IMAGE PROCESSING APPARATUS, RADIOLOGICAL IMAGE CAPTURE SYSTEM, IMAGE PROCESSING METHOD, AND IMAGE PROCESSING PROGRAM

Abstract

To provide an image processing device, a radiation ray image imaging system, an image processing method and an image processing program capable of accurately correcting a body motion of a subject.SOLUTION: A CPU 50A of a console 12 acquires a plurality of projection images, then performs optimization processing on the basis of a projection image for a plurality of radiation positions 19t, about a forward projection model 53 which has, as parameters, an absorption coefficient μ which is allocated for every voxel 91j of a three-dimensional model 90 which includes as constitution units, a plurality of voxels 91j which is virtually set on a three-dimensional space in which a subject U is arranged, a crossing length wtij for every voxel 91j in which a passage Xti of a radiation ray R radiated from the radiation position 19t crosses the three dimensional model 90, a body motion amount θt of the subject U, then generates a tomographic image of the subject U using the parameters subjected to the optimization processing.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present disclosure relates to an image processing device, a radiation image capturing system, an image processing method, and an image processing program. [Background technology]

[0002] 2. Description of the Related Art So-called tomosynthesis imaging is known in which a radiation source irradiates a subject from a plurality of irradiation positions each having a different irradiation angle, and a plurality of projection images of the subject are captured at different irradiation positions.

[0003] In tomosynthesis imaging, since multiple projection images are captured, positional deviations may occur between the projection images due to the influence of the subject's body movements, etc. A tomographic image generated using multiple projection images with positional deviations may be blurred.

[0004] Therefore, a technique for correcting the positional shift between projected images, i.e., the body movement of the subject, is known. For example, Patent Document 1 discloses a technique for deriving the amount of positional shift between a plurality of projected images on a slice plane corresponding to a slice image on which a feature point is detected, using the feature point as a reference, and generating a slice image using the projected images whose positional shifts have been corrected according to the derived amount of positional shift. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2020 / 067475 Summary of the Invention [Problem to be solved by the invention]

[0006] However, a projection image is an image in which a plurality of structures existing on the path of radiation are projected in a superimposed manner, and contains a lot of information. In the above conventional technology, there were cases where the body movement of the subject could not be corrected due to the influence of information on structures other than the feature points.

[0007] The present disclosure has been made in consideration of the above circumstances, and aims to provide an image processing device, a radiographic image capturing system, an image processing method, and an image processing program that can accurately correct the body movement of a subject. [Means for solving the problem]

[0008] In order to achieve the above object, an image processing device according to a first aspect of the present disclosure is an image processing device that processes a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, and includes at least one processor, wherein the processor acquires the plurality of projection images, and performs optimization processing based on the projection images for each of the plurality of irradiation positions for a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from the irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, and generates a tomographic image of the subject using the parameters thus optimized, When the amount of body movement derived by the optimization process exceeds a preset threshold, a warning is issued. .

[0009] An image processing device according to a second aspect of the present disclosure is the image processing device according to the first aspect, wherein the processor generates a tomographic image using absorption coefficients of the forward projection model that has been subjected to an optimization process.

[0010] According to a third aspect of the present disclosure, in the image processing device according to the first or second aspect, the processor performs optimization processing by selecting an image from a plurality of irradiation positions. doubt By performing pseudoprojection, each pixel value of a plurality of pseudoprojected images obtained by the forward projection model is made to approach the pixel values ​​of a plurality of projected images.

[0011] An image processing device of a fourth aspect of the present disclosure is the image processing device of the third aspect, in which a processor performs optimization processing by deriving an absorption coefficient and a body movement amount that bring the pixel values ​​of the pseudo projection image closer to the pixel values ​​of multiple projection images.

[0013] The present disclosure 5 The image processing device of the present embodiment is any one of the first to third embodiments. 4 In an image processing device of any one of the above aspects, a processor derives body movement based on a forward projection model using a three-dimensional model that is virtually set in a three-dimensional space corresponding to a characteristic region of the subject in the three-dimensional space in which the subject is placed, and generates a tomographic image using the derived body movement and the forward projection model using the three-dimensional model that is virtually set in the three-dimensional space in which the subject is placed.

