Correction device, system, method, and program

Abstract

Provided are a correction device, a correction system, a correction method, and a correction program with which it is possible to reduce calculation cost for correcting an artifact due to a beam-hardening effect in reconstruction of a CT image. A correction device 400 for correcting an artifact due to a beam-hardening effect in reconstruction of a CT image, comprises: an incident X-ray distribution acquisition unit 410 that acquires an incident X-ray distribution; a linear absorption coefficient model acquisition unit 420 for acquiring a linear absorption coefficient model in which energy dependence of a linear absorption coefficient is expressed by a scale factor including a parameter; a projected image acquisition unit 430 that acquires a projected image; and a correction unit 440 that corrects the projected image by using the incident X-ray distribution and the linear absorption coefficient model.

Description

Technical Field

[0001] The present invention relates to a correction device, system, method, and program for correcting artifacts.

Background Art

[0002] A CT device reconstructs a CT image from a plurality of projection images obtained while rotating a sample or a gantry. Since the CT device uses continuous X-rays and the linear absorption coefficient at each energy differs for each substance, artifacts due to the beam hardening effect occur in the reconstructed CT image.

[0003] In order to reduce such artifacts due to the beam hardening effect, correction has conventionally been performed by hardware or software. As a software correction method, for example, Patent Document 1 discloses a technique for reducing artifacts by performing segmentation of a reconstructed image, identifying a substance, and repeating reconstruction using the linear absorption coefficient of the substance. Further, Patent Document 2 discloses a technique for reducing artifacts by repeatedly performing forward projection calculation and back projection calculation so that the difference between the original CT image in which metal artifacts occur and the CT image obtained by performing back projection calculation using a forward projection calculation considering the energy dependence of the linear absorption coefficient of the substance and an image reconstruction algorithm for a single wavelength becomes small.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the technique described in Patent Document 1 requires prior knowledge of physical property values such as the mass density and mass absorption coefficient of the sample. In addition, since it is necessary to repeat segmentation and reconstruction, the calculation cost is high. The technique described in Patent Document 2 requires repeated forward projection calculations and back projection calculations, so the calculation cost is high.

[0006] The present invention has been made in view of such circumstances, and an object thereof is to provide a correction device, a system, a method, and a program capable of reducing the calculation cost for correcting artifacts due to beam hardening effects in CT image reconstruction.

Means for Solving the Problems

[0007] (1) To achieve the above object, a correction device of the present invention is a correction device for correcting artifacts due to beam hardening effects in CT image reconstruction, and includes an incident X-ray distribution acquisition unit that acquires an incident X-ray distribution, a linear absorption coefficient model acquisition unit that acquires a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including a parameter, a projection image acquisition unit that acquires a projection image, and a correction unit that corrects the projection image using the incident X-ray distribution and the linear absorption coefficient model.

[0008] (2) Further, in the correction device of the present invention, the linear absorption coefficient model is characterized in that it is represented by the product of the linear absorption coefficient at a reference energy and the scale factor.

[0009] (3) Further, in the correction device of the present invention, the parameter of the linear absorption coefficient model is characterized in that it is a single parameter.

[0010] (4) Further, in the correction device of the present invention, the scale factor is characterized in that it is represented by a power function having a power exponent as the parameter.

[0011] (5) Further, in the correction device of the present invention, the parameter of the linear absorption coefficient model is characterized in that it is determined based on the energy range of the incident X-ray distribution.

[0012] (6) Further, in the correction device of the present invention, the parameter of the linear absorption coefficient model is characterized in that it is determined from the linear absorption coefficients of a representative group of elements.

[0013] (7) Further, in the correction device of the present invention, the incident X-ray distribution acquisition unit is characterized in that it acquires the incident X-ray distribution based on the number, intensity, and energy value of monochromatic X-rays.

[0014] (8) Further, the correction device of the present invention includes a reconstruction unit that performs reconstruction based on the projection data corrected by the correction unit to generate a CT image, and a display unit that displays the CT image on a display device.

[0015] (9) Further, the system of the present invention includes a CT device including an X-ray source that generates X-rays, a detector that detects X-rays, and a rotation control unit that controls the rotation of the X-ray source and the detector, or a sample, and the correction device according to any one of (1) to (8) above.

