan image to obtain the target corrected scan image, the method further includes:

[0114] Step 802: traverse each detector channel in the extended field of view information to obtain detector channel traversal data.

[0115] The detector channel traversal data may be search data obtained by traversing each detector channel in the extended reconstructed scan image.

[0116] Specifically, each detector channel in the extended reconstructed scan image is traversed. During this traversal, the tissue scan values ​​or other related information for each channel must be obtained. This can be achieved by iteratively accessing the pixels or data points of each channel. The result of this traversal is a collection of tissue scan values ​​or other related information for each detector channel, namely, the detector channel traversal data. Each detector channel in the extended reconstructed scan image has ray beam information.

[0117] Step 804: determining actual field of view information corresponding to the region of interest based on the tissue scan values.

[0118] The actual field of view information may be field of view information actually required for scanning the region of interest of the target object, and the actual field of view information is used for data within a scanning field of view corresponding to the next scan of the region of interest.

[0119] Specifically, the information from each beam is applied to the corresponding tissue scan values. This may include adjusting the tissue scan values ​​within the region of interest based on the direction, intensity, or other characteristics of the beam. Subsequently, the tissue scan values ​​are accumulated and the extended field of view information corresponding to the region of interest is further adjusted based on the accumulated sum to obtain the actual field of view information. This may include a mapping or conversion process to translate the tissue scan values ​​into a specific region within the actual field of view. This entire process, based on the second beam information, derives the actual field of view information within the region of interest, thereby providing a more accurate and comprehensive image or data of that region.

[0120] In this embodiment, when traversing each detector channel in the extended reconstructed scan image, the tissue scan value or other related information for each channel is obtained by iteratively accessing the pixels or data points of each channel, forming a set of detector channel traversal data. These channels all carry second beam information, which is utilized and applied to the corresponding tissue scan values. This involves adjusting the tissue scan values ​​within the region of interest based on the direction, intensity, or other characteristics of the beam. Subsequently, the tissue scan values ​​are accumulated and calculated, and the extended field of view information corresponding to the region of interest is further adjusted based on the accumulated sum to obtain the actual field of view information. This includes a mapping or conversion process to translate the tissue scan values ​​into a specific area of ​​the actual field of view. The entire process derives the actual field of view information within the region of interest based on the beam information, which has the beneficial effect of providing more accurate and comprehensive images or data of that region.

[0121] In one embodiment, Figure 9 As shown, the actual field of view information corresponding to the region of interest is determined based on the scan values ​​of each tissue, including:

[0122] Step 902: Accumulate the tissue scan values ​​to obtain an extended tissue scan value.

[0123] The extended tissue scanning value may be the cumulative result of the tissue scanning values ​​of each detector channel in the extended field of view information.

[0124] Specifically, information from each beam is used as a constraint and applied to each detector channel. This involves weighting or otherwise combining the tissue scan values ​​from each detector channel to ensure that beam information from different directions is accounted for. Subsequently, the tissue scan values ​​from each detector channel are accumulated and summed to obtain a tissue scan value for the extended field of view. This process integrates information from various directions and, using the beam as a constraint, yields an expanded tissue scan value for the corresponding interval.

[0125] Step 904 : adjusting the data within the reconstructed field of view according to the extended tissue scan value until the extended tissue scan value is less than a preset tissue threshold, thereby obtaining actual field of view information.

[0126] The adjusting of the field of view information may be to find a field of view range that best suits the region of interest of the target object for scanning based on the expanded field of view information.

[0127] Specifically, if the extended tissue scan value between the data within the reconstructed FOV and the extended FOV information is greater than a preset tissue threshold, the scan field of view corresponding to the innermost detector channel between the data within the reconstructed FOV and the extended FOV information is added to the data within the reconstructed FOV. That is, based on the range of detector channels between the data within the reconstructed FOV and the extended FOV information, the FOV information of the detector channel closest to the data within the reconstructed FOV is selected and added to the data within the reconstructed FOV. This is done until the extended tissue scan value between the data within the reconstructed FOV and the extended FOV information is less than the preset tissue threshold, at which point the adjusted FOV information is used as the actual FOV information for the next scan.