[0014] The present disclosure 6 The image processing device of the present invention is 5 In the image processing device of the aspect, the characteristic region is a region including a structure having a feature amount equal to or greater than a threshold value.

[0015] The present disclosure 7 The image processing device of the present invention is 6 In the image processing device of the aspect, the subject is a breast, and the structure is at least one of calcification and mammary gland.

[0016] The present disclosure 8 The image processing device of the present embodiment is any one of the first to third embodiments. 7 In an image processing device of any one of the above aspects, a processor performs optimization processing on a first forward projection model using voxels of a first size, and performs optimization processing on a second forward projection model using voxels of a second size smaller than the first size, using the absorption coefficient and body movement amount of the optimized first forward projection model as initial values.

[0017] The present disclosure 9 The image processing device of the present invention is 8 In the image processing device of the aspect, the processor reduces the size of the voxels used and repeats the optimization process.

[0018] The present disclosure 10 The image processing device of the present embodiment is any one of the first to third embodiments. 9In the image processing device of any one of the aspects, the processor estimates the forward projection model using an energy function defined by an absorption coefficient, a cross length, and an amount of body motion.

[0019] In order to achieve the above object, the first aspect of the present disclosure 11 The radiation image capturing system of this embodiment includes a radiation source that generates radiation, a radiation image capturing device that performs tomosynthesis imaging in which radiation is irradiated from the radiation source toward a subject from each of a plurality of irradiation positions having different irradiation angles, and a projection image of the subject for each irradiation position is captured, and an image processing device of the present disclosure.

[0020] In order to achieve the above object, an image processing method according to a twelfth aspect of the present disclosure is an image processing method for processing a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, the method comprising the steps of: acquiring the plurality of projection images; optimizing a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from the irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, based on the projection images for each of the plurality of irradiation positions; and generating a tomographic image of the subject using the optimized parameters; When the amount of body movement derived by the optimization process exceeds a preset threshold, a warning is issued. This is an image processing method in which the processing is carried out by a computer.

[0021] In order to achieve the above object, an image processing program according to a thirteenth aspect of the present disclosure is an image processing program for processing a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, the image processing program including at least one processor, wherein the processor acquires the plurality of projection images, optimizes a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from the irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, based on the projection images for each of the plurality of irradiation positions, and generates a tomographic image of the subject using the parameters thus optimized, When the amount of body movement derived by the optimization process exceeds a preset threshold, a warning is issued. It is for causing a computer to execute the process. Effect of the Invention

[0022] According to the present disclosure, body movement of a subject can be corrected with high accuracy. [Brief description of the drawings]

[0023] [Figure 1] 1 is a configuration diagram illustrating an example of the overall configuration of a radiation image capturing system according to an embodiment; [Diagram 2] FIG. 1 is a diagram for explaining an example of tomosynthesis imaging. [Diagram 3] 1 is a block diagram showing an example of the configuration of a mammography apparatus and a console according to an embodiment. [Figure 4] FIG. 2 is a functional block diagram illustrating an example of functions of a console according to an embodiment. [Diagram 5] FIG. 1 is a diagram for explaining a forward projection model. [Figure 6] FIG. 13 is a diagram for explaining the amount of body movement for each voxel. [Figure 7] 11 is a diagram for explaining the relationship between the amount of body movement and the intersection length for each voxel. FIG. [Figure 8] FIG. 13 is a diagram for explaining a method for generating a tomographic image. [Figure 9] 10 is a flowchart illustrating an example of a flow of image processing by the console of the embodiment. [Figure 10] 11 is a flowchart showing an example of the flow of optimization processing in image processing. [Figure 11] FIG. 13 is a diagram for explaining the optimization process of the first modified example. [Figure 12] 13 is a flowchart illustrating an example of the flow of an optimization process according to the first modification. [Figure 13] FIG. 11 is a diagram for explaining the optimization process of the second modified example. [Figure 14] 13 is a flowchart illustrating an example of the flow of an optimization process according to the second modification. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0024] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiment.

