Method, device, system and storage medium for processing ring artifact of ct image

Abstract

This invention provides a method, apparatus, system, and storage medium for processing ring artifacts in CT images, belonging to the field of image processing technology. The method includes: acquiring an original CT image; performing a first filtering process on the original CT image to extract ring artifact images; performing a first transformation process on the ring artifact images to obtain a first ring artifact transformed image, and performing a second filtering process on the first ring artifact transformed image to obtain a second ring artifact transformed image; performing a second transformation process on the second ring artifact transformed image to obtain a third ring artifact transformed image, the second transformation process being the reverse of the first transformation process; and performing image subtraction between the original CT image and the third ring artifact transformed image to obtain a target CT image that does not contain ring artifacts. This invention effectively improves the accuracy of ring artifact processing, obtains higher quality artifact-free images, preserves image edges completely, and has a high signal-to-noise ratio.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and specifically to a method for processing ring artifacts in CT images, a device for processing ring artifacts in CT images, a system for processing ring artifacts in CT images, and a machine-readable storage medium. Background Technology

[0002] In geological image analysis, CT (Computed Tomography) electron microscopy is a common method for lithological detection. Due to factors such as detector pixel defects, X-ray intensity receiver errors, and the instrument's nonlinear response to the X-ray energy spectrum, ring artifacts often appear in CT images. These ring artifacts closely overlap with the image of the sample being examined, appearing as a series of concentric circles with varying radii centered on the image center. The presence of ring artifacts significantly degrades image quality, greatly hindering further processing and analysis such as image measurement, recognition, noise reduction, and image segmentation. Industrial CT scans containing ring artifacts directly impact the accurate diagnosis of lithological analysis. Summary of the Invention

[0003] The purpose of this invention is to provide a method, apparatus, system, and storage medium for processing ring artifacts in CT images, in order to solve the above-mentioned problems.

[0004] To achieve the above objectives, in a first aspect of the present invention, a method for processing ring artifacts in CT images is provided, comprising:

[0005] Acquire raw CT images with ring artifacts;

[0006] The original CT image is subjected to a first filtering process to extract the ring artifact image from the original CT image;

[0007] The ring artifact image is subjected to a first transformation process to obtain a first ring artifact transformed image, and the first ring artifact transformed image is subjected to a second filtering process to obtain a second ring artifact transformed image.

[0008] The second transformation process is performed on the second ring artifact transformed image to obtain the third ring artifact transformed image. The second transformation process is the reverse process of the first transformation process.

[0009] The original CT image and the third ring artifact transformed image are subjected to image subtraction to obtain a target CT image that does not include the ring artifact.

[0010] Optionally, the first filtering process is a non-local mean filtering process; performing the first filtering process on the original CT image to extract the ring artifact image in the original CT image includes:

[0011] The original CT image is subjected to nonlocal mean filtering to obtain a background image that does not include ring artifacts;

[0012] The original CT image is subtracted from the background image to obtain the ring artifact image in the original CT image.

[0013] Optionally, the first transformation process is a polar coordinate transformation; performing the first transformation process on the annular artifact image to obtain a first annular artifact transformed image includes:

[0014] The pixel of the ring artifact image is transformed into polar coordinates, converting the rectangular coordinates of each pixel into polar coordinates in a polar coordinate system with the same center point as the origin.

[0015] Based on the polar coordinates, each pixel of the annular artifact image is configured in the polar coordinate system to convert the annular artifact image into a strip artifact image, and the resulting strip artifact image is used as the first annular artifact converted image.

[0016] Optionally, the first annular artifact transformed image is subjected to a second filtering process to obtain a second annular artifact transformed image, including:

[0017] Construct a one-dimensional filter along the horizontal axis of the polar coordinate system, wherein the convolution kernel matrix of the one-dimensional filter has a size of n×m;

[0018] Using the one-dimensional filter, Gaussian low-pass filtering is applied sequentially to each pixel in the first annular artifact transformation image along the horizontal axis of the polar coordinate system, and the resulting blurred strip artifact image is used as the second annular artifact transformation image.

