Information processing device, information processing method, and program
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- FUJIFILM CORP
- Filing Date
- 2022-08-19
- Publication Date
- 2026-05-11
Smart Images
Figure 0007856524000015 
Figure 0007856524000016 
Figure 0007856524000017
Abstract
Description
[Technical Field]
[0001] The technology disclosed herein relates to an information processing device, an information processing method, and a program. [Background technology]
[0002] Radiation imaging systems, which use radiation to photograph subjects, employ radiation detectors such as FPDs (Flat Panel Detectors). These radiation detectors consist of multiple pixels arranged in a two-dimensional array, each generating and accumulating a signal charge corresponding to the incident radiation dose.
[0003] Defective pixels may exist among the multiple pixels installed in a radiation detector. Since defective pixels cannot obtain the correct signal charge, it is necessary to correct them using interpolation or other methods with the pixel values of surrounding normal pixels.
[0004] Patent Document 1 discloses a method for correcting linear defects. Specifically, Patent Document 1 proposes performing regression analysis using multiple normal pixels surrounding a defective pixel and correcting the defective pixel based on the regression curve obtained from the regression analysis.
[0005] Patent Document 2 proposes correcting a defective pixel by using the average value of the pixel values of a pair of normal pixels that have the smallest difference between them, from a pair of normal pixels that are point-symmetric with respect to the defective pixel. [Prior art documents] [Patent Documents]
[0006] [Patent Document 1] Japanese Patent Publication No. 2020-170959 [Patent Document 2] Japanese Patent Publication No. 2002-197450 [Overview of the project] [Problems that the invention aims to solve]
[0007] Radiographic images may contain high-contrast edges, such as the contours of finger bones or thin metal wires from pacemakers. In the correction method described in Patent Document 1, interpolation processing may be performed using surrounding pixels other than those in the edge direction when correcting defective pixels on edges. Therefore, it is expected that correction residuals will occur on edges in the correction method described in Patent Document 1, and these will be visible as artifacts. In particular, artifacts become more pronounced when high-frequency patterns are present in the radiation image. For example, as shown in Figure 21, when a thin line about one pixel wide intersects a line defect at an angle, the interpolation processing performed using only normal pixels in the horizontal direction adjacent to the line defect, as described in Patent Document 1, does not provide sufficient correction accuracy, and correction residuals occur. In such cases, it is necessary to perform interpolation processing using normal pixels in the diagonal direction.
[0008] The correction method described in Patent Document 2 selects pixels along the edge direction to correct defective pixels, so it can handle defects on high-frequency patterns to some extent. However, the correction method described in Patent Document 2 uses pixel pairs at discrete angles centered on the defective pixel for correction, so it cannot correct with high accuracy.
[0009] Thus, with conventional correction methods, especially when an edge intersects a line defect, correcting the defective pixel on the edge using adjacent pixels results in a large correction residual, making it impossible to accurately correct the defective pixel.
[0010] The present invention aims to provide an information processing device, an information processing method, and a program that enable accurate correction of defective pixels on edges intersecting line defects. [Means for solving the problem]
[0011] To achieve the above objective, the information processing device of the present disclosure is an information processing device that performs processing to correct line defects in a radiographic image obtained by radiography, and comprises a processor, which sets a first region and a second region at positions opposite each other in normal pixel regions on both sides separated by a line defect, with one pixel to be corrected selected from the line defect in between, calculates a first edge strength and a first edge angle of the first region, calculates a second edge strength and a second edge angle of the second region, calculates an integrated edge strength representing the edge strength around the pixel to be corrected by integrating the first edge strength and the second edge strength, calculates an integrated edge angle representing the edge direction around the pixel to be corrected by integrating the first edge angle and the second edge angle, and corrects the pixel to be corrected considering the integrated edge strength and integrated edge angle.
[0012] Preferably, the processor calculates two derivative values by applying two differential filters with different differential directions to the first and second regions, calculates the first edge strength and first edge angle based on the two derivative values calculated from the first region, and calculates the second edge strength and second edge angle based on the two derivative values calculated from the second region.
[0013] The first edge strength and the second edge strength are preferably the square root of the sum of the squares of the two differential values, or the sum of the absolute values of the two differential values.
[0014] Preferably, the first edge angle and the second edge angle are expressed by angles calculated by applying the ratio of two derivative values to the arctangent function.
[0015] Each of the differential filters is preferably a Prewitt filter or a Sobel filter.
[0016] Preferably, the processor uses the average value of the first edge strength and the second edge strength as the integrated edge strength, and the weighted average value of the first edge angle and the second edge angle, with the first edge strength and the second edge strength as the weights, as the integrated edge angle.
[0017] The processor sets the first region and the second region as the first A region and the second A region, and sets the first B region and the second B region obtained by shifting the first A region and the second A region by one pixel in the first direction along the line defect, and the first C region and the second C region obtained by shifting the first A region and the second A region by one pixel in the second direction, which is the opposite direction to the first direction. The processor calculates the first A edge strength and the first A edge angle of the first A region, the first B edge strength and the first B edge angle of the first B region, the first C edge strength and the first C edge angle of the first C region, the second A edge strength and the second A edge angle of the second A region, the second B edge strength and the second B edge angle of the second B region, and the second C edge strength and the second C edge angle of the second C region. Based on the first A edge strength, the first B edge strength, the first C edge strength, the first A edge angle, the first B edge angle, and the first C edge angle, the processor calculates the first edge strength and the first edge angle, and based on the second A edge strength, the second B edge strength, the second C edge strength, the second A edge angle, the second B edge angle, and the second C edge angle, it is preferable to calculate the second edge strength and the second edge angle.
[0018] When the first A edge strength is at or above the same level as the first B edge strength or the first C edge strength, it is preferable that the processor sets the first A edge strength and the first A edge angle as the first edge strength and the first edge angle. When the second A edge strength is at or above the same level as the second B edge strength or the second C edge strength, it is preferable that the processor sets the second A edge strength and the second A edge angle as the second edge strength and the second edge angle.