[0025] First, an example of the overall configuration of the radiation image capturing system of this embodiment will be described. Fig. 1 shows a configuration diagram showing an example of the overall configuration of the radiation image capturing system 1 of this embodiment. As shown in Fig. 1, the radiation image capturing system 1 of this embodiment includes a mammography device 10 and a console 12.

[0026] First, the mammography device 10 of this embodiment will be described. Fig. 1 shows a side view illustrating an example of the appearance of the mammography device 10 of this embodiment. Fig. 1 shows an example of the appearance of the mammography device 10 when viewed from the left side of a subject.

[0027] The mammography device 10 of this embodiment operates under the control of a console 12, and is a device that takes a radiographic image of a subject's breast by irradiating the breast with radiation R (e.g., X-rays) as a subject's subject. Note that the mammography device 10 may be a device that takes an image of the subject's breast not only when the subject is standing (standing position) but also when the subject is sitting in a chair (including a wheelchair) or the like (seated position).

[0028] In addition, the mammography apparatus 10 of this embodiment has the function of performing normal imaging, in which imaging is performed with the radiation source 29 positioned at an irradiation position along the normal direction of the detection surface 20A of the radiation detector 20, and so-called tomosynthesis imaging, in which imaging is performed by moving the radiation source 29 to each of a number of irradiation positions.

[0029] The radiation detector 20 detects radiation R that has passed through the breast, which is the subject. In detail, the radiation detector 20 detects radiation R that has entered the subject's breast and the imaging table 24 and reached the detection surface 20A of the radiation detector 20, generates a radiographic image based on the detected radiation R, and outputs image data representing the generated radiographic image. Hereinafter, the series of operations of irradiating radiation R from the radiation source 29 and generating a radiographic image by the radiation detector 20 may be referred to as "imaging". The detection surface 20A of the radiation detector 20 of this embodiment has i pixels (pixels 21 in FIG. 5) corresponding to the radiographic image generated by the radiation detector 20. i (see i=1, 2, . . . )) are arranged in a matrix. The type of radiation detector 20 in this embodiment is not particularly limited, and may be, for example, an indirect conversion type radiation detector that converts radiation R into light and then converts the converted light into an electric charge, or a direct conversion type radiation detector that directly converts radiation R into an electric charge.

[0030] 1, the radiation detector 20 is disposed inside an imaging stand 24. In the mammography apparatus 10 of this embodiment, when imaging is performed, the breast of the subject is positioned on the imaging surface 24A of the imaging stand 24 by the user.

[0031] The compression plate 38 used to compress the breast when imaging is performed is attached to a compression unit 36 ​​provided on the imaging table 24. In detail, the compression unit 36 ​​is provided with a compression plate drive section (not shown) that moves the compression plate 38 in a direction toward or away from the imaging table 24 (hereinafter referred to as the "up and down direction"). A support section 39 of the compression plate 38 is detachably attached to the compression plate drive section and is moved in the up and down direction by the compression plate drive section to compress the breast of the subject between the compression plate 38 and the imaging table 24. The compression plate 38 of this embodiment is an example of a compression member of the present disclosure.

[0032] As shown in Fig. 1, the mammography apparatus 10 of this embodiment includes an imaging table 24, an arm unit 33, a base 34, and an axis unit 35. The arm unit 33 is held by the base 34 so as to be movable in the vertical direction (Z-axis direction). The axis unit 35 enables the arm unit 33 to rotate relative to the base 34. The axis unit 35 is fixed to the base 34, and the axis unit 35 and the arm unit 33 rotate together.

[0033] Gears are provided on the shaft 35 and the compression unit 36 ​​of the imaging table 24, and by switching between an engaged state and a non-engaged state of these gears, it is possible to switch between a state in which the compression unit 36 ​​of the imaging table 24 and the shaft 35 are connected and rotate together, and a state in which the shaft 35 is separated from the imaging table 24 and rotates freely. Note that the switching between transmission and non-transmission of power to the shaft 35 is not limited to the above gears, and various mechanical elements can be used.