[0016] (10) Further, the method of the present invention is a method for correcting artifacts due to beam hardening effects in the reconstruction of CT images, and includes steps of acquiring an incident X-ray distribution, acquiring a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including parameters, acquiring a projection image, and correcting the projection image using the incident X-ray distribution and the linear absorption coefficient model.

[0017] (11) Further, the program of the present invention is a program for correcting artifacts caused by the beam hardening effect in the reconstruction of CT images, and includes a process of acquiring an incident X-ray distribution, a process of acquiring a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including parameters, a process of acquiring a projection image, and a process of correcting the projection image using the incident X-ray distribution and the linear absorption coefficient model, and is characterized in that the computer is caused to execute the processes.

Brief Description of Drawings

[0018]

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Embodiments for Carrying Out the Invention

[0019] Next, embodiments of the present invention will be described with reference to the drawings. For ease of understanding of the description, the same reference numerals are assigned to the same components in each drawing, and duplicate descriptions are omitted.

[0020] [Principle] The CT apparatus irradiates a sample with cone-shaped or parallel beams of X-rays from all angles, and a detector acquires the distribution of the X-ray absorption coefficient, that is, a projection image. In order to irradiate X-rays from all angles, the CT apparatus is configured to rotate a sample stage with respect to a fixed X-ray source and detector, or to rotate a gantry in which the X-ray source and detector are integrated.

[0021] In this way, the distribution of the linear absorption coefficient f of the sample can be estimated from the shades of the projection images of the sample obtained by performing projections from various angles. And obtaining a three-dimensional linear absorption coefficient distribution from two-dimensional projection images is called reconstruction. Reconstruction basically performs back-projection of the projection image.

[0022] In a CT apparatus, continuous X-rays are used as the incident X-rays, which are irradiated onto a sample to measure a projection image. The linear absorption coefficient of a substance has energy dependence, and X-rays with higher energy tend to be less absorbed. Therefore, when continuous X-rays pass through a sample as the incident X-rays, the energy distribution after passing through is not similar to the original distribution, and the centroid shifts to the high-energy side. This phenomenon is called beam hardening (hardening of the ray quality).

[0023] Reconstruction is usually performed assuming monochromatic X-rays. On the other hand, in actual measurement, continuous X-rays with a wide energy distribution are used. When continuous X-rays pass through a substance, X-rays with lower energy are more likely to be absorbed by the sample and attenuated compared to those with higher energy. Therefore, the linearity between the X-ray transmission distance and the X-ray attenuation is lost, and non-linearity appears. When monochromatic X-rays pass through a substance, linearity is maintained. Thus, artifacts occur because the reconstruction assumption does not match the actual phenomenon. Such artifacts are called artifacts due to the beam hardening effect.

[0024] Conventionally, to suppress artifacts due to the beam hardening effect, correction has been performed by hardware or software. Since no artifacts due to the beam hardening effect occur with completely monochromatic X-rays, in the hardware correction method, basically, by narrowing the width of the incident X-ray distribution, the artifacts due to the beam hardening effect are made less noticeable. For example, only X-rays near a specific energy are extracted using a filter, or monochromatic X-rays are extracted using a mirror.

[0025] In software-based correction, image processing is performed for correction. For example, the Helgason-Ludwig condition method reduces artifacts by nonlinearly correcting the intensity of projection images using physical conditions such as the conservation law of linear absorption coefficients. Since correction is performed based on the assumption that the projection image data is consistent in this method, for example, when the sample protrudes from the FOV during measurement (interior CT), when there are defects in the projection image, when there is a deviation in the optical system such as center shift, etc., it cannot be applied when phenomena other than the beam hardening effect occur. Also, since the calculation of the correction amount uses the integration of the projection image, due to the compression of information, the correction may not work well, such as the reversal of the magnitude relationship of X-ray intensities or the pixel values becoming negative.

[0026] There is also a method of reconstruction based on known conditions of the sample. For example, under the assumption that the sample should have many uniform parts and that non-uniform parts should be caused by artifacts, a method of sequentially reconstructing so that the total variation (TV) of the reconstructed image becomes small. Such a method requires knowing in advance what substances are contained in the sample. In medical and dental CT where the contained substances are limited, such a method is often used and is effective, but it cannot be used for samples whose contents are unknown. Also, in the sequential method using TV regularization, the calculation time is long, causing practical problems.

