X-ray imaging apparatus and x-ray imaging method

Abstract

To provide an X-ray imaging apparatus capable of performing area division for dividing the inside of a subject for each substance with high accuracy.SOLUTION: The X-ray imaging apparatus according to the present invention includes an X-ray source 1 for emitting an X-ray 11 for irradiating an object 2, an object moving mechanism 4 for rotating the object 2, an X-ray image detector 5 for detecting a projection image of the object 2 by the X-ray 11, an object temperature adjusting mechanism 9 for changing the temperature of the object 2, and a processing unit 7 for acquiring a cross-sectional image of the object 2 by reconstruction calculation from a plurality of projection images detected by the X-ray image detector 5 by rotating the object 2. The processing unit 7 acquires a plurality of cross-sectional images 31 and 32 of the object 2 captured at a plurality of temperatures T1 and T2 different from each other, and performs region division for dividing the inside of the object 2 for each material using distributions 33 of pixels of the cross-sectional images based on CT values at the plurality of temperatures T1 and T2 at which the cross-sectional images 31 and 32 of the object 2 are acquired.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an X-ray imaging apparatus and an X-ray imaging method for capturing an image of the inside of a subject. [Background technology]

[0002] X-ray CT (Computed Tomography) is a technology that non-destructively obtains cross-sectional images (CT images) of a subject by performing a calculation called reconstruction from multiple transmission images (projection images) obtained by rotating the subject relative to the X-ray source and projecting X-rays onto the subject at different angles. X-ray CT utilizes the high penetrating power of X-rays to enable non-destructive three-dimensional observation of the interior of a subject without cutting it, making it an essential non-destructive visualization technology in a wide range of fields, including medical diagnosis and product inspection.

[0003] An example of a conventional X-ray imaging device is described in Patent Document 1. The nondestructive analysis device described in Patent Document 1 performs CT imaging at multiple times, obtains CT values ​​at any two points from the CT imaging, and compares them to infer the temperature of the battery being inspected. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2019-90802 Summary of the Invention [Problem to be solved by the invention]

[0005] X-ray CT scans image the decrease in intensity (linear absorption coefficient) of X-rays due to their absorption as they pass through the subject. The linear absorption coefficient is given by the product of the subject's density and mass absorption coefficient, so two materials with different densities may have the same linear absorption coefficient depending on the value of the mass absorption coefficient. In this case, it is difficult to distinguish between materials with different densities and perform segmentation to separate the interior of the subject into regions by material.

[0006] To solve this problem, methods have been developed such as dual-energy CT, which uses X-ray CT measurements at multiple different X-ray energies to identify materials by taking advantage of the fact that the energy dependence of the linear absorption coefficient differs for each material. However, to achieve high discrimination, it is essential to use X-rays with a single energy (monochromatic X-rays). Conventional X-ray CT uses polychromatic X-rays (white X-rays) composed of various energies, and there is a problem in that very high-intensity X-rays, such as synchrotron radiation, are required to perform measurements using monochromatic X-rays in a practical time frame.

[0007] In addition to the above, a device (scanning X-ray microscope) has been developed that scans an object with X-rays focused into a pencil shape by an X-ray focusing element and identifies elements and materials from the energy analysis of fluorescent X-rays generated from each irradiation point. However, with such a device, the energy of the fluorescent X-rays is several tens of keV, and the fluorescent X-rays generated inside the object are absorbed by the object, making it difficult to measure deep inside the object nondestructively and with high precision.

[0008] The non-destructive analysis device described in Patent Document 1 can detect changes in the state inside a subject whose structure is known, but for a subject whose structure is unknown, it is difficult to divide the inside of the subject into regions by material.

[0009] As described above, conventional X-ray imaging devices have a problem in dividing the interior of a subject into regions of different materials with high accuracy.

[0010] An object of the present invention is to provide an X-ray imaging apparatus and an X-ray imaging method that can accurately divide the interior of a subject into regions according to material. [Means for solving the problem]

[0011] An X-ray imaging device according to the present invention comprises an X-ray source that emits X-rays to irradiate an object, an object moving mechanism that rotates the object, an X-ray image detector that detects projection images of the object by the X-rays, an object temperature adjustment mechanism that changes the temperature of the object, and a processing unit that acquires cross-sectional images of the object by reconstruction calculation from a plurality of the projection images detected by the X-ray image detector while rotating the object. The processing unit acquires a plurality of the cross-sectional images of the object imaged at a plurality of mutually different temperatures, and performs region division into regions by material inside the object using distributions of each pixel of the cross-sectional images based on CT values ​​at the plurality of temperatures at which the cross-sectional images of the object were acquired.