[0034] The arm unit 33 and the imaging stand 24 are separately rotatable relative to the base 34, with the shaft unit 35 as a rotation axis. In this embodiment, the base 34, the arm unit 33, and the compression unit 36 ​​of the imaging stand 24 are each provided with an engagement unit (not shown), and by switching the state of this engagement unit, each of the arm unit 33 and the compression unit 36 ​​of the imaging stand 24 is connected to the base 34. One or both of the arm unit 33 and the imaging stand 24 connected to the shaft unit 35 rotate together around the shaft unit 35.

[0035] When performing tomosynthesis imaging in the mammography apparatus 10, the radiation source 29 of the radiation irradiation unit 28 is moved sequentially to each of a plurality of irradiation positions having different irradiation angles by the rotation of the arm unit 33. The radiation source 29 has a radiation tube (not shown) that generates radiation R, and the radiation tube is moved to each of the plurality of irradiation positions in accordance with the movement of the radiation source 29. FIG. 2 shows a diagram for explaining an example of tomosynthesis imaging. Note that the compression plate 38 is not shown in FIG. 2. In this embodiment, as shown in FIG. 2, the radiation source 29 is moved sequentially to each of the irradiation positions 19 having irradiation angles that differ in increments of a predetermined angle β. t (t=1, 2, . . . , the maximum value is 7 in FIG. 2), in other words, the radiation detector 20 is moved to a position where the irradiation angle of the radiation R with respect to the detection surface 20A of the radiation detector 20 is different. t In response to an instruction from the console 12, radiation R is irradiated from the radiation source 29 toward the subject U, and a radiation image is captured by the radiation detector 20. t 19 to each of the irradiation positions 19 t In the example of Fig. 2, when tomosynthesis imaging is performed to capture radiation images at each irradiation position 19, seven radiation images are obtained. In the following, when describing the radiation images captured at each irradiation position 19 in tomosynthesis imaging in order to distinguish them from other radiation images, they will be referred to as "projection images." In addition, when referring to radiation images collectively regardless of the type of projection image or tomographic image, which will be described later, they will be simply referred to as "radiation images." In addition, in the following, when describing the radiation images collectively, regardless of the type of projection image or tomographic image, which will be described later, they will be simply referred to as "radiation images." t When collectively referring to the irradiation positions, the symbol t for distinguishing each irradiation position is omitted and they are referred to as "irradiation positions 19". t Projection images taken at 19 irradiation positions t For the corresponding images, the symbols representing each image are indicated with the irradiation position 19. t The symbol "t" is added to indicate this.

[0036] 2, the irradiation angle of radiation R refers to the angle α between a normal CL of the detection surface 20A of the radiation detector 20 and a radiation axis RC. The radiation axis RC refers to an axis connecting the focal point of the radiation source 29 at each irradiation position 19 and a preset position such as the center of the detection surface 20A. Here, the detection surface 20A of the radiation detector 20 is a surface that is approximately parallel to the imaging surface 24A.

[0037] On the other hand, when performing normal imaging in the mammography device 10, the radiation source 29 of the radiation irradiation unit 28 is positioned at the irradiation position 19 where the irradiation angle α is 0 degrees. t (Irradiation position along the normal direction 19 t 2), the radiation source 29 irradiates radiation R, and the radiation detector 20 captures a radiation image.

[0038] Fig. 3 is a block diagram showing an example of the configuration of the mammography apparatus and console of the embodiment. As shown in Fig. 3, the mammography apparatus 10 of the present embodiment further includes a control unit 40, a memory unit 42, an I / F (Interface) unit 44, an operation unit 46, and a radiation source movement unit 47. The control unit 40, the memory unit 42, the I / F unit 44, the operation unit 46, and the radiation source movement unit 47 are connected via a bus 49 such as a system bus or a control bus so that various information can be exchanged between them.

[0039] The control unit 40 controls the overall operation of the mammography apparatus 10 in response to control by the console 12. The control unit 40 includes a CPU (Central Processing Unit) 40A, a ROM (Read Only Memory) 40B, and a RAM (Random Access Memory) 40C. The ROM 40B stores various programs in advance, including an imaging program 41 for controlling radiographic imaging, which is executed by the CPU 40A. The RAM 40C temporarily stores various data.

