Method and device for removing ring artifact of ct image, electronic equipment and storage medium

Abstract

The application provides an image ring artifact removal method and device, electronic equipment and a storage medium, wherein the method comprises: performing normalization processing on an obtained original CT image to obtain a standard CT image; dividing the standard CT image into a plurality of standard sectors according to a target sector division mode, and dividing the original CT image into a plurality of original sectors according to the target sector division mode; determining a correction pixel value corresponding to each standard pixel in each standard sector; correcting an original pixel value of an original pixel in a main sector region in the original CT image according to the correction pixel value corresponding to each standard pixel in each standard sector, and performing linear transition on a pixel value of an original pixel in each boundary sector region in the original CT image according to two correction pixel values corresponding to each standard pixel in an overlapping region of each standard sector, so as to remove ring artifacts in the original CT image.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method and apparatus for removing ring artifacts in CT images, an electronic device, and a storage medium. Background Technology

[0002] During CT imaging, uneven detector response, gain deviation, and filtering algorithm defects can cause ring artifacts to appear in the obtained CT images, which seriously affect the quality of CT images and diagnostic accuracy.

[0003] In related technologies, the removal of annular artifacts mainly focuses on the projection domain or frequency domain. However, the methods used in these technologies have the following technical problems: the detection threshold for annular artifacts is unstable under different scanning locations, body sizes, or grayscale distributions, making them prone to missed or false detections; image domain correction methods based on direction or sector are prone to brightness abrupt changes or splicing artifacts at sector boundaries.

[0004] Therefore, it is evident that the methods for removing annular artifacts in related technologies suffer from poor performance in removing sector boundary artifacts. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for removing annular artifacts in CT images, to at least solve the technical problem of poor sector boundary artifact removal effect in related art methods for removing annular artifacts.

[0006] According to one aspect of the embodiments of this application, a method for removing ring artifacts in CT images is provided, comprising: The acquired raw CT images are normalized to obtain standard CT images, wherein the normalization process is used to unify the gray-scale distribution characteristics under different imaging conditions. According to the target sector division method, the standard CT image is divided into multiple standard sectors, and the original CT image is divided into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image. Determine the correction pixel value corresponding to each standard pixel within each standard sector; The original pixel values ​​of the original pixels in the main sector region of the original CT image are corrected according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and the pixel values ​​of the original pixels in each boundary sector region of the original CT image are linearly transitioned according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, so as to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

[0007] Optionally, as described above, the normalization process for the acquired raw CT image to obtain a standard CT image includes: Filter out original pixels in the original CT image whose pixel values ​​are greater than or equal to a predetermined pixel value; Determine the lower and upper limits of pixel values ​​from all the selected raw pixels; Based on the lower limit and the upper limit of the pixel value, the pixel values ​​of all the selected original pixels are normalized to obtain the normalized pixel corresponding to each selected original pixel. Calculate the standard deviation of the pixel values ​​of all normalized pixels to obtain the target standard deviation; Based on the target standard deviation, the preset mean, and the preset standard deviation, the pixel values ​​of all normalized pixels are standardized to obtain the standard CT image.

[0008] Optionally, as described above, determining the correction pixel value corresponding to each standard pixel within each standard sector includes: For each standard sector, the neighboring pixel difference information corresponding to each standard pixel is determined. For any standard pixel, the neighboring pixel difference information is used to indicate the pixel value difference between the corresponding standard pixel and other adjacent standard pixels. The spatial coordinates of each standard pixel in the standard CT image are mapped to the detector channel array to obtain the detector channel position value corresponding to each standard pixel, wherein the detector channel array is used to capture the original CT image; Based on the neighboring pixel difference information corresponding to each standard pixel in each standard sector, the marker ring value of each standard pixel in each standard sector is determined, wherein the marker ring value is used to indicate whether the corresponding standard pixel is a pixel in the ring artifact; Based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel in each standard sector, the correction pixel value corresponding to each standard pixel in each standard sector is determined.

[0009] Optionally, as described above, determining the neighboring pixel difference information corresponding to each standard pixel according to each standard sector includes: According to the weighted filter corresponding to each standard sector, the difference feature value of each standard pixel is determined by calculating the difference between each standard pixel in each standard sector and the mean of N neighboring standard pixels in the weighted filter. The neighboring pixel difference information includes the difference feature value, and N is an odd number greater than or equal to 3. According to the weighted filter corresponding to each standard sector, the edge feature value of each standard pixel is determined by calculating N-2 times the difference between the mean of the N-2 center neighboring standard pixels and the mean of the two edge standard pixels in the N neighborhood pixels of the weighted filter of each standard pixel in each standard sector, wherein the neighborhood pixel difference information includes the edge feature value.

[0010] Optionally, as described above, mapping the spatial coordinates of each standard pixel in the standard CT image to the detector channel array to obtain the detector channel position value corresponding to each standard pixel includes: Determine the spatial coordinates of the standard pixel relative to the image center of the standard CT image; Based on the size of the standard pixel, the distance from the X-ray tube to the rotation center, the distance from the X-ray tube to the detector, the detector channel spacing, and the number of detector channels, the detector channel position value corresponding to the standard pixel is determined.

[0011] Optionally, as described above, determining the tag ring value of each standard pixel within each standard sector based on the neighboring pixel difference information corresponding to each standard pixel within each standard sector includes: If the difference feature value of the standard pixel satisfies a first preset condition or the edge feature value of the standard pixel satisfies a second preset condition, the mark ring value of the standard pixel is determined to be 0. The first preset condition is that the absolute value of the difference feature value of the standard pixel is greater than the target difference feature value threshold of the standard pixel, and the second preset condition is that the absolute value of the edge feature value of the standard pixel is greater than the target edge feature value threshold of the standard pixel. The mark ring value of 0 is used to indicate that the standard pixel is not a pixel on a ring artifact. If the difference feature value of the standard pixel does not meet the first preset condition and the edge representation value of the standard pixel does not meet the second preset condition, the mark ring value of the standard pixel is determined to be 1. The mark ring value of 1 is used to indicate that the standard pixel is a pixel on a ring artifact.

[0012] Optionally, as described above, the method further includes: Determine the center distance between the standard pixel and the image center of the standard CT image; The target correction coefficient corresponding to the standard pixel is determined according to the distance range in which the center distance of the standard pixel is located; The target difference feature value threshold is determined based on the product of a preset difference feature value threshold and the target correction coefficient; the target edge feature value threshold is determined based on the product of a preset edge feature value threshold and the target correction coefficient.