[0019] Optionally, constructing a one-dimensional filter along the horizontal axis of the polar coordinate system includes:

[0020] Obtain the width of the strip artifact in the first ring artifact transformed image. When the width of the strip artifact is less than the threshold, determine n to be 3.

[0021] Optionally, the second transformation process is a rectangular coordinate transformation; the second transformation process is applied to the second annular artifact transformed image to obtain a third annular artifact transformed image, including:

[0022] The pixels of the second ring artifact transformed image are transformed into rectangular coordinates, converting the polar coordinates of each pixel into rectangular coordinates in the rectangular coordinate system.

[0023] Based on the Cartesian coordinates, each pixel of the second ring artifact transformed image is configured in the Cartesian coordinate system to transform the blurred strip artifact image into a blurred ring artifact image, and the resulting blurred ring artifact image is used as the third ring artifact transformed image.

[0024] In a second aspect of the invention, an apparatus for processing ring artifacts in CT images is provided, comprising:

[0025] The data acquisition module is configured to acquire raw CT images with ring artifacts;

[0026] The image processing module is configured to perform a first filtering process on the original CT image to extract the ring artifact image from the original CT image;

[0027] The first image conversion module is configured to perform a first conversion process on the ring artifact image to obtain a first ring artifact converted image, and to perform a second filtering process on the first ring artifact converted image to obtain a second ring artifact converted image.

[0028] The second image conversion module is configured to perform a second conversion process on the second ring artifact converted image to obtain a third ring artifact converted image, wherein the second conversion process is the reverse process of the first conversion process;

[0029] The artifact removal module is configured to perform image subtraction processing on the original CT image and the third ring artifact transformed image to obtain a target CT image that does not include the ring artifact.

[0030] In a third aspect of the invention, a system for processing ring artifacts in CT images is provided, comprising:

[0031] CT scanning equipment is used to perform CT scans on a target to acquire raw CT images; and

[0032] The above-mentioned device for processing ring artifacts in CT images.

[0033] In a fourth aspect of the invention, an electronic device is provided, comprising:

[0034] Memory, which stores computer-readable instructions;

[0035] The processor is configured to read computer-readable instructions stored in memory to execute the above-described method for processing ring artifacts in CT images.

[0036] In a fifth aspect of the invention, a machine-readable storage medium is provided, on which instructions are stored, which, when executed by a processor, cause the processor to be configured to perform the above-described method for processing ring artifacts in CT images.

[0037] The above-mentioned technical solution of the present invention transforms the ring artifacts in the rectangular coordinate system into strip artifacts in the polar coordinate system through coordinate transformation. Then, it smooths and blurs the image through Gaussian low-pass filtering. Next, it uses coordinate transformation to convert the strip artifacts into a blurred ring artifact image. Finally, it subtracts the processed blurred ring artifact image from the original ring artifact image to obtain the image with the ring artifacts removed. The present invention effectively improves the accuracy of ring artifact processing, corrects the original CT scan image more thoroughly, and can obtain a higher quality artifact-free image. The corrected artifact-free image has intact edges and a high signal-to-noise ratio.

[0038] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0039] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0040] Figure 1 This is a schematic diagram of the application environment provided by a preferred embodiment of the present invention;

[0041] Figure 2 This is a flowchart of a method for processing ring artifacts in CT images provided in a preferred embodiment of the present invention;

[0042] Figure 3 This is a schematic block diagram of a CT image ring artifact processing device provided in a preferred embodiment of the present invention;

[0043] Figure 4 This is a schematic block diagram of a CT image ring artifact processing system provided in a preferred embodiment of the present invention;

[0044] Figure 5 This is a schematic diagram of an electronic device provided in a preferred embodiment of the present invention. Detailed Implementation

[0045] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0046] like Figure 1The diagram illustrates an application environment for this embodiment, which includes a CT scanning device 110, a network 120, and a computer device 130. The network 120 can be a communication medium of various connection types capable of providing a communication link between the terminal device 110 and the server 130, such as a wired or wireless communication link. The computer device 130 can be a server, server cluster, or other device with computing capabilities, and is not specifically limited here.

