Analysis method, display device, and program

Abstract

According to the present invention, variations in feature quantities and feature quantity settings can be suppressed, thereby improving analysis accuracy. This analysis method (image analysis processing) performed by an information processing device for Talbot images obtained by imaging a subject using an X-ray Talbot imaging device includes: a determination step (step S13) for determining an analysis rule for the subject from among a plurality of preset analysis rules; and an image analysis step (step S15) for using the determined analysis rule to analyze the Talbot images obtained by imaging the subject.

Description

Analysis method, display device and program

[0001] The present invention relates to an analysis method, a display device, and a program.

[0002] In composite materials, which have been attracting attention in recent years, not only the material itself but also the fine internal structure of the composite material has a significant impact on its mechanical properties. For example, CFRP (Carbon Fiber Reinforced Plastics) has a three-dimensional structure due to the weave and orientation of the carbon fibers, and its mechanical strength is greatly affected by the fiber orientation and fiber density.

[0003] X-ray Talbot imaging systems using Talbot interferometers or Talbot-Lau interferometers, which utilize the Talbot effect, have become increasingly popular for inspecting such composite materials. The Talbot effect refers to the phenomenon in which, when coherent light passes through a first grating with slits at regular intervals, a grating image is formed at regular intervals in the direction of light propagation. This grating image is called a self-image. A Talbot interferometer places a second grating at the position where the self-image is formed, and measures the resulting moiré fringes by slightly shifting the second grating. Since placing an object in front of the second grating disrupts the moiré, X-ray imaging using a Talbot interferometer or Talbot-Lau interferometer allows for the object to be placed in front of or behind the first grating, irradiated with coherent X-rays, and then imaged using the resulting moiré fringes to obtain a display image of the object. Compared to conventional X-ray inspection systems and X-ray absorption CT, X-ray Talbot imaging systems can simultaneously obtain multiple Talbot images, including absorption images, differential phase images, small-angle scattering images, and orientation analysis images.

[0004] Meanwhile, with the recent development of machine learning and AI (artificial intelligence), it is possible to select feature quantities related to mechanical properties by setting feature quantities acquired by analyzing a Talbot image as explanatory variables, setting mechanical properties as objective variables, and having an information processing device perform analysis using machine learning or AI. The analysis of the Talbot image is performed in an analysis region manually set by a user, and feature quantities of the analysis region are acquired.

[0005] Furthermore, Patent Document 1 describes dividing an X-ray transmission image generated by an X-ray transmission inspection device into regions, and managing inspection results for each region.

[0006] Japanese Patent Application Laid-Open No. 2021-124394

[0007] As described above, before performing machine learning, it is necessary to analyze Talbot images and acquire feature values. When acquiring feature values, the analysis area is manually set by the user, which results in variability between users. Therefore, the feature values ​​themselves set in machine learning are prone to variability. Furthermore, when feature values ​​acquired from Talbot images are used as explanatory variables in machine learning, the setting of feature values ​​is prone to variability between users. This is because, as described above, there are many types of Talbot images, and Talbot images also include images that depend on the angle formed by the orientation of the subject and the orientation of the grid, further increasing the variety. In other words, not only are the feature values ​​themselves prone to variability, but the selection of feature values ​​to be used in machine learning is also prone to variability.

[0008] Therefore, an object of the present invention is to suppress variations in feature amounts and feature amount settings and improve analysis accuracy.

[0009] In order to solve the above problems, the analysis method of the present invention is a method for analyzing a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device, and includes: a selection step of selecting an analysis rule for the Talbot image from a plurality of predetermined analysis rules; and an image analysis step of analyzing the Talbot image using the selected analysis rule.

[0010] Furthermore, the display device of the present invention is a display device that displays a method for analyzing a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device, and includes a selection area that allows the user to select an analysis rule for the Talbot image.

[0011] Furthermore, the program of the present invention causes a computer of an analysis device for a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device to function as: a selection unit that selects an analysis rule for the Talbot image from a plurality of pre-set analysis rules; and an image analysis unit that analyzes the Talbot image using the selected analysis rule.

[0012] According to the present invention, variations in feature amounts and feature amount settings can be suppressed, and analysis accuracy is improved.