[0012] The X-ray imaging method according to the present invention includes a temperature changing step in which an object temperature adjustment mechanism changes the temperature of the object; an irradiation step in which an X-ray source irradiates the object with X-rays; a projection image detection step in which an X-ray image detector detects a projection image of the object formed by the X-rays; and a region dividing step in which a processing unit that rotates the object and obtains a cross-sectional image of the object by reconstruction calculation from a plurality of projection images detected by the X-ray image detector obtains a plurality of cross-sectional images of the object imaged at a plurality of mutually different temperatures, and divides the interior of the object into regions by material using the distribution of each pixel of the cross-sectional images based on the CT values ​​at the plurality of temperatures at which the cross-sectional images of the object were obtained. [Effects of the Invention]

[0013] According to the present invention, it is possible to provide an X-ray imaging apparatus and an X-ray imaging method that can perform region division into different materials within the subject with high accuracy. [Brief explanation of the drawings]

[0014] [Figure 1A]FIG. 10 is a diagram showing an example of a cross-sectional image of a subject at a temperature T1. [Figure 1B] FIG. 10 is a diagram showing an example of a cross-sectional image of a subject at a temperature T2. [Figure 1C] FIG. 10 is a diagram showing an example of a TT map. [Figure 1D] FIG. 10 is a diagram showing an example of a TT map in which plotted points are divided into point clouds. [Figure 1E] FIG. 10 is a diagram showing an example of a cross-sectional image in which regions are divided by color, in which the subject is divided into regions. [Figure 2] 10 is an example of a user interface displayed on the display unit of an X-ray imaging device, which is used when a user divides points plotted on a TT map into multiple point clouds. [Figure 3] FIG. 10 is a diagram showing an example of a TT map including a point cloud created from cross-sectional images acquired at temperatures higher and lower than the phase transition temperature. [Figure 4] FIG. 10 is a diagram showing an example of data showing the relationship between the volume expansion coefficient and the density of typical substances that make up a subject. [Figure 5] 1 is a diagram illustrating an example of the configuration of an X-ray imaging apparatus according to a first embodiment of the present invention. [Figure 6] 1 is a flowchart showing the procedure of an X-ray imaging method according to the first embodiment. [Figure 7] FIG. 10 is a diagram illustrating an example of the configuration of an X-ray imaging apparatus according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] In this invention, an X-ray CT using polychromatic X-rays (white X-rays) is used to change the temperature of the subject and obtain cross-sectional images of the subject at multiple different temperatures. A distribution map is then calculated based on the CT value (linear absorption coefficient) of each pixel in the cross-sectional image at each temperature, and this distribution map is used to divide the interior of the subject into regions by material. Hereinafter, this distribution map will be referred to as a "TT map" (Temperature-Temperature map).

[0016] According to the present invention, it is possible to identify materials and structures inside a subject whose internal structure is unknown, and to perform highly accurate region segmentation into regions for each material and structure inside the subject.

[0017] The basic concept of the present invention, that is, a method for dividing the interior of a subject into regions according to material using a cross-sectional image of the subject obtained by X-ray CT, will be described below with reference to the drawings.

[0018] In the drawings used in this specification, the same or corresponding components are designated by the same reference numerals, and repeated description of these components may be omitted.

[0019] In the present invention, the temperature T of the subject is changed, and cross-sectional images (CT images) of the subject are obtained by X-ray CT at multiple different temperatures Tn. The pixels of the CT image have CT values ​​that represent the linear absorption coefficient of X-rays.

[0020] In the following, as an example, a case will be described in which cross-sectional images of a subject are acquired by X-ray CT at two different temperatures T1 and T2.

[0021] FIG. 1A is a diagram showing an example of a cross-sectional image 31 of a subject at temperature T1. FIG. 1B is a diagram showing an example of a cross-sectional image 32 of a subject at temperature T2. The cross-sectional image 31 at temperature T1 shows a CT value I(x, y, T1) at each pixel (x, y) in the cross-sectional image (CT image). The cross-sectional image 32 at temperature T2 shows a CT value I(x, y, T2) at each pixel (x, y) in the cross-sectional image (CT image).

[0022] In the following, it is assumed that the subject is composed of multiple regions divided by the material that makes up the subject, and each region is identified by an identification number m. These regions can be determined according to the density of the material that makes up the subject.

[0023] If the density of region m at temperature T1 is ρm and the coefficient of thermal expansion is bm, the change in density Δρm when the temperature T of the object changes by ΔT from T1 to T2 is: Δρm=bm×ρm×ΔT (1) is given by

[0024] On the other hand, the linear absorption coefficient μm is given by μ'm, where μ'm is the mass absorption coefficient in region m. μm=ρm×μ'm (2) is given by

[0025] Taking advantage of the fact that the mass absorption coefficient μ'm is invariant with temperature, the change in linear absorption coefficient Δμm with respect to the temperature change ΔT can be calculated from equations (1) and (2) as follows: Δμm=bm×ρm×μ'm×ΔT (3) Therefore, the linear absorption coefficient μm of each region, i.e., the X-ray CT value, changes with respect to the change ΔT in temperature T, with bm×ρm×μ'm as the proportionality coefficient.

[0026] Therefore, when X-ray CT values ​​obtained at different temperatures T are compared, the subject can be accurately divided into multiple regions determined according to the volume expansion coefficient and density based on the differences in density ρm, volume expansion coefficient bm, and mass absorption coefficient μ'm. Furthermore, in the present invention, even without detecting absolute density, the subject can be divided into regions determined according to the relative density change of the subject caused by temperature change.

[0027] In conventional techniques, such as the technique described in Patent Document 1, the change in state at each pixel (x, y) is determined by simple subtraction or division of the CT value I(x, y, Tn) at each pixel (x, y) in cross-sectional images acquired at multiple different temperatures Tn. This method can detect changes in state inside a subject whose structure is known, but it is difficult to divide the inside of a subject whose structure is unknown into regions according to material (density).

[0028] In the present invention, the interior of the subject is divided into regions for each material according to density, using the procedure described below.