[0047] The CT scanning device 110 is used to perform CT scans on target objects to obtain CT scan images. For example, in lithological analysis, a core sample is CT scanned to obtain a CT scan image of the core sample, which is then analyzed to achieve the analysis of the core sample. The CT scanning device 110 scans the target object with X-rays at a certain thickness, and the X-rays passing through the target object are received by a detector. Since the target object is composed of multiple material components with different densities, the absorption coefficient of X-rays at different points in the target object is different. Therefore, the CT scan image of the target object can be formed by calculating the attenuation coefficient (or absorption coefficient) of the X-rays in each pixel received by the detector. During this process, ring artifacts may appear in the CT scan image due to factors such as defects in the detector pixels, errors in the X-ray intensity receiving elements, and the nonlinear response of the instrument to the X-ray energy spectrum.

[0048] Computer device 130 acquires CT scan images from CT scanning device 110 and performs filtering, coordinate transformation, and other processing on the CT scan images to remove ring artifacts and obtain clear CT scan images. Thus, the application environment formed by CT scanning device 110 and computer device 130 can remove ring artifacts from CT scan images, thereby improving the analysis quality of CT scan images.

[0049] like Figure 2 As shown, in a first aspect of this embodiment, a method for processing ring artifacts in CT images is provided, applied to a computer device 130, the method comprising:

[0050] S100. Acquire the raw CT image with ring artifacts;

[0051] S200. Perform a first filtering process on the original CT image to extract the ring artifact image from the original CT image;

[0052] S300. Perform a first transformation process on the ring artifact image to obtain a first ring artifact transformed image, and perform a second filtering process on the first ring artifact transformed image to obtain a second ring artifact transformed image.

[0053] S400. Perform a second transformation process on the second ring artifact transformed image to obtain a third ring artifact transformed image. The second transformation process is the reverse process of the first transformation process.

[0054] S500: Perform image subtraction on the original CT image and the converted image of the third ring artifact to obtain the target CT image that does not include the ring artifact.

[0055] Thus, this embodiment transforms the ring artifacts in the Cartesian coordinate system into strip artifacts in the polar coordinate system using coordinate transformation. Then, Gaussian low-pass filtering is applied to smooth and blur the image. Next, coordinate transformation is used to convert the strip artifacts into a blurred ring artifact image. Finally, the original ring artifact image is subtracted from the processed blurred ring artifact image to obtain the image with the ring artifacts removed. This invention effectively improves the accuracy of ring artifact processing, provides more thorough correction of the original CT scan image, and yields a higher quality artifact-free image. The corrected artifact-free image retains complete edges and has a high signal-to-noise ratio.

[0056] In step S100, the original CT image is obtained by scanning the target object using a CT scanning device 110. Since the original CT image is a digital image formed based on the absorption or attenuation coefficient of X-rays at various points in the target object, it is often affected by factors such as defects in the CT scanning device 110, resulting in ring artifacts. These ring artifacts are either due to the difference between the reconstructed data in the CT image and the actual attenuation coefficient of the target object, or they may be images displayed in the CT image that do not exist in the target object at all. The presence of ring artifacts makes it difficult for the CT image to reflect the true influence of the target object; therefore, the original CT scan image needs to be processed to remove the ring artifacts.

[0057] In step S200, the first filtering process is a non-local mean filtering process; the original CT image is subjected to the first filtering process to extract the ring artifact image in the original CT image, including:

[0058] S210. Perform nonlocal mean filtering on the original CT image to obtain a background image that does not include ring artifacts.

[0059] S220. Perform image subtraction on the original CT image and the background image to obtain the ring artifact image in the original CT image.

[0060] Specifically, the first filtering process on the original CT image is to separate the background image from the ring artifacts in order to extract the ring artifacts from the original CT image and form a ring artifact image.