[0013] FIG. 1 is a schematic diagram showing an overall image of an X-ray Talbot imaging device. FIG. 2 is a block diagram showing a schematic configuration of an information processing device. FIG. 3 is a display example of a sample shape registration screen. FIG. 4 is a display example of an analysis area registration screen. FIG. 5 is a flow chart showing analysis rule setting processing. FIG. 6 is a display example of an analysis rule setting screen. FIG. 7 is a flow chart showing image analysis processing. FIG. 8 is a display example of an image analysis execution screen. FIG. 9 is an image diagram of a range (analysis area) around a fracture position. FIG. 10 is an example of an optical image after destructive testing. FIG. 11 is an example of a combination of explanatory variables and objective variables. FIG. 12 is an image diagram of a sample including a weld line and a profile.

[0014] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, although the embodiments described below are subject to various technically preferable limitations for carrying out the present invention, the technical scope of the present invention is not limited to the following embodiments and illustrated examples.

[0015] In this embodiment, a method for analyzing a Talbot image of a subject H captured using an X-ray Talbot imaging device 10 by an information processing device 20 will be described. The analysis system 1 shown in Fig. 1 includes the X-ray Talbot imaging device 10, a controller 19, and an information processing device 20. The X-ray Talbot imaging device 10 is connected to the information processing device 20 via the controller 19 and a communication network N. The communication network N may be a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or the like.

[0016] [About the Subject] Here, we will explain the subject H. The subject H (sample) in this embodiment is made of a composite material (also called a composite material), and is used as a component of various products, such as space and aircraft related products, automobiles, ships, fishing rods, as well as electrical, electronic, and home appliance parts, parabolic antennas, bathtubs, flooring materials, roofing materials, etc. Known examples of such composite materials include CFRP (Carbon-Fiber-Reinforced Plastics), CFRTP (Carbon Fiber Reinforced Thermo Plastics), and FRP (Fiber-Reinforced Plastics) such as GFRP (Glass-Fiber-Reinforced Plastics), which use carbon fiber or glass fiber as reinforcing fibers, and CMC (Ceramic Matrix Composites), which use ceramic fiber as a reinforcing material. In a broad sense, the term may also include composite materials made of multiple types of wood, such as plywood. In addition, composite materials that do not contain fibers, such as MMC (Metal Matrix Composites) concrete and reinforced concrete, may also be included. Resins used in composite materials include, but are not limited to, general-purpose plastics, engineering plastics, and super engineering plastics. Resins are often used as resin composite materials to which fillers with micro- or nano-sized structures are added to impart specific properties such as strength, and are used as plastic molded products. Fillers include organic materials, inorganic materials, magnetic materials, and metal materials. For example, when strength and rigidity are required in plastic molded products, composite materials such as PPS, POM, PA, PC, and PP as resins and aramid fiber, talc, and cellulose fiber as fillers may be used. Furthermore, when the plastic molded product is a plastic-based composite, composite materials such as nylon as resin and strontium ferrite and samarium cobalt as fillers may be used.

[0017] The subject H is a molded product manufactured by pouring the composite material into a mold or extruding the composite material into a sheet, and then cut into a sample shape for various tests. Here, in the subject H, the direction of resin flow when the composite material is poured into the mold is called the MD (machine direction) direction, the direction perpendicular to the MD direction in the horizontal plane is called the TD (transverse direction) direction, and the direction perpendicular to the MD-TD plane is called the ND (normal direction) direction. Note that the subject H may be the molded product itself.

[0018] [Regarding the X-ray Talbot Imaging Device] In this embodiment, the X-ray Talbot imaging device 10 uses a Talbot-Lau interferometer equipped with a source grating 12. Note that it is also possible to use an X-ray Talbot imaging device that does not include the source grating 12 but uses a Talbot interferometer equipped only with a first grating 14 and a second grating 15.

[0019] 1 is a schematic diagram showing an overall view of an X-ray Talbot imaging device 10. The X-ray Talbot imaging device 10 according to this embodiment includes an X-ray generator 11, a source grating 12, a subject table 13, a first grating 14, a second grating 15, an X-ray detector 16, a support 17, and a base 18. The grating directions of the source grating 12, the first grating 14, and the second grating 15 are the same.