[0128] In this embodiment, individual beam information is applied as constraints to each detector channel. By weighting or otherwise combining the tissue scan values ​​in each channel, comprehensive consideration is ensured of beam information from different directions. Next, the tissue scan values ​​in each detector channel are accumulated and summed to obtain the tissue scan value for the expanded field of view information. This process integrates information from various directions and, using the beam as a constraint, yields the expanded tissue scan value for the corresponding interval. If the expanded tissue scan value between the data within the reconstructed field of view and the expanded field of view information exceeds a preset tissue threshold, the field of view corresponding to the innermost detector channel is added to the data within the reconstructed field of view. The field of view information of the detector channel closest to the data within the reconstructed field of view is then added to the data within the reconstructed field of view until the expanded tissue scan value falls below the preset tissue threshold. The resulting adjusted field of view information serves as the actual field of view for the next scan. This process effectively adjusts and optimizes the field of view information by integrating information from different directions, providing a more accurate and comprehensive data foundation for subsequent scans.

[0129] In one embodiment, Figure 10 As shown, the extended visual field information is adjusted according to the extended tissue scanning value until the extended tissue scanning value is less than the preset tissue threshold, and the adjusted visual field information is obtained, including:

[0130] Step 1002 : determining an inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information.

[0131] The innermost detector channel may be a detector channel closest to the data within the reconstructed field of view among the detector channels between the data within the reconstructed field of view and the extended field of view information.

[0132] The inner tissue scanning value may be a tissue scanning value obtained by scanning the innermost detector channel.

[0133] Specifically, each detector channel between the data within the reconstructed field of view and the extended field of view information is traversed to obtain the traversal information of the detector channel. According to the traversal information of the detector channel, the detector channel closest to the data within the reconstructed field of view in the area between the data within the reconstructed field of view and the extended field of view information is determined and used as the innermost detector channel, and the inner tissue scanning value corresponding to the innermost detector channel is read in the extended tissue scanning value accordingly.

[0134] Step 1004 , when the inner tissue scan value is greater than a preset tissue threshold, the field of view information corresponding to the inner tissue scan value is added to the data within the reconstructed field of view to obtain adjusted field of view information.

[0135] The adjusted field of view information may be a combination of data within the reconstructed field of view and field of view information corresponding to the inner layer tissue scan value.

[0136] Specifically, if the inner tissue scanning value is greater than the preset tissue threshold, it means that there are still objects in the scanning field of view corresponding to the inner tissue scanning value that are not included in the data within the reconstructed field of view. Therefore, the field of view information corresponding to the inner tissue scanning value is added to the data within the reconstructed field of view as a whole to obtain the adjusted field of view information.

[0137] Step 1006, using the adjusted field of view information as the data within the reconstructed field of view, returning to the step of determining the inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information, until the inner tissue scanning value is less than the preset tissue threshold, and obtaining the adjusted field of view information.

[0138] Specifically, the adjusted field of view information is used as the data within the reconstructed field of view, and the step of "traversing each detector channel between the data within the reconstructed field of view and the extended field of view information to obtain the traversal information of the detector channel, and determining the detector channel closest to the data within the reconstructed field of view in the area between the data within the reconstructed field of view and the extended field of view information according to the traversal information of the detector channel, and using it as the innermost detector channel, and correspondingly reading the inner tissue scan value corresponding to the innermost detector channel in the extended tissue scan value" is performed until it is detected that the inner tissue scan value is less than the preset tissue threshold, which means that the scanning field corresponding to the inner tissue scan value still does not contain objects that are not included in the data within the reconstructed field of view, and the adjusted field of view information is obtained as the data within the reconstructed field of view for the next scan. Figure 15 The figure shows the logical block diagram of the image reconstruction process for bone sclerosis correction.

[0139] In this embodiment, while traversing each detector channel between the data within the reconstructed field of view and the extended field of view information, detector channel traversal information is acquired. Based on this information, the detector channel closest to the data within the reconstructed field of view in the region between the data within the reconstructed field of view and the extended field of view information is determined and designated as the innermost detector channel. Accordingly, the inner tissue scan value corresponding to the innermost detector channel is read from the extended tissue scan value. If the inner tissue scan value is greater than a preset tissue threshold, it indicates that an object not included in the data within the reconstructed field of view exists within the scan field corresponding to the inner tissue scan value. Therefore, the field of view information corresponding to the inner tissue scan value is added to the data within the reconstructed field of view to obtain adjusted field of view information, which is then used as the new data within the reconstructed field of view. This process is repeated, repeatedly checking whether the inner tissue scan value is less than the preset tissue threshold, until it is confirmed that no object not included in the data within the reconstructed field of view exists within the scan field corresponding to the inner tissue scan value. Ultimately, the adjusted field of view information is obtained and serves as the data within the reconstructed field of view for the next scan. This strategy ensures the effective detection and supplementation of objects that are not included in the reconstruction field of view, improves the integrity and accuracy of the data within the reconstruction field of view, and provides a more accurate data basis for subsequent scans.