[0019] When the first A edge strength is not at or above the same level as the first B edge strength or the first C edge strength, the processor uses the average value of the first A edge strength, the first B edge strength, and the first C edge strength as the first edge strength, and uses the weighted average value of the first A edge angle, the first B edge angle, and the first C edge angle with the first A edge strength, the first B edge strength, and the first C edge strength as weights as the first edge angle. When the second A edge strength is not at or above the same level as the second B edge strength or the second C edge strength, the processor uses the average value of the second A edge strength, the second B edge strength, and the second C edge strength as the second edge strength, and uses the weighted average value of the second A edge angle, the second B edge angle, and the second C edge angle with the second A edge strength, the second B edge strength, and the second C edge strength as weights as the second edge angle, which is preferable.
[0020] The processor preferably determines the presence or absence of an edge around the pixel to be corrected by comparing the integrated edge strength with a threshold value.
[0021] When there is an edge, the processor performs a first correction process to correct the pixel to be corrected by attaching a first weight according to the difference angle, which is the angle formed by the direction from the pixel to be corrected to the normal pixel and the edge direction, and the distance from the pixel to be corrected to the normal pixel, to each normal pixel within the mask set centered on the pixel to be corrected. When there is no edge, the processor preferably performs a second correction process to correct the pixel to be corrected by attaching a second weight that depends only on the distance and not on the difference angle to each normal pixel.
[0022] The difference angle takes a value within the range of 0° to 180°, and the first weight is preferably represented by including a symmetric function centered on 90°, which is maximum when the difference angle is 0° and 180° and minimum when the difference angle is 90°.
[0023] The function is preferably represented by the power of the absolute value of the cosine of the difference angle.
[0024] The first weight preferably has a smaller dependence on the distance than the second weight.
[0025] Preferably, the processor performs a logarithmic transformation on the radiographic image and calculates the integrated edge intensity and integrated edge angle using the radiographic image after the logarithmic transformation.
[0026] Preferably, the processor performs a grid fringe removal process on the radiation image to remove grid fringes using a scatter removal grid, and then uses the radiation image after grid fringe removal to calculate the integrated edge intensity and integrated edge angle, and to correct the pixels to be corrected.
[0027] The information processing method disclosed herein is an information processing method for correcting line defects in a radiographic image obtained by radiography, and includes: setting a first region and a second region at positions opposite each other in normal pixel regions on both sides separated by a line defect, with one correction target pixel selected from the line defect in between; calculating a first edge strength and a first edge angle of the first region; calculating a combined edge strength representing the edge strength around the correction target pixel by integrating the first edge strength and the second edge strength; calculating a combined edge angle representing the edge direction around the correction target pixel by integrating the first edge angle and the second edge angle; and correcting the correction target pixel considering the combined edge strength and the combined edge angle.
[0028] The program of this disclosure is a program that causes a computer to perform a process to correct line defects in a radiographic image obtained by radiography, and causes the computer to perform a process that includes setting a first region and a second region at positions opposite each other in normal pixel regions on both sides separated by a line defect, with one pixel to be corrected selected from the line defect in between; calculating a first edge strength and a first edge angle of the first region; calculating a combined edge strength representing the edge strength around the pixel to be corrected by integrating the first edge strength and the second edge strength; calculating a combined edge angle representing the edge direction around the pixel to be corrected by integrating the first edge angle and the second edge angle; and correcting the pixel to be corrected considering the combined edge strength and the combined edge angle.
[0029] The technology of this disclosure provides an information processing device, an information processing method, and a program that enable accurate correction of defective pixels on edges intersecting line defects. [Brief explanation of the drawing]
[0030] [Figure 1] This is a diagram showing an example configuration of a radiography system. [Figure 2] This diagram illustrates the direction of the edges. [Figure 3] This figure shows an example of two differential filters used by the detection unit. [Figure 4] This figure shows an example of the setting region for a differential filter when a line defect with a width of 1 pixel is present in the radiographic image. [Figure 5] This figure shows an example of the setting region for a differential filter when a line defect with a width of 2 pixels is present in the radiographic image. [Figure 6] This diagram illustrates an example of a correction process for correcting pixels that are subject to correction. [Figure 7] This diagram illustrates another example of a correction process for correcting the target pixels. [Figure 8]This figure shows the dependence of the weight expressed by equation (6) on the difference angle. [Figure 9] This figure shows the dependence of the weight expressed by equation (6A) on the difference angle. [Figure 10] This figure shows an example of interpolation processing using two normal pixels adjacent to the pixel to be corrected. [Figure 11] This flowchart shows an example of the image processing flow by the image processing unit 14. [Figure 12] This is a diagram showing the Prewitt filter. [Figure 13] This figure shows the Sobel filter. [Figure 14] This figure shows an example of a differential filter that performs differentiation in an oblique direction. [Figure 15] This diagram illustrates the case where high-frequency patterns exist in the first and second regions. [Figure 16] This figure shows examples of settings for the 1A and 2A regions. [Figure 17] This figure shows examples of settings for the 1B and 2B regions. [Figure 18] This figure shows examples of settings for the first C region and the second C region. [Figure 19] This flowchart shows the flow of edge detection processing by the detection unit related to the modified example. [Figure 20] This flowchart shows the image processing flow by the image processing unit related to the modified example. [Figure 21] This diagram illustrates the problems with conventional correction methods. [Modes for carrying out the invention]
[0031] An example of an embodiment relating to the technology of this disclosure will be described with reference to the attached drawings.
[0032] [Embodiment] Figure 1 shows an example configuration of the radiography system 2. The radiography system 2 includes a radiation generator 3, a radiation tube 4, an FPD 5, and an information processing device 6.
[0033] The radiation generator 3 generates radiation R by applying a high-voltage pulse to the radiation tube 4 in response to the user operating an exposure switch (not shown). For example, radiation R is X-rays. The radiation R generated by the radiation tube 4 is irradiated onto the subject H. A portion of the radiation R passes through the subject H and reaches the FPD 5.
[0034] The FPD5 is detachably housed in the cassette holder 7. Radiation R that has passed through the object H passes through the detection surface 7A of the cassette holder 7 and enters the FPD5. A scatter removal grid 8 can also be detachably attached to the cassette holder 7. The scatter removal grid 8 is inserted into the detection surface 7A side of the FPD5. When the scatter removal grid 8 is attached to the cassette holder 7, radiation R that enters the detection surface 7A enters the FPD5 via the scatter removal grid 8. The scattered radiation is removed as the radiation R passes through the scatter removal grid 8.