[0013] Optionally, as described above, determining the correction pixel value corresponding to each standard pixel in each standard sector based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel within each standard sector includes: For each standard pixel in each standard sector, the formula is used. and formula Two weights are determined for each standard pixel, wherein each weight corresponds one-to-one with a detector channel of the standard pixel, and the weight indicates the proportion of contribution that the standard pixel allocates to the corresponding detector channel. A weight for the standard pixel. This is another weight for the standard pixel. The detector channel is the detector channel corresponding to one of the two detector channel position values ​​for each standard pixel. The detector channel corresponding to the other detector channel position value among the two detector channel position values ​​of each standard pixel; For any detector channel c in any standard sector q, the formula is used. The first weighted sum of the number of standard pixels identified as ring artifacts on the detector channel c of the standard sector q is determined using the formula... The second weighted sum of the edge feature values ​​of all standard pixels on the detector channel c of the standard sector q is determined, wherein, The total number of pixels in the standard sector q. The first sector in the standard sector q mapped to the detector channel c The marker ring value of a standard pixel, The first sector in the standard sector q mapped to the detector channel c The weights of the standard pixels in detector channel c The first sector in the standard sector q mapped to the detector channel c The edge feature values ​​of a standard pixel are defined as follows: a ring value of 0 indicates that the pixel is not a standard pixel on a ring artifact, and a ring value of 1 indicates that the standard pixel is a pixel on a ring artifact. For each detector channel in each standard sector, the ratio of the second weighted sum of the detector channel to the first weighted sum of the detector channel is calculated to obtain the weighted average edge feature value of the detector channel; For each standard pixel in each standard sector, the corrected pixel value of the standard pixel is determined based on the two weights of the pixel and the weighted average edge feature value of the two detector channels of the standard pixel.

[0014] Optionally, as described above, determining the corrected pixel value of the standard pixel for each standard pixel in each standard sector, based on the two weights of the pixel and the weighted average edge feature value of the two detector channels of the standard pixel, includes: Using formula Determine the corrected pixel value of the standard pixel, wherein, The corrected pixel value for the standard pixel. The weighted average edge feature value of one detector channel of the standard pixel in the standard sector. The weighted average edge feature value of the pixel in the standard sector is the value of another detector channel.

[0015] Optionally, as described above, the step of correcting the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the corrected pixel values ​​corresponding to each standard pixel in each standard sector, and performing a linear transition on the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two corrected pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, to remove the ring artifacts in the original CT image, includes: When the original pixel is located in the boundary sector region of its original sector, the formula is used. Determine the target corrected pixel value corresponding to the boundary sector region of the original pixel. ,in, , The azimuth angle of the original pixel. The azimuth angle of the common edge between the boundary sector region and the main sector region of the original sector. The central angle of the boundary sector region, Coordinates are The original pixel corresponds to the corrected pixel value of one of the two original sectors where the boundary sector region is located. Coordinates are The original pixel corresponds to the corrected pixel value of the other original sector among the two original sectors where the boundary sector region is located; When the original pixel is located in the main sector region of the original sector, the corrected pixel value of the original pixel is directly used as the target corrected pixel value of the original pixel. For each original pixel in each of the original sectors, the formula is used. Determine the target pixel value of the original pixel. ,in, Coordinates are The original pixel value of the original pixel. For radius-based empirical weighting coefficients, Coordinates are The target corrected pixel value of the original pixel.

[0016] According to another aspect of the embodiments of this application, a device for removing ring artifacts in CT images is also provided, comprising: The normalization module performs normalization processing on the acquired raw CT image to obtain a standard CT image, wherein the normalization processing is used to unify the gray-scale distribution characteristics under different imaging conditions. The segmentation module is used to divide the standard CT image into multiple standard sectors according to the target sector segmentation method, and to divide the original CT image into multiple original sectors according to the target sector segmentation method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image. The determination module is used to determine the correction pixel value corresponding to each standard pixel in each standard sector; The correction module is used to correct the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and to perform a linear transition on the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, so as to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

[0017] According to another aspect of the embodiments of this application, an electronic device is also provided, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; wherein the memory is used to store a computer program; and the processor is used to execute the method steps of any of the above embodiments by running the computer program stored in the memory.

[0018] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to execute the method steps of any of the above embodiments when running.

[0019] In this embodiment, the acquired original CT image is normalized to obtain a standard CT image, wherein the normalization process is used to unify the grayscale distribution characteristics under different imaging conditions; the standard CT image is divided into multiple standard sectors according to the target sector division method, and the original CT image is divided into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image; the correction pixel value corresponding to each standard pixel in each standard sector is determined; the original pixel value of the original pixel in the main sector region of the original CT image is corrected according to the correction pixel value corresponding to each standard pixel in each standard sector, and the two correction values ​​corresponding to each standard pixel in the overlapping area of ​​each standard sector are corrected. The pixel values ​​of the original pixels in each boundary sector region of the original CT image are linearly transitioned to remove ring artifacts in the original CT image. The boundary sector region is the overlapping area with other original sectors, and the main sector region is the area that does not overlap with other original sectors. By introducing image normalization to unify the grayscale distribution characteristics under different imaging conditions, and employing a sector division method with overlapping regions, and performing linear transition correction within the overlapping regions, the stability of ring artifact detection and correction under different scanning conditions can be improved, and splicing artifacts at sector boundaries can be avoided. This achieves a significant improvement in the technical effect of sector boundary artifact removal, thus solving the problem of poor sector boundary artifact removal effect in related technologies. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the hardware environment for an optional image ring artifact removal method according to an embodiment of this application; Figure 2 This is a schematic flowchart of an optional image ring artifact removal method according to an embodiment of this application; Figure 3This is a flowchart illustrating another optional image ring artifact removal method according to an embodiment of this application; Figure 4 This is a flowchart illustrating another optional image ring artifact removal method according to an embodiment of this application; Figure 5 A schematic diagram of sector division in a CT image; Figure 6 This is a schematic diagram showing the correspondence between pixels and weighted filters; Figure 7 This is a schematic diagram of mapping the coordinates of pixels in a CT image to the detector channel array. Figure 8(a) is a schematic diagram of a CT image before correction using the CT image ring artifact removal method of this application; Figure 8(b) is a schematic diagram of a CT image corrected using the CT image ring artifact removal method of this application; Figure 9(a) is a schematic diagram of a CT image (water model image) before correction using the CT image ring artifact removal method of this application; Figure 9(b) is a schematic diagram of a CT image (water model image) corrected using the CT image ring artifact removal method of this application; Figure 10(a) is a schematic diagram of a CT image corrected using the CT image ring artifact removal method of this application (without standardization processing); Figure 10(b) shows a CT image corrected using the CT image annular artifact removal method (after standardization) of this application; Figure 11 This is a structural block diagram of an optional image ring artifact removal apparatus according to an embodiment of this application; Figure 12 This is a structural block diagram of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] The following definitions are provided for the terms used in this application: CT scanner: It consists of an X-ray tube and a detector. The X-ray tube is used to generate an X-ray beam. During the imaging process, the X-ray tube and the detector rotate synchronously around the scanning rotation center. The object to be examined or the subject is located in the scanning area of ​​the rotation center. After the X-ray beam emitted by the X-ray tube penetrates the examined area, it is received by the detection channel array of the detector. Through continuous rotation scanning, multiple two-dimensional tomographic images of the object or human body examined area can be acquired. After reconstruction by the computer system, a clear three-dimensional structural image can be obtained.