[0027] There is also a method of considering the incident X-ray distribution and the energy dependence of the absorption coefficient and performing projection calculation assuming continuous X-rays for correction in the sequential method. In the sequential method using energy information, the calculation time inevitably becomes long, causing practical problems.

[0028] The present invention can correct the projection image by using a linear absorption coefficient model that represents the projection image with a scale factor (auxiliary variable) including the energy dependence of the incident X-ray distribution and the linear absorption coefficient, and can perform the correction for each detector pixel at each projection angle. As a result, segmentation is not required and accurate information of the sample is not used. Further, since the processing is performed before reconstruction, the computational cost for correcting artifacts due to the beam hardening effect in the reconstruction of the CT apparatus can be reduced. Furthermore, it can be applied even when phenomena other than the beam hardening effect occur. Note that the linear absorption coefficient model is a function selected to approximate the energy dependence of the distribution of the linear absorption coefficient. This model is represented, for example, by multiplying the distribution of the linear absorption coefficient at the energy E0 in the scale factor. Here, the scale factor is a non-negative function s(E) with respect to the energy E, whose value at a reference energy E0 is 1.

[0029] Hereinafter, the correction method of the present invention will be described in detail. In the present invention, first, it is assumed that the continuous X-ray is a collection of a finite number of monochromatic X-rays. FIGS. 1(a) and 1(b) are a conceptual diagram of the X-ray transmitted through the sample and a conceptual diagram showing the relationship between a part of the discretized monochromatic X-rays and the measurement space (voxel) of the sample measured by CT measurement, respectively. Generally, regarding the linearity between the transmission distance of the X-ray and the attenuation of the X-ray, the X-ray intensity I detected by the detector is expressed by Equation (1) when the thickness of the object is l, the linear absorption coefficient is μ, and the incident X-ray intensity is I0 (Lambert-Beer 's law).

[0030]

Equation

[0031] Assuming that the continuous X-ray is a collection of N finite monochromatic X-rays, the incident X-ray intensity I0 is the intensity I of each monochromatic X-ray kIt is replaced with the intensity integrated for (k = 1, 2, …, N). Also, the X-ray transmission distance and the non-linearity of X-ray attenuation are represented by adding up the attenuation of each monochromatic X-ray with the total energy. The intensity I detected by each detector pixel is expressed by the following formula (2) as the sum of the intensities of each monochromatic X-ray attenuated by the substance.

[0032]

Equation

[0033] The energy distribution of the continuous X-ray is the intensity I of N monochromatic X-rays k and the energy E of each monochromatic X-ray k which can be represented as a distribution as shown in FIG. 2. FIG. 2 is a graph showing an example of the incident X-ray distribution. For example, when an incident X-ray distribution as shown in FIG. 2 is assumed, if the continuous X-ray is represented as an energy distribution composed of N = 10 monochromatic X-rays, the energy range of the incident X-ray distribution and the energy values E of N monochromatic X-rays k (k = 1, 2, …, N) are set. For example, assuming that the energy range of the incident X-ray distribution is 10 keV to 55 keV, 10 energy values and numbers such as 10, 15, 20, …, 55 keV may be set at equal intervals. Also, from the shape of the distribution, the energy values and numbers of the monochromatic X-rays may be determined such that those with large changes are taken densely and those with low intensity are taken sparsely.

[0034] Setting the energy value, number, and intensity of the monochromatic X-ray corresponds to setting I in formula (2). k The number of monochromatic X-rays to be set needs to be 3 or more, and preferably 5 or more. Since the incident X-ray distribution can be somewhat understood from the information on the tube voltage and the filter, such knowledge may be utilized. Also, the user may arbitrarily select or specify it.

[0035] In the present invention, f(E on the right side of formula (2) kReplace it with a linear absorption coefficient model that represents the energy dependence of with a scale factor including parameters. The energy dependence of the linear absorption coefficient is represented by a scale factor including parameters. The scale factor s(E k ) The energy range (domain of s(E k ) for calculation) is set to include the energy range where the incident X-ray distribution is set. For example, f(E k ) can be expressed as the product of the linear absorption coefficient f(E0) for a certain reference energy E0 included in the domain of the scale factor and the scale factor s(E k ) including parameters, as shown in Equation (3) below. By performing correction using such a linear absorption coefficient model, a projection image of the distribution of the linear absorption coefficient at the reference energy can be obtained.