[0029] Step 1) For one pixel (xn,yn) in the cross-sectional images acquired at temperatures T1 and T2, a point is plotted based on the CT value at this pixel (xn,yn) at a position where the horizontal axis represents the CT value at temperature T1 and the vertical axis represents the CT value at temperature T2. That is, for the point plotted corresponding to this pixel (xn,yn), the position along the horizontal axis is the CT value I(xn,yn,T1) at temperature T1, and the position along the vertical axis is the CT value I(xn,yn,T2) at temperature T2.

[0030] Step 2) The process of step 1) is performed for all pixels of the acquired cross-sectional image to create a TT map. As already explained, a TT map is a distribution diagram showing the distribution of each pixel in the cross-sectional image based on the CT values ​​at multiple temperatures (multiple measurement temperatures) at which the cross-sectional image of the subject was acquired. The points plotted on the TT map correspond to the pixels of the cross-sectional image.

[0031] 1C is a diagram showing an example of a TT map 33. In this TT map 33, pixels in a cross-sectional image are plotted as multiple points 34, with the horizontal axis representing the CT value at temperature T1 and the vertical axis representing the CT value at temperature T2.

[0032] Step 3) The points 34 plotted on the TT map 33 are divided into multiple point groups (groups of points that can be considered as one set), and each of these point groups is assigned a different number (identification number). Different colors are assigned to these numbers.

[0033] The point cloud of the TT map 33 represents a set of pixels that have the same physical properties (for example, the same volume expansion coefficient). In other words, dividing the points 34 (pixels in the cross-sectional image) into multiple point clouds means dividing the pixels into pixels that have the same physical properties. From this TT map 33, a group of pixels with the same physical properties can be obtained.

[0034] Fig. 1D is a diagram showing an example of a TT map 33 in which plotted points 34 are divided into point groups. In the example shown in Fig. 1D, the plotted points 34 are divided into four point groups 35a to 35d. That is, the TT map 33 shown in Fig. 1D shows the existence of regions divided according to four types of physical properties (for example, the coefficient of volume expansion).

[0035] The point groups 35a to 35d are each assigned a number (identification number) to identify them. Different colors are assigned to these identification numbers. In Fig. 1D, the different colors are indicated by different hatching.

[0036] Step 4) Each pixel (x, y) is assigned a color that corresponds to the identification number assigned to each pixel group (i.e., point groups 35a to 35d), and a new cross-sectional image is generated using the colored pixels (x, y). In this newly generated cross-sectional image, regions are separated by color. In other words, the internal region of the subject is separated based on the pixel groups (point groups 35a to 35d).

[0037] FIG. 1E is a diagram showing an example of a cross-sectional image 36 in which regions are divided by color, and is a diagram showing the region division of an object. In the example shown in FIG. 1E, the cross-sectional image 36 (segmentation image) is divided into four regions of different colors. Note that in FIG. 1E, the differences in color are indicated by different hatching. As shown in FIG. 1E, an object can be divided into regions according to relative density, without determining absolute density.

[0038] As described above, the present invention makes it possible to perform highly accurate region division into separate regions for each material inside the subject by using cross-sectional images of the subject obtained by X-ray CT.

[0039] In the above description, an example has been described in which cross-sectional images of a subject are acquired at two temperatures (T1 and T2), but cross-sectional images of a subject can also be acquired at three or more different temperatures. When cross-sectional images are acquired at three or more temperatures, the ability to distinguish regions can be improved.

[0040] In addition, in the above explanation, the TT map 33 is created from a two-dimensional cross-sectional image obtained by X-ray CT, but it is also possible to create a TT map from a three-dimensional cross-sectional image obtained by X-ray CT and use this TT map to divide the subject into regions in three dimensions.

[0041] In step 3, the points 34 plotted on the TT map 33 can be divided into multiple point groups automatically by the X-ray imaging device using any automatic classification algorithm, or manually by the user while viewing the TT map 33 displayed on the display unit of the X-ray imaging device. The automatic classification algorithm is an algorithm that classifies data based on, for example, a self-organizing map method or machine learning.

[0042] 2 is an example of a user interface displayed on the display unit of the X-ray imaging device, which is used when a user divides the points 34 plotted on the TT map 33 into multiple point clouds. The user can divide the points 34 plotted on the TT map 33 into multiple point clouds by using the user interface shown in FIG.

[0043] Note that when cross-sectional images of the subject are acquired at three or more temperatures, it is impossible to display the TT map as a two-dimensional image. Therefore, it is preferable that the points 34 plotted on the TT map be divided into multiple point clouds automatically by the X-ray imaging device using an automatic classification algorithm.

[0044] In the present invention, the larger the temperature difference ΔT (=|T1-T2|) between the temperatures T1 and T2 at which the cross-sectional image of the subject is obtained, the larger the difference Δμm in the linear absorption coefficient μm due to the difference in the bulk expansion coefficient bm, enabling region division with higher accuracy.

[0045] Furthermore, if cross-sectional images of the subject are acquired at temperatures higher and lower than the phase transition temperature of the substance expected to comprise the subject (for example, 0°C if the substance is water or ice), the substance can be identified with higher accuracy. Generally, the density of a substance changes or inverts significantly due to a phase transition. For this reason, on a TT map, point clouds created from cross-sectional images acquired at temperatures higher and lower than the phase transition temperature show a unique distribution. This allows this point cloud to be distinguished from other point clouds with high accuracy, enabling highly accurate region segmentation.