[0035] The FPD5 has a pixel array in which multiple pixels are arranged in a two-dimensional array, each generating and accumulating a signal charge corresponding to the incident dose of radiation R. Each pixel contains a photoelectric conversion element. The photoelectric conversion element converts radiation R, which has been converted into visible light by a phosphor, into a signal charge and accumulates it. The FPD5 generates a radiation image corresponding to the signal charge of each pixel and transmits the generated radiation image to the information processing device 6 wirelessly or via a wired connection. Note that the FPD5 is not limited to an indirect type of radiation detector that first converts radiation R into visible light and then converts that visible light into a signal charge, but may also be a direct type of radiation detector that directly converts the irradiation of radiation R into a signal charge.
[0036] The information processing device 6 includes a control unit 10, a display 11, an operation unit 12, a storage unit 13, and an image processing unit 14. The information processing device 6 performs processing based on the radiation image received from the FPD 5.
[0037] The control unit 10 comprises one or more processors (not shown) and implements various functions by executing programs 15 stored in the memory unit 13. The memory unit 13 is composed of, for example, ROM (Read Only Memory), RAM (Random Access Memory), etc. The memory unit 13 stores radiation images received by the control unit 10 from the FPD 5, images after image processing by the image processing unit 14, and various data used by the image processing unit 14 for image processing.
[0038] Furthermore, the memory unit 13 stores defective pixel data 16. The defective pixel data 16 is information representing the location, type, etc., of defective pixels in the pixel array of the FPD 5. The types of defective pixels include point defects and line defects. Point defects are isolated defective pixels. Line defects are defective pixels that are continuous in a linear fashion. Line defects occur in the row or column direction of the pixel array. The defective pixel data 16 is acquired by calibration radiography, which is performed in addition to normal radiography. Calibration is performed at the time of product shipment, installation, and during periodic maintenance.
[0039] The image processing unit 14 performs image processing on the radiation image received by the control unit 10 from the FPD 5. In this disclosure, the image processing unit 14 performs defective pixel correction for line defects in the radiation image.
[0040] The image processing unit 14 has an acquisition unit 20, a detection unit 21, and a correction unit 22 as its functional configuration. As will be described in detail later, the acquisition unit 20 acquires the radiation image received by the control unit 10 from the FPD 5. The detection unit 21 detects the edges of the subject H that are captured in the radiation image. The correction unit 22 performs defective pixel correction based on the defective pixel data 16 and the result of edge detection by the detection unit 21. In this disclosure, edge detection means detecting the presence or absence of an edge around a defective pixel and, if an edge is present, detecting the direction of the edge.
[0041] These functional configurations may be realized by the processor of the control unit 10 executing processing based on the program 15. Alternatively, these functional configurations may be realized by one or more processors in the image processing unit 14 executing processing based on the program 15 read from the storage unit 13.
[0042] The processors of the control unit 10 and the image processing unit 14 are composed of, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). Each part of the image processing unit 14 may be composed of an integrated circuit or the like, as long as it performs a similar function.
[0043] The display 11 displays the radiation image received by the control unit 10 from the FPD 5, the image processed by the image processing unit 14, etc. The operation unit 12 allows input of instructions to the control unit 10, FPD 5, etc., and accepts input of instructions to the FPD 5 via a user interface (not shown).
[0044] Figure 2 illustrates the edge direction. Assume that the pixels constituting the radiation image are arranged parallel to the X and Y directions. The X and Y directions are orthogonal to each other. In this disclosure, the angle between the X direction and the edge direction is denoted as α. Hereinafter, angle α will be referred to as the edge angle α. The edge direction is represented by the edge angle α.
[0045] The detection unit 21 performs edge detection processing using two differential filters with different differential directions. In this embodiment, the detection unit 21 performs LOG conversion processing on the radiation image and then performs edge detection processing on the radiation image after LOG conversion. LOG conversion is a type of grayscale conversion. By performing LOG conversion on a radiation image in which pixel values depend linearly on the radiation dose, an image is generated in which the contrast does not depend on the dose. However, the correction unit 22 may perform correction processing on the radiation image before LOG conversion.
[0046] Figure 3 shows an example of two differential filters used by the detection unit 21. Differential filters Fx and Fy are first-order differential filters each with a size of 3x3 pixels. Differential filter Fx is a first-order differential filter that obtains the differential value in the X direction. Differential filter Fy is a first-order differential filter that obtains the differential value in the Y direction. Hereafter, the pixel value of one pixel included in the radiation image will be represented as QL(X,Y). Also, the differential value in the X direction obtained by differential filter Fx is Δ X This is denoted as QL(X,Y). The derivative in the Y direction due to the differential filter Fy is Δ Y This is represented as QL(X,Y).
[0047] Figure 4 shows an example of the setting range for differential filters Fx and Fy when a line defect with a width of 1 pixel is present in the radiographic image. The line defect shown in Figure 4 extends in the X direction and has a width of 1 pixel in the Y direction. The normal pixel area is separated in the Y direction by the line defect.
[0048] When correcting such line defects, the detection unit 21 sets a first region FR1 and a second region FR2 at positions opposite each other in the normal pixel regions on both sides separated by the line defect, with one correctable pixel Ps selected from the line defect in between. The first region FR1 and the second region FR2 are the same size as the differential filters Fx and Fy, respectively. That is, in this embodiment, the size of the first region FR1 and the second region FR2 is 3 × 3 pixels each.
[0049] In the example shown in Figure 4, since the width of the line defect is 1 pixel, the first region FR1 and the second region FR2 are adjacent to the pixel Ps to be corrected. Furthermore, the pixel Ps to be corrected lies on the line connecting the center of the first region FR1 and the center of the second region FR2. In other words, the first region FR1 and the second region FR2 are arranged symmetrically with respect to a straight line that passes through the pixel Ps to be corrected and extends in a direction perpendicular to the extension direction of the line defect.
[0050] Figure 5 shows an example of the setting range for differential filters Fx and Fy when a line defect with a width of 2 pixels is present in the radiographic image. The line defect shown in Figure 5 extends in the X direction and has a width of 2 pixels in the Y direction. The normal pixel area is separated in the Y direction by the line defect.