[0026] Rotation center: The rotation center can refer to the geometric center between the rotation axis of the X-ray tube and the detector.

[0027] Water model image: obtained by CT scanning of a water model made of water with a specific shape that has an attenuation coefficient similar to that of human tissue.

[0028] According to one aspect of the embodiments of this application, a method for removing ring artifacts in CT images is provided. Optionally, in this embodiment, the above-described method for removing ring artifacts in CT images can be applied to, for example... Figure 1 The hardware environment shown consists of terminal 1402 and server 1404. For example... Figure 1 As shown, server 1404 is connected to terminal 1402 via a network and can be used to provide services (such as game services, application services, etc.) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 1404.

[0029] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal may not be limited to PC, mobile phone, tablet computer, etc.

[0030] The CT image ring artifact removal method of this application embodiment can be executed by a server, a terminal, or both. Alternatively, the terminal can execute the CT image ring artifact removal method of this application embodiment by a client installed on it.

[0031] Taking the CT image ring artifact removal method in this embodiment, executed by the server, as an example, Figure 2 A method for removing ring artifacts in CT images provided in this application includes the following steps: Step S202: Normalize the acquired raw CT image to obtain a standard CT image. The normalization process is used to unify the grayscale distribution characteristics under different imaging conditions.

[0032] The CT image ring artifact removal method in this embodiment can be applied to scenarios involving the removal of ring artifacts from CT images obtained by a CT scanner.

[0033] Specifically, the original CT image can be obtained by transforming the image coordinates of a CT image (denoted as the pre-expansion CT image) obtained by scanning with a CT scanner.

[0034] Furthermore, the original CT image is expanded according to the rotation center offset of the pre-expansion CT image and the original image size to obtain the original CT image. Specifically, the original CT image can be obtained by performing the following steps on the pre-expansion CT image: obtaining the width of the pre-expansion CT image. and length Lateral offset of the center of rotation and vertical offset It's easy to understand that the lateral offset here... This refers to the horizontal distance between the pixel corresponding to the rotation center and the center pixel. The unit of this distance is not pixels; the vertical offset follows the same principle. The horizontal relative offset of the rotation center... Convert to pixel units to obtain the pixel lateral offset of the rotation center. The longitudinal offset of the rotation center Convert to pixel units to obtain the vertical offset of the pixel at the rotation center. Edge expansion is performed on the CT image before expansion based on the pixel lateral offset and pixel vertical offset of the rotation center. The width of the original CT image after edge expansion is... ( ) and length ( Furthermore, the center pixel of the original CT image is the pixel corresponding to the rotation center. Additionally, the pixel values ​​of the pixels added through edge expansion are set to 0.

[0035] Normalizing raw CT images can unify image data from different sources or with different scanning parameters, facilitating subsequent analysis and comparison. The pixel values ​​of raw CT images typically reflect the tissue's absorption rate of X-rays, and their range can vary depending on factors such as equipment and scanning parameters. Normalization first involves adjusting these values ​​to a common standard range, such as between 0 and 1 or between -1000 and 400 Hounsfield units (HU), which can be selected based on the specific application requirements. This process not only improves the comparability between images but also helps improve the performance of subsequent image processing tasks such as segmentation and feature extraction. Furthermore, normalization helps reduce data bias during model training, improving the diagnostic accuracy based on CT images.

[0036] like Figure 3 As shown, as an optional embodiment, step S202, which involves normalizing the acquired raw CT image, can be implemented through the following steps to obtain a standard CT image: Step S302: Select original pixels in the original CT image whose pixel values ​​are greater than or equal to a predetermined pixel value.

[0037] Specifically, the pixel value of each raw pixel in the original CT image can be checked to filter out pixels with raw pixel values ​​not less than a predetermined pixel value. The original pixels are selected to avoid affecting subsequent normalization processing by using original pixels with values ​​smaller than a predetermined value. These pixel values ​​are stored as floating-point numbers for subsequent statistical calculations. The set of original pixel values ​​is... ,in, It is the pixel value of the original pixel.

[0038] Step S304: Determine the lower limit and upper limit of pixel values ​​among all the selected raw pixels.

[0039] Specifically, the original pixel values ​​of the filtered pixels are sorted from smallest to largest or largest to smallest to determine the lower limit of the smallest pixel value and the upper limit of the largest pixel value among the original pixels. The lower limit of the pixel value is the A% quantile of the sorted pixel values, and the upper limit of the pixel value is the B% quantile of the sorted pixel values, where A is less than B.

[0040] Specifically, after determining the lower and upper limits of pixel values, the distribution of the original pixel values ​​of the filtered pixels can be further referenced to calculate the 1st percentile (a pixel value representing 1% of the sorted pixel values ​​less than that value) and 99th percentile (a pixel value representing 99% of the sorted pixel values ​​less than that value). The 1st percentile value is... The 99th percentile value is ,Will and As a reference range for the following normalization process, the formula is used. get Using formula get ,in, This indicates that the data is sorted according to pixel value. for The total number of pixel values ​​in the data.

[0041] Step S306: Based on the lower limit and upper limit of pixel value, normalize the pixel values ​​of all selected original pixels to obtain the normalized pixel corresponding to each selected original pixel.

[0042] In other words, after determining the lower and upper limits of pixel values, specifically, based on and Using formula The pixel values ​​of the filtered original pixels are normalized, whereby... lie in Within the range. In fact, it is only not less than... and not greater than of The normalized pixel values ​​will participate in subsequent correction calculations. In other words, the original pixels with pixel values ​​greater than or equal to the lower limit of the above pixel values ​​and less than or equal to the upper limit of the above pixel values ​​are selected at the same time.

[0043] Step S308: Calculate the standard deviation of the pixel values ​​of all normalized pixels to obtain the target standard deviation.

[0044] Specifically, it can be done through formulas The mean of the pixel values ​​of all normalized pixels after normalization is calculated to obtain the target mean, where, The target mean, For the first The pixel value of each normalized pixel is calculated using the formula... Calculate the standard deviation of the pixel values ​​of all normalized pixels to obtain the target standard deviation, where, The target standard deviation is denoted as .

[0045] Step S310: Standardize the pixel values ​​of all normalized pixels according to the target standard deviation, the preset mean, and the preset standard deviation to obtain a standard CT image.

