Information processing device, information processing method, and program

Abstract

To provide an information processing device, an information processing method, and a program capable of accurately correcting a defective pixel present on an edge.SOLUTION: An information processing device executes processing for correcting a defective pixel of a radiation image acquired by radiographing, and includes a processor. The processor selects one defective pixel included in the radiation image as a pixel to be corrected, and detects presence or absence of an edge in the periphery of the selected pixel to be corrected. If there is the edge, the processor executes first correction processing for correcting the pixel to be corrected by subjecting each of normal pixels in a mask set with the pixel to be corrected as a center to a first weight according to a difference angle, which is an angle formed by a direction of the normal pixel from the pixel to be corrected and an edge direction, and a distance from the pixel to be corrected to the normal pixel. If there is no edge, the processor executes second correction processing for correcting the pixel to be corrected by subjecting each of the normal pixels to a second weight depending only on the distance without depending on the difference angle.SELECTED DRAWING: Figure 5

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] Radiological images may contain high-contrast edges, such as the contours of finger bones or thin metal wires in pacemakers. In the correction method described in Patent Document 1, as shown in Figure 17, when a thin line with a width of about 1 pixel intersects a line defect at an angle, interpolation is performed using only the horizontally normal pixels adjacent to the line defect. As a result, the correction accuracy is insufficient and correction residuals occur. In such cases, it is necessary to perform interpolation using the diagonally oriented normal pixels.

[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] The present invention aims to provide an information processing device, an information processing method, and a program that enable accurate correction of defective pixels present on edges. [Means for solving the problem]

[0010] To achieve the above objective, the information processing apparatus of the present disclosure is an information processing apparatus that performs processing to correct defective pixels in a radiographic image obtained by radiography, and comprises a processor, the processor selects one defective pixel in the radiographic image as a pixel to be corrected, detects the presence or absence of an edge around the selected pixel to be corrected, and if an edge is present, performs a first correction process to correct the pixel to be corrected by assigning a first weight to each normal pixel in a mask set centered on the pixel to be corrected, which is the difference angle between the direction of the normal pixel from the pixel to be corrected and the edge direction, and the distance from the pixel to the normal pixel, and if there is no edge, performs a second correction process to correct the pixel to be corrected by assigning a second weight to each normal pixel that does not depend on the difference angle but depends only on the distance.

[0011] Preferably, the difference angle takes a value within the range from 0° to 180°, and the first weight is represented by including a function that is maximum when the difference angle is 0° and 180°, minimum when the difference angle is 90°, and is symmetric about 90°.

[0012] Preferably, the function is represented by a power of a value obtained by taking the absolute value of the cosine of the difference angle.

[0013] Preferably, the first weight has lower dependence on distance than the second weight.

[0014] Preferably, the processor calculates two differential values using two differential filters having different differential directions, calculates edge strength based on the two differential values, and detects the presence or absence of an edge by comparing the edge strength with a threshold value.

[0015] Preferably, the edge strength is the square root of the sum of squares of the two differential values, or the sum of the absolute values of the two differential values.

[0016] Preferably, the processor calculates an edge direction based on the two differential values.

[0017] Preferably, the edge direction is represented by an angle calculated by applying a ratio of the two differential values to an arctangent function.

[0018] Preferably, each of the differential filters is a Prewitt filter or a Sobel filter.

[0019] The processor may calculate, for a plurality of directions, absolute differences between pixel values of a pair of normal pixels that are point-symmetric with respect to a correction target pixel, calculate edge strength based on a maximum value, a sum, or a square root of sum of squares of the plurality of calculated absolute differences, and detect the presence or absence of an edge by comparing the edge strength with a threshold value.

[0020] Preferably, the processor detects, as the edge direction, the direction in which the minimum value among the plurality of absolute differences is obtained.

