Ring artifact correction method, system, electronic device, storage medium and chip

Abstract

The application provides a circular artifact correction method, system, electronic equipment, storage medium and chip, the correction method comprises: determining an original image; coordinate conversion is carried out to the original image in the range of its circumscribed circle, and a polar coordinate image is determined; the polar coordinate image is circumferentially projected to obtain a projection curve, the first gradient of the pixel point on the projection curve is calculated, and the artifact where the pixel point is located is a thick ring if the first gradient is greater than a first threshold value; the polar coordinate image is filtered to remove the thick ring and obtain a first correction image; the second gradient of the pixel point on the first correction image is calculated, and the artifact where the pixel point is located is a thin ring if the second gradient is greater than a second threshold value and not greater than the first threshold value, and the first threshold value is greater than the second threshold value; the first correction image is filtered to remove the thin ring and obtain a second correction image; coordinate conversion is carried out to the second correction image in the range of its circumscribed circle, and a rectangular coordinate system image is obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical image correction, in particular to a method for correcting ring artifacts of adaptive medical images, a system for correcting ring artifacts of adaptive medical images, an electronic device, a computer readable storage medium and a chip. BACKGROUND

[0002] Factors such as inconsistent detector channel responses and data acquisition system failures can cause ring artifacts in CT images. Ring artifacts appear as alternating light and dark lines in the projection sinogram, which seriously affects the accuracy of CT detection.

[0003] In related technologies, there are two types of correction methods for ring artifacts. The first type is a correction method based on reconstructed images, and the second type is a correction method based on projection sinograms. The latter has many limitations, such as difficulty in threshold selection, many uncertain parameters, and the risk of incomplete correction. Therefore, the first type of correction method is used more frequently. The correction method based on reconstructed images converts the circular ring in the rectangular coordinate system to a straight line in the polar coordinate system, and then uses filtering to smooth the CT image in the polar coordinate system to filter out the straight line. Finally, the polar coordinate image without the straight line is converted back to the rectangular coordinate image.

[0004] In the process of implementing the present application, the inventors found that the first type of correction method in related technologies has at least the following problems: it cannot be targeted to distinguish and process artifacts with obvious differences in gradient values, the correction effect is poor, and the adaptive ability of the algorithm, i.e., the ability to automatically adjust the processing method, is low. SUMMARY

[0005] To solve or improve at least one of the above technical problems, one object of the present application is to provide a method for correcting ring artifacts of adaptive medical images.

[0006] Another object of the present application is to provide a system for correcting ring artifacts of adaptive medical images.

[0007] Another object of the present application is to provide an electronic device.

[0008] Another object of the present application is to provide a computer readable storage medium.

[0009] Another object of the present application is to provide a chip.

[0010] To achieve the above objectives, the first aspect of the present invention provides an adaptive method for correcting ring artifacts in medical images, comprising: determining an original image; performing coordinate transformation on the original image within its circumcircle to determine a polar coordinate image, wherein ring artifacts in the original image are converted into straight line artifacts in the polar coordinate image; performing circumferential projection on the polar coordinate image to obtain a projection curve, calculating a first gradient of a pixel on the projection curve, wherein if the first gradient is greater than a first threshold, the artifact at the pixel is a coarse ring; filtering out the coarse rings from the polar coordinate image to obtain a first corrected image; calculating a second gradient of a pixel on the first corrected image, wherein if the second gradient is greater than a second threshold but not greater than the first threshold, the artifact at the pixel is a thin ring, wherein the first threshold is greater than the second threshold; filtering out the thin rings from the first corrected image to obtain a second corrected image; and performing coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate system image.

[0011] According to an embodiment of the adaptive medical image ring artifact correction method provided by the present invention, coordinate transformation is performed on the original image or the second corrected image within its circumcircle, which can effectively avoid image processing blind spots. Furthermore, the rings (ring artifacts) are divided into coarse and fine rings based on the image pixel gradient values, facilitating targeted filtering of both in subsequent steps. Filtering out coarse and fine rings sequentially improves the correction effect. In the smoothing stage, the present invention achieves adaptive smoothing; the smoothing intensity can be controlled according to relevant constraints for both coarse and fine rings, ensuring the correction effect while minimizing image information loss. The correction method defined by the present invention has a high degree of adaptability, i.e., the ability to automatically adjust the processing method.

[0012] An adaptive method for correcting ring artifacts in medical images is used to correct ring artifacts in medical images. The specific steps include:

[0013] The first step is to determine the original image. The original image is a medical image in a Cartesian coordinate system. Factors such as inconsistent detector channel response and data acquisition system malfunctions can cause ring artifacts in the original image. Optionally, the original image is a CT image;

[0014] Secondly, the original image is converted in the range of its circumscribed circle to determine the polar coordinate image, and the ring-shaped artifact in the original image is converted into a straight line artifact in the polar coordinate image.

[0015] Thirdly, the polar coordinate image is projected in the circumferential direction to obtain a projection curve, and the first gradient of the pixel point on the projection curve is calculated, and if the first gradient is greater than a first threshold value, the artifact where the pixel point is located is a thick ring. The image under the polar coordinate system is projected in the circumferential direction to obtain a projection curve, the abscissa of the projection curve corresponds to the radius, and the ordinate of the projection curve corresponds to the pixel value. The first gradient of the pixel point on the projection curve is calculated, and the gradient can be understood as the rate of change of the pixel value. The greater the gradient value is, the greater the rate of change of the pixel value is. Further, the first gradient is compared with the first threshold value and a second threshold value, if the first gradient is greater than the first threshold value, the pixel point is on the artifact and the artifact where the pixel point is located is a thick ring; if the first gradient is greater than the second threshold value and not greater than the first threshold value, the pixel point is on the artifact and the artifact where the pixel point is located is a thin ring; if the first gradient is not greater than the second threshold value, the pixel point is not on the artifact. In the technical solution defined in the application, the circular ring (ring-shaped artifact) is divided into thick and thin rings according to the image pixel gradient value, which facilitates the subsequent step of targeted filtering treatment of the two rings;

[0016] Fourthly, the polar coordinate image is filtered to remove the thick ring and obtain a first corrected image. The purpose of this step is to remove the thick ring by targeted measures to obtain the first corrected image. Specifically, the smooth spline function (smooth spline interpolation function) is used to fit the projection curve data to obtain low-frequency information. The projection curve data here refers to the first gradient. The difference between the projection data and the low-frequency data is obtained to obtain a high-frequency straight line artifact, and the straight line artifact is copied along the circumferential direction to obtain an image containing only the straight line artifact. The polar coordinate image is subtracted from the straight line artifact image to obtain the first corrected image under the polar coordinate system. Optionally, for the thick ring, the polar coordinate image is projected in the circumferential direction to obtain a projection curve, and the smooth spline function combined with the ring strength parameter (maximum directional derivative of the ring position segment) is used to adaptively smooth the projection data. The influence area of the correction method is controlled by adjusting the size of the radial extension of the ring, which can produce a smooth transition effect and obtain a better correction result;

[0017] The fifth step is to calculate the second gradient of the pixels in the first corrected image. If the second gradient is greater than the second threshold but not greater than the first threshold, the artifact containing the pixel is a thin ring, and the first threshold is greater than the second threshold. The pixel is further compared with the second threshold to determine whether it is on an artifact. Specifically, if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on an artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on an artifact. The thin ring here includes the coarse ring processed in the previous steps. In the technical solution defined by this invention, the circular ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, facilitating targeted filtering of the two in subsequent steps.