[0046] Specifically, based on the target standard deviation, the preset mean, and the preset standard deviation, the formula is used. The pixel values ​​of all normalized pixels are standardized, whereby... As the preset mean, To preset the standard deviation, the preset mean can be the average pixel value of the water phantom image at the time of manufacture, and the preset standard deviation can be the average pixel value of the water phantom image at the time of manufacture of the CT scanner. After standardizing all normalized pixels using the above method, a standard CT image corresponding to the original CT image can be obtained.

[0047] The method in this embodiment normalizes and standardizes all pixels, so that the pixel values ​​of the final standardized pixels have the same statistical characteristics, which facilitates the use of a unified correction method in the future.

[0048] Step S204: Divide the standard CT image into multiple standard sectors according to the target sector division method, and divide the original CT image into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image.

[0049] In other words, both standard CT images and raw CT images are divided into sectors using the same target sector division method. Furthermore, taking a standard CT image as an example, every two adjacent standard sectors in the resulting division have overlapping areas; that is, two adjacent standard sectors share a small sector. Similarly, for raw CT images, every two adjacent raw sectors in the resulting division also have overlapping areas.

[0050] like Figure 5 As shown, an optional method for image sector division and overlapping region setting is provided: Sector Division: The image is divided into 8 sectors, each with an angle of 45°, as detailed below: Sector 1: 0° to 45°; Sector 2: 45° to 90°; Sector 3: 90° to 135°; Sector 4: 135° to 180°; Sector 5: 180° to 225°; Sector 6: 225° to 270°; Sector 7: 270° to 315°; Sector 8: 315° to 360°.

[0051] Overlapping region: Defined between adjacent sectors To ensure a smooth transition, overlapping areas are defined, including: The overlapping areas contained in sector 1 and sector 5 are: ( )arrive( ); The overlapping areas contained in sector 2 and sector 6 are: ( )arrive( ); The overlapping areas contained in sector 3 and sector 7 are: ( )arrive( ); The overlapping areas contained in sector 4 and sector 8 are: ( )arrive( ).

[0052] Figure 5 In the diagram, overlap18 is the area where sector 1 and sector 8 overlap, overlap12 is the area where sector 1 and sector 2 overlap, overlap23 is the area where sector 2 and sector 3 overlap, overlap34 is the area where sector 3 and sector 4 overlap, overlap45 is the area where sector 4 and sector 5 overlap, overlap56 is the area where sector 5 and sector 6 overlap, overlap67 is the area where sector 6 and sector 7 overlap, and overlap78 is the area where sector 7 and sector 8 overlap.

[0053] Step S206: Determine the correction pixel value corresponding to each standard pixel in each standard sector.

[0054] Specifically, determining the corrected pixel value for each standard pixel within each standard sector refers to performing localized, refined corrections on the original projection data or reconstructed image to address image artifacts caused by factors such as detector response inconsistencies, ray hardening, scattering, or geometric deviations. Optionally, within each standard sector, the corrected pixel value for each standard pixel can be calculated based on a calibration model (such as gain / offset correction based on water phantom scanning, ray hardening correction curves, or deep learning priors). This corrected pixel value can be used to weight, compensate, or replace the original pixel values ​​of the original pixels, thereby obtaining corrected pixel values ​​that more accurately reflect the true attenuation characteristics of the tissue. This process effectively improves image uniformity, contrast, and the accuracy of quantitative analysis.

[0055] Step S208 involves correcting the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and linearly transitioning the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, in order to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

[0056] Specifically, since standard CT images are obtained by normalizing and standardizing the original CT images, there is a one-to-one correspondence between the pixels in the standard CT images and the pixels in the original CT images. Furthermore, for any given standard sector, each standard pixel within that sector obtains a corresponding corrected pixel value through step S206. Therefore, for the main sector region in the original CT image, since the original pixels in the main sector region exist only in one original sector and thus correspond to only one standard pixel, correction can be directly performed using the corrected pixel value of the corrected pixel corresponding to that original pixel.

[0057] For each original pixel in a boundary sector region of the original CT image, since the original pixel in the boundary sector region exists simultaneously in two original sectors of the original CT image, and each original sector corresponds to a standard sector, there are also two standard pixels corresponding to the original pixels in the boundary sector region. Therefore, in this embodiment, based on the two correction pixel values ​​corresponding to each standard pixel in the overlapping area of ​​each standard sector, a smooth transition correction value can be generated by weighting these two correction pixel values. Finally, this smooth transition correction value replaces the pixel value of the original pixel, realizing pixel-by-pixel correction of the original CT image. This method can effectively suppress systematic errors such as ring artifacts and detector response inconsistencies, while ensuring natural transitions between sectors, avoiding the introduction of new boundary artifacts, and improving image uniformity and diagnostic reliability.

[0058] In this embodiment, the acquired original CT image is normalized to obtain a standard CT image, wherein the normalization process is used to unify the grayscale distribution characteristics under different imaging conditions; the standard CT image is divided into multiple standard sectors according to the target sector division method, and the original CT image is divided into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image; the correction pixel value corresponding to each standard pixel in each standard sector is determined; the original pixel value of the original pixel in the main sector region of the original CT image is corrected according to the correction pixel value corresponding to each standard pixel in each standard sector, and the correction pixel value is also corrected according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping area of ​​each standard sector. This method involves linearly transitioning the pixel values ​​of the original pixels in each boundary sector region of the original CT image to remove ring artifacts. The boundary sector region is the overlapping area with other original sectors, while the main sector region is the area that does not overlap with other original sectors. By introducing image normalization to unify grayscale distribution characteristics under different imaging conditions, and employing a sector division method with overlapping regions, and performing linear transition correction within the overlapping areas, the stability of ring artifact detection and correction under different scanning conditions can be improved, and splicing artifacts at sector boundaries can be avoided. This effectively enhances the removal of sector boundary artifacts, thus solving the problem of poor sector boundary artifact removal performance in related techniques.

[0059] like Figure 4 As shown, as an optional embodiment, the method described above can be implemented by determining the correction pixel value corresponding to each standard pixel in each standard sector through the following steps: Step S402: For each standard sector, determine the neighboring pixel difference information corresponding to each standard pixel. The neighboring pixel difference information is used to indicate the pixel value difference between the corresponding standard pixel and other adjacent standard pixels.

[0060] Specifically, for each standard sector, the difference between each standard pixel and its neighboring pixels can be determined, and based on this difference, the neighborhood pixel difference information corresponding to each standard pixel can be determined. In other words, in ring artifact detection, the difference between each standard pixel and its neighboring pixels needs to be calculated first. This can be done using a weighted filter corresponding to the standard sector, such as... Figure 6As shown, different sectors correspond to different weighting filters: sectors 1 and 5 use weighting filter I, sectors 2 and 6 use weighting filter II, sectors 3 and 7 use weighting filter III, and sectors 4 and 8 use weighting filter IV. For each pixel, its difference from surrounding pixels is calculated and then weighted using the corresponding weighting filter.