[0021] Preferably, when either of the pair of pixels selected as a pair of normal pixels is a defective pixel, the processor searches for a normal pixel in a direction away from the correction target pixel while maintaining the angle of the pair of pixels, and selects the normal pixel found as a result of the search.

[0022] Preferably, the processor performs LOG conversion processing on the radiation image, and detects the presence or absence of an edge using the radiation image after LOG conversion.

[0023] Preferably, the processor performs grid stripe removal processing for removing grid stripes caused by a scattered radiation removal grid on the radiation image, and detects the presence or absence of an edge and corrects the correction target pixel using the radiation image after grid stripe removal.

[0024] An information processing method of the present disclosure is an information processing method that performs processing for correcting defective pixels in a radiation image obtained by radiography, the method comprising: selecting one defective pixel included in the radiation image as a correction target pixel; detecting the presence or absence of an edge around the selected correction target pixel; when there is an edge, performing a first correction process of correcting the correction target pixel by assigning a first weight to each normal pixel in a mask set centered on the correction target pixel, the first weight being determined in accordance with a difference angle, which is an angle formed between the direction of the normal pixel from the correction target pixel and the edge direction, and a distance from the correction target pixel to the normal pixel; and when there is no edge, performing a second correction process of correcting the correction target pixel by assigning a second weight that depends only on the distance without depending on the difference angle to each normal pixel.

[0025] The program of this disclosure is a program that causes a computer to perform a process to correct defective pixels in a radiographic image obtained by radiography, and the program causes the computer to perform a process that includes: selecting one defective pixel in the radiographic image as a pixel to be corrected; detecting the presence or absence of an edge around the selected pixel to be corrected; if an edge is present, performing a first correction process in which each normal pixel in a mask set with the pixel to be corrected as the center is given a first weight corresponding to the difference angle, which is the angle between the direction of the normal pixel from the pixel to be corrected and the direction of the edge, and the distance from the pixel to the normal pixel; and if there is no edge, performing a second correction process in which each normal pixel is given a second weight that does not depend on the difference angle but depends only on the distance.

[0026] The technology disclosed herein provides an information processing device, an information processing method, and a program that enable accurate correction of defective pixels present on edges. [Brief explanation of the drawing]

[0027] [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 shifting the coefficients when a defective pixel is located at the position of the coefficients of a differential filter. [Figure 5] This diagram illustrates the correction process for point defects present on edges. [Figure 6] This diagram illustrates the correction process for line defects, including defective pixels located on edges. [Figure 7] This figure shows the dependence of the weight expressed by equation (4) on the difference angle. [Figure 8] This figure shows the dependence of the weight expressed by equation (4A) on the difference angle. [Figure 9]This flowchart shows an example of the image processing flow by the image processing unit. [Figure 10] This is a diagram showing the Prewitt filter. [Figure 11] This figure shows the Sobel filter. [Figure 12] This figure shows an example of a differential filter that performs differentiation in an oblique direction. [Figure 13] This figure shows an example of multiple masks used for edge detection. [Figure 14] This figure shows other examples of multiple masks used for edge detection. [Figure 15] This figure shows an example of searching for a normal pixel while maintaining the angle between a pair of pixels. [Figure 16] This flowchart shows the image processing flow by the image processing unit related to the modified example. [Figure 17] This diagram illustrates the problems with conventional correction methods. [Modes for carrying out the invention]

[0028] An example of an embodiment relating to the technology of this disclosure will be described with reference to the attached drawings.

[0029] [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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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 on the radiation image.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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).

[0041] 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.

[0042] The detection unit 21 performs edge detection by calculating two differential values ​​using two differential filters with different differential directions. In this embodiment, the detection unit 21 performs LOG conversion on the radiation image and performs edge detection on the radiation image after LOG conversion. LOG conversion is a type of grayscale conversion. By performing LOG conversion on a radiation image whose 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.

[0043] 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).