[0020] With this X-ray Talbot imaging device 10, at least three types of images (two-dimensional images) can be reconstructed (referred to as reconstructed images) by capturing a moiré image Mo of a subject H located at a predetermined position relative to the subject table 13 using a method based on the principles of fringe scanning and analyzing the moiré image Mo using a Fourier transform. These three types of images include an absorption image (same as a normal X-ray absorption image) that visualizes the average component of the moiré fringes in the moiré image Mo, a differential phase image that visualizes the phase information of the moiré fringes, and a small-angle scattering image that visualizes the visibility of the moiré fringes. Of the reconstructed images, the differential phase image and the small-angle scattering image have angle dependence with respect to the lattice direction. Specifically, if the lattice direction is defined as an angle of 0° in the 12 o'clock direction and as clockwise, a small-angle scattering image with a lattice direction in the up-down direction can be defined as a small-angle scattering image (lattice angle 0°), a small-angle scattering image with a lattice direction in the left-right direction can be defined as a small-angle scattering image (lattice angle 90°), and an image with a lattice angle intermediate between the two can be defined as a small-angle scattering image (lattice angle 45°) or a small-angle scattering image (lattice angle 135°).

[0021] Even more types of images can be generated by recombining the three types of reconstructed images. For example, small-angle scattering images captured at multiple (three or more) grating opposing angles are used, and after aligning each image, fitting is performed for each pixel using a sine wave to extract fitting parameters. The sine wave graph has the relative angle between the sample and the grating on the horizontal axis and the small-angle scattering signal value of a given pixel on the vertical axis. The fitting parameters are the amplitude, average, and phase of the sine wave. An image representing the amplitude value for each pixel is called the orientation image, an image showing the average value for each pixel is called the scattering intensity image, and an image showing the phase for each pixel is called the orientation angle image. Note that the fitting method is not limited to the sine wave. Hereinafter, the images (orientation image, scattering intensity image, and orientation angle image) generated by recombining the reconstructed images are referred to as the orientation analysis image. In other words, the orientation analysis image is generated based on multiple small-angle scattering images captured by changing the relative angle of the subject with respect to the grating slits of the X-ray Talbot imaging device, and is an image that reflects the grating angle dependency.

[0022] It is also possible to perform image processing such as filtering, clarification, and contour extraction on the reconstructed image and the orientation analysis image, as well as image processing for combining two or more types of images. Hereinafter, an image that has undergone such image processing will be referred to as a secondary image. If the reconstructed image that is the basis of the secondary image contains an element that has angle dependency, the secondary image will also have angle dependency.

[0023] Hereinafter, the term "Talbot photography" will refer to not only the photography of the moiré image Mo, but also the generation of the reconstructed image, orientation analysis image, and secondary image described above. Also, hereinafter, the reconstructed image, orientation analysis image, and secondary image will be collectively referred to as "Talbot images."

[0024] The fringe scanning method is a method in which one of multiple gratings is moved in the direction of the slit period by 1 / M of the grating slit period (M is a positive integer, M>2 for absorption images, and M>3 for differential phase images and small-angle scattering images) and then a moiré image Mo is captured M times, and reconstruction is performed using the captured image to obtain a high-resolution reconstructed image.

[0025] The Fourier transform method is a method in which, in the presence of a subject, one moiré image Mo is captured using an X-ray Talbot imaging device, and then, in image processing, the moiré image Mo is subjected to a Fourier transform or the like to reconstruct and generate an image such as a differential phase image.

[0026] The configuration of other parts of the X-ray Talbot imaging device 10 according to this embodiment will be described. This embodiment is a so-called vertical type, in which the X-ray generator 11, source grating 12, subject table 13, first grating 14, second grating 15, and X-ray detector 16 are arranged in this order in the z direction, which is the direction of gravity. That is, in this embodiment, the z direction is the irradiation direction of X-rays from the X-ray generator 11.

[0027] The X-ray generator 11 includes an X-ray source 11a, such as a Coolidge X-ray source or a rotating anode X-ray source, which are widely used in medical settings. Other X-ray sources may also be used. The X-ray generator 11 of this embodiment irradiates X-rays in a cone beam shape from a focal point. That is, as shown in FIG. 1 , the X-rays are irradiated so that they spread out as they move away from the X-ray generator 11, with the X-ray irradiation axis Ca coinciding with the z direction as the central axis (i.e., the X-ray irradiation range).

[0028] In this embodiment, the controller 19 (see FIG. 1) is configured by a computer having a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), an input / output interface, etc., all of which are not shown, connected to a bus. The controller 19 is also provided with appropriate means and devices, such as input means including an operation unit, output means, storage means, and communication means, all of which are not shown.

[0029] The controller 19 performs overall control of the X-ray Talbot imaging device 10. That is, for example, the controller 19 is connected to the X-ray generator 11, and is capable of setting the tube voltage, tube current, irradiation time, etc. of the X-ray source 11a.