[0061] As an optional embodiment, the method described above can be implemented by the following steps: Step S402, which determines the neighboring pixel difference information corresponding to each standard pixel according to each standard sector, includes: According to the weighted filter corresponding to each standard sector, the difference feature value of each standard pixel is determined by calculating the difference between each standard pixel in each standard sector and the mean of the N neighboring standard pixels in the weighted filter. The difference information of the neighboring pixels includes the difference feature value, and N is an odd number greater than or equal to 3.

[0062] According to the weighted filter corresponding to each standard sector, the edge feature value of each standard pixel is determined by calculating N-2 times the difference between the mean of the N-2 center standard pixels in the N neighborhood pixels of the weighted filter of each standard pixel in each standard sector and the mean of the two edge standard pixels. The difference information of the neighborhood pixels includes the edge feature value.

[0063] Specifically, N can be 7. Therefore, for each standard pixel in a standard CT image, the formula can be used. To determine the difference feature values ​​of standard pixels, the formula is used. Determine the edge feature values ​​of standard pixels, where, These are the difference feature values ​​of standard pixels. The edge feature values ​​of standard pixels, The first in the weighted filter corresponding to the standard pixel The pixel value of each pixel is used, and the aforementioned standard pixel is used as the 4th pixel in the corresponding weighted filter. The weighted filter contains 7 pixels. The difference between the pixel value of the center pixel (i.e., the 4th pixel when N is 7) and the mean pixel value of all standard pixels in the filter highlights ring artifacts or anomalous abrupt changes (i.e., local contrast abnormalities in pixels). The difference between the pixel value of the central standard pixel (the 4th standard pixel), the mean of the remaining 5 standard pixels in the filter, and the mean of the pixel values ​​of the two standard pixels at the edges of the filter is five times, emphasizing abrupt changes in a certain direction, used to detect ring artifacts in a specific direction. For example... Figure 7As shown, Sector4,8 are the weighted filters corresponding to standard sectors 4 and 8; Sector1,5 are the weighted filters corresponding to standard sectors 1 and 5; Sector2,6 are the weighted filters corresponding to standard sectors 2 and 6; and Sector3,7 are the weighted filters corresponding to standard sectors 3 and 7.

[0064] Step S404: Map the spatial coordinates of each standard pixel in the standard CT image to the detector channel array to obtain the detector channel position value corresponding to each standard pixel. The detector channel array is used to capture the original CT image.

[0065] As an optional embodiment, the method described above can be used to map the spatial coordinates of each standard pixel in a standard CT image to a detector channel array through the following steps to obtain the detector channel position value corresponding to each standard pixel: determine the spatial coordinates of the standard pixel relative to the image center of the standard CT image; determine the detector channel position value corresponding to the standard pixel based on the size of the standard pixel, the distance from the X-ray tube to the rotation center, the distance from the X-ray tube to the detector, the detector channel spacing, and the number of detector channels.

[0066] like Figure 7 As shown, Center of rotation For the detector channel array, the following formula is used. and formula Determine the detector channel position value of the pixel. ,in, The coordinates of a standard pixel. The pixel size of a standard pixel. Indicates taking The absolute value, The distance from the X-ray tube to the center of rotation. This represents the distance from the X-ray tube to the detector. This represents the total number of detector channels in the detector channel array within the detector. This is for channel offset correction. Furthermore, it can be... Round down to obtain the detector channel position value of the main channel. c1 The detector channel position value of its previous channel is c2=c1+1 .

[0067] Step S406: Determine the tag ring value of each standard pixel in each standard sector based on the difference information of the neighboring pixels corresponding to each standard pixel in each standard sector. The tag ring value is used to indicate whether the corresponding standard pixel is a pixel in the ring artifact.

[0068] Specifically, within each standard sector, the difference information of neighboring pixels corresponding to each standard pixel is acquired. If the difference information of a certain standard pixel indicates that the difference between the standard pixel and its neighboring pixels is significantly higher than the surrounding background noise level, it is determined that it may belong to a ring artifact. Accordingly, a ring value is assigned to the pixel (for example, using a binary label: 1 represents "a ring artifact pixel", 0 represents "a non-ring artifact pixel"; or a continuous confidence score). This ring value not only reflects the degree of abnormality of the pixel itself, but can also be optimized in combination with spatial consistency constraints within the sector (such as multiple high-response points on the same radial line are more likely to be real rings), thereby improving the accuracy and robustness of detection and providing a reliable basis for subsequent artifact correction.

[0069] As an optional embodiment, the method described above can be implemented by determining the tag ring value of each standard pixel in each standard sector based on the difference information of neighboring pixels corresponding to each standard pixel within each standard sector through the following steps: If the difference feature value of the standard pixel meets the first preset condition or the edge feature value of the standard pixel meets the second preset condition, the mark ring value of the standard pixel is determined to be 0. The first preset condition is that the absolute value of the difference feature value of the standard pixel is greater than the target difference feature value threshold of the standard pixel, and the second preset condition is that the absolute value of the edge feature value of the standard pixel is greater than the target edge feature value threshold of the standard pixel. The mark ring value of 0 is used to indicate that the standard pixel is not a pixel on the ring artifact. If the difference feature value of the standard pixel does not meet the first preset condition and the edge representation value of the standard pixel does not meet the second preset condition, the mark ring value of the standard pixel is determined to be 1. The mark ring value of 1 is used to indicate that the standard pixel is a pixel on the ring artifact.

[0070] Specifically, the first preset condition is: ,in, These are the difference feature values ​​of standard pixels. The threshold for the target difference feature value of standard pixels. This indicates taking the absolute value of the difference feature value of the standard pixels, with the second preset condition being: ,in, The edge feature values ​​of standard pixels, The threshold value for the target edge feature value of a standard pixel. This represents the absolute value of the edge feature value of a standard pixel.

[0071] Specifically, and Both represent the pixel value differences of local standard pixels. or If the difference between the standard pixel and its surrounding pixels is significant, the standard pixel belongs to a true edge and is not a ring artifact. In this case, the ring marker value of the pixel is set to 0, and no correction is made. Otherwise, if the difference between the standard pixel and its surrounding standard pixels is not significant, the standard pixel belongs to a ring artifact. In this case, the ring marker value of the standard pixel is set to 1, and the ring value is adjusted accordingly. d pAAd Record to image d pAAe This is used for subsequent correction.