[0044] The detection unit 21 applies differential filters Fx and Fy respectively with the correction target pixel Ps as the center to obtain a differential value Δ X QL(X,Y) and Δ Y QL(X,Y). The correction target pixel Ps is one defective pixel included in the radiation image. The central coefficients of the differential filters Fx and Fy corresponding to the correction target pixel Ps are 0. The differential value Δ X QL(X,Y) is the difference between pixel values of normal pixels adjacent to the correction target pixel Ps in the X direction. The differential value Δ Y QL(X,Y) is the difference between pixel values of normal pixels adjacent to the correction target pixel Ps in the Y direction.

[0045] After calculating the differential value Δ X QL(X,Y) and Δ Y QL(X,Y), the detection unit 21 calculates the edge strength Ei using the following formula (1). The following formula (1) represents that the square root of the sum of squares of the differential value Δ X QL(X,Y) and Δ Y QL(X,Y) is taken as the edge strength E. [Formula]

[0046] The detection unit 21 may calculate the edge strength E using the following formula (1A) instead of the above formula (1). The following formula (1A) represents that the sum of absolute values of the differential value Δ X QL(X,Y) and Δ Y QL(X,Y) is taken as the edge strength E. [Formula]

[0047] The detection unit 21 compares the calculated edge strength E with a threshold to determine whether there is an edge around the correction target pixel Ps. The detection unit 21 determines that an edge exists when the edge strength E is equal to or greater than the threshold, and determines that no edge exists when the edge strength E is less than the threshold.

[0048] Further, the detection unit 21 calculates the differential value ΔX QL(X,Y) and Δ Y After calculating QL(X,Y), the edge angle α 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 by applying the ratio of QL(X,Y) to the arctangent function.

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[0049] The detection unit 21 supplies the edge detection result (i.e., whether or not there is an edge, and the edge angle α if there is an edge) to the correction unit 22.

[0050] Furthermore, when the detection unit 21 applies the differential filters Fx and Fy, if the pixel corresponding to a position where the coefficient is not zero is a defective pixel, it moves the position of the coefficient outward by at least one pixel while maintaining the direction from the corrected pixel Ps to the coefficient. In other words, the detection unit 21 moves the coefficient outward until the position of the coefficient becomes a normal pixel. For example, as shown in Figure 4, if the position of the coefficient "-1" of the differential filter Fx is a defective pixel, the detection unit 21 moves the position of the coefficient "-1" away from the corrected pixel Ps in the -X direction.

[0051] 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, and corrects the pixel Ps to be corrected using a weighted sum of the pixel values ​​of the normal pixels included within the mask.

[0052] Figure 5 illustrates the correction process for point defects present on edges. The mask size shown in Figure 5 is 5x5 pixels. θ(X,Y) represents the angle with respect to the X direction of the line connecting one pixel in the mask and the pixel to be corrected Ps. D(X,Y) represents the distance between the pixel and the pixel to be corrected Ps. In this example, one defective pixel (point defect) on an edge is selected as the pixel to be corrected Ps, and the coordinates of the pixel to be corrected Ps are set as the origin.

[0053] 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 (3) to (5). The Σ in equation (3) means that the addition is performed by changing X and Y within the ranges of -2≦X≦2 and -2≦Y≦2 (excluding the origin).

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[0054] Furthermore, the weight W(X,Y) in equation (3) above is expressed by equation (4) below. In equation (4) below, n and m are parameters, which can be set to positive integers, for example.

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[0055] Furthermore, the difference angle δ(X,Y) in equation (4) above is expressed by equation (5) 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°.

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[0056] Equation (4) 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°.

[0057] Equations (3) to (5) 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 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.

[0058] Figure 6 illustrates the correction process for line defects, including defective pixels located on edges. The correction process for line defects is similar to that for point defects; defective pixels are excluded from the pixels included in the mask, and QL(0,0) is calculated.

[0059] In the case of point defects and line defects, the correction unit 22 may use the lower equation (4A) instead of the upper equation (4) when correcting defective pixels that exist on the edge.