[0036]

Equation

[0037] Replacing f(E k ) on the right side of Equation (1) with the equation on the right side of Equation (3), Equation (2) becomes the following Equation (4).

[0038]

Equation

[0039] Equation (2) calculates the line integral of the projection image for all energies. Therefore, Equation (2) needs to calculate the value of the line integral for each energy. In contrast, Equation (4) calculates the line integral of the projection image for a certain energy E0. Therefore, Equation (4) can obtain information on other energies from the absorption coefficient at the reference energy through the scale factor. Since the number of unknowns decreases, the calculation becomes easier. Also, the parameter of the scale factor is preferably set to one parameter. This makes the calculation even easier. However, when calculating accurately, multiple parameters may be set.

[0040] Solving this equation by the Newton method or the like makes it possible to obtain a projection image of the distribution of the linear absorption coefficient at a certain energy E0. The value of this line integral corresponds to the projection of the distribution of the linear absorption coefficient at the energy E0. This is taken as the corrected projection image. That is, the projection image of the continuous X-ray is converted into the projection image at a certain energy E0. Reconstruction using such a corrected projection image can obtain a CT image with artifacts reduced due to the beam hardening effect.

[0041] The reference energy E0 can be selected arbitrarily as long as it is within the domain of s(E k ). For example, it may be the lower limit value of the energy range of the incident X-ray distribution, or it may be the average value of the energy range of the incident X-ray distribution.

[0042] Next, a functional form representing the linear absorption coefficient model is set. The scale factor of the linear absorption coefficient model is preferably represented by a power function with a power exponent as a parameter. This makes the calculation for correction even easier. That the scale factor of the linear absorption coefficient model is represented by a power function means, for example, that s(E k ) in Equation (3) is represented as in the following Equation (5). However, the scale factor included in the linear absorption coefficient model is not limited to this. Any function that can approximate the energy dependence of the linear absorption coefficient may be used. For example, an exponential function, a logarithmic function, etc. may be used. The scale factor included in the linear absorption coefficient model is preferably selected from the viewpoints of both the degree of approximation of the energy dependence of the linear absorption coefficient and the subsequent calculation cost.

[0043]

Equation

[0044] As a result, the linear absorption coefficient model is represented as in the following Equation (6). Also, when representing the intensity I detected by each detector pixel using the linear absorption coefficient model, it is represented as in Equation (7).

[0045] [Number]

[0046] [Number]

[0047] Further, the linear absorption coefficient model is preferably determined based on the energy range of the incident X-ray distribution. Thereby, an appropriate linear absorption coefficient model can be determined according to the linear absorption coefficients of typical element groups, and artifacts due to the beam hardening effect can be corrected more appropriately. That the linear absorption coefficient model is determined based on the energy range of the incident X-ray distribution means that s(E k ) and E0 in Equation (4) can be changed according to the energy range of the incident X-ray distribution. When using the linear absorption coefficient model, the linear absorption coefficient of each monochromatic X-ray can be calculated from the behavior of the linear absorption coefficients of typical elements in the assumed incident X-ray distribution. For example, when the incident X-ray distribution is in the energy range used in a general CT apparatus (for example, 10 to 100 keV), if the energy dependence of the linear absorption coefficients of elements (such as Ti, Fe, etc.) considered as causes of metal artifacts is known, from the ratio of the scale factors at the reference energy E0 and the energy E k of each monochromatic X-ray, the linear absorption coefficient f(E k ) of each monochromatic X-ray can be calculated based on the linear absorption coefficient f(E0) at the reference energy E0. At this time, only the values of the parameters may be changed with the same function. When the linear absorption coefficient model is represented by a power function, it is preferable to determine and change the parameter α as follows.