[0072] Furthermore, the target difference feature value threshold and the target edge feature value threshold of standard pixels can be achieved through the following steps: Based on the spatial position of the standard pixel (distance r from the rotation center ISO) and the output difference of the weighted filter, a dynamic threshold is used to determine the ring artifact.

[0073] For each standard pixel in a standard CT image First, calculate the distance r between it and the rotation center ISO. The formula for this calculation is:

[0074] Where w is the center position of the image width, h is the center position of the image height, and x and y are the positions of the current standard pixels.

[0075] Based on the calculated distance r, select the appropriate dynamic threshold. and The threshold decreases as r increases. The specific dynamic threshold settings are as follows: like Then select the threshold. ; like Then select the threshold. ; like Then select the threshold. ; like Then select the threshold. ; For any standard pixel Calculate the difference between its result and the filter result. and Then use dynamic thresholding. and The following formula is used to determine these differences:

[0076] in, and It is the initial threshold. and These are initialization coefficients. This is the dynamic threshold calculated based on the distance r between the standard pixel and the ISO center.

[0077] In this embodiment, if the difference feature value of the standard pixel does not meet the first preset condition and the edge representation value of the standard pixel does not meet the second preset condition, the mark ring value of the standard pixel is determined to be 1. That is, a dual judgment condition is adopted to determine whether the standard pixel forms a ring artifact, so as to improve the accuracy of the judgment.

[0078] Step S408: Based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel in each standard sector, determine the correction pixel value corresponding to each standard pixel in each standard sector.

[0079] As an optional embodiment, the method described above can be implemented by the following steps: Step S408 determines the correction pixel value corresponding to each standard pixel in each standard sector based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel in each standard sector: For each standard pixel in each standard sector, the formula is used. and formula Two weights are determined for each standard pixel. Each standard pixel's weight corresponds one-to-one with a detector channel of that pixel, indicating the proportion of contribution a standard pixel makes to its corresponding detector channel. A weight for a standard pixel. Another weight for standard pixels, For each standard pixel, the detector channel corresponds to one of the two detector channel position values. The detector channel corresponding to the other detector channel position value among the two detector channel position values ​​for each standard pixel; For any detector channel c in any standard sector q, the formula is used. The first weighted sum of the number of standard pixels on detector channel c of standard sector q that are identified as ring artifacts is determined using the formula. The second weighted sum of the edge feature values ​​of all standard pixels on detector channel c of standard sector q is determined, where, This represents the total number of pixels in the standard sector q. The first sector in standard sector q mapped to detector channel c The marker ring value of a standard pixel, The first sector in standard sector q mapped to detector channel c The weight of each standard pixel in detector channel c, The first sector in standard sector q mapped to detector channel c The edge feature values ​​of a standard pixel are marked with a ring value of 0 to indicate that the pixel is not a standard pixel on the ring artifact, and a ring value of 1 to indicate that the standard pixel is a pixel on the ring artifact. For each detector channel in each standard sector, the ratio of the second weighted sum of the detector channels to the first weighted sum of the detector channels is calculated to obtain the weighted average edge feature value of the detector channels; specifically, the formula is used. Calculate the weighted average edge feature value of the detector channel, where, For the first The weighted average edge feature value of each detector channel. .

[0080] For each standard pixel in each standard sector, the corrected pixel value of the standard pixel is determined based on the two weights of the standard pixel and the weighted average edge feature value of the two detector channels of the standard pixel.

[0081] As an optional embodiment, the method described above further includes: Determine the center distance between the image centers of the standard pixels and the standard CT image; Determine the target correction coefficient corresponding to the standard pixel based on the distance range in which the center distance of the standard pixel is located; The target difference feature value threshold is determined by the product of the preset difference feature value threshold and the target correction coefficient; the target edge feature value threshold is determined by the product of the preset edge feature value threshold and the target correction coefficient.

[0082] As an optional embodiment, as described above, for each standard pixel in each standard sector, the corrected pixel value of the standard pixel is determined based on the two weights of the pixel and the weighted average edge feature value of the two detector channels of the standard pixel, including: Using formula Determine the corrected pixel value for the standard pixel, where, The corrected pixel value for the standard pixel. This is the weighted average edge feature value of a detector channel for a standard pixel in a standard sector. This is the weighted average edge feature value of another detector channel for a pixel in the standard sector.

[0083] As an optional embodiment, the method described above removes annular artifacts in the original CT image by correcting the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the corrected pixel values ​​corresponding to each standard pixel within each standard sector, and by linearly transitioning the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two corrected pixel values ​​corresponding to each standard pixel within the overlapping region of each standard sector. When the original pixel is located in the boundary sector region of its original sector, the formula is used. Determine the target corrected pixel value corresponding to the boundary sector region of the original pixel. ,in, , The azimuth angle of the original pixel. The azimuth angle of the common edge between the boundary sector region and the main sector region of the original sector. The central angle of the boundary sector region. Coordinates are The original pixel corresponds to the corrected pixel value of one of the two original sectors where the boundary sector region is located. Coordinates are The original pixel corresponds to the corrected pixel value of the other original sector among the two original sectors where the boundary sector region is located; further, That is, the angle between the original pixel and the X-axis. This refers to the overlapping boundary angle.

[0084] If the original pixel is located in the main sector area of ​​its original sector, the corrected pixel value of the original pixel is directly used as the target corrected pixel value of the pixel; that is, if the original pixel is located in the main sector area of ​​its original sector, the corrected pixel value of the original pixel is directly updated to its corresponding target corrected pixel value.

[0085] For each original pixel in each original sector, the formula is used. Determine the target pixel value of the original pixel. ,in, Coordinates are The original pixel value of the original pixel. These are radius-based empirical weighting coefficients used to balance the artifact suppression capabilities of regions with different radii. Coordinates are The target corrected pixel value of the original pixel. Specifically, Figure 8(a) is the CT image before correction using the CT image annular artifact removal method of this application, and Figure 8(b) is the CT image after correction using the CT image annular artifact removal method of this application. It can be seen that the annular artifact pointed to by the white arrow in Figure 8(a) has been completely eliminated in Figure 8(b).

[0086] Specifically, Figure 9(a) is a CT image (water model image) before correction using the CT image ring artifact removal method of this application, and Figure 9(b) is a CT image (water model image) after correction using the CT image ring artifact removal method of this application. It can be seen that the ring artifact pointed to by the white arrow in Figure 9(a) has been completely eliminated in Figure 9(b).

[0087] Specifically, Figure 10(a) is a CT image corrected using the CT image ring artifact removal method of this application (but without standardization), and Figure 10(b) is a CT image corrected using the CT image ring artifact removal method of this application (with standardization). It can be seen that a new ring artifact is introduced in Figure 10(a), as indicated by the white arrow, while no new ring artifact is introduced in Figure 10(b).