[0018] Step 6: Filter out the fine rings from the first corrected image to obtain the second corrected image. The purpose of this step is to remove the fine rings using targeted measures to obtain the corrected image. Specifically, the corresponding sigma is determined based on the image pixel gradient values. The variance is calculated, and sigma is substituted into the Gaussian function to generate the necessary smoothing coefficients. A sigma-gradient function is designed and applied to a five-point cubic smoothing filter. The first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The difference between the first corrected image and the smoothed image is calculated to generate a basic loop image. The average pixel value of each row in the basic loop image is calculated, and the average value is used to cover the pixel values ​​at the broken lines to generate a connected loop image. Straight lines in the connected loop image are filtered out using a comb filter to obtain a line-free image; the line-free image is subtracted from the first corrected image to obtain a second corrected image.

[0019] Step 7: Perform coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate image. The second corrected image is in polar coordinates. By drawing a circumcircle around the second corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar to rectangular coordinates, thus determining the rectangular coordinate image. This rectangular coordinate image is the medical image with the annular artifacts removed. Performing coordinate transformation on the second corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0020] In the technical solution defined in the present application, the coordinate conversion is performed on the original image or the second corrected image within the range of the circumscribed circle, which can effectively avoid the image processing blind area. In addition, the annular ring (annular artifact) is divided into coarse and fine rings according to the image pixel gradient value, which facilitates the subsequent step of applying targeted filtering processing to the two rings, and the coarse ring and the fine ring in the annular artifact are filtered out in sequence, which is beneficial to improve the correction effect. In the smoothing stage, the present application can achieve an adaptive smoothing effect. Whether it is a coarse ring or a fine ring, the smoothing strength can be controlled according to the relevant constraint conditions to ensure the correction effect while reducing the loss of image information. The adaptive ability of the correction method defined in the present application, that is, the ability to automatically adjust the processing method, is relatively high.

[0021] In addition, the above technical solution provided by the present application can further have the following additional technical features:

[0022] In the above technical solution, the steps further include: after the coordinate conversion of the original image within the range of the circumscribed circle and the determination of the polar coordinate image, the third gradient of the pixel point of the polar coordinate image in the y direction is calculated, and it is judged whether the third gradient is greater than the second threshold value. If yes, the pixel point belongs to the straight line artifact, and if not, the pixel point does not belong to the straight line artifact.

[0023] In the technical solution, after the coordinate conversion of the original image and the determination of the polar coordinate image, the steps of the adaptive medical image annular artifact correction method further include:

[0024] The third gradient of the pixel point of the polar coordinate image in the y direction is calculated, and it is judged whether the third gradient is greater than the second threshold value. If yes, the pixel point belongs to the straight line artifact, and if not, the pixel point does not belong to the straight line artifact. By comparing the third gradient with the second threshold value, it is determined whether the pixel point is on the straight line artifact. The greater the gradient value, the greater the rate of change of the pixel value. When the third gradient is greater than the second threshold value, the pixel point is on the straight line artifact; when the third gradient is not greater than the second threshold value, the pixel point is not on the straight line artifact.

[0025] In the technical scheme, the polar coordinate image is filtered to remove coarse rings and obtain a first corrected image, which comprises: determining the interval of two adjacent straight line artifacts, judging whether the interval is less than a third threshold, if yes, the two adjacent straight line artifacts are same position segment artifacts, if not, the two adjacent straight line artifacts are different position segment artifacts, and the maximum third gradient in the same position segment artifact is taken as a ring strength parameter; determining a smoothness parameter according to the ring strength parameter; substituting the smoothness parameter into a smooth spline interpolation function, fitting the first gradient by using the smooth spline interpolation function to smooth the projection curve and obtain low frequency information; subtracting the low frequency information from the first gradient to obtain high frequency straight line artifacts, copying the high frequency straight line artifacts along the circumferential direction to obtain a straight line artifact image; and subtracting the straight line artifact image from the polar coordinate image to obtain a corrected image.

[0026] In the technical scheme, the polar coordinate image is filtered to remove coarse rings and obtain a first corrected image, and the specific steps comprise:

[0027] Determining the interval of two adjacent straight line artifacts, judging whether the interval is less than a third threshold, if yes, the two adjacent straight line artifacts are same position segment artifacts, if not, the two adjacent straight line artifacts are different position segment artifacts, and the maximum third gradient in the same position segment artifact is taken as a ring strength parameter. Under the premise that the positions of each straight line artifact are determined by comparing the third gradient with the second threshold, whether the interval of adjacent straight line artifacts is less than the third threshold is judged, the artifacts are divided into different position segments, and the maximum gradient value of each position segment is calculated as a ring strength parameter. The smoothness of the subsequent fitting step depends on the ring strength parameter. By judging whether the interval of adjacent straight line artifacts is less than the third threshold, the artifacts are divided into different position segments, and the maximum gradient value of each position segment is calculated as a ring strength parameter. The smoothness of the subsequent fitting step depends on the ring strength parameter;

[0028] Determining a smoothness parameter according to the ring strength parameter. The ring strength parameter and the smoothness parameter satisfy the following relationship:

[0029] ,

[0030] wherein, , are two pairs of control points of the ring strength parameter and the smoothness parameter , which can control the shape of the curve. Under the premise that the ring strength parameter is known, the smoothness parameter can be obtained from the functional relationship;

[0031] The smoothness parameter is substituted into the smooth spline interpolation function, and the first gradient is fitted by using the smooth spline interpolation function to smooth the projection curve and obtain low-frequency information. The projection curve data can be understood as the first gradient, and the smooth spline function is used to fit the projection curve data to smooth the low-frequency information;

[0032] The first gradient is subtracted from the low-frequency information to obtain a high-frequency straight line artifact, and the high-frequency straight line artifact is copied along its circumferential direction to obtain a straight line artifact image;

[0033] The polar coordinate image is subtracted from the straight line artifact image to obtain a corrected image. Optionally, for the coarse ring, the polar coordinate image is projected circumferentially to obtain a projection curve, and then the smooth spline function combined with the ring position segment maximum directional derivative is used to adaptively smooth the projection data. By adjusting the ring radial extension size to control the influence area of the correction method, a smooth transition effect can be produced to obtain a better correction result.

[0034] In the above technical solution, the first corrected image is filtered to remove the fine ring and obtain a second corrected image, including: determining a gradient parameter; determining a variance according to the gradient parameter; substituting the variance into a Gaussian function to obtain a smoothing coefficient, and applying the smoothing coefficient to a five-point cubic smoothing filter; smoothing the polar coordinate image by the five-point cubic smoothing filter to generate a smoothed image; subtracting the polar coordinate image from the smoothed image to generate a basic ring image; calculating the average value of each row of pixel values in the basic ring image, and covering the pixel values at the broken line with the average value to generate a connected ring image; performing cubic spline interpolation on the connected ring image to increase the sampling rate, and obtaining a new connected ring image; using a comb filter to filter out straight lines in the new connected ring image to obtain a line-removed image; and subtracting the line-removed image from the polar coordinate image to obtain a corrected image.