[0061] In one specific embodiment of this method, the first filtering process can employ Non-Local Means (NLM) filtering to filter the original CT image. NLM is an improved filtering algorithm based on traditional neighborhood filtering methods. It considers the self-similarity of images, fully utilizes redundant information in the image, and preserves image details to the greatest extent possible while denoising. The background image of the original CT image can be obtained using NLM. Then, image subtraction is performed between the original CT image and the background image. By subtracting the background image from the original CT image, the ring artifacts can be extracted, resulting in a ring artifact image.

[0062] Specifically, the nonlocal mean filtering algorithm needs to calculate the similarity between all pixels in the image and the current pixel. Considering the computational cost and efficiency, two fixed-size windows are usually set: a large search window (D×D) and a small neighborhood window (d×d). The neighborhood window slides within the search window, and the influence of the corresponding center pixel on the current pixel, i.e., the weight, is determined based on the similarity between neighbors.

[0063] In this embodiment, let the size of the original CT image be M*N, and denote the original CT image as f = {f(i) | i ∈ Ω}, where Ω is the image region in the original CT image, and f(i) represents the gray value of pixel i in the original CT image. The calculation method of the nonlocal mean filtering algorithm is as follows:

[0064]

[0065]

[0066]

[0067] in, denoted as pixel value i after nonlocal homogeneous filtering; w(i,j) represents the weight assigned to the original CT image f(i); a is the standard deviation of the Gaussian kernel function. Using a Gaussian kernel to convolve image blocks can reduce the impact of noise on distance calculation and highlight the role of the image block center on the pixel; d(i,j) represents the weighted distance between two image blocks; N(i) and N(j) represent image blocks with pixel center i and pixel center j, respectively; h is the filtering parameter controlling the smoothness; I represents the search area centered on pixel i.

[0068] In this embodiment, the nonlocal mean filtering process incorporates the weight value of each pixel in the calculation, which ensures that the mutual influence between adjacent and significantly different pixels is reduced when averaging within the box. This allows for better preservation of image edge details, effectively improving image clarity and resulting in better image quality.

[0069] In step S300, the first transformation process is a polar coordinate transformation; the first transformation process is performed on the annular artifact image to obtain a first annular artifact transformed image, including:

[0070] S310. Perform polar coordinate transformation on each pixel of the ring artifact image, converting the rectangular coordinates of each pixel into polar coordinates in a polar coordinate system with the same center point as the origin.

[0071] S320. Based on polar coordinates, each pixel of the ring artifact image is configured in the polar coordinate system to convert the ring artifact image into a strip artifact image, and the resulting strip artifact image is used as the first ring artifact converted image.

[0072] Ring artifact images are images in a rectangular coordinate system, which appear as multiple concentric circles. To make the calculation more convenient, this implementation first performs a polar coordinate transformation on the ring artifact image, converting the ring artifact image from a rectangular coordinate system to a polar coordinate system, so as to transform the ring artifact into a strip artifact, also known as a linear artifact.

[0073] Specifically, the polar coordinate system includes a horizontal axis θ and a vertical axis ρ. The horizontal axis θ ranges from 0 to 2π, and the vertical axis ρ ranges from 0 to 2π. Where M and N are the original CT image dimensions. To avoid losing image information, when determining the pixel values ​​of each point in the image in the polar coordinate system, the annular artifact image is not directly transformed. Instead, the rectangular coordinates are first mapped to polar coordinates. The mapping method is the transformation relationship between the polar coordinate system and the rectangular coordinate system. For a point (x, y) in the rectangular coordinate system, its corresponding polar coordinates are (θ, ρ), and the transformation relationship is:

[0074]

[0075] After polar coordinate transformation, the annular artifact appears as a straight line parallel to the horizontal axis θ of the polar coordinate system. Thus, the annular artifact is transformed into a stripe artifact, resulting in a stripe artifact image.

[0076] In this embodiment, the pixel values ​​of each pixel in the circular artifact image in the polar coordinate system are determined by bilinear interpolation, thereby converting the circular artifact image into a strip artifact image.