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[0060] Figure 7 shows the dependence of the weight W(X,Y) expressed by equation (4) above on the difference angle δ(X,Y). Figure 8 shows the dependence of the weight W(X,Y) expressed by equation (4A) above on the difference angle δ(X,Y). As shown in Figures 7 and 8, 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.

[0061] 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.

[0062] The weight W(X,Y) expressed by equation (4) or (4A) 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.

[0063] Hereinafter, the correction process using the weight W(X,Y) represented by equation (4) or equation (4A) 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 (4) or equation (4A) above is an example of the "first weight" relating to the technology of this disclosure.

[0064] If the edge strength E is less than the threshold, i.e., if there is no edge, the correction unit 22 performs the correction process using the lower equation (4B) instead of the upper equation (4).

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[0065] Equation (4B) above is obtained by setting δ(X,Y)=0 in equation (4) or equation (4A) above. That is, the weight W(X,Y) expressed in equation (4B) 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 (4B) 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.

[0066] 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.

[0067] 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.

[0068] Note that the mask size is not limited to 5x5 pixels; it may also be 3x3, 7x7, 9x9, etc. For example, when correcting pixels on line defects with a width of 2 pixels, using a larger mask such as 7x7 or 9x9 pixels improves the correction accuracy by increasing 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 mask size according to the pattern to be corrected.

[0069] Figure 9 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, the detection unit 21 selects one defective pixel as the pixel to be corrected Ps based on the defective pixel data 16 stored in the storage unit 13 (step S12).

[0070] Next, the detection unit 21 performs edge detection processing by applying differential filters Fx and Fy, respectively, centered on the pixel Ps to be corrected (step S13). Specifically, the detection unit 21 calculates the edge intensity E and the edge angle α.

[0071] 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 edge intensity E is greater than or equal to a threshold, and determines that there is no edge if the edge intensity E is less than the threshold.

[0072] If there is an edge (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 an isotropic second correction process that does not take the edge direction into consideration (step S16).

[0073] After performing the first or second correction process, the correction unit 22 determines whether or not the correction of all defective pixels has been completed (step S17). If the correction unit 22 determines that the correction of all defective pixels 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 has been completed (step S17: YES), it terminates the process.

[0074] In conventional correction methods, if a defective pixel exists on a high-contrast edge, a correction residual is visible in the corrected radiographic image. In particular, the correction residual is significant in high-contrast and high-frequency patterns. In contrast, in the correction method according to this disclosure, if there is an edge around a defective pixel Ps selected as the pixel to be corrected from the radiographic image, the pixel to be corrected Ps is corrected by assigning a first weight W(X,Y) to each normal pixel within a mask set centered on the pixel to be corrected Ps, which is the difference angle δ(X,Y) between the direction of the normal pixel from the pixel to be corrected Ps and the edge direction, and the distance D(X,Y) from the pixel to be corrected Ps to the normal pixel. This allows for accurate correction of defective pixels present on edges. In particular, good correction results without correction residuals can be obtained even for line defects spanning edges.

[0075] [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 10 or Figure 11 may be used. The differential filters Fx and Fy shown in Figure 10 are called Prewitt filters. The differential filters Fx and Fy shown in Figure 11 are called Sobel filters. By using a Prewitt filter or a Sobel filter, the influence of noise can be reduced.

[0076] Furthermore, the detection unit 21 may use the differential filters Fx and Fy shown in Figure 12, 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 12, the coefficients "1" and "-1" are arranged obliquely. That is, the differential filters Fx and Fy shown in Figure 12 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.