[0035] In this technical solution, the first corrected image is filtered to remove the fine ring and obtain a second corrected image, and the specific steps include:

[0036] Determine the gradient parameter. Calculate the third gradient of the pixel points of the polar coordinate image in the y direction and the fourth gradient in the x direction. Take the minimum value of the third gradient and the fourth gradient as the gradient parameter;

[0037] Determine the variance according to the gradient parameter. The variance satisfies the following variance-gradient function (sigma-gradient function) relationship:

[0038] ,

[0039] wherein, ​The control factor is used to adjust the concave-convex degree of the curve. The variance can be obtained from the functional relationship under the premise of known gradient parameter.

[0040] The variance is substituted into the Gaussian function to obtain a smoothing coefficient, and the smoothing coefficient is applied to the five-point cubic smoothing filter. The smoothing filter is a spatial domain filtering technique for low-frequency enhancement. The smoothing filter in the spatial domain is generally performed by using a simple average method to obtain the average brightness value of the adjacent pixel points. Alternatively, the variance and the smoothing coefficient satisfy a Gaussian function relationship, and the smoothing coefficient is 5 symmetrical parameters;

[0041] The first corrected image is smoothed by the five-point cubic smoothing filter to generate a smoothed image. The purpose of this step is to smooth the image;

[0042] The first corrected image and the smoothed image are subtracted to generate a basic ring image;

[0043] The average value of each row of pixel values in the basic ring image is calculated, and the average value is used to cover the pixel values at the broken line to generate a connected ring image. By covering the average value of each row of pixel values with the pixel values at the broken line, the correction effect is improved;

[0044] The connected ring image is subjected to cubic spline interpolation to increase the sampling rate, and a new connected ring image is obtained. By cubic spline interpolation, the sampling rate is increased, and the correction effect is improved;

[0045] A comb filter is used to filter out straight lines in the new connected ring image to obtain a line-removed image;

[0046] The first corrected image is subtracted from the line-removed image to obtain a second corrected image.

[0047] In the above technical solution, it further includes: while calculating the third gradient of the pixel point of the polar coordinate image in the y direction, calculating the fourth gradient of the pixel point of the polar coordinate image in the x direction; determining the gradient parameter, specifically: taking the minimum value of the third gradient and the fourth gradient as the gradient parameter.

[0048] In this technical solution, while calculating the third gradient of the pixel point of the polar coordinate image in the y direction, the adaptive medical image ring artifact correction method further includes the following steps:

[0049] Calculating the fourth gradient of the pixel point of the polar coordinate image in the x direction. The rate of change of the pixel value of the pixel point in the x direction is calculated.

[0050] On this basis, the gradient parameter is determined, specifically:

[0051] Taking the minimum value of the third gradient and the fourth gradient as the gradient parameter. By calculating and comparing multiple sets of data, the accuracy of the correction result is improved.

[0052] In the above technical solution, filtering out the fine loops from the first corrected image to obtain the second corrected image further includes: using a comb filter to filter out the straight lines in the image after connecting the loops to obtain the line-removed image, then performing cubic spline interpolation on the line-removed image to obtain the final line-removed image; subtracting the line-removed image from the first corrected image to obtain the second corrected image, specifically: subtracting the final line-removed image from the first corrected image to obtain the second corrected image.

[0053] In this technical solution, after obtaining the de-lined image and before obtaining the corrected image, the specific steps of filtering out the fine rings from the first corrected image and obtaining the second corrected image further include:

[0054] The final image with lines removed is obtained by performing cubic spline interpolation on the image. This cubic spline interpolation yields a more accurate image with lines removed, which improves the correction effect.

[0055] Based on this, the second corrected image is obtained by subtracting the delineated image from the first corrected image. The specific steps are as follows:

[0056] The second corrected image is obtained by subtracting the final de-lined image from the first corrected image. The second corrected image is more accurate by subtracting the first corrected image from the final de-lined image, which helps improve the correction effect.

[0057] A second aspect of the present invention provides an adaptive medical image ring artifact correction system, comprising: a reading unit for reading and determining an original image; a first coordinate transformation unit for performing coordinate transformation on the original image within its circumcircle to obtain a polar coordinate image; a first calculation unit for calculating the third gradient of a pixel in the polar coordinate image in the y-direction; a first judgment unit for judging whether the third gradient is greater than a second threshold, if so, the pixel belongs to a straight line artifact, otherwise the pixel does not belong to a straight line artifact; a processing unit for performing circumferential projection on the polar coordinate image to obtain a projection curve; a second calculation unit for calculating the first gradient of a pixel on the projection curve; a second judgment unit for judging whether the first gradient is greater than a first threshold, if so, the artifact where the pixel is located is a coarse ring, otherwise the artifact where the pixel is located is a fine ring, the first threshold being greater than the second threshold; a first correction unit for smoothing low-frequency information using a smooth spline interpolation function, filtering out coarse rings and obtaining a corrected image; a second correction unit for filtering out fine rings using a comb filter and obtaining a corrected image; and a second coordinate transformation unit for performing coordinate transformation on the corrected image within its circumcircle to obtain a rectangular coordinate system image.

[0058] According to an embodiment of the adaptive medical image ring artifact correction system of the present invention, the adaptive medical image ring artifact correction system includes a reading unit, a first coordinate transformation unit, a processing unit, a first calculation unit, a first judgment unit, a first correction unit, a second calculation unit, a second judgment unit, a second correction unit, and a second coordinate transformation unit. Specifically, the reading unit is used to read and determine the original image. The original image is a medical image in a rectangular coordinate system. Factors such as inconsistent detector channel response and data acquisition system failure can cause ring artifacts in the original image. Optionally, the original image is a CT image. Further, the first coordinate transformation unit is used to perform coordinate transformation on the original image within its circumcircle to obtain a polar coordinate image. A circumcircle is drawn for the original image, and coordinate transformation is performed on the original image within the circumcircle, converting it from the previous rectangular coordinate system to a polar coordinate system to determine the polar coordinate image. The ring artifacts in the original image are converted into straight line artifacts in the polar coordinate image, which facilitates the study of parameters such as the position, spacing, and gradient value of the artifacts. In the technical solution defined by the present invention, performing coordinate transformation on the original image within its circumcircle can effectively avoid the occurrence of image processing blind spots. The adaptive ring artifact correction method can automatically adjust the smoothing intensity in the edge and non-edge regions of medical images, ensuring the correction effect while enhancing the image visibility.

[0059] Further, the processing unit performs circumferential projection on the polar coordinate image to obtain a projection curve. The horizontal coordinate of the projection curve corresponds to the radius, and the vertical coordinate corresponds to the pixel value. The first calculation unit calculates the first gradient of the pixel on the projection curve. The gradient can be understood as the rate of change of the pixel value. The larger the gradient value, the greater the rate of change of the pixel value. Further, the first judgment unit determines whether the first gradient is greater than a first threshold. If the first gradient is greater than the first threshold, the pixel artifact is a coarse ring. Further, the first correction unit filters out the coarse ring from the polar coordinate image to obtain the first corrected image. Targeted measures are used to remove the coarse ring to obtain the first corrected image. Specifically, the smoothspline function is used to fit the projection curve data to smooth low-frequency information. Here, the projection curve data refers to the first gradient. The difference between the projection data and the low-frequency data is used to obtain the high-frequency straight line artifact, which is then copied circumferentially to obtain an image containing only the straight line artifact. The straight line artifact image is subtracted from the polar coordinate image to obtain the first corrected image in the polar coordinate system. Optionally, for coarse rings, the polar coordinate image is circumferentially projected to obtain the projection curve, and then the projection data is adaptively smoothed using a smooth spline function that incorporates the ring strength parameter (the maximum directional derivative of the ring position segment). By adjusting the size of the ring's radial extension, the area affected by the correction method can be controlled, resulting in a smooth transition and better correction results.