[0048] The parameters α in Equation (6) and Equation (7) are preferably set so that the attenuation manner of the mass absorption coefficient of the element applied to the correction is similar to that of the elements contained in the sample. Since the mass absorption coefficient has characteristics such as different slopes for different elements, different positions of absorption edges, and different slopes before and after the absorption edges, it is preferable to set α by the following method. (i) Select representative elements. For example, elements such as Ti (α = -2.667) and Fe (α = -2.707) can be selected as representative elements. FIGS. 3 and 4 are graphs showing the mass absorption coefficients of Ti and Fe, respectively. The representative elements are preferably elements contained in the sample. Also, it is preferable to select an element whose absorption edge is not included in the energy range used. (ii) The representative elements to be selected are preferably selected from among the light element group, the middle element group, and the heavy element group. For example, the light element group can be from H to Ne, the middle element group can be from Na to Ca, and the heavy element group can be Sc and later. The boundaries of the light element group, the middle element group, and the heavy element group can be changed depending on the field. Also, it is preferable to identify elements with similar energy dependencies of the linear absorption coefficient. The parameter α is preferably calculated by fitting a power function, but it does not necessarily have to match the fitting result, and it can be arbitrarily set based on the fitting result as a reference. (iii) When an element whose absorption edge is included in the energy range to be used is selected, the slope α before the absorption edge R , the slope α after the absorption edge L It is preferable to calculate the average slope and use it as α.

[0049] As described above, by expressing the linear absorption coefficient model with a power factor and appropriately setting the value of the parameter α within a predetermined range, the calculation for correction becomes easier, and artifacts due to the beam hardening effect in the reconstruction of the CT apparatus can be effectively corrected. Also, the calculation cost for this can be significantly reduced.

[0050] [Overall system] FIG. 5 is a schematic diagram showing the configuration of an entire system 100 including a CT apparatus 200, a processing apparatus 300, a correction apparatus 400, an input apparatus 510, and a display apparatus 520 connected thereto. Here, the CT apparatus 200 shown in FIG. 5 is configured to rotate a sample with respect to an X-ray source 260 and a detector 270, but is not limited thereto, and may be configured to rotate a gantry in which the X-ray source and the detector are integrated. Further, the CT apparatus 200 can use either an apparatus using a parallel beam or an apparatus using a cone beam.

[0051] The processing apparatus 300 is connected to the CT apparatus 200 and controls the CT apparatus 200 and processes the acquired data. The correction apparatus 400 corrects projection images. The processing apparatus 300 and the correction apparatus 400 may be a PC terminal or a server on the cloud. The input apparatus 510 is, for example, a keyboard and a mouse, and inputs to the processing apparatus 300 and the correction apparatus 400. The display apparatus 520 is, for example, a display, and displays projection images and the like.

[0052] Note that in FIG. 5, in order to emphasize the correction function of the correction apparatus 400, the processing apparatus 300 and the correction apparatus 400 are shown as separate components. However, as shown in FIG. 6, the correction apparatus 400 may be configured as a part of the functions included in the processing apparatus 300, or the correction apparatus 400 and the processing apparatus 300 may be configured as an integral unit. FIG. 6 is a schematic diagram showing a modification of the configuration of the entire system. By using such a system, the computational cost for correcting artifacts due to the beam hardening effect in the reconstruction of CT images can be reduced.

[0053] [CT Apparatus] As shown in FIG. 5, the CT apparatus 200 includes a rotation control unit 210, a sample stage 250, an X-ray source 260, a detector 270, and a drive unit 280. An X-ray CT image is taken by rotating the sample stage 250 installed between the X-ray source 260 and the detector 270. Note that the X-ray source 260 and the detector 270 may be installed on a gantry (not shown), and the gantry may be rotated with respect to a sample fixed to the sample stage 250.

[0054] The CT device 200 drives the sample stage 250 at the timing instructed by the processing device 300 and acquires a projection image of the sample. The measurement data is transmitted to the processing device 300. The CT device 200 is suitable for use in precision industrial products such as semiconductor devices, and can be applied not only to industrial devices but also to animal devices.

[0055] The X-ray source 260 irradiates the X-rays toward the detector 270. The detector 270 has a light-receiving surface for receiving the X-rays, and can measure the intensity distribution of the X-rays transmitted through the sample by a large number of pixels. The rotation control unit 210 rotates the sample stage 250 at the speed set during CT imaging by the drive unit 280.

[0056] [Processing device] FIG. 7 is a block diagram showing the configurations of the processing device 300 and the correction device 400. The processing device 300 is configured by a computer in which a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and a memory are connected to a bus. The processing device 300 is connected to the CT device 200 and receives information.

[0057] The processing device 300 includes a measurement data storage unit 310, a device information storage unit 320, a reconstruction unit 330, and a display unit 340. Each unit can transmit and receive information via the control bus L. The input device 510 and the display device 520 are connected to the CPU via appropriate interfaces.