[0051] Similar to the case in Figure 4, the detection unit 21 sets a first region FR1 and a second region FR2 at positions opposite each other in the normal pixel regions on both sides separated by the line defect, with one correction target pixel Ps selected from the line defect in between. The sizes of the first region FR1 and the second region FR2 are the same as in the case in Figure 4.
[0052] In the example shown in Figure 5, since the width of the line defect is 2 pixels, either the first region FR1 or the second region FR2 is adjacent to the pixel Ps to be corrected. In the example shown in Figure 5, the first region FR1 is adjacent to the pixel Ps to be corrected. Furthermore, the pixel Ps to be corrected lies on the line connecting the center of the first region FR1 and the center of the second region FR2. In other words, the first region FR1 and the second region FR2 are arranged symmetrically with respect to a straight line that passes through the pixel Ps to be corrected and extends in a direction perpendicular to the extension direction of the line defect.
[0053] Even when a line defect with a width of 3 pixels or more exists, the detection unit 21 similarly sets the first region FR1 and the second region FR2 at positions opposite each other, with one correction target pixel Ps selected from the line defect in between, in the normal pixel regions on both sides separated by the line defect. Figures 4 and 5 show the case where the line defect extends in the X direction, but even when the line defect extends in the Y direction, the detection unit 21 similarly sets the first region FR1 and the second region FR2.
[0054] The detection unit 21 applies differential filters Fx and Fy to the first region FR1 and the second region FR2, respectively, and calculates the differential value Δ for each of the first region FR1 and the second region FR2. X QL(X,Y) and Δ Y Calculate QL(X,Y). The derivative value is Δ. XQL(X, Y) is the difference in pixel values of normal pixels adjacent in the X direction with respect to the pixel at the center of the differential filter Fx. The differential value Δ Y QL(X, Y) is the difference in pixel values of normal pixels adjacent in the Y direction with respect to the pixel at the center of the differential filter Fy.
[0055] The detection unit 21 calculates the differential value Δ X QL(X, Y) and Δ Y After calculating QL(X, Y), the edge strength E(i) is calculated using the following formula (1). Formula (1) represents X taking the square root of the sum of the squares of the differential values Δ Y QL(X, Y) and Δ
Equation
[0056] Here, i is a parameter for distinguishing between the first region FR1 and the second region FR2. i = 1 corresponds to the first region FR1. i = 2 corresponds to the second region FR2. E(1) is the edge strength of the first region FR1 (hereinafter referred to as the first edge strength). E(2) is the edge strength of the second region FR2 (hereinafter referred to as the second edge strength).
[0057] The detection unit 21 may calculate the edge strength E(i) using the following formula (1A) instead of the above formula (1). Formula (1A) represents X taking the absolute value sum of the differential values Δ Y QL(X, Y) and Δ
Equation
[0058] Also, the detection unit 21 calculates the differential value Δ X QL(X, Y) and Δ YAfter calculating QL(X,Y), the edge angle α(i) is calculated using equation (2) below. Equation (2) below is the derivative Δ X QL(X,Y) and Δ Y This represents calculating the edge angle α(i) by applying the ratio of QL(X,Y) to the arctangent function.
number
[0059] α(1) is the edge angle of the first region FR1 (hereinafter referred to as the first edge angle). α(2) is the edge angle of the second region FR2 (hereinafter referred to as the second edge angle).
[0060] The detection unit 21 uses the first edge intensity E(1) and the second edge intensity E(2) to calculate the integrated edge intensity E, which represents the edge intensity around the pixel Ps to be corrected. Specifically, the detection unit 21 calculates the integrated edge intensity E using the following equation (3). The following equation (3) indicates that the average value of the first edge intensity E(1) and the second edge intensity E(2) is used as the integrated edge intensity E.
number
[0061] Furthermore, the detection unit 21 uses the first edge angle α(1) and the second edge angle α(2) to calculate an integrated edge angle α, which represents the edge direction around the pixel Ps to be corrected. Specifically, the detection unit 21 calculates the edge angle α around the pixel Ps to be corrected using the following equation (4). The following equation (4) indicates that the integrated edge angle α is the weighted average of the first edge angle α(1) and the second edge angle α(2), with the first edge intensity E(1) and the second edge intensity E(2) as the weights.
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[0062] The detection unit 21 determines the presence or absence of edges around the pixel Ps to be corrected by comparing the calculated integrated edge intensity E with a threshold. The detection unit 21 determines that there are edges if the integrated edge intensity E is equal to or greater than the threshold, and determines that there are no edges if the integrated edge intensity E is less than the threshold.
[0063] The detection unit 21 supplies the edge detection result (i.e., whether or not there is an edge, and the integrated edge angle α if there is an edge) to the correction unit 22.
[0064] Next, the correction process performed by the correction unit 22 will be described. The correction unit 22 sets a mask centered on the pixel Ps to be corrected on the line defect, and corrects the pixel Ps to be corrected using a weighted sum of the pixel values of the normal pixels included within the mask.
[0065] Figure 6 illustrates an example of a correction process for correcting the target pixel Ps. The mask size shown in Figure 6 is 5x5 pixels. θ(X,Y) represents the angle with respect to the X direction of the line connecting one pixel within the mask and the target pixel Ps. D(X,Y) represents the distance between the pixel and the target pixel Ps. In this example, the coordinates of the target pixel Ps are set as the origin.
[0066] The correction unit 22 replaces the pixel value of the pixel Ps to be corrected with QL(0,0) calculated based on the following equations (5) to (7). The Σ in equation (5) means that addition is performed by changing X and Y within the range of -2≦X≦2 and -2≦Y≦2 (excluding the coordinates of the origin and defective pixels).
number
[0067] Furthermore, the weight W(X,Y) in equation (5) above is expressed by equation (6) below. In equation (6) below, n and m are parameters, which can be set to positive integers, for example.
number
[0068] Furthermore, the difference angle δ(X,Y) in equation (6) above is expressed by equation (7) below. The difference angle δ(X,Y) is the angle between the direction of the normal pixel used for correction from the pixel Ps to be corrected and the edge direction. The difference angle δ(X,Y) takes values within the range of 0° to 180°.
number
[0069] Equation (6) above includes a function that can be expressed as a power of the absolute value of the cosine of the difference angle δ(X,Y). That is, the weight W(X,Y) is expressed as a function that is symmetric about 90°, with the maximum value when the difference angle δ(X,Y) is 0° and 180°, and the minimum value when the difference angle δ(X,Y) is 90°.