[0030] [Regarding the Information Processing Device] In this embodiment, a general-purpose computer device (control PC) is used as the information processing device 20 that executes various processes. However, this is not limited to this, and some of the functions of the information processing device 20 may be provided on a network so that each process can be executed by exchanging data via communication. As shown in Figure 2, the information processing device 20 includes a control unit 21, an operation unit 22, a communication unit 23, a storage unit 24, and a display unit 25.

[0031] The control unit 21 is composed of a CPU (Central Processing Unit), RAM (Random Access Memory), etc. The CPU of the control unit 21 reads out various programs stored in the storage unit 24, loads them into the RAM, and executes various processes (e.g., the analysis rule setting process described below) in accordance with the loaded programs, thereby controlling the operation of each unit of the information processing device 20. The control unit 21 functions as a display control unit that displays a first screen including a selection area for selecting an analysis rule for the subject. The control unit 21 functions as a determination unit that determines an analysis rule for the subject automatically and / or by user selection from a plurality of pre-set analysis rules. The control unit 21 functions as an image analysis unit that analyzes a Talbot image of the subject using the determined analysis rule.

[0032] The operation unit 22 is a keyboard equipped with cursor keys, numeric input keys, various function keys, etc., a pointing device such as a mouse, a touch panel laminated on the surface of the display unit 25, etc. The operation unit 22 is configured to be operable by an operator, and outputs various signals to the control unit 21 based on operations performed by the operator.

[0033] The communication unit 23 is capable of transmitting and receiving various signals and various data to and from other devices connected via the communication network N.

[0034] The storage unit 24 is configured by a non-volatile semiconductor memory, a hard disk, or the like, and stores various programs executed by the control unit 21, parameters required for executing the programs, various data (for example, Talbot images), and the like.

[0035] The display unit 25 is configured with a monitor such as an LCD (Liquid Crystal Display), and displays various screens and the like in accordance with instructions of a display signal input from the control unit 21 .

[0036] [Regarding Advance Preparation] Here, advance preparation for the analysis rule setting process described below will be described. The advance preparation includes Talbot photography, sample shape registration, analysis region registration, and analysis method registration.

[0037] As the details of the Talbot imaging have been described above, a detailed description thereof will be omitted. As a preliminary step, various Talbot images for each sample are generated by the X-ray Talbot imaging device 10 and stored in the storage unit 24 of the information processing device 20 via the network N.

[0038] The subsequent various registrations are performed by the control unit 21 storing various registration information in the memory unit 24 in accordance with signals input from the operation unit 22 when the user operates the operation unit 22 of the information processing device 20.

[0039] Sample shape registration will be described using the sample shape registration screen shown in Figure 3. In sample shape registration, information defining the sample shape is registered. The information defining the sample shape includes sample shape information, origin information, and relative angle information. Sample shape information is information (name) indicating the shape of the sample. For example, a dumbbell test specimen (150 mm square) is used. The user inputs the sample shape name using the operation unit 22. Origin information is information indicating which point on the sample is the origin. Specifically, for the dumbbell test specimen (150 mm square) shown in Figure 3, the origin is the upper left corner of the page. The user imports an image of the shape of the dumbbell test specimen (150 mm square) and selects the origin. Relative angle information is information defining the relative angle of the sample with respect to the lattice. In the example shown in Figure 3, the lattice direction is registered as perpendicular to the tensile direction of the sample. The lattice direction is defined on the sample shape registration screen shown in Figure 3, and in the example shown in Figure 3, the lattice direction refers to the up-down direction. The user sets the relative angle by rotating the grid direction image adjacent to the image of the shape of a dumbbell test specimen (150 mm square). The relative angle information may be the grid angle relative to the sample, such as a grid angle of 90° relative to the tensile direction of the sample. The relative angle information may also be the relative angle between the MD or TD direction of the sample and the grid direction. In the example of Figure 3, the sample is a dumbbell test specimen, and the grid direction is defined based on the tensile direction of the sample. However, this is not limited to this. For example, if the sample is for a bending test, the grid direction may be defined based on the bending direction of the sample. The test method is not limited to the tensile test or bending test described above. If the sample shape has a characteristic feature, the relative angle may be defined based on the characteristic location. For example, for a long and narrow sample, the longitudinal direction of the sample may be aligned with the grid direction, and the grid direction when the longitudinal direction of the sample and the grid direction are aligned may be defined as a relative angle of 0°.