[0040] The storage unit 42 stores image data of a radiation image captured by the radiation detector 20 and various other information. Specific examples of the storage unit 42 include a hard disk drive (HDD) and a solid state drive (SSD). The I / F unit 44 communicates various information with the console 12 by wireless communication or wired communication. Image data of a radiation image captured by the radiation detector 20 in the mammography apparatus 10 is transmitted to the console 12 via the I / F unit 44 by wireless communication or wired communication.

[0041] In this embodiment, the control unit 40 , the storage unit 42 , and the I / F unit 44 are each provided inside the imaging stand 24 .

[0042] The operation unit 46 is provided as a plurality of switches on, for example, the imaging table 24 of the mammography apparatus 10. The operation unit 46 may be provided as a touch panel switch, or as a foot switch that is operated by a user such as a doctor or technician with his / her foot.

[0043] As described above, when tomosynthesis imaging is performed, the radiation source moving unit 47 has a function of moving the radiation source 29 to each of the multiple irradiation positions 19 under the control of the control unit 40. Specifically, the radiation source moving unit 47 moves the radiation source 29 to each of the multiple irradiation positions 19 by rotating the arm unit 33 relative to the imaging table 24. The radiation source moving unit 47 in this embodiment is provided inside the arm unit 33.

[0044] On the other hand, the console 12 in this embodiment has the function of controlling the mammography apparatus 10 using shooting orders and various information obtained from a RIS (Radiology Information System) or the like via a wireless communication LAN (Local Area Network) or the like, and instructions given by a user via an operation unit 56 or the like.

[0045] The console 12 of this embodiment is, for example, a server computer. As shown in Fig. 3, the console 12 includes a control unit 50, a storage unit 52, an I / F unit 54, an operation unit 56, and a display unit 58. The control unit 50, the storage unit 52, the I / F unit 54, the operation unit 56, and the display unit 58 are connected to each other via a bus 59 such as a system bus or a control bus so as to be able to transmit and receive various information to and from each other.

[0046] The control unit 50 of this embodiment controls the overall operation of the console 12. The control unit 50 includes a CPU 50A, a ROM 50B, and a RAM 50C. The ROM 50B stores various programs including an image generation program 51 executed by the CPU 50A in advance. The RAM 50C temporarily stores various data. In this embodiment, the CPU 50A is an example of a processor of the present disclosure, and the console 12 is an example of an image processing device of the present disclosure. Moreover, the image generation program 51 of this embodiment is an example of an image processing program of the present disclosure.

[0047] The storage unit 52 stores image data of radiographic images captured by the mammography apparatus 10 and various other information. The storage unit 52 also stores a forward projection model 53, the details of which will be described later. Specific examples of the storage unit 52 include an HDD and an SSD.

[0048] The operation unit 56 is used by the user to input instructions regarding radiographic image capture, including instructions for irradiating radiation R, and various types of information. The operation unit 56 is not particularly limited, and examples thereof include various switches, a touch panel, a touch pen, and a mouse. The display unit 58 displays various types of information. The operation unit 56 and the display unit 58 may be integrated into a touch panel display.

[0049] The I / F unit 54 communicates various types of information with the mammography apparatus 10, the RIS, and a PACS (Picture Archiving and Communication System) via wireless or wired communication. In the radiation image capturing system 1 of this embodiment, image data of a radiation image captured by the mammography apparatus 10 is received by the console 12 from the mammography apparatus 10 via the I / F unit 54 via wireless or wired communication.

[0050] The console 12 of this embodiment has a function of correcting the body movement of a subject in tomosynthesis imaging. Fig. 4 shows a functional block diagram of an example of a configuration related to the function of correcting the body movement of a subject in tomosynthesis imaging in the console 12 of this embodiment. As shown in Fig. 4, the console 12 includes an image acquisition unit 60, an optimization unit 62, a tomographic image generation unit 64, and a display control unit 66. As an example, in the console 12 of this embodiment, the CPU 50A of the control unit 50 executes an image generation program 51 stored in the ROM 50B, so that the CPU 50A functions as the image acquisition unit 60, the optimization unit 62, the tomographic image generation unit 64, and the display control unit 66.