[0140] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0141] Based on the same inventive concept, embodiments of the present application also provide an image artifact correction device for implementing the aforementioned image artifact correction method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following embodiments of the image artifact correction device can be found in the aforementioned limitations of the image artifact correction method and will not be further elaborated here.

[0142] In one embodiment, Figure 16 As shown, an image artifact correction device is provided, comprising: a scanning data acquisition module 1602, an image reconstruction module 1604 and a sclerosis correction module 1606, wherein:

[0143] Scanning data acquisition module 1602 is used to acquire target scanning data corresponding to the region of interest; the target scanning data includes data within the reconstruction field of view and data within the scanning field of view;

[0144] An image reconstruction module 1604 is configured to reconstruct an image of the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0145] The sclerosis correction module 1606 is used to perform sclerosis correction on the target reconstructed scan image when the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstruction field of view is less than a preset tissue threshold to obtain a target corrected scan image.

[0146] In one embodiment, the sclerosis correction module 1606 is also used to determine the field of view interval corresponding to the data within the scanning field of view and the data within the reconstruction field of view; calculate the corresponding detector interval channel range in the field of view interval; accumulate the tissue scanning value according to the detector interval channel range to obtain the interval tissue scanning value; the tissue scanning value is the scanning value corresponding to any detector channel in the detector interval channel range.

[0147] In one embodiment, the sclerosis correction module 1606 is also used to calculate the detector field of view channel range corresponding to all detector channels in the data within the scanning field of view; calculate the detector reconstruction channel range corresponding to all detector channels in the data within the reconstruction field of view; and obtain the detector interval channel range based on the detector field of view channel range and the detector reconstruction channel range.

[0148] In one embodiment, the sclerosis correction module 1606 is further configured to determine each detector interval channel in the field of view interval according to the detector interval channel range; and accumulate the tissue scanning values ​​of each detector interval channel to obtain an interval tissue scanning value.

[0149] In one embodiment, the sclerosis correction module 1606 is further used to determine the accumulation model corresponding to the tissue scanning value of each detector interval channel; and accumulate each tissue scanning value according to the accumulation model to obtain the interval tissue scanning value.

[0150] In one embodiment, the sclerosis correction module 1606 is also used to expand the data within the scanning field of view to obtain extended field of view information when the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstruction field of view is greater than a preset tissue threshold; perform image reconstruction on the extended scanning data based on the extended field of view information to obtain an extended reconstructed scanning image; perform sclerosis correction based on the extended reconstructed scanning image and the target reconstructed scanning image to obtain a target corrected scanning image.

[0151] In one embodiment, the sclerosis correction module 1606 is also used to traverse each detector channel in the extended field of view information to obtain detector channel traversal data; the detector channel traversal data includes the tissue scanning value corresponding to each detector channel; the actual field of view information corresponding to the region of interest is determined based on each tissue scanning value; the actual field of view information is used for the data within the scanning field of view corresponding to the next scan of the region of interest.

[0152] In one embodiment, sclerosis correction module 1606 is further configured to accumulate the tissue scan values ​​to obtain an extended tissue scan value; and adjust the data within the reconstructed field of view based on the extended tissue scan value until the extended tissue scan value is less than a preset tissue threshold, thereby obtaining actual field of view information.

[0153] In one embodiment, the sclerosis correction module 1606 is also used to determine the inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information; when the inner tissue scanning value is greater than the preset tissue threshold, the field of view information corresponding to the inner tissue scanning value is added to the data within the reconstructed field of view to obtain the adjusted field of view information; the adjusted field of view information is used as the data within the reconstructed field of view, and the step of determining the inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information is returned to execute until the inner tissue scanning value is less than the preset tissue threshold to obtain the adjusted field of view information.

[0154] Each module in the aforementioned image artifact correction device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0155] In one embodiment, an image artifact correction system is provided, the system comprising: a scanning device and a computer;

[0156] a scanning device for scanning an area of ​​interest;

[0157] A computer is used to obtain target scanning data corresponding to the region of interest; the target scanning data includes data within the reconstructed field of view and data within the scanned field of view;

[0158] The computer is further used to reconstruct an image of the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image;

[0159] The computer is further used to perform sclerosis correction on the target reconstructed scan image to obtain a target corrected scan image if the tissue scan value of the area between the scanning field of view and the reconstruction field of view is less than a preset tissue threshold.

[0160] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 17 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store server data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements an image artifact correction method.