[0060] Furthermore, the second calculation unit is used to calculate the second gradient of the pixels on the first corrected image. The second judgment unit is used to determine whether the second gradient is greater than a second threshold, where the first threshold is greater than the second threshold. If the second gradient is greater than the second threshold but not greater than the first threshold, the artifact where the pixel is located is a thin ring. Given that the gradient value is greater than the second threshold, the gradient value is compared with the first threshold to divide the ring (ring artifact) into two types: coarse and thin rings, facilitating targeted filtering of the two types in subsequent steps.

[0061] Furthermore, the second correction unit is used to filter out the fine rings from the first corrected image to obtain the second corrected image. Targeted measures are used to remove the fine rings to obtain the second corrected image. Specifically, the corresponding sigma is determined based on the image pixel gradient values. The variance is calculated, and sigma is substituted into the Gaussian function to generate the necessary smoothing coefficients. A sigma-gradient function is designed and applied to a five-point cubic smoothing filter. The first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The difference between the first corrected image and the smoothed image is calculated to generate a basic loop image. The average pixel value of each row in the basic loop image is calculated, and the average value is used to cover the pixel values ​​at the broken lines to generate a connected loop image. Straight lines in the connected loop image are filtered out using a comb filter to obtain a line-free image; the line-free image is subtracted from the first corrected image to obtain the second corrected image.

[0062] Furthermore, the second coordinate transformation unit performs coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate system image. The second corrected image is in polar coordinates. By drawing a circumcircle around the second corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar to rectangular coordinates, thus determining the rectangular coordinate system image. This rectangular coordinate system image is a medical image with the annular artifacts removed. Performing coordinate transformation on the second corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0063] In the technical solution defined in this invention, coordinate transformation is performed on the original image or the second corrected image within its circumcircle, effectively avoiding blind spots in image processing. Furthermore, the annular artifacts (ring-shaped artifacts) are divided into coarse and fine rings based on the image pixel gradient values, facilitating targeted filtering of both in subsequent steps. Filtering out the coarse and fine rings sequentially improves the correction effect. During the smoothing stage, this invention achieves adaptive smoothing; the smoothing intensity can be controlled according to relevant constraints for both coarse and fine rings, ensuring the correction effect while minimizing image information loss.

[0064] A third aspect of the present invention provides an electronic device, including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein when the program or instructions are executed by the processor, the steps of the adaptive medical image ring artifact correction method in any of the above embodiments are implemented.

[0065] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the adaptive medical image ring artifact correction method in any of the above embodiments.

[0066] The fifth aspect of the present invention provides a chip including a processor and a communication interface, the communication interface and the processor being coupled, the processor being used to run a program or instructions to implement the steps of the adaptive medical image ring artifact correction method in any of the above embodiments.

[0067] Additional aspects and advantages of embodiments of the present invention will become apparent in the following description or may be learned by practice of the invention. Attached Figure Description

[0068] Figure 1 A first flowchart of an adaptive medical image ring artifact correction method according to an embodiment of the present invention is shown;

[0069] Figure 2 A second flowchart of an adaptive medical image ring artifact correction method according to an embodiment of the present invention is shown;

[0070] Figure 3 A third flowchart of an adaptive medical image ring artifact correction method according to an embodiment of the present invention is shown;

[0071] Figure 4 A schematic diagram of an adaptive medical image ring artifact correction system according to an embodiment of the present invention is shown.

[0072] in, Figure 4 The correspondence between the reference numerals and component names in the attached drawings is as follows:

[0073] 400: Adaptive medical image ring artifact correction system; 410: Reading unit; 421: First coordinate transformation unit; 422: Second coordinate transformation unit; 431: First calculation unit; 432: Second calculation unit; 441: First judgment unit; 442: Second judgment unit; 450: Processing unit; 461: First correction unit; 462: Second correction unit. Detailed Implementation

[0074] To better understand the above-described objectives, features, and advantages of the embodiments of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0075] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, embodiments of the invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of this application is not limited to the specific embodiments disclosed below.

[0076] The following reference Figures 1 to 4 This invention describes a method for correcting ring artifacts in adaptive medical images, a system for correcting ring artifacts in adaptive medical images, an electronic device, a computer-readable storage medium, and a chip, all provided according to some embodiments of the invention.

[0077] Example 1

[0078] like Figure 1 As shown, an embodiment of the present invention provides an adaptive medical image ring artifact correction method for correcting ring artifacts in medical images. The specific method steps include:

[0079] S102, Determine the original image. The original image is a medical image in a Cartesian coordinate system. Factors such as inconsistent detector channel response and data acquisition system malfunctions can cause ring artifacts in the original image. Optionally, the original image is a CT image;

[0080] S104, the original image is subjected to coordinate transformation within its circumcircle to determine a polar coordinate image. The annular artifacts in the original image are converted into linear artifacts in the polar coordinate image. A circumcircle is drawn around the original image, and coordinate transformation is performed within this circumcircle, converting it from a Cartesian coordinate system to a polar coordinate system to determine the polar coordinate image. The conversion of annular artifacts in the original image into linear artifacts in the polar coordinate image facilitates the study of parameters such as the position, spacing, and gradient values ​​of the artifacts. In the technical solution defined in this invention, performing coordinate transformation within the circumcircle of the original image effectively avoids image processing blind spots. The adaptive annular artifact correction method can automatically adjust the smoothing intensity in the edge and non-edge regions of medical images, ensuring the correction effect while enhancing image visibility.

[0081] S106, circumferentially project the polar coordinate image to obtain a projection curve, calculate the first gradient of the pixel on the projection curve. If the first gradient is greater than a first threshold, the artifact where the pixel is located is a coarse ring. The image in polar coordinates is circumferentially projected to obtain the projection curve, where the horizontal coordinate corresponds to the radius and the vertical coordinate corresponds to the pixel value. The first gradient of the pixel on the projection curve is calculated; the gradient can be understood as the rate of change of the pixel value. The larger the gradient value, the greater the rate of change of the pixel value. Further, the first gradient is compared with a first threshold and a second threshold. If the first gradient is greater than the first threshold, the pixel is on an artifact and the artifact it is on is a coarse ring; if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on an artifact and the artifact it is on is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on an artifact. In the technical solution defined in this invention, the ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, facilitating targeted filtering of the two in subsequent steps.

[0082] S108, Filter out coarse rings from the polar coordinate image to obtain the first corrected image. The purpose of this step is to remove coarse rings using targeted measures to obtain the corrected image. Specifically, the smooth spline function is used to fit the projection curve data to obtain low-frequency information. Here, the projection curve data refers to the first gradient. Subtract the projection data from the low-frequency data to obtain high-frequency line artifacts, and then copy them circumferentially to obtain an image containing only line artifacts. Subtract the line artifact image from the polar coordinate image to obtain the first corrected image in the polar coordinate system. Optionally, for coarse rings, the polar coordinate image is circumferentially projected to obtain the projection curve, and then the smooth spline function combined with the ring strength parameter (the maximum directional derivative of the ring position segment) is used to adaptively smooth the projection data. By adjusting the size of the ring radial extension, the area affected by the correction method can be controlled, resulting in a smooth transition effect and a better correction result.