[0040] Here, we will explain the benefits of setting the relationship between the subject's orientation and the grid direction, using a dumbbell test specimen as an example. Dumbbell test specimens are designed for longitudinal tensile testing. If the image type is specified by the grid angle, the dependency on the grid angle will differ by 90° depending on whether the initial position of the sample is perpendicular or horizontal to the grid. If the grid direction is specified as parallel or perpendicular to the tensile direction (i.e., the longitudinal direction of the dumbbell) rather than the grid angle, the same feature values ​​can be obtained regardless of the initial sample position. In this way, the relationship between the grid angle and the tensile direction is clarified, allowing us to understand the relationship between feature values ​​and strength regardless of the sample's orientation.

[0041] Analysis area registration will be explained using the analysis area registration screen shown in Figure 4. In analysis area registration, information about the analysis area is registered in association with the sample shape. The information about the analysis area includes sample shape information, the analysis area name, the analysis area, and the relative coordinates of the analysis area. The sample shape information is information indicating the shape of the sample. For example, a dumbbell test piece (150 mm square). The user selects the sample shape from options. The options are the sample shape names entered in the sample shape registration screen shown in Figure 3. In the example of Figure 4, the selection is made from a pull-down menu. When sample shape information is selected, an image (image of the origin and sample shape) is displayed in the analysis area field in the center of the screen. The analysis area name is the name of the analysis area to be analyzed in the sample. The analysis area is displayed, for example, surrounded by a frame. In the example of Figure 4, the rectangular framed area of ​​the dumbbell test piece is the analysis area. The user selects the analysis area by specifying the area. The relative coordinates of the analysis area are the coordinates of the analysis area relative to the origin. The relative coordinates of the analysis region are automatically calculated and displayed by the control unit 21. Once the analysis region is registered, information about the analysis region is registered for each sample shape, as shown in Figure 5. In the above example, the analysis region is selected by the user. However, the analysis region may also be the area around the fracture position. Specifically, the user checks the checkbox for the area around the fracture position and inputs the range around the fracture position (e.g., "5 mm square"). Then, during the analysis described below, the control unit 21 may perform image analysis to select the area around the fracture position as the analysis region. Alternatively, the user may input the relative coordinates of the analysis region and move the frame indicating the analysis region. While the relative coordinates are specified in units of millimeters in the example shown in Figure 4, they may also be specified in terms of the number of pixels in the image, such as "100 pixels square." In this case, it is important to note that the actual size may vary depending on the image pitch of the device.

[0042] This section explains the registration of calculation methods. The calculation method registration involves registering the calculation method name and calculation method. The calculation method name is the name of the calculation method. A calculation method is a specific method for analyzing a Talbot image and obtaining feature quantities (e.g., statistical values ​​such as the mean value, deviation value, maximum value, minimum value, coefficient of variation, and percentile value). A calculation method is defined as a function that, when the analysis area of ​​a specific Talbot image is input, receives a two-dimensional numerical array and outputs a numerical value such as an integer or floating point number. Furthermore, a calculation method can receive the type of Talbot image as input, and is registered so that processing branches based on the type of Talbot image. This is because, for example, even when obtaining an average value, it is not sufficient to simply average the pixel values ​​of the Talbot image; the calculation method for the average differs for each Talbot image. For example, an orientation analysis image includes an orientation angle image. When calculating the average angle, calculations must take into account the periodicity of the angle (0° and 360° are the same). Applying a general scalar value average calculation will result in an incorrect value. An explanation of the calculation method may also be registered. Providing an explanation of the operation makes it easier for users to understand the details of the operation rules.

[0043] [Regarding the Analysis Rule Setting Process] The analysis rule setting process will be described with reference to Figs. 6 and 7. The analysis rule setting process shown in Fig. 6 is a process for setting an analysis rule for analyzing various Talbot images and acquiring feature quantities. At each step, a user inputs information by operating the operation unit 22 on the analysis rule setting screen (second screen) shown in Fig. 7, and the control unit 21 stores various pieces of information in the storage unit 24 in accordance with signals from the operation unit 22. Note that the order of the steps is not limited to that shown in Fig. 6.

[0044] First, the user inputs an analysis rule name using the operation unit 22. The control unit 21 sets the analysis rule name by storing it in the storage unit 24 (step S1; analysis rule name setting step).

[0045] Next, the user inputs an explanation of the analysis rule using the operation unit 22. The control unit 21 sets the explanation of the analysis rule by storing it in the storage unit 24 (step S2; analysis rule explanation setting step).