[0046] Figure 3 is a diagram showing an example of a TT map including point clouds created from cross-sectional images acquired at temperatures higher and lower than the phase transition temperature. The TT map shown in Figure 3 shows point cloud 37 created from cross-sectional images acquired at two temperatures T1 and T2, higher and lower than the phase transition temperature of a certain substance, and point cloud 38 for a substance whose phase transition temperature on the same cross section is not between temperatures T1 and T2. In the TT map, the position of point cloud 37 is significantly different from the position of point cloud 38. Therefore, by acquiring cross-sectional images of a subject at temperatures higher and lower than the phase transition temperature, it is possible to segment the subject into regions with high accuracy.

[0047] X-rays are electromagnetic waves with short wavelengths, and when they pass through a subject, not only does their intensity decrease due to absorption, but a phase change (phase shift) also occurs. For light elements, X-rays have the characteristic that their phase shift is more than 1,000 times greater than the intensity decrease. Therefore, X-ray CT (phase CT) is used, which uses phase contrast X-ray imaging to visualize the phase shift. Phase CT allows for the observation of soft tissue specimens and organic materials, which are primarily composed of light elements such as oxygen and carbon, with high density resolution. For example, phase CT is used to observe the organs of small animals with high resolution.

[0048] The complex refractive index n of the object is n=1-δ+iβ (4) In equation (4), the real part δ and the imaginary part β are respectively expressed as follows:

[0049]

number

[0050]

number

[0051] where λ is the wavelength of the X-ray, and re is the classical electron radius (2.818×10 -15 m), Nj is the atomic density, Zj is the number of electrons in the atom (atomic number), and f' and f" are the real and imaginary parts of the anomalous dispersion term of the atomic scattering factor.

[0052] When comparing the real part δ and the imaginary part β, the difference is (Z + f') and f". Because the ratio of the two is more than 1000 times and δ >> β, phase CT has high sensitivity. The phase CT value (phase shift) imaged by phase CT is the real part δ of equation (4), and takes on different values ​​depending on the temperature.

[0053] The linear absorption coefficient μ is the sum of the imaginary part β given by equation (6) and

[0054]

number

[0055] Furthermore, as shown in equation (2), the linear absorption coefficient μ is given by the product of the density ρ of the object and the mass absorption coefficient μ', and the mass absorption coefficient μ' is a quantity that depends on the element.

[0056] From these facts, it is clear that in order to accurately calculate the density from the linear absorption coefficient μ, i.e., the CT value, it is impossible to know the elemental composition of the subject.

[0057] On the other hand, phase CT images the real part δ, i.e. (Z+f'), instead of the imaginary part β. f' is extremely small, about 1 / 10,000 of Z. For this reason, the phase CT value (phase shift) imaged by phase CT is a value roughly proportional to Z, i.e., the electron density.

[0058] Therefore, unlike X-ray CT, which images the linear absorption coefficient, phase CT can accurately determine the density of a subject even if the elemental composition of the subject is unknown.

[0059] In a TT map created from a cross-sectional image acquired using phase CT, the phase CT values ​​of the pixels represent density, and the newly generated cross-sectional image in step 4) shows the density distribution. Utilizing this feature, it is possible to clarify the material and composition of each region that makes up the subject based on the volume expansion coefficient and density calculated from the phase CT values ​​(or the temperature change ΔT in the CT values) acquired at multiple different temperatures (for example, temperatures T1 and T2) and the data indicating the relationship between the volume expansion coefficient and density prepared in advance.

[0060] Fig. 4 is a diagram showing an example of data showing the relationship between the coefficient of volume expansion and the density of representative materials constituting a subject. The X-ray imaging device according to the present invention can be provided with a database in which data such as that shown in Fig. 4 is pre-stored. By comparing phase CT values ​​acquired at a plurality of different temperatures (for example, temperatures T1 and T2) with the data shown in Fig. 4, the X-ray imaging device can not only divide the subject into regions but also identify the materials constituting each region.

[0061] An X-ray imaging apparatus and an X-ray imaging method according to an embodiment of the present invention will be described below with reference to the drawings. [Example]

[0062] 5 is a diagram showing an example of the configuration of an X-ray imaging apparatus according to a first embodiment of the present invention. The X-ray imaging apparatus according to this embodiment includes a subject holder 3, an X-ray source 1, a subject moving mechanism 4, an X-ray image detector 5, a subject temperature adjusting mechanism 9, a subject temperature adjusting mechanism control unit 10, a control unit 6, a processing unit 7, and a display unit 8. The X-ray imaging method according to this embodiment is executed by the X-ray imaging apparatus according to this embodiment.

[0063] The subject holder 3 is provided on the subject moving mechanism 4 and holds the subject 2 .

[0064] The X-ray source 1 emits X-rays 11 , and irradiates the subject 2 held by the subject holder 3 with the X-rays 11 .

[0065] The subject moving mechanism 4 is a mechanism that rotates the subject holder 3 to rotate the subject 2, and adjusts the irradiation position and irradiation angle of the X-rays 11 on the subject 2. The subject moving mechanism 4 can also move the subject holder 3 to adjust the position of the subject 2 relative to the position of the X-ray 11 beam.