[0058] The measurement data storage unit 310 stores the measurement data acquired from the CT apparatus 200. The measurement data includes rotation angle information and the corresponding projection images. The apparatus information storage unit 320 stores the apparatus information acquired from the CT apparatus 200. The apparatus information includes the apparatus name, beam shape, geometry at the time of measurement, scanning method, etc. The reconstruction unit 330 reconstructs a CT image from the target projection image. The display unit 340 causes the reconstructed CT image to be displayed on the display device 520. Thereby, the user can confirm the CT image based on the corrected projection image. Also, the user can give instructions and designations to the processing device, correction device, etc. based on the CT image.

[0059] [Correction device] The correction device 400 is constituted by a computer in which a CPU, ROM, RAM, and memory are connected to a bus. The correction device 400 may be directly connected to the CT apparatus 200, or may be connected to the CT apparatus 200 via the processing device 300. Also, the correction device 400 may receive information from the CT apparatus 200, or may receive information from the processing device 300. Note that, as shown in FIG. 8, the correction device 400 may be configured as a part of the functions included in the processing device 300, or as shown in FIG. 9, the correction device 400 and the processing device 300 may be configured as an integral unit. Also, the correction device 400 may have a part of the functions of the processing device 300.

[0060] The correction device 400 includes an incident X-ray distribution acquisition unit 410, a linear absorption coefficient model acquisition unit 420, a projection image acquisition unit 430, and a correction unit 440. Each unit can transmit and receive information via the control bus L. When the correction device 400 and the processing device 300 have separate configurations, the input device 510 and the display device 520 are also connected to the CPU of the correction device 400 via appropriate interfaces. In this case, the input device 510 and the display device 520 may be different from those connected to the processing device 300.

[0061] The incident X-ray distribution acquisition unit 410 acquires the incident X-ray distribution. It is preferable that the incident X-ray distribution acquisition unit 410 acquires the incident X-ray distribution based on the number, intensity, and energy value of the monochromatic X-rays. Thereby, a more appropriate incident X-ray distribution according to the situation can be acquired. Also, it is preferable that the incident X-ray distribution acquisition unit 410 acquires the incident X-ray distribution based on user designation. Thereby, the user can select a more appropriate incident X-ray distribution according to the situation. When the incident X-ray distribution is designated by the user, for example, one is designated from a plurality of incident X-ray distributions stored in advance by a mouse operation, a point on the graph of the incident X-ray distribution is moved, the number of points on the graph is increased or decreased, etc., it is preferable to use a UI function capable of setting the incident X-ray distribution. The incident X-ray distribution may be set in advance. Also, the incident X-ray distribution may be automatically selected and acquired according to device information or the like.

[0062] The linear absorption coefficient model acquisition unit 420 acquires a linear absorption coefficient model in which the energy dependence of the linear absorption coefficient is represented by a scale factor including parameters. It is preferable that the linear absorption coefficient model acquisition unit 420 acquires the linear absorption coefficient model based on user designation. A functional form representing the energy dependence of the linear absorption coefficient is stored in a storage unit (not shown) of the correction device 400 or the processing device 300. For example, an expression representing the model of the linear absorption coefficient f(E k ), or an expression representing the reference energy (E0) and the scale factor s(E k ) is stored. Also, the element group that may be included in the sample is correlated with the parameter α of the linear absorption coefficient model and stored. When the linear absorption coefficient model is designated by the user, for example, one is designated from a plurality of functional forms representing the linear absorption coefficients stored in advance by a mouse operation, and the parameter α is set by selecting the element group. Also, the parameter α may be directly inputtable by the user. Thus, it is preferable to use a UI function capable of setting the linear absorption coefficient model. The linear absorption coefficient model may be set in advance. Also, the linear absorption coefficient model may be automatically selected and acquired according to sample information or the like.

[0063] The projection image acquisition unit 430 acquires a projection image from the CT apparatus 200 or the processing apparatus 300. The correction unit 440 corrects the projection image using the incident X-ray distribution and the linear absorption coefficient model. As a result, a CT image with reduced artifacts due to the beam hardening effect can be obtained.

[0064] [Measurement method] A sample is placed in the CT apparatus 200, and by repeating the movement of the rotation axis and the projection of X-rays under predetermined conditions, a projection image is acquired while irradiating the sample with X-rays. The CT apparatus 200 transmits apparatus information such as the scanning method and the acquired projection image as measurement data to the processing apparatus 300 or the correction apparatus 400.