[0046] Next, the user selects a Talbot image type. The control unit 21 sets the Talbot image type by storing it in the storage unit 24 (step S3; first setting step). It is assumed that the options are set in advance. Since differential phase images and small-angle scattering images are lattice-angle dependent, options are set that also specify the lattice angle direction. Since absorption images and orientation analysis images are not lattice-angle dependent or contain dependency, it is not necessary to specify the lattice angle direction.

[0047] Next, the user selects a sample shape. The options are the sample shape names entered on the sample shape registration screen shown in Fig. 3. That is, in step S4, the information entered on the sample shape registration screen shown in Fig. 3 is linked to the analysis rule and set. The control unit 21 stores the sample shape information in the storage unit 24 (step S4; second setting step).

[0048] Next, the user selects an analysis region associated with the sample shape. The options are the analysis regions registered on the analysis region registration screen shown in FIG. 4. The control unit 21 sets the analysis region by storing it in the storage unit 24 (step S5; third setting step). In step S5, in addition to the above, the area around the fracture position may be added to the options so that it can be selected.

[0049] Next, the user selects a calculation method. The options are the calculation methods registered in the calculation method registration process described above. The control unit 21 sets the calculation method by storing it in the storage unit 24 (step S6; fourth setting step).

[0050] [Image Analysis Processing] The image analysis processing will be described with reference to FIGS. 8 and 9. The image analysis processing shown in FIG. 8 is processing for analyzing various Talbot images and acquiring feature amounts (feature amount generation). In other words, the analysis (feature amount generation) is processing for acquiring a Talbot image as an analysis target by applying an analysis rule to one or more samples, and generating feature amounts in an analysis region of the sample captured in the Talbot image based on a registered analysis method. At each step, a user inputs information by operating the operation unit 22 on the image analysis execution screen (first screen) shown in FIG. 9, and the control unit 21 executes image analysis in accordance with a signal from the operation unit 22.

[0051] First, the user selects a sample to be image-analyzed using the operation unit 22. In the example of FIG. 9, samples A, B, and C are selected. The control unit 21 sets information about the sample to be image-analyzed (step S11). At this time, the control unit 21 functions as a sample information setting unit. Next, the control unit 21 acquires information about the sample to be image-analyzed from the storage unit 24 (step S12).

[0052] Next, the control unit 21 displays the analysis rules on the image analysis execution screen shown in FIG. 9 (step S13). The control unit 21 acquires and displays, from the storage unit 24, feature quantity rules associated with the sample shape included in the sample information acquired in step S12. Alternatively, all feature quantity rules stored in the storage unit 24 may be initially displayed, and the control unit 21 may switch the display. Next, the user selects an analysis rule using the operation unit 22. The control unit 21 determines the selected analysis rule as the analysis rule for the sample (step S13; determination step). In the example shown in FIG. 9, three analysis rules are selected. As shown in FIG. 9, displaying not only the name of the analysis rule but also its description makes it easier to understand the analysis content. The control unit 21 acquires the analysis rules from the storage unit 24 (step S14).

[0053] Next, the user presses the analysis execution button using the operation unit 22. The control unit 21 executes the analysis (step S15; image analysis step). At this time, the control unit 21 functions as an image analysis unit. According to the Talbot image type included in the selected analysis rule, the control unit 21 acquires Talbot images of the selected Talbot image type from various Talbot images of one or more samples and analyzes the set analysis region using the set analysis method. Note that if the analysis region is the vicinity of the fracture position, the control unit 21 automatically sets the analysis region around the fracture position by analyzing the Talbot image during analysis. When specifying the vicinity of the fracture position as the analysis region, after photographing the subject (sample) with the X-ray Talbot imaging device 10, it is necessary to perform a destructive test such as a tensile test or a bending test, and then link the subject and the destructive test results and register them in the system. During registration, the fracture location of each subject is registered along with the fracture strength results, as shown in Table I below. For example, in the case of a dumbbell test piece, the distance from a reference position (the left side of the dumbbell test piece in FIG. 10) to the fractured point (the center position of the fractured point) may be shown in actual size. As shown in FIG. 11, the control unit 21 may acquire optical images after the destructive test, and automatically read in the information on the fractured location from the results of the optical images by performing image processing.

[0054] After the above-described analysis, the user can use the feature quantities obtained by the above-described analysis as explanatory variables and the strength test results performed for each sample as objective variables, as shown in FIG. 12 , and load these into a machine learning device or AI to extract explanatory variables (feature quantities) that have a high degree of influence on the objective variables.