[0066] The X-ray image detector 5 detects the X-rays 11 that have passed through the subject 2 and detects a projection image of the subject 2 formed by the X-rays 11 .

[0067] The subject temperature adjustment mechanism 9 is a mechanism that changes the temperature of the subject 2. Figure 5 shows, as an example, a subject temperature adjustment mechanism 9 that changes the temperature of the subject 2 by blowing cooled or heated gas 12 onto the subject 2.

[0068] The object temperature adjustment mechanism control unit 10 controls the object temperature adjustment mechanism 9 .

[0069] The control unit 6 controls the object temperature adjustment mechanism 9 to change the temperature of the object 2, and controls the object movement mechanism 4 to rotate and move the object 2, and captures an image of the object 2 using the X-ray CT.

[0070] The processing unit 7 acquires a cross-sectional image of the subject 2 by X-ray CT from the multiple projection images detected by the X-ray image detector 5, synthesizes a sinogram image from the cross-sectional images of the subject 2, and calculates the cross-sectional image of the subject 2 by reconstruction calculation, thereby acquiring a cross-sectional image of the subject 2 by X-ray CT. Furthermore, the processing unit 7 creates a TT map from the cross-sectional images of the subject 2 acquired at multiple temperatures, and performs region division of the subject 2 using the TT map.

[0071] The display unit 8 is a display device that displays a cross-sectional image of the subject 2 (for example, FIGS. 1A and 1B), a TT map (for example, FIGS. 1C and 1D), and a cross-sectional image of the subject 2 divided into regions (for example, FIG. 1E).

[0072] The X-ray imaging apparatus according to this embodiment executes the X-ray imaging method described below, and divides the subject 2 into regions.

[0073] 6 is a flowchart showing the procedure of the X-ray imaging method according to this embodiment. In the X-ray imaging method according to this embodiment, cross-sectional images of the subject 2 are obtained at a plurality of mutually different temperatures (for example, n temperatures Tn) using the X-ray imaging device according to this embodiment, according to the procedure shown below. These plurality of temperatures (measurement temperatures Tn) are determined in advance.

[0074] In S60, the user places the subject 2 on the subject holder 3.

[0075] In S61, the subject moving mechanism 4 moves the subject holder 3 to align the subject 2 with the center of the X-ray 11 beam.

[0076] In S62, the control unit 6 sends an instruction to the subject temperature adjustment mechanism control unit 10 to set the temperature of the subject 2 to the measurement temperature Tn. The subject temperature adjustment mechanism control unit 10 controls the subject temperature adjustment mechanism 9 to set the temperature of the subject 2 to the measurement temperature Tn.

[0077] In S63, the X-ray imaging device images the subject 2 using X-ray CT. First, the subject movement mechanism 4 rotates the subject holder 3 to rotate the subject 2 so that the position where the X-rays 11 are projected onto the subject 2 is a predetermined position (origin). Next, the subject movement mechanism 4 moves the subject 2 away from the optical path of the X-rays 11, and the X-ray image detector 5 acquires a background image of the subject 2. Next, the subject movement mechanism 4 returns the subject 2 to the optical path of the X-rays 11. Next, the subject movement mechanism 4 rotates the subject 2 by a predetermined angle, and the X-ray image detector 5 detects the projection image of the subject 2 by the X-rays 11 at each rotation angle. The rotation of the subject 2 and the detection of the projection image are repeated until the rotation angle of the subject 2 reaches 180 degrees or 360 degrees. When the rotation angle of the subject 2 reaches 180 degrees or 360 degrees, the subject movement mechanism 4 moves the subject 2 away from the optical path of the X-rays 11, and the X-ray image detector 5 acquires a background image of the subject 2. Then, the object moving mechanism 4 returns the object 2 to the optical path of the X-rays 11 .

[0078] In S64, the processing unit 7 calculates a cross-sectional image of the subject 2 by reconstruction calculation using the acquired group of projection images of the subject 2 and the background image, and acquires the cross-sectional image of the subject 2 by X-ray CT. The display unit 8 displays the cross-sectional image of the subject 2.

[0079] In S65, the processing unit 7 determines whether or not cross-sectional images of the subject 2 have been acquired at all of the predetermined n measurement temperatures Tn. If cross-sectional images of the subject 2 have not been acquired at all of the measurement temperatures Tn, the process returns to step S62, where the temperature of the subject 2 is changed and cross-sectional images of the subject 2 are acquired. If cross-sectional images of the subject 2 have been acquired at all of the n measurement temperatures Tn, the process proceeds to step S66, since cross-sectional images of the subject 2 at each measurement temperature Tn have been acquired.

[0080] In S66, the processing unit 7 creates a TT map from the cross-sectional images of the subject 2 acquired at each measurement temperature Tn. The TT map (for example, FIGS. 1C and 1D) is created according to the procedure described above.

[0081] In S67, the processing unit 7 uses the TT map to divide the subject 2 into regions. The division of the subject 2 into regions (e.g., FIG. 1E) is performed according to the procedure described above. The display unit 8 displays a cross-sectional image of the subject 2 divided into regions.