[0161] Those skilled in the art will understand that Figure 17 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0162] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0163] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

[0164] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of each of the above-described method embodiments.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0166] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0167] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0168] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for correcting image artifacts, characterized in that: The method comprises: Acquire target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstructed field of view and data within a scan field of view; Performing image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image; For the area between the scanning field of view and the reconstruction field of view, if the tissue scanning value is less than a preset tissue threshold, sclerosis correction is performed on the target reconstructed scan image to obtain a target corrected scan image.

2. The method according to claim 1, characterized in that After the step of reconstructing the image of the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image, the method further includes: Determine a field of view interval corresponding to the data within the scan field of view and the data within the reconstructed field of view; Calculate the corresponding detector interval channel range in the field of view interval; The tissue scanning values ​​are accumulated according to the detector interval channel range to obtain the interval tissue scanning value; the tissue scanning value is the scanning value corresponding to any detector channel within the detector interval channel range.

3. The method according to claim 2, characterized in that The calculating the detector interval channel range corresponding to the field of view interval includes: Calculate the detector field of view channel range corresponding to all detector channels in the data within the scanning field of view; Calculate the detector reconstruction channel ranges corresponding to all detector channels in the data within the reconstruction field of view; The detector interval channel range is obtained according to the detector field of view channel range and the detector reconstruction channel range.

4. The method according to claim 2, characterized in that The step of accumulating tissue scan values ​​according to the detector interval channel range to obtain the interval tissue scan value includes: Determining each detector interval channel in the field of view interval according to the detector interval channel range; The tissue scanning values ​​of each detector interval channel are accumulated to obtain the interval tissue scanning value.

5. The method according to claim 4, characterized in that The step of accumulating the tissue scanning values ​​of the detector interval channels using the ray beams as constraint information conditions to obtain the interval tissue scanning value includes: Determine the cumulative model corresponding to the tissue scanning value of each detector interval channel; The tissue scanning values ​​are accumulated according to the accumulation model to obtain the interval tissue scanning value.

6. The method according to claim 1, characterized in that The method further comprises: When the interval tissue scanning value corresponding to the data within the scanning field of view and the data within the reconstructed field of view is greater than a preset tissue threshold, the data within the scanning field of view is expanded to obtain expanded field of view information; Scanning the region of interest according to the extended field of view information to obtain extended scan data; performing image reconstruction on the extended scan data according to the extended field of view information to obtain an extended reconstructed scan image; Sclerosis correction is performed based on the extended reconstructed scan image and the target reconstructed scan image to obtain the target corrected scan image.

7. The method according to claim 6, characterized in that After the step of performing sclerosis correction based on the extended reconstructed scan image and the target reconstructed scan image to obtain the target corrected scan image, the method further includes: Traversing each detector channel in the extended field of view information to obtain detector channel traversal data; the detector channel traversal data includes tissue scanning values ​​corresponding to each detector channel; The actual field of view information corresponding to the region of interest is determined according to each of the tissue scanning values; the actual field of view information is used for reconstructing data within a field of view corresponding to the next scan of the region of interest.

8. The method according to claim 7, characterized in that The determining of the actual field of view information corresponding to the region of interest according to each of the tissue scan values ​​includes: Accumulating the tissue scan values ​​to obtain an extended tissue scan value; The data within the reconstructed field of view is adjusted according to the extended tissue scan value until the extended tissue scan value is less than the preset tissue threshold, thereby obtaining the actual field of view information.

9. The method according to claim 8, characterized in that The step of adjusting the data within the reconstructed field of view according to the extended tissue scan value until the extended tissue scan value is less than the preset tissue threshold, thereby obtaining the actual field of view information, includes: Determine an inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information; When the inner layer tissue scan value is greater than the preset tissue threshold, adding the field of view information corresponding to the inner layer tissue scan value to the data within the reconstructed field of view to obtain adjusted field of view information; Use the adjusted field of view information as the data within the reconstructed field of view, return to the step of determining the inner tissue scanning value corresponding to the innermost detector channel of each detector channel between the data within the reconstructed field of view and the expanded field of view information, until the inner tissue scanning value is less than the preset tissue threshold, and obtain the adjusted field of view information.

10. An image artifact correction system, characterized in that: The system includes: a scanning device and a computer; The scanning device is used to scan the region of interest; The computer is used to obtain target scanning data corresponding to the region of interest; the target scanning data includes data within a reconstruction field of view and data within a scanning field of view; The computer is further configured to perform image reconstruction on the region of interest based on the data within the reconstruction field of view to obtain a target reconstructed scan image; The computer is further configured to perform sclerosis correction on the target reconstructed scan image to obtain a target corrected scan image if the tissue scan value of the area between the scanning field of view and the reconstruction field of view is less than a preset tissue threshold.

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