[0055] (Other: Calculation Method When Using a Sample Containing a Weld Line) While the above description was given using a dumbbell test piece as an example, here we will describe a calculation method when using a sample containing a weld line as shown in Figure 13. For a sample containing a weld line, an image is obtained that has a peak value at the weld line position. In this case, information such as the peak value and half-width of the peak in the image can be used as a feature. One example of a method for determining the peak value and half-width of the peak is a method using function fitting. For example, when a two-dimensional numerical array I(x, y) is input as the analysis region of a Talbot image, a one-dimensional profile YProfile(y) can be obtained in the direction in which the weld peak is visible. The coefficients can be determined by fitting a Gaussian function containing unknown coefficients (A, B, μ, σ) to this one-dimensional profile YProfile(y) so that the error is minimized, as shown in the following equation (1). In Fig. 13, the solid line SL indicates the profile in the y direction, and the dashed line DL indicates the results of fitting with a Gaussian curve. Z = A x exp {-[(y - μ) / σ] ２} + B ... (1) Values ​​corresponding to the peak value can be obtained from the obtained coefficient A, and the half-width can be obtained from σ. This is just one example, but by assuming a fitting function that includes unknowns and determining those unknowns, it is possible to quantify the image features (solid line SL, peak position P).

[0056] The analysis rule setting process ( FIG. 6 ) for a sample containing a weld line will now be described. Steps other than steps S3, S4, and S6 are similar to those described above, and therefore will not be described again. First, the user selects a Talbot image type. The control unit 21 then sets the Talbot image type by storing it in the memory unit 24 (step S3; first setting step). The options are pre-set. Multiple image types can be selected. For example, the user can select an absorption image and a small-angle scattering image (with lattice angles in the tensile direction and horizontal direction). Next, the user selects a calculation method. The options are the calculation methods registered in the calculation method registration described above, and calculations that can be performed on multiple images are displayed. As the calculation method, a calculation rule is set that outputs numerical values ​​when multiple images are input and a two-dimensional numerical array is given as the analysis domain (set in step S5). For example, if a scattering intensity image obtained by averaging the lattice dependence of the absorption image and the small-angle scattering image is selected in step S3, the feature value corresponding to the ratio of the resin to the fiber amount can be calculated by calculating the average value of the absorption image corresponding to the resin density and the average value of the scattering intensity image corresponding to the fiber amount from each image and then calculating the ratio between the two.The control unit 21 then sets the calculation method by storing it in the memory unit 24 (step S6; fourth setting step).

[0057] (Effects) As described above, the analysis method (image analysis processing) is a method for analyzing Talbot images obtained by photographing a subject using an X-ray Talbot imaging device using an information processing device, and includes a determination step (step S13) of determining an analysis rule for the subject from among a plurality of predetermined analysis rules, and an image analysis step (step S15) of analyzing the Talbot image photographed of the subject using the determined analysis rule. This reduces variations in feature amounts and feature amount settings, improving analysis accuracy. Furthermore, the setting of the analysis rule includes a first setting step of setting the type of Talbot image, a second setting step of setting shape information of the subject, a third setting step of setting an analysis region for the Talbot image, and a fourth setting step of setting a calculation method for the analysis region.

[0058] In addition, in the second setting step, the relationship between the orientation of the subject and the grid direction of the X-ray Talbot imaging device is further set. In other words, the grid direction is stored in association with the sample shape. Therefore, when analyzing test pieces of the same shape, it is possible to prevent different grid direction settings from being made for each user.

[0059] In addition, in the third setting step, the analysis area is automatically set based on the shape information. That is, the analysis area is linked to the sample shape and stored. Therefore, when analyzing test pieces of the same shape, it is possible to prevent different settings of the analysis area for each user.

[0060] In addition, in the third setting step, the area around the destruction site of the subject is automatically set as the analysis site. In other words, since the destruction site is different for each sample, it is not necessary to set the area around the destruction site as the analysis site one by one. In addition, since the area of ​​the set size around the destruction site is automatically set, it is possible to prevent the setting of the analysis site from being different for each user.

[0061] In addition, in the fourth setting step, the calculation method is automatically switched depending on the Talbot image, so that, even if the calculation method is generally the average and deviation, the specific calculation method differs for each Talbot image, and the user does not need to be aware of the specific calculation method.

[0062] Also, the display device (information processing device 20) displays a method for analyzing a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device, and includes a display control unit that displays a first screen (FIG. 9; image analysis execution screen) including a selection area for selecting an analysis rule for the subject. This reduces variations in feature amounts and feature amount settings, improving analysis accuracy.