[0065] [Correction method] FIG. 10 is a flowchart showing an example of the operation of the correction apparatus 400. First, the correction apparatus 400 acquires the incident X-ray distribution (step S1). Next, the linear absorption coefficient model is acquired (step S2). Next, the projection image is acquired (step S3). Then, the acquired projection image is corrected using the incident X-ray distribution and the linear absorption coefficient model (step S4). In this way, the projection image can be corrected using a linear absorption coefficient model that represents the energy dependence of the incident X-ray distribution and the linear absorption coefficient by a scale factor including parameters. Note that the acquisition of the incident X-ray distribution, the acquisition of the linear absorption coefficient model, and the acquisition of the projection image may be performed in any order.

[0066] [Correction and reconstruction method] The flowchart of FIG. 10 shows only the operation of the correction apparatus 400. Although this is sufficient for the correction of the projection image, for the sake of clarity of the difference from the prior art, the operations including the measurement and reconstruction of the projection image will also be described.

[0067] FIG. 11 is a flowchart showing an example of the operation of system 100. First, correction device 400 acquires the incident X-ray distribution (step T1). Next, it acquires the linear absorption coefficient model (step T2). Next, CT device 200 measures the projection image (step T3). The measurement of the projection image includes the movement of the rotation axis and the repetition of X-ray projection. Next, correction device 400 acquires the projection image (step T4). Next, it corrects the projection image using the acquired incident X-ray distribution and the linear absorption coefficient model (step T5). Then, processing device 300 or correction device 400 reconstructs the CT image using the corrected projection image (step T6). In this way, a CT image reconstructed using the corrected projection image can be obtained. Note that, similar to the above, the acquisition of the incident X-ray distribution, the acquisition of the linear absorption coefficient model, and the acquisition of the projection image can be performed in any order without problem.

[0068] In the prior art, after obtaining the reconstructed CT image, image processing for artifact reduction was repeated. In contrast, in the present invention, correction for artifact reduction is performed on the projection image before reconstruction. By doing so, the computational cost can be reduced.

[0069] FIG. 12 is a flowchart showing a modified example of the operation of system 100. First, correction device 400 acquires the incident X-ray distribution (step U1). Next, it acquires the linear absorption coefficient model (step U2). Next, CT device 200 moves the rotation axis (step U3). Next, it performs X-ray projection (step U4). Next, correction device 400 acquires the projection image projected previously (step U5). Next, it corrects the projection image using the acquired incident X-ray distribution and the linear absorption coefficient model (step U6).

[0070] Next, the processing device 300 or the correction device 400 determines whether the measurement is completed (step U7). In step U7, if it is determined that the measurement is not completed (step U7, NO), the process returns to step U3. On the other hand, in step U7, if the processing device 300 or the correction device 400 determines that the measurement is completed (step U7, YES), a CT image is reconstructed using the corrected projection image (step U8). By doing so, the measurement of the projection image and the correction of the measured projection image can be processed in parallel, and the overall time can be shortened. Note that the acquisition of the incident X-ray distribution and the acquisition of the linear absorption coefficient model may be performed in the reverse order without any problem.

[0071] [Example 1] Using the system 100 configured as described above, a cross-section of a hydroxyapatite phantom (manufactured by QRM: Micro-CT HA Phantom) (sample 1) was observed. For the CT device 200, measurement was performed at a tube voltage of 60 kV using Rigaku's CTLabHX. FIGS. 13(a) and (b) are the CT images of sample 1 reconstructed using the uncorrected projection image and the CT image of sample 1 reconstructed using the corrected projection image, respectively. Also, FIGS. 14(a) and (b) are graphs showing the line profiles on the straight line AB of the CT images of FIGS. 13(a) and (b), respectively. The reconstruction used the FDK method.

[0072] By comparing FIGS. 13(a) and (b), it was found that the streak artifact between the two high absorbers was reduced by the correction. Also, by comparing FIGS. 14(a) and (b), it was confirmed that the capping artifact at the end of the high absorber was reduced.