[0083] S110, calculate the second gradient of the pixel on the first corrected image. If the second gradient is greater than a second threshold but not greater than a first threshold, the artifact containing the pixel is a thin ring. The first threshold is greater than the second threshold. By further comparing the gradient value with the second threshold, it is determined whether the pixel is on an artifact. Specifically, if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on an artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on an artifact. The thin ring here includes the coarse ring processed in the above steps. In the technical solution defined by this invention, the circular ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, which facilitates the subsequent steps to apply targeted filtering processing to the two.

[0084] S112, the fine rings are filtered out from the first corrected image to obtain the second corrected image. The purpose of this step is to remove the fine rings using targeted measures to obtain the corrected image. Specifically, the corresponding sigma is determined based on the image pixel gradient values. The variance is calculated, and sigma is substituted into the Gaussian function to generate the necessary smoothing coefficients. A sigma-gradient function is designed and applied to a five-point cubic smoothing filter. The first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The difference between the first corrected image and the smoothed image is calculated to generate a basic loop image. The average pixel value of each row in the basic loop image is calculated, and the average value is used to cover the pixel values ​​at the broken lines to generate a connected loop image. Straight lines in the connected loop image are filtered out using a comb filter to obtain a line-free image; the line-free image is subtracted from the first corrected image to obtain a second corrected image.

[0085] S114, perform coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate image. The second corrected image is in polar coordinates. By drawing a circumcircle on the second corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar to rectangular coordinates, thus determining the rectangular coordinate image. This rectangular coordinate image is a medical image with the annular artifacts removed. Performing coordinate transformation on the second corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0086] In the technical solution defined in this invention, coordinate transformation is performed on the original image or the second corrected image within its circumcircle, effectively avoiding image processing blind spots. Furthermore, the annular artifacts (ring-shaped artifacts) are divided into coarse and fine rings based on the image pixel gradient values, facilitating targeted filtering of both in subsequent steps. Filtering out the coarse and fine rings sequentially improves the correction effect. During the smoothing stage, this invention achieves adaptive smoothing; the smoothing intensity can be controlled according to relevant constraints for both coarse and fine rings, ensuring the correction effect while minimizing image information loss. The correction method defined in this invention has a high degree of adaptability, i.e., the ability to automatically adjust the processing method.

[0087] Example 2

[0088] like Figure 2 As shown, an embodiment of the present invention provides an adaptive medical image ring artifact correction method for correcting ring artifacts in medical images. The specific method steps include:

[0089] S202, Determine the original image. The original image is a medical image in a Cartesian coordinate system. Factors such as inconsistent detector channel response and data acquisition system malfunctions can cause ring artifacts in the original image. Optionally, the original image is a CT image;

[0090] S204, the original image is subjected to coordinate transformation within its circumcircle to determine the polar coordinate image. The annular artifacts in the original image are converted into linear artifacts in the polar coordinate image. A circumcircle is drawn around the original image, and coordinate transformation is performed within this circumcircle, converting the original image from a Cartesian coordinate system to a polar coordinate system to determine the polar coordinate image. The conversion of annular artifacts in the original image into linear artifacts in the polar coordinate image facilitates the study of parameters such as the position, spacing, and gradient values ​​of the artifacts. In the technical solution defined in this invention, performing coordinate transformation within the circumcircle of the original image effectively avoids image processing blind spots. The adaptive annular artifact correction method can automatically adjust the smoothing intensity in the edge and non-edge regions of medical images, ensuring the correction effect while enhancing image visibility.

[0091] S206, Calculate the third gradient of a pixel in the polar coordinate image in the y-direction;

[0092] It should be noted that the y-direction here can be understood as the axial dimension in a Cartesian coordinate system.

[0093] S208, determine if the third gradient is greater than the second threshold. By comparing the third gradient with the second threshold, determine if the pixel is on a straight line artifact. The gradient can be understood as the rate of change of pixel value. The larger the gradient value, the greater the rate of change of pixel value;

[0094] S210, if so, the pixel belongs to the line artifact. When the third gradient is greater than the second threshold, the pixel is on the line artifact;

[0095] S212, otherwise the pixel does not belong to the line artifact. When the third gradient is not greater than the second threshold, the pixel is not on the line artifact;

[0096] S214, a circumferential projection is performed on the polar coordinate image to obtain a projection curve. The first gradient of each pixel on the projection curve is calculated. If the first gradient is greater than a first threshold, the artifact containing the pixel is a coarse ring. The image in polar coordinates is circumferentially projected to obtain the projection curve. The horizontal coordinate of the projection curve corresponds to the radius, and the vertical coordinate corresponds to the pixel value. Further, the first gradient is compared with the first threshold and the second threshold. If the first gradient is greater than the first threshold, the pixel is on the artifact and the artifact it contains is a coarse ring; if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on the artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on the artifact. In the technical solution defined in this invention, the ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, which facilitates targeted filtering of the two in subsequent steps.

[0097] S216, Determine the ring strength parameter. By determining whether the distance between adjacent line artifacts is less than a third threshold, the artifacts are divided into different position segments. Simultaneously, the maximum gradient value of each position segment is calculated as the ring strength parameter. The smoothness of the fitting in subsequent steps depends on the ring strength parameter.

[0098] S218, Determine the smoothness parameter based on the ring strength parameter. The ring strength parameter and the smoothness parameter satisfy a functional relationship; given the ring strength parameter, the smoothness parameter can be obtained from this functional relationship.

[0099] S220: Substitute the smoothness parameter into the smooth spline interpolation function, and use the smooth spline interpolation function to fit the first gradient to smooth the projection curve and obtain low-frequency information. The smooth spline function is used to fit the projection curve data to smooth the low-frequency information; the projection curve data here can be understood as the first gradient.

[0100] S222, the first gradient is subtracted from the low-frequency information to obtain the high-frequency line artifact, and the high-frequency line artifact is copied along its circumference to obtain the line artifact image.

[0101] S224, subtract the straight-line artifact image from the polar coordinate image to obtain the first corrected image. Optionally, for a thick ring, the polar coordinate image is circumferentially projected to obtain a projection curve, and then the projection data is adaptively smoothed using a smooth spline function that incorporates the ring strength parameter (the maximum directional derivative of the ring position segment). By adjusting the size of the ring's radial extension, the area affected by the correction method can be controlled, resulting in a smooth transition and better correction results.

[0102] S226, calculate the second gradient of the pixel on the first corrected image. If the second gradient is greater than a second threshold but not greater than a first threshold, the artifact containing the pixel is a thin ring. The first threshold is greater than the second threshold. By further comparing the gradient value with the second threshold, it is determined whether the pixel is on an artifact. Specifically, if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on an artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on an artifact. The thin ring here includes the coarse ring processed in the above steps. In the technical solution defined by this invention, the ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, which facilitates the subsequent steps to apply targeted filtering processing to the two.