[0077] Bilinear interpolation, also known as bilinear interpolation, is a linear interpolation extension of an interpolation function with two variables. Its core idea is to perform linear interpolation in two directions separately. By using bilinear interpolation to determine the pixel values ​​of each pixel in the ring artifact image in the polar coordinate system, a strip artifact image is obtained. In this embodiment, by first performing coordinate system mapping and then using bilinear interpolation to transform the ring artifact image into a strip artifact image, information loss during image conversion is effectively reduced. The image quality after magnification using the bilinear interpolation algorithm is high, and there are no discontinuous pixel values.

[0078] In step S300, the first ring artifact transformed image is subjected to a second filtering process to obtain a second ring artifact transformed image, including:

[0079] Construct a one-dimensional filter in the horizontal direction of the polar coordinate system. The size of the convolution kernel matrix of the one-dimensional filter is n×m.

[0080] Using a one-dimensional filter, Gaussian low-pass filtering is applied sequentially to each pixel in the first annular artifact transformation image along the horizontal axis of the polar coordinate system, and the resulting blurred strip artifact image is used as the second annular artifact transformation image.

[0081] Specifically, digital images are often affected by noise interference from imaging equipment and the external environment during their formation, transmission, and storage, resulting in noisy images. Noise affects image quality, making post-processing difficult. To remove interference signals from the stripe artifact image, i.e., to remove image noise, this embodiment also performs a second filtering process on the stripe artifact image. Since noise removal actually removes some noise information from the stripe artifact image, it is equivalent to a certain degree of information loss in the stripe artifact image. Therefore, the image after denoising will be blurry compared to the image before denoising; that is, the image obtained after the second filtering process is a blurred stripe artifact image.

[0082] Typically, the second filtering process can employ appropriate filters for denoising, such as mean filters, adaptive Wiener filters, median filters, morphological noise filters, wavelet denoising, etc. In a specific embodiment of this application, the second filtering process uses Gaussian filtering for denoising. Gaussian filtering is a process of weighted averaging across the entire image; the value of each pixel is obtained by weighted averaging of its own value and the values ​​of other pixels in its neighborhood. Specifically, Gaussian filtering involves scanning each pixel in the image with a convolution kernel of a set size, and replacing the gray value of the pixel at the center of the convolution kernel with the weighted average gray value of the pixels in the neighborhood defined by the convolution kernel.

[0083] In one specific embodiment of this method, a one-dimensional Gaussian low-pass filter is used to denoise the stripe artifact image. First, a one-dimensional filter is constructed along the horizontal axis θ of the polar coordinate system, and the matrix size of the convolution kernel is set to n×m (n is the number of rows in the convolution kernel matrix, and m is the number of columns). The matrix size of the convolution kernel is related to the width of the stripe artifact; the wider the stripe artifact, the larger the matrix size of the convolution kernel should be. In this embodiment, when the width of the stripe artifact is less than a threshold, n ≤ 3, preferably n = 3. Then, the convolution kernel moves along the horizontal axis θ, scanning each pixel in the stripe artifact image. The value G(x) of the center pixel of the convolution kernel is obtained by weighted averaging of its own value and the values ​​of other pixels in its neighborhood, calculated as follows:

[0084]

[0085] Where σ is the standard deviation, also known as the Gaussian radius. 2 Indicates variance.

[0086] Once the convolution kernel has scanned all pixels in the stripe artifact image, image denoising is complete, resulting in a blurred stripe artifact image. The blurred stripe artifact image obtained after denoising using this embodiment exhibits significantly improved image smoothness while effectively reducing noise.

[0087] In step S400, the second transformation process is a rectangular coordinate transformation; the second transformation process is applied to the second annular artifact transformed image to obtain the third annular artifact transformed image, including:

[0088] S410. Perform a rectangular coordinate transformation on each pixel of the second ring artifact transformed image, converting the polar coordinates of each pixel into rectangular coordinates in the rectangular coordinate system.

[0089] S420. Based on rectangular coordinates, each pixel of the second annular artifact transformation image is configured in a rectangular coordinate system to transform the blurred strip artifact image into a blurred annular artifact image, and the resulting blurred annular artifact image is used as the third annular artifact transformation image.