[0070] Equations (5) to (7) above represent the correction of the target pixel Ps by assigning a weight W(X,Y) to each normal pixel within the mask, corresponding to the difference angle δ(X,Y) and the distance D(X,Y). The weight W(X,Y) increases as the difference angle δ(X,Y) decreases. In other words, the weight W(X,Y) is largest for normal pixels that are located in the edge direction from the target pixel Ps. As a result, even defective pixels that span the edge can be corrected with good correction results and minimal correction residuals.
[0071] The correction unit 22 may use a 7x7 pixel mask as shown in Figure 7 instead of the 5x5 pixel mask shown in Figure 6. Furthermore, the size of the mask may be 9x9 pixels or the like. For example, when correcting pixels on line defects with a width of two pixels or more, the correction accuracy can be improved by using a larger mask such as 7x7 pixels or 9x9 pixels in order to increase the number of normal pixels used for interpolation. On the other hand, using a larger mask increases the risk of deterioration in correction accuracy because normal pixels that are farther away from the target pixel Ps are used for correction. For this reason, it is preferable to adjust the size of the mask according to the width of the line defect to be corrected.
[0072] Furthermore, the correction unit 22 may use the lower formula (6A) instead of the upper formula (6).
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[0073] Figure 8 shows the dependence of the weight W(X,Y) expressed by equation (6) above on the difference angle δ(X,Y). Figure 9 shows the dependence of the weight W(X,Y) expressed by equation (6A) above on the difference angle δ(X,Y). As shown in Figures 8 and 9, by changing the parameter n, the weight of pixels along the edge direction (pixels around δ(X,Y)=0° or δ(X,Y)=180°) can be adjusted.
[0074] For example, when a radiographic image contains high-contrast, high-frequency patterns such as resolution charts, increasing the pixel weight W(X,Y) along the edge direction can improve the accuracy of defective pixel correction. Therefore, when detecting pattern regions of resolution charts from radiographic images and correcting defective pixels within those regions, it is also preferable to adjust parameters such as increasing the parameter n.
[0075] The weight W(X,Y) expressed by equation (6) or (6A) above decreases as the distance D(X,Y) increases. However, in cases such as resolution charts, where the weight W(X,Y) should be increased for pixels with a difference angle δ(X,Y) of approximately 0 even if the distance D(X,Y) is large, the parameter m should be set to 0 or a value close to 0.
[0076] Hereinafter, the correction process using the weight W(X,Y) represented by equation (6) or equation (6A) above (i.e., the correction process that takes the edge direction into consideration) will be referred to as the first correction process. The weight W(X,Y) represented by equation (6) or equation (6A) above is an example of the "first weight" relating to the technology of this disclosure.
[0077] If the integrated edge strength E is less than the threshold, i.e., if there are no edges, the correction unit 22 performs the correction process using the lower equation (6B) instead of the upper equation (6).
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[0078] Equation (6B) above is obtained by setting δ(X,Y)=0 in equation (6) or equation (6A) above. That is, the weight W(X,Y) expressed in equation (6B) above is an isotropic weight that does not depend on the difference angle δ(X,Y) but depends only on the distance D(X,Y). The weight W(X,Y) expressed in equation (6B) above is an example of the "second weight" relating to the technology of this disclosure. Hereinafter, the correction process using the isotropic second weight will be referred to as the second correction process.
[0079] In the following, when there is no need to distinguish between the first correction process and the second correction process, they will simply be referred to as the correction process.
[0080] In the second correction process, the value of parameter m may be different from that in the first correction process. If there are no edges, it is not necessary to set parameter m to 0 or a value close to 0, as is done when there are edges. For this reason, when there are no edges, it is preferable to simply set parameter m so that the smaller the distance D(X,Y), the larger the weight W(X,Y). In other words, the first weight may have less dependence on the distance D(X,Y) than the second weight.
[0081] If there is no edge, the correction unit 22 may correct the target pixel Ps by performing interpolation using two normal pixels Pi adjacent to the target pixel Ps, as shown in Figure 10. In the example shown in Figure 10, the correction unit 22 performs interpolation using two normal pixels Pi that are opposite each other across the line defect and adjacent to the target pixel Ps.
[0082] Figure 11 shows an example of the image processing flow by the image processing unit 14. First, the acquisition unit 20 acquires the radiation image received from the FPD 5 by the control unit 10 (step S10). Next, the detection unit 21 performs LOG conversion processing on the radiation image (step S11). Then, based on the defective pixel data 16 stored in the storage unit 13, the detection unit 21 selects one defective pixel included in the linear defect as the pixel to be corrected Ps (step S12).
[0083] Next, the detection unit 21 performs the edge detection process described above using the differential filters Fx and Fy (step S13). Specifically, the detection unit 21 calculates the integrated edge strength E and integrated edge angle α through the above process.
[0084] Next, the detection unit 21 determines whether or not there is an edge around the pixel Ps to be corrected (step S14). Specifically, the detection unit 21 determines that there is an edge if the integrated edge intensity E is greater than or equal to a threshold, and determines that there is no edge if the integrated edge intensity E is less than the threshold.
[0085] If an edge is present (step S14: YES), the correction unit 22 performs a first correction process that takes the edge direction into consideration (step S15). On the other hand, if there is no edge (step S14: NO), the correction unit 22 performs a second correction process that does not take the edge direction into consideration (step S16).
[0086] After performing the first or second correction process, the correction unit 22 determines whether the correction of all defective pixels included in the linear defect has been completed (step S17). If the correction unit 22 determines that the correction of all defective pixels included in the linear defect has not been completed (step S17: NO), it returns to step S12. In step S12, the detection unit 21 selects the defective pixels that have not been corrected as the pixels to be corrected Ps. Then, if the correction unit 22 determines that the correction of all defective pixels included in the linear defect has been completed (step S17: YES), it terminates the process.
[0087] In conventional correction methods, when an edge intersects a line defect, correcting the defective pixel on the edge using adjacent pixels results in a correction residual being visible in the corrected radiographic image. This correction residual is particularly pronounced in high-contrast and high-frequency patterns. In contrast, the correction method according to this disclosure corrects the target pixel Ps considering the integrated edge intensity E and integrated edge angle α calculated by the above-described process, thereby enabling accurate correction of defective pixels on edges intersecting line defects.