[0082] The subject temperature adjustment mechanism 9 can be a mechanism that uses thermal conduction to change the temperature of the subject 2, or a mechanism that changes the temperature of the subject 2 by spraying a gas such as cooled or heated dry nitrogen onto the subject 2. Mechanisms that use thermal conduction include, for example, heating the subject holder 3 with a heater or cooling it with a cooling solvent. Mechanisms that spray gas onto the subject 2 can rapidly change the temperature of the gas, thereby changing the temperature of the subject 2 in a short period of time and suppressing the formation of frost on the surface of the subject 2 due to cooling. As a result, this mechanism can obtain high-precision cross-sectional images in a short period of time that are free from the effects of frost.

[0083] Furthermore, the X-ray imaging device according to this embodiment can be equipped with a non-contact temperature detection mechanism such as a thermograph, or a contact temperature detection mechanism such as a thermocouple. By monitoring the temperature of the subject 2 with the temperature detection mechanism, the X-ray imaging device according to this embodiment can confirm whether the temperature of the subject 2 has reached the measurement temperature Tn, allowing the temperature of the subject 2 to be set more accurately and enabling more accurate measurements.

[0084] A detector that directly detects incident X-rays, such as an X-ray flat panel or a back-illuminated CCD, can be used as the X-ray image detector 5. In this type of X-ray image detector 5, the pixel size is fixed, but it can detect X-rays with high efficiency.

[0085] Alternatively, the X-ray image detector 5 may be an X-ray image intensifier or a lens-coupled X-ray detector, which converts incident X-rays into electrons or visible light using a phosphor and then detects them with an image sensor. This type of X-ray image detector 5 allows for the magnification of the lens system to be changed, allowing X-rays to be detected at any desired magnification. Furthermore, because X-rays are not irradiated onto the image sensor, damage to the image sensor due to X-rays can be significantly reduced compared to methods that directly detect incident X-rays. Furthermore, by changing the thickness and type of phosphor depending on the measurement conditions, X-rays can be detected under optimal conditions.

[0086] When performing region segmentation of the subject 2 using the TT map, the processing unit 7 can divide the points plotted on the TT map into multiple point groups using, for example, an automatic classification algorithm based on a self-organizing map method or machine learning. As already mentioned, the region segmentation of the subject 2 may be performed manually by a user while viewing the TT map displayed on the display unit 8 of the X-ray imaging device using a user interface such as that shown in FIG.

[0087] As described above, the X-ray imaging device and X-ray imaging method according to this embodiment can use cross-sectional images of a subject acquired by X-ray CT at multiple temperatures to perform highly accurate region segmentation of the interior of a subject whose internal structure is unknown, dividing it into regions by material or structure. [Example]

[0088] Second Embodiment An X-ray imaging apparatus and an X-ray imaging method according to a second embodiment of the present invention will be described.

[0089] In the first embodiment, an X-ray CT imaging system has been described that visualizes changes in X-ray intensity that occur when X-rays pass through a subject. The X-ray imaging device and the X-ray imaging method according to the first embodiment have a problem in observing biological soft tissues and organic materials that are mainly composed of light elements with low absorption with high resolution. As described above, the linear absorption coefficient μ imaged in the first embodiment is given by the product of the density ρ of the subject and the mass absorption coefficient μ'. Therefore, it is difficult to accurately detect the density of the subject unless the elemental composition is known.

[0090] Therefore, the X-ray imaging device and X-ray imaging method according to this embodiment image the phase change (phase shift) of X-rays caused by the subject. In the hard X-ray region, the cross-section causing the phase shift is characterized by being more than 1000 times larger for light elements than the cross-section causing absorption. Therefore, by utilizing the phase shift, it is possible to observe biological soft tissues and organic materials, which are mainly composed of light elements, with high sensitivity and high resolution. Furthermore, because the phase shift is nearly proportional to the density, it is possible to accurately detect the density of a subject whose elemental composition is unknown.

[0091] Current technology does not allow for direct detection of the phase shift. Therefore, the phase shift must be converted into detectable X-ray intensity using an X-ray optical element or other suitable device. Examples of conversion methods include (1) X-ray interferometry using an X-ray interferometer, (2) refraction contrast detection using X-ray diffraction to detect X-ray refraction, (3) Talbot interferometry using a Talbot interferometer, and (4) propagation detection using Fresnel fringes. Among these, Talbot interferometry has the significant advantage of being applicable to quasi-monochromatic and diverging X-ray sources, i.e., laboratory X-ray sources. Furthermore, Talbot interferometry has a wide dynamic range in terms of density, making it possible to measure composite materials that combine metals and organic materials. In this example, we will explain an example using Talbot interferometry.

[0092] 7 is a diagram showing an example of the configuration of an X-ray imaging apparatus according to a second embodiment of the present invention. The X-ray imaging apparatus according to this embodiment is a phase X-ray CT equipped with a Talbot interferometer, which images a phase change (phase shift) of X-rays caused by a subject 2 by Talbot interferometry.

[0093] In the following, the X-ray imaging apparatus and X-ray imaging method according to this embodiment will be described, focusing mainly on the differences from the first embodiment.

[0094] The Talbot interferometer is a diffraction grating interferometer equipped with multiple X-ray diffraction gratings, namely, phase gratings 20 and absorption gratings 21. The X-ray diffraction grating has multiple regions in a lattice pattern, each with a different thickness and different X-ray transmittance. Below, an example will be described in which the Talbot interferometer is equipped with one phase grating 20 and one absorption grating 21.