[0077] Alternatively, instead of using a differential filter for detection, the detection unit 21 may perform edge detection by calculating the absolute difference in pixel values ​​of a pair of normal pixels that are point-symmetric with respect to the pixel Ps to be corrected, in multiple directions. For example, the detection unit 21 applies one of the eight types of masks shown in Figure 13 to a region centered on the pixel Ps to be corrected. The eight types of masks shown in Figure 13 have a mask size of 5 × 5 pixels and each has a pair of normal pixels Pi that are point-symmetric with respect to the pixel Ps to be corrected. Each mask has a different orientation for the pair of normal pixels Pi. In Figure 13, the pixels with hatched diagonal lines are the normal pixels Pi used for edge detection.

[0078] The detection unit 21 calculates the absolute difference value using the entire mask and finds the maximum and minimum values ​​of the multiple calculated absolute difference values. The detection unit 21 detects the presence or absence of an edge by comparing the maximum value with a threshold. Specifically, the detection unit 21 determines that an edge exists if the maximum value is greater than or equal to the threshold, and determines that there is no edge if the maximum value is less than the threshold. Alternatively, the detection unit 21 may detect the presence or absence of an edge by comparing the sum of the multiple absolute difference values, or the square root of the sum of the squares of the multiple absolute difference values, with the threshold instead of the maximum value of the multiple absolute difference values.

[0079] Furthermore, if an edge is present, the detection unit 21 detects the direction in which the minimum value of multiple absolute difference values ​​is obtained as the edge direction.

[0080] The detection unit 21 may use a mask larger than 5x5 pixels. For example, the detection unit 21 may use a mask with a size of 7x7 pixels as shown in Figure 14. By using a size of 7x7 pixels, the orientation of a pair of normal pixels Pi can be set more precisely, resulting in 16 types of masks. By using such a large-sized mask, the edge direction can be detected with greater accuracy.

[0081] The orientation of a pair of normal pixels Pi can be defined by the angle of the line connecting the pair of normal pixels Pi, or by the angle of the line connecting one normal pixel Pi and the pixel Ps to be corrected. Specifically, if the distance between the pixels in the X direction is ΔX and the distance between the pixels in the Y direction is ΔY, then the angle is tan. -1 It is defined as (ΔY / ΔX).

[0082] Furthermore, in order to correct the target pixel Ps, both pixels selected as the pair of normal pixels Pi mentioned above must not be defective pixels. Therefore, if either of the pair of pixels is a defective pixel, the normal pixel Pi should be searched for in the direction away from the target pixel Ps while maintaining the angle of the pair of pixels, and the normal pixel Pi found as a result of the search should be selected. Figure 15 shows the process of searching for a normal pixel Pi while maintaining the angle of 26.6° when one of a pair of pixels with an angle of 26.6° is a defective pixel. However, the pair of normal pixels Pi selected as a result will have different distances from the target pixel Ps, so they will not be point-symmetric with respect to the target pixel Ps.

[0083] Furthermore, since performing edge detection using a pair of normal pixels Pi that are more than a certain distance away from the pixel Ps to be corrected may reduce detection accuracy, it is preferable to limit the search range so that the distance of the pair of normal pixels Pi from the pixel Ps to be corrected is less than a certain value. In this case, if a pair of normal pixels Pi is not found within a certain distance from the pixel Ps to be corrected, the angle between them can be ignored and the edge detection process can be performed.

[0084] In this modified example, it is preferable that the detection unit 21 performs edge detection processing on the radiation image after LOG conversion. However, the correction unit 22 may perform correction processing on the radiation image before LOG conversion.

[0085] 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.

[0086] Figure 16 shows the image processing flow by the image processing unit 14 according to a modified example. The flowchart shown in Figure 16 differs from the flowchart shown in Figure 9 only in that it includes steps S20 and S21 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 S20). If the grid fringe removal processing unit determines that the scattered radiation removal grid 8 is installed (step S20: YES), it performs the grid fringe removal processing described above on the radiation image acquired in step S10 (step S21). If the grid fringe removal processing unit determines that the scattered radiation removal grid 8 is not installed (step S20: NO), it proceeds to step S11.