[0088] [Differentiation] Next, various modifications of the above embodiment will be described. In the above embodiment, the detection unit 21 calculates the derivative value using the differential filters Fx and Fy shown in Figure 3, but instead, the differential filters Fx and Fy shown in Figure 12 or Figure 13 may be used. The differential filters Fx and Fy shown in Figure 12 are called Prewitt filters. The differential filters Fx and Fy shown in Figure 13 are called Sobel filters. By using a Prewitt filter or a Sobel filter, the influence of noise can be reduced.
[0089] Furthermore, the detection unit 21 may use the differential filters Fx and Fy shown in Figure 14, which perform differentiation in an oblique direction, instead of the differential filters Fx and Fy shown in Figure 3. In the differential filters Fx and Fy shown in Figure 14, the coefficients "1" and "-1" are arranged obliquely. That is, the differential filters Fx and Fy shown in Figure 14 make it possible to obtain the differential value in the direction that is 45° with respect to the X direction and the differential value in the direction that is 45° with respect to the Y direction. Note that similar modifications are possible when using a Prewitt filter or a Sobel filter.
[0090] Next, a modified example of the edge detection process by the detection unit 21 will be described. In the above embodiment, as shown in Figure 15, even if high-frequency patterns exist in the first region FR1 and the second region FR2, if the high-frequency patterns within each region are symmetrical in the direction of extension of the linear defect, the derivative in that direction will be almost zero, and there is a possibility that edges in that direction will not be detected.
[0091] In this modified example, as shown in Figures 16 to 18, the detection unit 21 sets multiple regions in the direction of extension of the linear defect by shifting each of the first region FR1 and the second region FR2 in the direction of extension of the linear defect. The first A region FR1A and the second A region FR2A shown in Figure 16 are the same as the first region FR1 and the second region FR2 in the above embodiment, and are arranged symmetrically with respect to a straight line that passes through the pixel Ps to be corrected and extends in a direction perpendicular to the direction of extension of the linear defect.
[0092] The first B region FR1B and the first B region FR1B shown in Figure 17 are regions obtained by shifting the first A region FR1A and the second A region FR2A shown in Figure 16 by one pixel in the first direction (in this example, the +X direction) along the line defect. The first C region FR1C and the second C region FR2C shown in Figure 18 are regions obtained by shifting the first A region FR1A and the second A region FR2A shown in Figure 16 by one pixel in the second direction (in this example, the -X direction), which is the opposite direction to the first direction.
[0093] In this modified example, the detection unit 21 applies differential filters Fx and Fy to each region, thereby calculating the differential value Δ for each region. X QL(X,Y) and Δ Y QL(X,Y) is calculated. Then, the detection unit 21 calculates the edge strength E(i,k) and edge angle α(i,k) for each region using equations (7) and (8) below.
number
number
[0094] Here, i and k are parameters used to distinguish each region. Parameter i indicates which of the two normal pixel regions separated by the line defect the region belongs to. Parameter k indicates the location of the region along the line defect.
[0095] E(1,1) and α(1,1) are the edge strength (hereinafter referred to as the 1A edge strength) and edge angle (hereinafter referred to as the 1A edge angle) of the 1A region FR1A. E(1,2) and α(1,2) are the edge strength (hereinafter referred to as the 1B edge strength) and edge angle (hereinafter referred to as the 1B edge angle) of the 1B region FR1B. E(1,3) and α(1,3) are the edge strength (hereinafter referred to as the 1C edge strength) and edge angle (hereinafter referred to as the 1C edge angle) of the 1C region FR1C.
[0096] E(2,1) and α(2,1) are the edge strength (hereinafter referred to as the 2A edge strength) and edge angle (hereinafter referred to as the 2A edge angle) of the 2A region FR2A. E(2,2) and α(2,2) are the edge strength (hereinafter referred to as the 2B edge strength) and edge angle (hereinafter referred to as the 2B edge angle) of the 2B region FR2B. E(2,3) and α(2,3) are the edge strength (hereinafter referred to as the 2C edge strength) and edge angle (hereinafter referred to as the 2C edge angle) of the 2C region FR2C.
[0097] The detection unit 21 calculates the first edge strength E(1) by integrating the first A edge strength E(1,1), the first B edge strength E(1,2), and the first C edge strength E(1,3), and calculates the first edge angle α(1) by integrating the first A edge angle α(1,1), the first B edge angle α(1,2), and the first C edge angle α(1,3). The detection unit 21 also calculates the second edge strength E(2) by integrating the second A edge strength E(2,1), the second B edge strength E(2,2), and the second C edge strength E(2,3), and calculates the second edge angle α(2) by integrating the second A edge angle α(2,1), the second B edge angle α(2,2), and the second C edge angle α(2,3).
[0098] Here, if the detection unit 21 determines that the first A edge strength E(1,1) is at or above the same level as the first B edge strength E(1,2) or the first C edge strength E(1,3), it sets the first A edge strength E(1,1) as the first edge strength E(1) and the first A edge angle α(1,1) as the first edge angle α(1). Also, if the detection unit 21 determines that the second A edge strength E(2,1) is at or above the same level as the second B edge strength E(2,2) or the second C edge strength E(2,3), it sets the second A edge strength E(2,1) as the second edge strength E(2) and the second A edge angle α(2,1) as the second edge angle α(2).
[0099] Figure 19 shows the flow of edge detection processing by the detection unit 21 in a modified example. First, the detection unit 21 sets the parameter i to "1" (step S20). Next, the detection unit 21 calculates E(i,k) and α(i,k) for k=1, 2, and 3 respectively (step S21).
[0100] Next, the detection unit 21 determines whether the value obtained by multiplying E(i,1) by the coefficient β is greater than or equal to E(i,2) (step S22). That is, the detection unit 21 determines whether E(i,1) is at or above the same level as E(i,2). The constant β is a positive value and may be 1. If the value obtained by multiplying E(i,1) by the coefficient β is greater than E(i,2) (step S22: YES), the detection unit 21 proceeds to step S24. If the value obtained by multiplying E(i,1) by the coefficient β is less than or equal to E(i,2) (step S22: NO), the detection unit 21 proceeds to step S23.