[0103] S228, Determine the gradient parameters. Calculate the third gradient of the pixel in the polar coordinate image in the y-direction and the fourth gradient in the x-direction. Take the minimum value between the third and fourth gradients as the gradient parameters;

[0104] S230, the variance is determined based on the gradient parameters. and gradient parameters If the variance gradient function (sigma-gradient function) relationship is satisfied, the variance can be obtained from the functional relationship given the gradient parameters;

[0105] S232, the smoothing coefficients are determined based on the variance and applied to the five-point cubic smoothing filter. Smoothing filtering is a spatial domain filtering technique for low-frequency enhancement. Spatial domain smoothing filtering generally uses a simple averaging method to calculate the average brightness value of neighboring pixels. Optionally, the variance and smoothing coefficients satisfy a Gaussian function relationship, and the smoothing coefficients are five symmetrical parameters;

[0106] S234, the first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The purpose of this step is to smooth the image;

[0107] S236, Subtract the first corrected image from the smoothed image to generate a basic ring image;

[0108] S238, calculate the average pixel value of each row in the basic loop image, and use the average value to cover the pixel value at the break point to generate the connected loop image. Covering the pixel value at the break point with the average pixel value of each row helps to improve the correction effect;

[0109] S240, use a comb filter to filter out straight lines in the image after connecting the loops to obtain a line-free image;

[0110] S242, Subtract the delineated image from the first corrected image to obtain the second corrected image;

[0111] S244, the second corrected image is subjected to coordinate transformation within its circumcircle to obtain a rectangular coordinate system image. The second corrected image is in polar coordinates. By drawing a circumcircle around the second corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar coordinates to rectangular coordinates, thus determining the rectangular coordinate system image. This rectangular coordinate system image is a medical image with the annular artifacts removed. Performing coordinate transformation on the second corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0112] Example 3

[0113] like Figure 3 As shown, an embodiment of the present invention provides an adaptive medical image ring artifact correction method for correcting ring artifacts in medical images. The specific method steps include:

[0114] S302, Determine the original image. The original image is a medical image in a Cartesian coordinate system. Factors such as inconsistent detector channel response and data acquisition system malfunctions can cause ring artifacts in the original image. Optionally, the original image is a CT image;

[0115] S304, the original image is subjected to coordinate transformation within its circumcircle to determine the polar coordinate image. The annular artifacts in the original image are converted into linear artifacts in the polar coordinate image. A circumcircle is drawn around the original image, and coordinate transformation is performed within this circumcircle, converting the original image from a Cartesian coordinate system to a polar coordinate system to determine the polar coordinate image. The conversion of annular artifacts in the original image into linear artifacts in the polar coordinate image facilitates the study of parameters such as the position, spacing, and gradient values ​​of the artifacts. In the technical solution defined in this invention, performing coordinate transformation on the original image within its circumcircle effectively avoids image processing blind spots. The adaptive annular artifact correction method can automatically adjust the smoothing intensity in the edge and non-edge regions of medical images, ensuring the correction effect while enhancing image visibility.

[0116] S306, calculate the third gradient of the pixel in the polar coordinate image along the y-direction; S308, determine if the third gradient is greater than the second threshold. By comparing the third gradient with the second threshold, it is determined whether the pixel is on a straight line artifact. The gradient can be understood as the rate of change of the pixel value. The larger the gradient value, the greater the rate of change of the pixel value;

[0117] S310, if so, the pixel belongs to the line artifact. When the third gradient is greater than the second threshold, the pixel is on the line artifact;

[0118] S312, otherwise the pixel does not belong to the line artifact. When the third gradient is not greater than the second threshold, the pixel is not on the line artifact;

[0119] S314, a circumferential projection is performed on the polar coordinate image to obtain a projection curve. The first gradient of each pixel on the projection curve is calculated. If the first gradient is greater than a first threshold, the artifact containing the pixel is a coarse ring. The image in the polar coordinate system is circumferentially projected to obtain the projection curve. The horizontal coordinate of the projection curve corresponds to the radius, and the vertical coordinate of the projection curve corresponds to the pixel value. Further, the first gradient is compared with the first threshold and the second threshold. If the first gradient is greater than the first threshold, the pixel is on the artifact and the artifact it contains is a coarse ring; if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on the artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on the artifact. In the technical solution defined by this invention, the ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, which facilitates the subsequent steps to apply targeted filtering processing to the two types of rings.

[0120] S316, determines the spacing between two adjacent line artifacts;

[0121] S318, determine whether the spacing is less than the third threshold;

[0122] S320, if so, then two adjacent line artifacts are artifacts of the same position segment;

[0123] S322, otherwise the two adjacent line artifacts are artifacts of different position segments;

[0124] S324: The largest third gradient among artifacts at the same location segment is used as the loop strength parameter. After determining the position of each line artifact by comparing the third gradient with the second threshold, it is determined whether the distance between adjacent line artifacts is less than the third threshold. The artifacts are then divided into different location segments, and the maximum gradient value of each location segment is calculated as the loop strength parameter. The smoothness of the fitting in subsequent steps depends on the loop strength parameter.

[0125] S326, determine the smoothness parameter based on the ring strength parameter. Ring strength parameter and smoothness parameters The following functional relationship is satisfied:

[0126] ,

[0127] in, , These are control points for two pairs of loop strength parameters and smoothness parameters. The curve shape can be controlled. Given the ring strength parameter, the smoothness parameter can be obtained from a functional relationship.

[0128] S328, the smoothness parameter is substituted into the smooth spline interpolation function, and the first gradient is fitted using the smooth spline interpolation function to smooth the projection curve and obtain low-frequency information. The smooth spline function is used to fit the projection curve data to smooth the low-frequency information; the projection curve data here can be understood as the first gradient.

[0129] S330, the first gradient is subtracted from the low-frequency information to obtain the high-frequency line artifact, and the high-frequency line artifact is copied along its circumference to obtain the line artifact image.

[0130] S332, subtract the straight-line artifact image from the polar coordinate image to obtain the first corrected image. Optionally, for a thick ring, the polar coordinate image is circumferentially projected to obtain a projection curve, and then the projection data is adaptively smoothed using a smooth spline function that incorporates the ring strength parameter (the maximum directional derivative of the ring position segment). By adjusting the size of the ring's radial extension, the area affected by the correction method can be controlled, resulting in a smooth transition and better correction results.

[0131] S334, calculate the second gradient of the pixel on the first corrected image. If the second gradient is greater than a second threshold but not greater than a first threshold, the artifact containing the pixel is a thin ring. The first threshold is greater than the second threshold. By further comparing the gradient value with the second threshold, it is determined whether the pixel is on an artifact. Specifically, if the first gradient is greater than the second threshold but not greater than the first threshold, the pixel is on an artifact and the artifact it contains is a thin ring; if the first gradient is not greater than the second threshold, the pixel is not on an artifact. The thin ring here includes the coarse ring processed in the above steps. In the technical solution defined by this invention, the ring (ring-shaped artifact) is divided into coarse and thin rings according to the image pixel gradient value, which facilitates the subsequent steps to apply targeted filtering processing to the two.

[0132] S336, Determine the gradient parameters. Calculate the third gradient of the pixel in the polar coordinate image in the y-direction and the fourth gradient in the x-direction. Take the minimum of the third and fourth gradients as the gradient parameters;

[0133] It should be noted that the x and y directions here can be understood as the axial dimensions in a Cartesian coordinate system.

[0134] S338, determine the variance based on the gradient parameters. With gradient parameters It satisfies the following variance gradient function (sigma-gradient function) relationship:

[0135] ,

[0136] in, This is a control factor used to adjust the convexity or concavity of the curve. Given the gradient parameters, the variance can be obtained from the functional relationship.