[0095] The X-ray imaging apparatus according to the present embodiment includes a phase grating 20 and an absorption grating 21 between the subject 2 and the X-ray image detector 5, i.e., between the subject holder 3 and the X-ray image detector 5, in the X-ray imaging apparatus according to embodiment 1 (FIG. 5). The X-ray imaging apparatus according to the present embodiment further includes a phase grating moving mechanism 22 that moves or rotates the phase grating 20 relative to the absorption grating 21, and an absorption grating moving mechanism 23 that moves or rotates the absorption grating 21 relative to the phase grating 20. The phase grating moving mechanism 22 adjusts the position of the phase grating 20 relative to the subject 2. The absorption grating moving mechanism 23 adjusts the position of the absorption grating 21 relative to the phase grating 20.

[0096] The phase grating 20 and the absorption grating 21 are placed between the subject 2 and the X-ray image detector 5. Of the phase grating 20 and the absorption grating 21, the phase grating 20 is placed at a position closer to the subject 2 (or the X-ray source 1), and the absorption grating 21 is placed at a position closer to the X-ray image detector 5. The phase grating 20 is driven by a phase grating moving mechanism 22, and the absorption grating 21 is driven by an absorption grating moving mechanism 23, and their respective positions relative to the subject 2 are determined.

[0097] The interference fringes generated by the Talbot interferometer are measured by the X-ray image detector 5 .

[0098] The phase shift image is quantitatively acquired from a plurality of interference fringe images obtained by relatively moving the phase grating 20 and the absorption grating 21 by 1 / n (n is 3 or more) of the spacing between the phase grating 20 and the absorption grating 21. The processing unit 7 acquires such interference fringe images from the projection image of the subject 2 detected by the X-ray image detector 5 (the projection image obtained by relatively moving the phase grating 20 and the absorption grating 21). This interference fringe image is an image of the spatial differential amount of the phase, i.e., corresponds to a spatial differential distribution image of the phase shift.

[0099] The processing unit 7 calculates the phase shift by the following calculation. If the m-th interference image is Im, the phase shift φ is calculated as follows:

[0100]

number

[0101] It can be calculated by:

[0102] Furthermore, since the phase shift φ is proportional to the spatial differential of the density of the subject 2, a spatial distribution image of the phase shift, i.e., a density distribution image, can be obtained by integrating the obtained phase shift image in the same direction as the relative movement of the phase grating 20 and the absorption grating 21. By performing such calculations, the processing unit 7 can obtain the density distribution of the subject 2 from the obtained phase shift φ.

[0103] The procedure of the X-ray imaging method according to this embodiment is the same as that of embodiment 1 except that, instead of using X-ray CT in the flowchart (FIG. 6) shown in embodiment 1, phase X-ray CT using a fringe scanning method is used.

[0104] For the phase grating 20, it is preferable to use a diffraction grating in which the spacing between gratings (areas with different X-ray transmittances) is several micrometers and the phase of the X-rays is shifted by 1 / 4 or 1 / 2 of the wavelength of the X-rays, i.e., the difference in thickness between the gratings is 1 / 4 or 1 / 2 of the wavelength of the X-rays.

[0105] The absorption grating 21 preferably has a grating spacing of several micrometers, with one grating being thick enough to completely absorb X-rays. However, even if gold is used, a thickness of several tens of micrometers or more is required, which makes fabrication difficult. Therefore, a somewhat thinner diffraction grating, i.e., a diffraction grating with a difference in X-ray transmittance between gratings of approximately 30% or more, may be used for the absorption grating 21. However, in this case, the image clarity (visibility) of the interference image decreases, and the density resolution also decreases accordingly.

[0106] The phase grating 20 is positioned relative to the subject 2 by a phase grating moving mechanism 22, and the absorption grating 21 is positioned relative to the subject 2 by an absorption grating moving mechanism 23. If the axis used for fringe scanning is PZT driven (piezoelectrically driven), scanning can be performed at high speed, and data can be acquired in a shorter measurement time.

[0107] In this embodiment, the process up to the calculation of the TT map is the same as in Example 1. However, in this embodiment, the CT values ​​shown in the TT map are phase CT values, which are density distribution images. Therefore, by storing data showing the relationship between the volume expansion coefficient and density of a material in advance in a database, as shown in Figure 4, and comparing this data with the density change (volume expansion coefficient) accompanying the temperature change obtained from the TT map, it is possible not only to divide the subject into regions, but also to identify the material that constitutes each region.

[0108] For example, the processing unit 7 can compare the CT value (phase CT value) at temperature T1 or the CT value (phase CT value) at temperature T2 with the volume expansion coefficient, which is data stored in a database, to identify the material constituting each region of the subject 2 based on either or both of the volume expansion coefficient and density.

[0109] As described above, in the X-ray imaging apparatus and X-ray imaging method according to this embodiment, by using a Talbot interferometer, it is possible to perform highly accurate region division into materials or structures within the interior of a subject whose internal structure is unknown, and further to identify the materials that make up each region.