[0051] The image acquisition unit 60 has a function of acquiring a plurality of projection images. Specifically, the image acquisition unit 60 of this embodiment acquires image data representing a plurality of projection images acquired by tomosynthesis imaging in the mammography apparatus 10. The image acquisition unit 60 outputs the image data representing the acquired plurality of projection images to the optimization unit 62.

[0052] The optimization unit 62 has a function of performing optimization processing on the forward projection model 53 for each of the multiple irradiation positions 19 based on the projection image.

[0053] The forward projection model 53 is a model for performing forward projection, which projects data from a three-dimensional space, which is a real space, onto the detection surface 20A of the radiation detector 20. The forward projection model 53 will be described with reference to FIG.

[0054] As shown in FIG. 5, the three-dimensional space in which the object U is placed includes a plurality of voxels 91 j A three-dimensional model 90 having (j=1, 2, . . . , J) as a constituent unit is virtually set. Note that, as an example, the space in which the optimization unit 62 of the present embodiment sets the three-dimensional model 90 is a space in which it is assumed in advance that the subject U exists according to the imaging stand 24, etc.

[0055] In FIG. 5, the irradiation position 19 t The radiation detector 20 detects radiation from a radiation source 29 located at i Path X of radiation R being irradiated to t i The route is shown as X t i and each voxel 91 of the three-dimensional model 90 j Voxel 91 where and intersect j The intersection length for each t ij And voxel 91 j The absorption coefficient for each

number

[0056] Then, the irradiation position is 19 t When radiation R is irradiated from the i-th pixel of the radiation detector 20, the number of photons detected at the i-th pixel is p t i A forward projection model 53 representing the above is expressed by the following equation (1).

number

[0057] Here, the logarithm of the above formula (1) is taken, and the number of photons measured by the radiation detector 20, p t i The logarithm of y t i Then, each variable is expressed in vector form

number

number

[0058] The projection process can be expressed by the determinant of equation (3) below.

number

[0059] The above formula (3) is applied to the irradiation position 19. t The absorption coefficient μ can be derived by solving the simultaneous equations of the following equation (4):

number

[0060] However, the intersection length w expressed by the above formula (2) t ijSince the size of the determinant expressing is large, it is not easy to solve the simultaneous equations of the above equation (4). In addition, since the number T of projection images obtained by tomosynthesis imaging is generally relatively small, an ill-posed problem occurs in that the number of equations for the above equation (4) is insufficient. Therefore, in this embodiment, as an example, the parameter μ that satisfies the above equation (1) of the forward projection model 53 is optimized, and the following equation (5) is minimized for the optimization. As a specific method, the following equation (5) may be minimized using a gradient method or the like. Note that the following equation (5) is introduced as an example of estimating μ, but other expressions such as adding conditions to μ are also fully conceivable, and it is sufficient that the energy function is minimized, and it goes without saying that the present disclosure is not limited to this equation. In addition, "optimize" and "minimize" mean "perform an optimization process" and "perform a minimization process", respectively, and do not necessarily mean that a better solution cannot be found by any other method.

number

[0061] Route X t i and each voxel 91 of the three-dimensional model 90 j Voxel 91 where and intersect j Intersection length w t ij changes according to the body movement of the subject U. As shown in FIG. 6, the body movement of the subject U is expressed as a vector θ t The amount of body movement θ t For example, voxel 91 before the position change j voxel 91 after the position change from the center of gravity of j It can be defined as a vector pointing to the center of gravity of pixel 21. i The amount of body movement θ varies depending on the t Assume that the body movement amount θ t Pixel 21 i As a variable for each t =(θ t 1,θ t 2, ,θ tJ ) can be defined as follows. t ij The three-dimensional model 90 corresponds to the three-dimensional space in which the subject U is placed, so the position of the three-dimensional model 90 changes in conjunction with the body movement of the subject U. In other words, the voxels 91 of the three-dimensional model 90 j The position of voxel 91 corresponds to the body movement of the subject U. As shown in FIG. j Even if the position of changes, the path of radiation R t i does not change, so voxel 91 j Path X intersecting with t i Intersection length w t ij changes according to the body movement of the subject U.