[0063] The display means is a display device (information processing device 20) that displays a method for setting analysis rules for Talbot images obtained by photographing a subject using an X-ray Talbot imaging device, and the display control unit further displays a second screen ( FIG. 7 ; analysis rule setting screen) that includes a first setting area for setting the type of Talbot image, a second setting area for setting shape information of the subject, a third setting area for setting an analysis area for the Talbot image, and a fourth setting area for setting an analysis area calculation method. This suppresses variations in feature amounts and feature amount settings, improving analysis accuracy.

[0064] Additionally, analysis rules and explanations of the analysis rules are displayed, making it easier for each user to understand the details of the analysis process, even when analysis is performed by a variety of users.

[0065] The program also causes a computer of an analysis device (information processing device 20) for Talbot images obtained by photographing a subject using an X-ray Talbot imaging device to function as a selection unit (control unit 21) that selects an analysis rule for the Talbot image from a plurality of pre-set analysis rules, and as an image analysis unit (control unit 21) that analyzes the Talbot image using the selected analysis rule, thereby suppressing variations in feature amounts and feature amount settings and improving analysis accuracy.

[0066] The embodiment of the present invention has been described above, but the description of the above embodiment is a preferred example of the present invention, and the present invention is not limited to this.

[0067] In the above description, examples have been given in which a hard disk or a semiconductor nonvolatile memory is used as a computer-readable medium for the program according to the present invention, but the present invention is not limited to these examples. Other computer-readable media may also be used, such as a portable recording medium such as a CD-ROM.

[0068] In addition, the detailed configuration and operation of each device can be modified as appropriate without departing from the spirit of the invention.

[0069] The present disclosure can be used in an analysis method, a display device, and a program.

[0070] REFERENCE SIGNS LIST 1 Analysis system 10 X-ray Talbot imaging device 11 X-ray generator 19 Controller 20 Information processing device (display device, analysis device) 21 Control unit 22 Operation unit 23 Communication unit 24 Storage unit 25 Display unit H Subject

Claims

1. A method for analyzing a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device using an information processing device, comprising: a determination step of determining an analysis rule for the subject from a plurality of pre-set analysis rules; and an image analysis step of analyzing the Talbot image obtained by photographing the subject using the determined analysis rule.

2. The analysis method according to claim 1, wherein the setting of the analysis rules includes a first setting step of setting the type of the Talbot image, a second setting step of setting shape information of the subject, a third setting step of setting an analysis area of the Talbot image, and a fourth setting step of setting a calculation method for the analysis area.

3. The analysis method according to claim 2, wherein the second setting step further sets the relationship between the direction of the subject and the grid direction of the X-ray Talbot imaging device.

4. The analysis method according to claim 3, wherein the relationship is the relationship between the tensile direction or bending direction of the subject and the lattice direction of the X-ray Talbot imaging device.

5. The analysis method according to claim 3, wherein the relationship is the relationship between the MD (machine direction) direction or TD (transverse direction) direction of the subject and the lattice direction of the X-ray Talbot imaging device.

6. The analysis method according to claim 2, wherein in the third setting step, the analysis region is set in actual size.

7. The analysis method according to claim 2, wherein in the third setting step, the analysis region is automatically set based on the shape information.

8. The analysis method according to claim 2, wherein in the third setting step, an area around the destruction point of the subject is automatically set as the analysis area.

9. The analysis method according to claim 2, wherein in the fourth setting step, the calculation method is automatically switched depending on the Talbot image.

10. A display device that displays an analysis method for a Talbot image obtained by photographing a subject using an X-ray Talbot imaging device, the display device having a display control unit that displays a first screen including a selection area for selecting an analysis rule for the subject.

11. The display device according to claim 10, wherein the display control unit displays the analysis rule and an explanation of the analysis rule in the selection area.

12. A display device according to claim 10, which displays a setting area for the analysis rule, wherein the display control unit further displays a second screen including: a first setting area for setting the type of the Talbot image; a second setting area for setting shape information of the subject; a third setting area for setting the analysis area of the Talbot image; and a fourth setting area for setting a calculation method for the analysis area.

13. A program that causes a computer of an analysis device for Talbot images obtained by photographing a subject using an X-ray Talbot imaging device to function as: a determination unit that determines an analysis rule for the subject from a plurality of pre-set analysis rules; and an image analysis unit that analyzes the Talbot images photographed of the subject using the determined analysis rule.

Images