[0073] [Example 2] Next, five acrylic rods with a diameter of 3 mm and four aluminum rods with a diameter of 9 mm were inserted into the wood, and Sample 2 was prepared with two hollow holes having a diameter of 3 mm and two hollow holes having a diameter of 1.5 mm. Using the above system 100, the cross-section of Sample 2 was observed. The tube voltage was set to 100 kV. FIGS. 15(a) and (b) are respectively the CT image of Sample 2 reconstructed using the uncorrected projection image and the CT image of Sample 2 reconstructed using the corrected projection image. Also, FIGS. 16(a) and (b) are graphs showing the line profiles on the straight line AB of the CT images of FIGS. 15(a) and (b), respectively.

[0074] By comparing FIGS. 15(a) and (b), it was found that the streak artifacts and dark bands were reduced by the correction. Also, by comparing FIGS. 16(a) and (b), reduction of the capping artifacts at the ends of the aluminum rods was confirmed.

[0075] From the above results, it was confirmed that the correction device, system, method, and program of the present invention can effectively correct the artifacts due to the beam hardening effect in the reconstruction of CT images and can reduce the computational cost.

[0076] This application claims priority based on Japanese Patent Application No. 2021-122585 filed on July 27, 2021, and incorporates the entire contents of Japanese Patent Application No. 2021-122585 into this application.

Explanation of Reference Numerals

[0077] 100 System 200 CT Apparatus 210 Rotation Control Unit 250 Sample Stage 260 X-ray Source 270 Detector 280 Driving Unit 300 Processing Device 310 Measurement Data Storage Unit 320 Device Information Storage Unit 330 Reconstruction Unit 340 Display unit 400 Correction device 410 Incident X-ray distribution acquisition unit 420 Linear absorption coefficient model acquisition unit 430 Projection image acquisition unit 440 Correction unit 510 Input device 520 Display device

Claims

1. A correction device for correcting artifacts caused by beam hardening effects in the reconstruction of CT images, comprising: An incident X-ray distribution acquisition unit for acquiring an incident X-ray distribution; A linear absorption coefficient model acquisition unit for acquiring a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including parameters; A projection image acquisition unit for acquiring a projection image; A correction unit for correcting the projection image using the incident X-ray distribution and the linear absorption coefficient model, The correction device, wherein the linear absorption coefficient model is represented by the product of the linear absorption coefficient at a reference energy and the scale factor.

2. The correction device according to claim 1, wherein the parameter of the linear absorption coefficient model is one parameter.

3. The correction device according to claim 1 or claim 2, wherein the scale factor is represented by a power function having a power exponent as the parameter.

4. The correction device according to any one of claims 1 to 3, wherein the parameter of the linear absorption coefficient model is determined based on the energy range of the incident X-ray distribution.

5. The correction device according to any one of claims 1 to 4, wherein the parameter of the linear absorption coefficient model is determined from the linear absorption coefficients of a representative group of elements.

6. The correction device according to any one of claims 1 to 5, wherein the incident X-ray distribution acquisition unit acquires the incident X-ray distribution based on the number, intensity, and energy value of monochromatic X-rays.

7. A reconstruction unit for performing reconstruction based on the projection image corrected by the correction unit to generate a CT image, The correction device according to any one of claims 1 to 6, further comprising a display unit for displaying the CT image on a display device.

8. A CT device comprising an X-ray source for generating X-rays, a detector for detecting X-rays, and a rotation control unit for controlling the rotation of the X-ray source and the detector, or a sample, The system, further comprising the correction device according to any one of claims 1 to 7.

9. A method for correcting artifacts caused by beam hardening effects in the reconstruction of CT images, comprising: A step of acquiring an incident X-ray distribution; A step of acquiring a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including parameters; A step of acquiring a projection image; correcting the projection image using the incident X-ray distribution and the linear absorption coefficient model; The method is characterized in that the linear absorption coefficient model is represented by the product of the linear absorption coefficient at a reference energy and the scale factor. **Claim 10** A program for correcting artifacts caused by beam hardening effects in CT image reconstruction, a process of obtaining an incident X-ray distribution, a process of obtaining a linear absorption coefficient model representing the energy dependence of the linear absorption coefficient by a scale factor including parameters, a process of obtaining a projection image, causing a computer to execute a process of correcting the projection image using the incident X-ray distribution and the linear absorption coefficient model; The program is characterized in that the linear absorption coefficient model is represented by the product of the linear absorption coefficient at a reference energy and the scale factor.

Images