[0090] Since the obtained blurred stripe artifact image is in polar coordinates, it needs to be transformed into a Cartesian coordinate system to obtain a blurred ring artifact image. In the Cartesian coordinate system, the artifacts in the blurred ring artifact image also appear as ring artifacts. The inverse process of converting Cartesian coordinates to polar coordinates is as follows: For a point (θ, ρ) in the polar coordinate system, its corresponding Cartesian coordinates are (x, y). The formula for the inverse polar coordinate transformation is shown below:

[0091]

[0092] The above steps completely extract the ring artifacts from the original CT image. In step S500, the original CT image and the blurred ring artifact image are subtracted. By subtracting the blurred ring artifact image from the original CT image, the ring artifacts in the original CT image can be removed, and the artifact-free CT image can be obtained.

[0093] This implementation starts with the edge characteristics of annular artifacts, separating them through nonlocal mean filtering and polar coordinate transformation. The annular artifact in the Cartesian coordinate system is transformed into a linear artifact in the polar coordinate system using coordinate transformation. Then, a one-dimensional Gaussian low-pass filter is applied to smooth and blur the image. The processed image is obtained by subtracting the original annular artifact image from the processed image, thus improving the accuracy of annular artifact processing and providing a more thorough correction of the original CT scan image. This results in a high-quality artifact-free image with well-preserved edges and a high signal-to-noise ratio.

[0094] like Figure 3 As shown, in a second aspect of the present invention, an apparatus for processing ring artifacts in CT images is provided, comprising:

[0095] The data acquisition module is configured to acquire raw CT images with ring artifacts;

[0096] The image processing module is configured to perform a first filtering process on the original CT image to extract the ring artifact image from the original CT image;

[0097] The first image conversion module is configured to perform a first conversion process on the ring artifact image to obtain a first ring artifact converted image, and to perform a second filtering process on the first ring artifact converted image to obtain a second ring artifact converted image.

[0098] The second image conversion module is configured to perform a second conversion process on the second ring artifact converted image to obtain a third ring artifact converted image. The second conversion process is the reverse process of the first conversion process.

[0099] The artifact removal module is configured to perform image subtraction on the original CT image and the third ring artifact transformed image to obtain a target CT image that does not include the ring artifact.

[0100] like Figure 4 As shown, in a third aspect of the present invention, a system for processing ring artifacts in CT images is provided, comprising:

[0101] CT scanning equipment is used to perform CT scans on a target to acquire raw CT images; and

[0102] The above-mentioned device for processing ring artifacts in CT images.

[0103] like Figure 5 As shown, in a fourth aspect of the present invention, an electronic device is provided, comprising:

[0104] Memory, which stores computer-readable instructions;

[0105] The processor is configured to read computer-readable instructions stored in memory to execute the above-described method for processing ring artifacts in CT images.

[0106] in, Figure 5 The electronic device 600 shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this application. Figure 5 As shown, the electronic device 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 602 or programs loaded from storage section 608 into random access memory (RAM). The RAM 603 also stores various programs and data required for system operation. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output interface 605 (I / O interface) is also connected to the bus 604.

[0107] The following components are connected to the input / output interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a local area network card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0108] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by central processing unit 601, it performs various functions defined in the system of this application.

[0109] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the method according to the embodiments of this application.

[0110] In a fifth aspect of the invention, a machine-readable storage medium is provided, on which instructions are stored, which, when executed by a processor, cause the processor to be configured to perform the above-described method for processing ring artifacts in CT images.

[0111] Machine-readable storage media include both permanent and non-permanent, removable and non-removable media, which can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0112] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0113] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0114] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0115] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0116] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.

[0117] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.

[0118] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, and should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for processing ring artifacts in CT images, characterized in that, include: Acquire raw CT images with ring artifacts; The original CT image is subjected to a first filtering process to extract the ring artifact image from the original CT image; The ring artifact image is subjected to a first transformation process to obtain a first ring artifact transformed image, and the first ring artifact transformed image is subjected to a second filtering process to obtain a second ring artifact transformed image. The second transformation process is performed on the second ring artifact transformed image to obtain the third ring artifact transformed image. The second transformation process is the reverse process of the first transformation process. The original CT image and the third ring artifact transformed image are subjected to image subtraction to obtain a target CT image that does not include the ring artifact.