[0101] In step S23, it is determined whether the value obtained by multiplying E(i,1) by the coefficient β is greater than or equal to E(i,3). That is, the detection unit 21 determines whether E(i,1) is at or above the same level as E(i,3). The constant β is a positive value and may be 1. If the value obtained by multiplying E(i,1) by the coefficient β is greater than E(i,3) (step S23: YES), the detection unit 21 proceeds to step S24. If the value obtained by multiplying E(i,1) by the coefficient β is less than or equal to E(i,3) (step S23: NO), the detection unit 21 proceeds to step S26.
[0102] In step S24, the detection unit 21 sets E(i) = E(i,1). In the following step S25, the detection unit 21 sets α(i) = α(i,1).
[0103] In step S26, the detection unit 21 calculates E(i) using the following equation (9). The following equation (9) indicates that E(i) is the average value of E(i,k) for parameter k.
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[0104] Furthermore, the detection unit 21 calculates α(i) using the following equation (10) (step S27). The following equation (10) represents that α(i) is the weighted average of α(i,k) with E(i,k) as the weight.
number
[0105] After step S25 or step S27, the detection unit 21 determines whether parameter i is "2" or not (step S28). If parameter i is not "2" (step S28: NO), the detection unit 21 increments parameter i to "2" (step S29) and returns to step S21. After this, the detection unit 21 performs the same processing.
[0106] If parameter i is "2" (step S28: YES), the detection unit 21 calculates the integrated edge strength E and integrated edge angle α using equations (3) and (4) above (step S30). This completes the edge detection process.
[0107] As described above, when the high-frequency pattern in the first A region FR1A and the second A region FR2A is not symmetrical in the direction of extension of the linear defect, E(i,1) and α(i,1) are considered to be the integrated edge strength E and integrated edge angle α. On the other hand, when the high-frequency pattern in the first A region FR1A and the second A region FR2A is symmetrical in the direction of extension of the linear defect, the average value of E(i,k) and the weighted average value of α(i,k) are considered to be the integrated edge strength E and integrated edge angle α.
[0108] According to the edge detection process of this modified example, edges can be detected even when the high-frequency patterns in the first A region FR1A and the second A region FR2A are symmetrical in the direction of extension of the linear defect. The correction process performed by the correction unit 22 is the same as in the above embodiment.
[0109] Furthermore, it is preferable that the image processing unit 14 also includes a grid fringe removal processing unit that performs a process to remove grid fringes from the radiation image when a scatter removal grid 8 is attached to the cassette holder 7. The grid fringe removal processing unit detects whether or not the scatter removal grid 8 is attached, and if so, the direction and number of grids, and removes the grid fringes, which are high-frequency components. For example, the grid fringe removal processing unit removes the grid fringes from the radiation image and creates a radiation image having low-frequency components from which the grid fringes have been removed. In this case, the detection unit 21 performs edge detection processing and defective pixel correction processing on the radiation image after grid fringe removal.
[0110] Figure 20 shows the image processing flow by the image processing unit 14 according to a modified example. The flowchart shown in Figure 20 differs from the flowchart shown in Figure 11 only in that it includes steps S40 and S41 between steps S10 and S11. After step S10, the grid fringe removal processing unit determines whether or not the scattered radiation removal grid 8 is installed (step S40). If the grid fringe removal processing unit determines that the scattered radiation removal grid 8 is installed (step S40: YES), it performs the grid fringe removal processing described above on the radiation image acquired in step S10 (step S41). If the grid fringe removal processing unit determines that the scattered radiation removal grid 8 is not installed (step S40: NO), it proceeds to step S11.
[0111] The grid fringe removal processing unit may perform the grid fringe removal process after the LOG conversion process is performed in step S11.
[0112] In the above embodiment, the hardware structure of the Processing Unit, which performs various processes such as the acquisition unit 20, the detection unit 21, the correction unit 22, and the grid fringe removal processing unit, can be the various processors shown below. As mentioned above, the various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as a PLD (Programmable Logic Device), which is a processor whose circuit configuration can be changed after manufacturing, such as an FPGA (Field Programmable Gate Array), and a dedicated electrical circuit, which is a processor with a circuit configuration specifically designed to perform a particular process, such as an ASIC (Application Specific Integrated Circuit).
[0113] A single processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, and / or a combination of a CPU and an FPGA). Alternatively, multiple processing units may be composed of a single processor.
[0114] Examples of configuring multiple processing units with a single processor include, firstly, a configuration where one or more CPUs and software combine to form a single processor, as exemplified by client and server computers, and this processor functions as multiple processing units. Secondly, a configuration using a processor that realizes the functions of the entire system, including multiple processing units, on a single IC (Integrated Circuit) chip, as exemplified by System-on-a-Chip (SoC). Thus, various processing units are configured, in terms of hardware structure, using one or more of the above-mentioned processors.
[0115] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.
[0116] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. [Explanation of Symbols]
[0117] 2. Radiography System 3. Radiation Generating Devices 4 Radiation tubes 6. Information Processing Device 7 Cassette holder 7A Detection surface 8. Scatter Removal Grid 10 Control Unit 11 displays 12 Control section 13 Storage section 14 Image Processing Unit 15 Programs 16. Defective pixel data 20 Acquisition Department 21 Detection unit 22 Correction section α Integrated edge angle Fx, Fy Differential Filter H Subject Pi Normal Pixel Ps Correction Target Pixels R radiation FR1 1st area FR1A 1A area FR1B 1B area FR1C 1st C area FR2 2nd area FR2A 2ndA area FR2B 2nd B area FR2C 2nd C area
Claims
1. An information processing device that performs processing to correct line defects in radiographic images obtained by radiography, Equipped with a processor, The aforementioned processor, In the normal pixel regions on both sides separated by the line defect, a first region and a second region are set at positions opposite each other, with one pixel to be corrected selected from the line defect in between. The first edge strength and first edge angle of the first region are calculated, The second edge strength and second edge angle of the second region are calculated, By integrating the first edge strength and the second edge strength, an integrated edge strength representing the edge strength around the pixel to be corrected is calculated. By integrating the first edge angle and the second edge angle, an integrated edge angle representing the edge direction around the pixel to be corrected is calculated. The pixels to be corrected are corrected considering the integrated edge strength and the integrated edge angle. Information processing device.