[0087] The grid fringe removal processing unit may perform the grid fringe removal process after the LOG conversion process is performed in step S11.

[0088] 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).

[0089] 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.

[0090] 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.

[0091] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices.

[0092] 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]

[0093] 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 edge angle Fx, Fy Differential Filter H Subject Pi Normal Pixel Ps Correction Target Pixels R radiation

Claims

1. An information processing device that performs processing to correct defective pixels in a radiographic image obtained by radiography, Equipped with a processor, The aforementioned processor, Select one defective pixel in the aforementioned radiation image as the pixel to be corrected, and detect the presence or absence of edges around the selected pixel to be corrected. If an edge exists, the edge direction, which is the direction of the edge, is detected, and a first correction process is performed to correct the target pixel by assigning a first weight to each normal pixel within a mask set with the target pixel as the center, which weight corresponds to the difference angle, which is the angle between the direction of the normal pixel from the target pixel and the detected 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. Information processing device.

2. 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 1.

3. 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 2.

4. The first weight has less dependence on the distance than the second weight. The information processing apparatus according to claim 1.

5. The aforementioned processor, Two derivative values ​​are calculated using two differential filters with different differential directions. The edge strength is calculated based on the two derivative values ​​mentioned above. The presence or absence of the edge is detected by comparing the edge strength with a threshold. The information processing apparatus according to claim 1.

6. The edge strength is 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 5.

7. The processor calculates the edge direction based on the two derivative values. The information processing apparatus according to claim 5.

8. The aforementioned edge direction is represented by the angle calculated by applying the ratio of the two derivative values ​​to the arctangent function. The information processing apparatus according to claim 7.

9. Each of the aforementioned differential filters is either a Prewitt filter or a Sobel filter. The information processing apparatus according to claim 5.

10. The aforementioned processor, The absolute difference between the pixel values ​​of a pair of normal pixels that are point-symmetric with respect to the pixel to be corrected is calculated in multiple directions, and the edge strength is calculated based on the maximum value, sum, or square root of the sum of the calculated absolute difference values. The presence or absence of the edge is detected by comparing the edge strength with a threshold. The information processing apparatus according to claim 1.

11. The processor detects the direction in which the minimum value of the multiple absolute difference values ​​is obtained as the edge direction. The information processing apparatus according to claim 10.

12. The processor, if either of the pair of pixels selected as the pair of normal pixels is a defective pixel, searches for a normal pixel in a direction away from the pixel to be corrected while maintaining the angle of the pair of pixels, and selects the normal pixel found as a result of the search. The information processing apparatus according to claim 10.

13. The processor performs logarithmic transformation on the radiation image and uses the logarithmic transformation of the radiation image to detect the presence or absence of the edge. The information processing apparatus according to claim 1.

14. 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 detect the presence or absence of edges and correct the pixels to be corrected. The information processing apparatus according to claim 1.

15. An information processing method for correcting defective pixels in a radiographic image obtained by radiography, Select one defective pixel in the aforementioned radiation image as the pixel to be corrected, and detect the presence or absence of edges around the selected pixel to be corrected. If an edge exists, the edge direction, which is the direction of the edge, is detected, and a first correction process is performed to correct the target pixel by assigning a first weight to each normal pixel within a mask set with the target pixel as the center, the difference angle which is the angle between the direction of the normal pixel from the target pixel and the detected 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. Information processing methods including

16. A program that causes a computer to perform a process to correct defective pixels in radiographic images obtained by radiography, Select one defective pixel in the aforementioned radiation image as the pixel to be corrected, and detect the presence or absence of edges around the selected pixel to be corrected. If an edge exists, the edge direction, which is the direction of the edge, is detected, and a first correction process is performed to correct the target pixel by assigning a first weight to each normal pixel within a mask set with the target pixel as the center, the difference angle which is the angle between the direction of the normal pixel from the target pixel and the detected 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. A program that causes a computer to perform a process that includes [a specific action].

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