[0137] S340, substitute the variance into the Gaussian function to obtain the smoothing coefficient, and apply the smoothing coefficient to the five-point cubic smoothing filter. Determine the corresponding sigma based on the image pixel gradient values. The variance is calculated by substituting sigma into a Gaussian function to generate the necessary smoothing coefficients. Smoothing filtering is a spatial domain filtering technique that enhances low frequencies. Spatial domain smoothing filtering generally uses a simple averaging method to calculate the average brightness value of neighboring pixels. Optionally, the variance and smoothing coefficients satisfy a Gaussian function relationship, and the smoothing coefficients are five symmetrical parameters.

[0138] S342, the first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The purpose of this step is to smooth the image;

[0139] S344, Subtract the first corrected image from the smoothed image to generate a basic loop image;

[0140] S346, calculate the average pixel value of each row in the basic loop image, and use the average value to cover the pixel value at the break point to generate the connected loop image. Covering the pixel value at the break point with the average pixel value of each row helps to improve the correction effect;

[0141] S348, cubic spline interpolation is performed on the image after connecting the loops to increase the sampling rate and obtain a new image after connecting the loops. Cubic spline interpolation helps to increase the sampling rate and improve the correction effect.

[0142] S350 uses a comb filter to remove straight lines from the new connected loop image, resulting in a line-free image. Using a comb filter to remove the new connected loop image improves the correction effect.

[0143] S352, perform cubic spline interpolation on the line-removed image to obtain the final line-removed image. By performing cubic spline interpolation on the line-removed image, a more accurate line-removed image can be obtained, which is beneficial to improving the correction effect;

[0144] S354, Subtract the final de-lined image from the first corrected image to obtain the second corrected image. By subtracting the polar coordinate image from the final de-lined image, the obtained corrected image is more accurate, which helps to improve the correction effect;

[0145] S356, Perform coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate image. The corrected image is in polar coordinates. By drawing a circumcircle on the corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar to rectangular coordinates, thus determining the rectangular coordinate image. This rectangular coordinate image is a medical image with the annular artifacts removed. Performing coordinate transformation on the corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0146] Example 4

[0147] like Figure 4 As shown, an embodiment of the present invention provides an adaptive medical image ring artifact correction system 400, including a reading unit 410, a first coordinate transformation unit 421, a processing unit 450, a first calculation unit 431, a first judgment unit 441, a first correction unit 461, a second calculation unit 432, a second judgment unit 442, a second correction unit 462, and a second coordinate transformation unit 422. Specifically, the reading unit 410 is used to read and determine the original image. The original image is a medical image in a rectangular coordinate system. Factors such as inconsistent detector channel response and data acquisition system failure can cause ring artifacts in the original image. Optionally, the original image is a CT image. Further, the first coordinate transformation unit 421 is used to perform coordinate transformation on the original image within its circumcircle to obtain a polar coordinate image. A circumcircle is drawn for the original image, and coordinate transformation is performed on the original image within the circumcircle, converting it from the previous rectangular coordinate system to the polar coordinate system to determine the polar coordinate image. The annular artifacts in the original image are converted into linear artifacts in the polar coordinate image, facilitating the study of parameters such as the position, spacing, and gradient values ​​of the artifacts. In the technical solution defined in this invention, coordinate transformation is performed on the original image within its circumcircle, effectively avoiding image processing blind spots. The adaptive annular artifact correction method can automatically adjust the smoothing intensity in edge and non-edge regions of medical images, ensuring correction effectiveness while enhancing image visibility.

[0148] Further, the processing unit 450 performs circumferential projection on the polar coordinate image to obtain a projection curve. The horizontal coordinate of the projection curve corresponds to the radius, and the vertical coordinate corresponds to the pixel value. The first calculation unit 431 calculates the first gradient of the pixel on the projection curve. The gradient can be understood as the rate of change of the pixel value. The larger the gradient value, the greater the rate of change of the pixel value. Further, the first judgment unit 441 determines whether the first gradient is greater than a first threshold. If the first gradient is greater than the first threshold, the artifact of the pixel is a coarse ring.

[0149] Further, the first correction unit 461 is used to filter out coarse rings from the polar coordinate image to obtain the first corrected image. Targeted measures are employed to remove coarse rings, thus obtaining the first corrected image. Specifically, a smooth spline function is used to fit the projection curve data to smooth low-frequency information. Here, the projection curve data refers to the first gradient. The difference between the projection data and the low-frequency data is used to obtain high-frequency line artifacts, which are then copied circumferentially to obtain an image containing only the line artifacts. The line artifact image is subtracted from the polar coordinate image to obtain the first corrected image in the polar coordinate system. Optionally, for coarse rings, the polar coordinate image is circumferentially projected to obtain a projection curve, and then the projection data is adaptively smoothed using a smooth spline function incorporating the ring strength parameter (the maximum directional derivative of the ring position segment). By adjusting the radial extension size of the ring, the affected area of ​​the correction method can be controlled, resulting in a smooth transition effect and a better correction result.

[0150] Furthermore, the second calculation unit 432 is used to calculate the second gradient of the pixels on the first corrected image. The second judgment unit 442 is used to determine whether the second gradient is greater than a second threshold, where the first threshold is greater than the second threshold. If the second gradient is greater than the second threshold but not greater than the first threshold, the artifact where the pixel is located is a thin ring. Given that the gradient value is greater than the second threshold, the gradient value is compared with the first threshold to divide the ring (ring artifact) into two types: coarse and thin rings, facilitating targeted filtering of the two types in subsequent steps.

[0151] Further, the second correction unit 462 is used to filter out the fine rings from the first corrected image to obtain the second corrected image. Targeted measures are used to remove the fine rings to obtain the second corrected image. Specifically, the corresponding sigma is determined based on the image pixel gradient values. The variance is calculated, and sigma is substituted into the Gaussian function to generate the necessary smoothing coefficients. A sigma-gradient function is designed and applied to a five-point cubic smoothing filter. The first corrected image is smoothed using a five-point cubic smoothing filter to generate a smoothed image. The difference between the first corrected image and the smoothed image is calculated to generate a basic loop image. The average pixel value of each row in the basic loop image is calculated, and the average value is used to cover the pixel values ​​at the broken lines to generate a connected loop image. Straight lines in the connected loop image are filtered out using a comb filter to obtain a line-free image; the line-free image is subtracted from the first corrected image to obtain the second corrected image.

[0152] Furthermore, the second coordinate transformation unit 422 is used to perform coordinate transformation on the second corrected image within its circumcircle to obtain a rectangular coordinate system image. The second corrected image is an image in polar coordinates. By drawing a circumcircle around the second corrected image and performing coordinate transformation within that circumcircle, the image is converted from polar coordinates to rectangular coordinates, thus determining the rectangular coordinate system image. This rectangular coordinate system image is a medical image with the annular artifacts removed. Performing coordinate transformation on the second corrected image within its circumcircle effectively avoids image processing blind spots, ensuring the correction effect while minimizing image information loss.

[0153] In the technical solution defined in this invention, coordinate transformation is performed on the original image or the second corrected image within its circumcircle, effectively avoiding blind spots in image processing. Furthermore, the annular artifacts (ring-shaped artifacts) are divided into coarse and fine rings based on the image pixel gradient values, facilitating targeted filtering of both in subsequent steps. Filtering out the coarse and fine rings sequentially improves the correction effect. During the smoothing stage, this invention achieves adaptive smoothing; the smoothing intensity can be controlled according to relevant constraints for both coarse and fine rings, ensuring the correction effect while minimizing image information loss.