[0110] The present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to embodiments including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment. It is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to delete part of the configuration of each embodiment, or to add or replace other configurations. [Explanation of symbols]

[0111] 1...X-ray source, 2...subject, 3...subject holder, 4...subject moving mechanism, 5...X-ray image detector, 6...controller, 7...processing unit, 8...display unit, 9...subject temperature adjustment mechanism, 10...subject temperature adjustment mechanism control unit, 11...X-ray, 12...gas, 20...phase grating, 21...absorption grating, 22...phase grating moving mechanism, 23...absorption grating moving mechanism, 31...cross-sectional image at temperature T1, 32...cross-sectional image at temperature T2, 33...TT map, 34...points, 35a to 35d...point cloud, 36...cross-sectional image with regions separated by color, 37...point cloud created from cross-sectional images acquired at temperatures higher and lower than the phase transition temperature, 38...point cloud created from cross-sectional images acquired only at temperatures higher (or lower) than the phase transition temperature.

Claims

1. an X-ray source that emits X-rays that irradiate the subject; a subject moving mechanism that rotates the subject; an X-ray image detector for detecting a projection image of the subject by the X-rays; a subject temperature adjustment mechanism for changing the temperature of the subject; a processing unit that rotates the object and acquires a cross-sectional image of the object by reconstruction calculation from the plurality of projection images detected by the X-ray image detector; Equipped with the processing unit acquires a plurality of cross-sectional images of the subject captured at a plurality of temperatures different from each other, and divides the interior of the subject into regions by material using a distribution of pixels of the cross-sectional images based on CT values ​​at the plurality of temperatures at which the cross-sectional images of the subject were acquired. An X-ray imaging device characterized by:

2. the processing unit creates a distribution map showing a distribution of each pixel of the cross-sectional image based on a CT number at a first temperature and a CT number at a second temperature among the plurality of temperatures, divides the pixels plotted on the distribution map into a plurality of point clouds, and performs the region division based on the point clouds. The X-ray imaging device according to claim 1 .

3. the processing unit divides the pixels plotted on the distribution map into a plurality of point clouds using an automatic classification algorithm; The X-ray imaging device according to claim 2 .

4. the processing unit uses an algorithm that classifies data based on a self-organizing map method as the automatic classification algorithm; The X-ray imaging device according to claim 3 .

5. the first temperature is higher than a phase transition temperature of a material constituting the subject; the second temperature is lower than the phase transition temperature; The X-ray imaging device according to claim 2 .

6. a plurality of diffraction gratings for X-rays are provided between the object and the X-ray image detector; the processing unit calculates a phase shift from a plurality of interference fringe images obtained from a plurality of the diffraction gratings, and calculates a density distribution of the object from the phase shift. The X-ray imaging device according to claim 2 .

7. a database storing data indicating the relationship between the coefficient of volume expansion and the density of the material constituting the subject; the processing unit compares the CT number at the first temperature or the CT number at the second temperature with the volume expansion coefficient to identify a material inside the subject that has been divided into regions.

7. The X-ray imaging device according to claim 6.

8. two of the diffraction gratings, Of the two diffraction gratings, the diffraction grating installed closer to the subject has a difference in thickness between the gratings of ¼ or ½ of the wavelength of the X-rays, and the diffraction grating installed closer to the X-ray image detector has a difference in transmittance of the X-rays between the gratings of 30% or more.

7. The X-ray imaging device according to claim 6.

9. two of the diffraction gratings, a mechanism for moving one of the diffraction gratings relative to the other of the diffraction gratings; the processing unit acquires the interference fringe image from the projected image of the object obtained by moving the two diffraction gratings relative to one another.

7. The X-ray imaging device according to claim 6.

10. a temperature changing step in which the object temperature adjusting mechanism changes the temperature of the object; an irradiation step in which an X-ray source irradiates the object with X-rays; a projection image detection step in which an X-ray image detector detects a projection image of the subject formed by the X-rays; a region dividing step in which a processing unit that rotates the subject and obtains cross-sectional images of the subject by reconstruction calculation from the plurality of projection images detected by the X-ray image detector obtains the plurality of cross-sectional images of the subject imaged at a plurality of temperatures different from each other, and divides the interior of the subject into regions by material using distributions of pixels of the cross-sectional images based on CT values ​​at the plurality of temperatures at which the cross-sectional images of the subject were obtained; An X-ray imaging method comprising:

11. In the region dividing step, the processing unit creates a distribution map showing a distribution of each pixel of the cross-sectional image based on a CT number at a first temperature and a CT number at a second temperature among the plurality of temperatures, divides the pixels plotted on the distribution map into a plurality of point clouds, and performs the region dividing based on the point clouds. The X-ray imaging method according to claim 10.

12. In the region dividing step, the processing unit divides the pixels plotted on the distribution map into a plurality of point clouds using an automatic classification algorithm. The X-ray imaging method according to claim 11.

13. the first temperature is higher than a phase transition temperature of a material constituting the subject; the second temperature is lower than the phase transition temperature; The X-ray imaging method according to claim 11.

14. a plurality of diffraction gratings for X-rays are installed between the subject and the X-ray image detector; a density acquisition step in which the processing unit obtains a phase shift from a plurality of interference fringe images obtained from a plurality of the diffraction gratings, and obtains a density distribution of the object from the phase shift; The X-ray imaging method according to claim 11.

15. In the density acquisition step, the processing unit uses data indicating the relationship between the volume expansion coefficient and the density of the material constituting the object, and compares the CT number at the first temperature or the CT number at the second temperature with the volume expansion coefficient to identify the material inside the object after the region division.

15. The X-ray imaging method according to claim 14.

Images