2. The method for processing ring artifacts in CT images according to claim 1, characterized in that, The first filtering process is a non-local mean filtering process; The original CT image is subjected to a first filtering process to extract the ring artifact image from the original CT image, including: The original CT image is subjected to nonlocal mean filtering to obtain a background image that does not include ring artifacts; The original CT image is subtracted from the background image to obtain the ring artifact image in the original CT image.

3. The method for processing ring artifacts in CT images according to claim 1, characterized in that, The first transformation process is a polar coordinate transformation; The first transformation process is performed on the ring artifact image to obtain a first ring artifact transformed image, including: The pixel of the ring artifact image is transformed into polar coordinates, converting the rectangular coordinates of each pixel into polar coordinates in a polar coordinate system with the same center point as the origin. Based on the polar coordinates, each pixel of the annular artifact image is configured in the polar coordinate system to convert the annular artifact image into a strip artifact image, and the resulting strip artifact image is used as the first annular artifact converted image.

4. The method for processing ring artifacts in CT images according to claim 3, characterized in that, The first ring artifact transformed image is subjected to a second filtering process to obtain a second ring artifact transformed image, including: Construct a one-dimensional filter along the horizontal axis of the polar coordinate system, wherein the convolution kernel matrix of the one-dimensional filter has a size of n×m; Using the one-dimensional filter, Gaussian low-pass filtering is applied sequentially to each pixel in the first annular artifact transformation image along the horizontal axis of the polar coordinate system, and the resulting blurred strip artifact image is used as the second annular artifact transformation image.

5. The method for processing ring artifacts in CT images according to claim 4, characterized in that, Constructing a one-dimensional filter along the horizontal axis of the polar coordinate system includes: Obtain the width of the strip artifact in the first ring artifact transformed image. When the width of the strip artifact is less than the threshold, determine n to be 3.

6. The method for processing ring artifacts in CT images according to claim 4, characterized in that, The second transformation is a rectangular coordinate transformation; The second transformation process is applied to the second ring artifact transformed image to obtain the third ring artifact transformed image, including: The pixels of the second ring artifact transformed image are transformed into rectangular coordinates, converting the polar coordinates of each pixel into rectangular coordinates in the rectangular coordinate system. Based on the Cartesian coordinates, each pixel of the second ring artifact transformed image is configured in the Cartesian coordinate system to transform the blurred strip artifact image into a blurred ring artifact image, and the resulting blurred ring artifact image is used as the third ring artifact transformed image.

7. A device for processing ring artifacts in CT images, characterized in that, include: The data acquisition module is configured to acquire raw CT images with ring artifacts; The image processing module is configured to perform a first filtering process on the original CT image to extract the ring artifact image from the original CT image; The first image conversion module is configured to perform a first conversion process on the ring artifact image to obtain a first ring artifact converted image, and to perform a second filtering process on the first ring artifact converted image to obtain a second ring artifact converted image. The second image conversion module is configured to perform a second conversion process on the second ring artifact converted image to obtain a third ring artifact converted image, wherein the second conversion process is the reverse process of the first conversion process; The artifact removal module is configured to perform image subtraction processing on the original CT image and the third ring artifact transformed image to obtain a target CT image that does not include the ring artifact.

8. A system for processing ring artifacts in CT images, characterized in that, include: CT scanning equipment is used to perform CT scans on a target to acquire raw CT images; as well as The apparatus for processing ring artifacts in CT images as described in claim 7.

9. An electronic device, characterized in that, include: Memory, which stores computer-readable instructions; The processor is configured to read computer-readable instructions stored in memory to perform the method for processing CT image ring artifacts as described in any one of claims 1 to 6.

10. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform the method for processing CT image ring artifacts as described in any one of claims 1 to 6.

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