[0154] Example 5

[0155] An embodiment of the present invention provides an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the steps of the adaptive medical image ring artifact correction method in any of the above embodiments.

[0156] Example 6

[0157] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the adaptive medical image ring artifact correction method in any of the above embodiments.

[0158] Example 7

[0159] An embodiment of the present invention provides a chip including a processor and a communication interface, the communication interface and the processor being coupled, the processor being used to run a program or instructions to implement the steps of the adaptive medical image ring artifact correction method in any of the above embodiments.

[0160] According to embodiments of the adaptive medical image ring artifact correction method, system, electronic device, computer-readable storage medium, and chip of the present invention, coordinate transformation is performed on the original image or the corrected image within its circumcircle, effectively avoiding image processing blind spots. Furthermore, the rings (ring artifacts) are divided into coarse and fine rings based on the image pixel gradient values, facilitating targeted filtering of both in subsequent steps. During the smoothing stage, the present invention achieves adaptive smoothing; the smoothing intensity can be controlled according to relevant constraints for both coarse and fine rings, ensuring the correction effect while minimizing image information loss.

[0161] In this invention, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more unless otherwise explicitly defined. The terms "install," "connect," "link," and "fix" should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; "link" can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0162] In the description of this invention, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or unit referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0163] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0164] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An adaptive method for correcting ring artifacts in medical images, characterized in that, include: Determine the original image; The original image is subjected to coordinate transformation within its circumcircle to determine a polar coordinate image, and the annular artifacts in the original image are converted into linear artifacts in the polar coordinate image; The polar coordinate image is circumferentially projected to obtain a projection curve. The first gradient of the pixel on the projection curve is calculated. If the first gradient is greater than a first threshold, the artifact where the pixel is located is a coarse ring. The polar coordinate image is filtered to remove the thick ring, and a first corrected image is obtained; Calculate the second gradient of the pixel in the first corrected image. If the second gradient is greater than the second threshold and not greater than the first threshold, the artifact where the pixel is located is a thin ring. The first threshold is greater than the second threshold. The first corrected image is filtered to remove the thin ring, resulting in a second corrected image; The second corrected image is subjected to coordinate transformation within the range of its circumcircle to obtain a rectangular coordinate system image.

2. The method for correcting ring artifacts in adaptive medical images according to claim 1, characterized in that, Also includes: After performing coordinate transformation on the original image within its circumcircle to determine the polar coordinate image, and converting the annular artifacts in the original image into straight line artifacts in the polar coordinate image, the third gradient of the polar coordinate image in the y-axis direction of the Cartesian coordinate system is calculated. It is then determined whether the third gradient is greater than the second threshold. If it is, the pixel belongs to the straight line artifact; otherwise, the pixel does not belong to the straight line artifact.

3. The method for correcting ring artifacts in adaptive medical images according to claim 2, characterized in that, The step of filtering out the coarse ring from the polar coordinate image to obtain the first corrected image includes: Determine the distance between two adjacent line artifacts, and determine whether the distance is less than a third threshold. If it is, the two adjacent line artifacts are artifacts of the same position segment; otherwise, the two adjacent line artifacts are artifacts of different position segments. The largest third gradient among the artifacts of the same position segment is taken as the ring strength parameter. The smoothness parameter is determined based on the ring strength parameter. and the smoothness parameter The following relationship must be satisfied: ， in, , These are the control points for the two pairs of ring strength parameters and the smoothness parameters. The curve shape can be controlled; The smoothness parameter is substituted into the smooth spline interpolation function, and the smooth spline interpolation function is used to fit the first gradient to smooth the projection curve and obtain low-frequency information. The high-frequency line artifact is obtained by subtracting the first gradient from the low-frequency information, and the high-frequency line artifact is copied along its circumference to obtain the line artifact image. The first corrected image is obtained by subtracting the straight line artifact image from the polar coordinate image.

4. The method for correcting ring artifacts in adaptive medical images according to claim 2 or 3, characterized in that, The step of filtering out the thin ring from the first corrected image to obtain the second corrected image includes: Determine the gradient parameters; The variance is determined based on the gradient parameters. With the gradient parameters The variance gradient function must satisfy the following relationship: ， in, It is a control factor used to adjust the convexity or concavity of the curve; The variance is substituted into the Gaussian function to obtain the smoothing coefficient, and the smoothing coefficient is applied to the five-point cubic smoothing filter. The first corrected image is smoothed by the five-point cubic smoothing filter to generate a smooth image; The difference between the first corrected image and the smoothed image is used to generate a basic loop image; Calculate the average value of each row of pixels in the basic loop image, and use the average value to cover the pixel values ​​at the broken line to generate the connected loop image; The image after the connection loop is subjected to cubic spline interpolation to increase the sampling rate and obtain a new image after the connection loop; A comb filter is used to remove straight lines from the new connected loop image to obtain a line-free image; The second corrected image is obtained by subtracting the delineated image from the first corrected image.

5. The method for correcting ring artifacts in adaptive medical images according to claim 4, characterized in that, Also includes: While calculating the third gradient of the polar image in the y-axis direction of the Cartesian coordinate system, the fourth gradient of the polar image in the x-axis direction of the Cartesian coordinate system is also calculated. The determination of the gradient parameters specifically involves: The minimum value between the third gradient and the fourth gradient is taken as the gradient parameter.

6. The method for correcting ring artifacts in adaptive medical images according to claim 4, characterized in that, The step of filtering out the thin ring from the first corrected image to obtain the second corrected image further includes: After filtering out straight lines in the connected loop image using the comb filter to obtain the line-free image, cubic spline interpolation is performed on the line-free image to obtain the final line-free image. The step of subtracting the delineated image from the first corrected image to obtain the second corrected image specifically involves: The second corrected image is obtained by subtracting the final delineated image from the first corrected image.

7. An adaptive medical image ring artifact correction system, characterized in that, include: Reading unit (410) is used to read and determine the original image; The first coordinate transformation unit (421) is used to perform coordinate transformation on the original image within the range of its circumcircle to obtain a polar coordinate image; Processing unit (450) is used to perform circumferential projection on the polar coordinate image to obtain a projection curve; The first calculation unit (431) is used to calculate the first gradient of the pixel points on the projection curve; The first judgment unit (441) is used to determine whether the first gradient is greater than the first threshold. If the first gradient is greater than the first threshold, the artifact where the pixel is located is a thick ring. The first correction unit (461) is used to filter out the thick ring from the polar coordinate image and obtain the first corrected image; The second calculation unit (432) is used to calculate the second gradient of the pixel points on the first corrected image; The second judgment unit (442) is used to determine whether the second gradient is greater than the second threshold. The first threshold is greater than the second threshold. If the second gradient is greater than the second threshold but not greater than the first threshold, then the artifact where the pixel is located is a thin ring. The second correction unit (462) is used to filter out the thin ring from the first correction image and obtain the second correction image; The second coordinate transformation unit (422) is used to perform coordinate transformation on the second corrected image within the range of its circumcircle and obtain a rectangular coordinate system image.

8. An electronic device, characterized in that, The method includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the adaptive medical image ring artifact correction method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the adaptive medical image ring artifact correction method as described in any one of claims 1 to 6.

10. A chip, characterized in that, The chip includes a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the steps of the adaptive medical image ring artifact correction method as described in any one of claims 1 to 6.

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