[0088] According to another aspect of the embodiments of this application, an electronic device is also provided, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; wherein the memory is used to store a computer program; and the processor is used to execute the method steps of any of the above embodiments by running the computer program stored in the memory.

[0089] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to execute the method steps of any of the above embodiments when running.

[0090] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0091] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0092] According to another aspect of the embodiments of this application, a CT image annular artifact removal apparatus for implementing the above-described CT image annular artifact removal method is also provided. Figure 11 This is a structural block diagram of an optional CT image ring artifact removal device according to an embodiment of this application, such as... Figure 11 As shown, the device may include: The normalization module 1101 performs normalization processing on the acquired raw CT image to obtain a standard CT image. The normalization processing is used to unify the gray-scale distribution characteristics under different imaging conditions. The segmentation module 1102 is used to divide a standard CT image into multiple standard sectors according to the target sector segmentation method, and to divide an original CT image into multiple original sectors according to the target sector segmentation method, wherein every two adjacent standard sectors in the multiple standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image. The determination module 1103 is used to determine the correction pixel value corresponding to each standard pixel in each standard sector; The correction module 1104 is used to correct the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and to perform a linear transition on the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, so as to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

[0093] It should be noted that the normalization module 1101 in this embodiment can be used to perform the above step S202, the division module 1102 in this embodiment can be used to perform the above step S204, the determination module 1103 in this embodiment can be used to perform the above step S206, and the correction module 1104 in this embodiment can be used to perform the above step S208.

[0094] In addition to the modules described above, the apparatus in this embodiment may also include modules that perform any method as described in any of the foregoing embodiments of CT image ring artifact removal methods.

[0095] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of a device, can operate in situations such as... Figure 1 The hardware environment shown can be implemented through software or hardware, and the hardware environment includes the network environment.

[0096] According to another aspect of the embodiments of this application, an electronic device for implementing the above-described method for removing ring artifacts in CT images is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0097] According to another embodiment of this application, an electronic device is also provided, comprising: Figure 12 As shown, the electronic device may include: a processor 1501, a communication interface 1502, a memory 1503, and a communication bus 1504, wherein the processor 1501, the communication interface 1502, and the memory 1503 communicate with each other through the communication bus 1504.

[0098] Memory 1503 is used to store computer programs; When processor 1501 executes the program stored in memory 1503, it performs the following steps: Step S202: Normalize the acquired raw CT image to obtain a standard CT image. The normalization process is used to unify the grayscale distribution characteristics under different imaging conditions.

[0099] Step S204: Divide the standard CT image into multiple standard sectors according to the target sector division method, and divide the original CT image into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image.

[0100] Step S206: Determine the correction pixel value corresponding to each standard pixel in each standard sector.

[0101] Step S208 involves correcting the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and linearly transitioning the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, in order to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

[0102] Optionally, in this embodiment, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used to represent it in the figure, but this does not mean that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned electronic device and other devices.

[0103] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0104] As an example, the memory 1503 described above may include, but is not limited to, the normalization module 1101, the partitioning module 1102, the determination module 1103, and the correction module 1104 from the CT image annular artifact removal device described above. Furthermore, it may include, but is not limited to, other module units from the CT image annular artifact removal device described above, which will not be elaborated upon in this example.

[0105] The processor mentioned above can be a general-purpose processor, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0106] This application also provides a computer-readable storage medium, which includes a stored program, wherein the program executes the method steps of the above method embodiments when it runs.

[0107] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, ROMs, RAMs, portable hard drives, magnetic disks, or optical disks.

[0108] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0109] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0110] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0112] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the solution provided in this embodiment, depending on actual needs.

[0113] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0114] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for removing ring artifacts in CT images, characterized in that, include: The acquired raw CT images are normalized to obtain standard CT images, wherein the normalization process is used to unify the gray-scale distribution characteristics under different imaging conditions. According to the target sector division method, the standard CT image is divided into multiple standard sectors, and the original CT image is divided into multiple original sectors according to the target sector division method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image. Determine the correction pixel value corresponding to each standard pixel within each standard sector; The original pixel values ​​of the original pixels in the main sector region of the original CT image are corrected according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and the pixel values ​​of the original pixels in each boundary sector region of the original CT image are linearly transitioned according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, so as to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

2. The method according to claim 1, characterized in that, The normalization process for the acquired raw CT images to obtain standard CT images includes: Filter out original pixels in the original CT image whose pixel values ​​are greater than or equal to a predetermined pixel value; Determine the lower and upper limits of pixel values ​​from all the selected raw pixels; Based on the lower limit and the upper limit of the pixel value, the pixel values ​​of all the selected original pixels are normalized to obtain the normalized pixel corresponding to each selected original pixel. Calculate the standard deviation of the pixel values ​​of all normalized pixels to obtain the target standard deviation; Based on the target standard deviation, the preset mean, and the preset standard deviation, the pixel values ​​of all normalized pixels are standardized to obtain the standard CT image.

3. The method according to claim 1, characterized in that, Determining the corrected pixel value corresponding to each standard pixel within each standard sector includes: For each standard sector, the neighboring pixel difference information corresponding to each standard pixel is determined. For any standard pixel, the neighboring pixel difference information is used to indicate the pixel value difference between the corresponding standard pixel and other adjacent standard pixels. The spatial coordinates of each standard pixel in the standard CT image are mapped to the detector channel array to obtain the detector channel position value corresponding to each standard pixel, wherein the detector channel array is used to capture the original CT image; Based on the neighboring pixel difference information corresponding to each standard pixel in each standard sector, the marker ring value of each standard pixel in each standard sector is determined, wherein the marker ring value is used to indicate whether the corresponding standard pixel is a pixel in the ring artifact; Based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel in each standard sector, the correction pixel value corresponding to each standard pixel in each standard sector is determined.

4. The method according to claim 3, characterized in that, The step of determining the neighboring pixel difference information corresponding to each standard pixel according to each standard sector includes: According to the weighted filter corresponding to each standard sector, the difference feature value of each standard pixel is determined by calculating the difference between each standard pixel in each standard sector and the mean of N neighboring standard pixels in the weighted filter. The neighboring pixel difference information includes the difference feature value, and N is an odd number greater than or equal to 3. According to the weighted filter corresponding to each standard sector, the edge feature value of each standard pixel is determined by calculating N-2 times the difference between the mean of the N-2 center neighboring standard pixels and the mean of the two edge standard pixels in the N neighborhood pixels of the weighted filter of each standard pixel in each standard sector, wherein the neighborhood pixel difference information includes the edge feature value.