2. The aforementioned processor, Two derivative values are calculated by applying two differential filters with different differential directions to the first and second regions, respectively. Based on the two differential values calculated from the first region, the first edge strength and the first edge angle are calculated. The second edge strength and the second edge angle are calculated based on the two differential values calculated from the second region. The information processing apparatus according to claim 1.
3. The first edge strength and the second edge strength are, respectively, the square root of the sum of the squares of the two differential values, or the sum of the absolute values of the two differential values. The information processing apparatus according to claim 2.
4. The first edge angle and the second edge angle are each represented by angles calculated by applying the ratio of the two derivative values to the arctangent function. The information processing apparatus according to claim 2.
5. Each of the aforementioned differential filters is either a Prewitt filter or a Sobel filter. The information processing apparatus according to claim 2.
6. The aforementioned processor, The average value of the first edge strength and the second edge strength is defined as the integrated edge strength. The combined edge angle is defined as the weighted average of the first edge angle and the second edge angle, with the first edge strength and second edge strength as the weights. The information processing apparatus according to claim 2.
7. The aforementioned processor, The first region and the second region are referred to as the first A region and the second A region, A first B region and a second B region are set by shifting the first A region and the second A region by one pixel in a first direction along the line defect, and a first C region and a second C region are set by shifting the first A region and the second A region by one pixel in a second direction opposite to the first direction. The first A edge strength and first A edge angle of the first A region are calculated. The first B edge strength and first B edge angle of the first B region are calculated, The first C edge strength and first C edge angle of the first C region are calculated. The 2A edge strength and 2A edge angle of the 2A region are calculated. The second B edge strength and second B edge angle of the second B region are calculated, The second C edge strength and second C edge angle of the second C region are calculated. Based on the first A edge strength, the first B edge strength, the first C edge strength, the first A edge angle, the first B edge angle, and the first C edge angle, the first edge strength and the first edge angle are calculated. Based on the 2A edge strength, 2B edge strength, 2C edge strength, 2A edge angle, 2B edge angle, and 2C edge angle, the 2nd edge strength and 2nd edge angle are calculated. The information processing apparatus according to claim 1.
8. The aforementioned processor, If the first A edge strength is at or above the level of the first B edge strength or the first C edge strength, then the first A edge strength and the first A edge angle are set as the first edge strength and the first edge angle. If the second A edge strength is at or above the level of the second B edge strength or the second C edge strength, then the second A edge strength and the second A edge angle shall be set as the second edge strength and the second edge angle. The information processing apparatus according to claim 7.
9. The aforementioned processor, If the first A edge strength is not at or above the level of the first B edge strength or the first C edge strength, the average of the first A edge strength, the first B edge strength, and the first C edge strength is set as the first edge strength, and the weighted average of the first A edge angle, the first B edge angle, and the first C edge angle, with the first A edge strength, the first B edge strength, and the first C edge strength as the weights, is set as the first edge angle. If the second A edge strength is not at or above the level of the second B edge strength or the second C edge strength, the average of the second A edge strength, the second B edge strength, and the second C edge strength is defined as the second edge strength, and the weighted average of the second A edge angle, the second B edge angle, and the second C edge angle, with the second A edge strength, the second B edge strength, and the second C edge strength as the weights, is defined as the second edge angle. The information processing apparatus according to claim 8.
10. The processor determines the presence or absence of edges around the pixel to be corrected by comparing the integrated edge strength with a threshold. The information processing apparatus according to claim 1.
11. The aforementioned processor, If the aforementioned edge exists, a first correction process is performed to correct the target pixel by assigning a first weight to each normal pixel within a mask set centered on the target pixel, which is the difference angle between the direction of the normal pixel from the target pixel and the edge direction, and the distance from the target pixel to the normal pixel. If the aforementioned edge is absent, a second correction process is performed to correct the target pixel by assigning a second weight to each of the normal pixels, which is independent of the difference angle and depends only on the distance. The information processing apparatus according to claim 10.
12. The aforementioned difference angle takes a value within the range of 0° to 180°. The first weight is expressed by including a function symmetric about 90°, which is maximum when the difference angle is 0° and 180°, and minimum when the difference angle is 90°. The information processing apparatus according to claim 11.
13. The aforementioned function is expressed as a power of the absolute value of the cosine of the difference angle, The information processing apparatus according to claim 12.
14. The first weight has less dependence on the distance than the second weight. The information processing apparatus according to claim 11.
15. The processor performs logarithmic transformation on the radiation image and calculates the integrated edge intensity and integrated edge angle using the radiation image after logarithmic transformation. The information processing apparatus according to claim 1.
16. The processor performs a grid fringe removal process on the radiation image to remove grid fringes using a scatter removal grid, and uses the radiation image after grid fringe removal to calculate the integrated edge intensity and integrated edge angle and correct the pixels to be corrected. The information processing apparatus according to claim 1.
17. An information processing method for correcting line defects in radiographic images obtained by radiography, In the normal pixel regions on both sides separated by the aforementioned line defect, a first region and a second region are set at positions opposite each other, with one pixel to be corrected selected from the line defect in between. To calculate the first edge strength and first edge angle of the first region, To calculate the second edge strength and second edge angle of the second region, By integrating the first edge strength and the second edge strength, an integrated edge strength representing the edge strength around the pixel to be corrected is calculated. By integrating the first edge angle and the second edge angle, an integrated edge angle representing the edge direction around the pixel to be corrected is calculated. Correcting the target pixel considering the integrated edge strength and integrated edge angle, Information processing methods including
18. A program that causes a computer to perform a process to correct line defects in radiographic images obtained by radiography, In the normal pixel regions on both sides separated by the aforementioned line defect, a first region and a second region are set at positions opposite each other, with one pixel to be corrected selected from the line defect in between. To calculate the first edge strength and first edge angle of the first region, To calculate the second edge strength and second edge angle of the second region, By integrating the first edge strength and the second edge strength, an integrated edge strength representing the edge strength around the pixel to be corrected is calculated. By integrating the first edge angle and the second edge angle, an integrated edge angle representing the edge direction around the pixel to be corrected is calculated. Correcting the target pixel considering the integrated edge strength and integrated edge angle, A program that causes a computer to perform a process that includes [a specific action].