5. The method according to claim 3, characterized in that, The step of mapping the spatial coordinates of each standard pixel in the standard CT image to the detector channel array to obtain the detector channel position value corresponding to each standard pixel includes: Determine the spatial coordinates of the standard pixel relative to the image center of the standard CT image; Based on the size of the standard pixel, the distance from the X-ray tube to the rotation center, the distance from the X-ray tube to the detector, the detector channel spacing, and the number of detector channels, the detector channel position value corresponding to the standard pixel is determined.

6. The method according to claim 4, characterized in that, The step of determining the tag ring value of each standard pixel in each standard sector based on the neighboring pixel difference information corresponding to each standard pixel in each standard sector includes: If the difference feature value of the standard pixel satisfies a first preset condition or the edge feature value of the standard pixel satisfies a second preset condition, the mark ring value of the standard pixel is determined to be 0. The first preset condition is that the absolute value of the difference feature value of the standard pixel is greater than the target difference feature value threshold of the standard pixel, and the second preset condition is that the absolute value of the edge feature value of the standard pixel is greater than the target edge feature value threshold of the standard pixel. The mark ring value of 0 is used to indicate that the standard pixel is not a pixel on a ring artifact. If the difference feature value of the standard pixel does not meet the first preset condition and the edge representation value of the standard pixel does not meet the second preset condition, the mark ring value of the standard pixel is determined to be 1. The mark ring value of 1 is used to indicate that the standard pixel is a pixel on a ring artifact.

7. The method according to claim 6, characterized in that, The method further includes: Determine the center distance between the standard pixel and the image center of the standard CT image; The target correction coefficient corresponding to the standard pixel is determined according to the distance range in which the center distance of the standard pixel is located; The target difference feature value threshold is determined based on the product of a preset difference feature value threshold and the target correction coefficient; the target edge feature value threshold is determined based on the product of a preset edge feature value threshold and the target correction coefficient.

8. The method according to claim 4, characterized in that, The step of determining the correction pixel value corresponding to each standard pixel in each standard sector based on the neighboring pixel difference information, detector channel position value, and marker ring value corresponding to each standard pixel in each standard sector includes: For each standard pixel in each standard sector, the formula is used. and formula Two weights are determined for each standard pixel, wherein each weight corresponds one-to-one with a detector channel of the standard pixel, and the weight indicates the proportion of contribution that the standard pixel allocates to the corresponding detector channel. A weight for the standard pixel. This is another weight for the standard pixel. The detector channel is the detector channel corresponding to one of the two detector channel position values ​​for each standard pixel. The detector channel corresponding to the other detector channel position value among the two detector channel position values ​​of each standard pixel; For any detector channel c in any standard sector q, the formula is used. The first weighted sum of the number of standard pixels identified as ring artifacts on the detector channel c of the standard sector q is determined using the formula... The second weighted sum of the edge feature values ​​of all standard pixels on the detector channel c of the standard sector q is determined, wherein, The total number of pixels in the standard sector q. The first sector in the standard sector q mapped to the detector channel c The marker ring value of a standard pixel, The first sector in the standard sector q mapped to the detector channel c The weights of the standard pixels in detector channel c The first sector in the standard sector q mapped to the detector channel c The edge feature values ​​of a standard pixel are defined as follows: a ring value of 0 indicates that the pixel is not a standard pixel on a ring artifact, and a ring value of 1 indicates that the standard pixel is a pixel on a ring artifact. For each detector channel in each standard sector, the ratio of the second weighted sum of the detector channel to the first weighted sum of the detector channel is calculated to obtain the weighted average edge feature value of the detector channel; For each standard pixel in each standard sector, the corrected pixel value of the standard pixel is determined based on the two weights of the standard pixel and the weighted average edge feature value of the two detector channels of the standard pixel.

9. The method according to claim 8, characterized in that, For each standard pixel in each standard sector, determining the corrected pixel value of the standard pixel based on the two weights of the pixel and the weighted average edge feature value of the two detector channels of the standard pixel includes: Using formula Determine the corrected pixel value of the standard pixel, wherein, The corrected pixel value for the standard pixel. The weighted average edge feature value of one detector channel of the standard pixel in the standard sector. The weighted average edge feature value of the pixel in the standard sector is the value of another detector channel.

10. The method according to claim 9, characterized in that, The step of correcting the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel value corresponding to each standard pixel in each standard sector, and performing a linear transition on the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, in order to remove the ring artifacts in the original CT image, includes: When the original pixel is located in the boundary sector region of its original sector, the formula is used. Determine the target corrected pixel value corresponding to the boundary sector region of the original pixel. ,in, , The azimuth angle of the original pixel. The azimuth angle of the common edge between the boundary sector region and the main sector region of the original sector. The central angle of the boundary sector region, Coordinates are The original pixel corresponds to the corrected pixel value of one of the two original sectors where the boundary sector region is located. Coordinates are The original pixel corresponds to the corrected pixel value of the other original sector among the two original sectors where the boundary sector region is located; When the original pixel is located in the main sector region of the original sector, the corrected pixel value of the original pixel is directly used as the target corrected pixel value of the original pixel. For each original pixel in each of the original sectors, the formula is used. Determine the target pixel value of the original pixel. ,in, Coordinates are The original pixel value of the original pixel. For radius-based empirical weighting coefficients, Coordinates are The target correction pixel value of the original pixel. In other words, after determining the target correction pixel value corresponding to each original pixel, it can be obtained using the above formula. The corrected target pixel value is calculated.

11. A device for removing ring artifacts in CT images, characterized in that, include: The normalization module performs normalization processing on the acquired raw CT image to obtain a standard CT image, wherein the normalization processing is used to unify the gray-scale distribution characteristics under different imaging conditions. The segmentation module is used to divide the standard CT image into multiple standard sectors according to the target sector segmentation method, and to divide the original CT image into multiple original sectors according to the target sector segmentation method, wherein every two adjacent standard sectors have an overlapping area, and the vertex of each standard sector is the rotation center of the standard CT image. The determination module is used to determine the correction pixel value corresponding to each standard pixel in each standard sector; The correction module is used to correct the original pixel values ​​of the original pixels in the main sector region of the original CT image according to the correction pixel values ​​corresponding to each standard pixel in each standard sector, and to perform a linear transition on the pixel values ​​of the original pixels in each boundary sector region of the original CT image according to the two correction pixel values ​​corresponding to each standard pixel in the overlapping region of each standard sector, so as to remove the ring artifacts in the original CT image. The boundary sector region is the overlapping region with other original sectors in the original sector, and the main sector region is the region that does not overlap with other original sectors in the original sector.

12. An electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein, The processor, the communication interface, and the memory communicate with each other via the communication bus, characterized in that... The memory is used to store computer programs; The processor is configured to perform the method of any one of claims 1 to 10 by running the computer program stored in the memory.

13. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 10 when run on a processor.

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