[0062] The forward projection model 53 when the subject U moves can be expressed using the energy function of the following equation (6). Note that solving the following equation (6) requires the absorption coefficient μ and the amount of movement θ t Simultaneous optimization of these two variables is required, but a solution can be derived by sequentially repeating the optimization of μ and the optimization of θ.

number

[0063] In this way, when the subject U moves, the forward projection model 53 is a voxel 91 of the three-dimensional model 90. j The absorption coefficient μ assigned to each voxel is j Intersection length w t ij and the amount of body movement of the subject U, θ t It is defined by the intersection length w t ij The method of deriving is not particularly limited, and a geometric method may be applied, or approximation calculation may be used to derive.

[0064] Using the forward projection model 53 when the subject U moves, the irradiation position 19 tBy performing pseudo projection from the forward projection model 53, a pseudo projection image can be obtained when body movement occurs in the subject U. The optimization process for the forward projection model 53 refers to making the forward projection model 53 closer to the position of the subject U, including body movement, when the tomosynthesis imaging is actually performed, by making the pseudo projection image obtained using the forward projection model 53 closer to the projection image actually obtained by tomosynthesis imaging. The absorption coefficient μ and body movement amount θ in the forward projection model 53 that has been subjected to the optimization process t corresponds to the position and body movement of the subject U when the projection image is actually captured by tomosynthesis imaging.

[0065] As described above, the optimization unit 62 has a function of performing optimization processing on the forward projection model 53. Specifically, the optimization unit 62 optimizes a plurality of voxels 91 in a three-dimensional space in which the subject U is placed. j The optimization unit 62 virtually sets a three-dimensional model 90 having a plurality of projection images actually captured by tomosynthesis imaging and a plurality of irradiation positions 19 at which the projection images were captured. t The optimization unit 62 performs optimization processing on the forward projection model 53 by solving the energy function of the above equation (6) using these. The optimization unit 62 obtains the absorption coefficient μ and the body motion amount θ obtained by the forward projection model 53 that has been optimized. t to the tomographic image generating unit 64. Note that when solving the energy function of (6) above, a process is performed in which the pixel value of each pixel of the pseudo projection image obtained by the forward projection model 53 through pseudo projection is made to approach the pixel value of the corresponding pixel of the projection image, so that T images serving as a plurality of pseudo projection images are not obtained.

[0066] The tomographic image generating unit 64 has a function of generating tomographic images of the breast, which is the subject U. Specifically, it generates a plurality of tomographic images in each of a plurality of tomographic planes of the subject U. An example of a method of generating tomographic images in the tomographic image generating unit 64 of this embodiment will be described with reference to FIG. 8. In the example shown in FIG. 8, voxel 91 jThe tomographic planes 921 to 926 for generating the tomographic images are planes approximately parallel to the imaging surface 24A of the imaging table 24, and the slice thickness of the tomographic images, which is the interval h between the tomographic planes 92, is the same as the irradiation position 19. t The height H of a tomographic image refers to the height from the imaging surface 24A of the imaging table 24 to the tomographic plane corresponding to the tomographic image, and the height H to the tomographic plane 922 is shown in FIG.

[0067] When generating a tomographic image on the tomographic plane 922, the tomographic image generating unit 64 selects a plurality of voxels 91 whose upper surfaces are in contact with the tomographic plane 922. j Using each absorption coefficient μ, a tomographic image is generated. In the example shown in FIG. 8, the tomographic image generating unit 64 extracts voxel 91 present in the region surrounded by the dotted line D. j Each absorption coefficient μ is used to generate a tomographic image.

[0068] Note that the radiation image obtained by normal radiography is displayed as a radiation image using a value obtained by logarithmically converting the number of photons detected by the radiation detector 20, or a value obtained by LUT (Look Up Table) conversion, etc. For this reason, the absorption coefficient μ may also be displayed as a tomographic image using a value obtained by logarithmically converting or LUT conversion, etc. In this way, by making the display form of the tomographic image generated using the forward projection model 53 the same as the display form of the normal radiography, the image appears in a similar form, making it easier for the user to interpret the image.

[0069] In this embodiment, the interval h of the slice plane 92 of the tomographic image generated by the tomographic image generating unit 64 is set to the voxel 91. j However, the interval h of the slice plane 92 is not limited to this embodiment. For example, the interval h may be specified by a user. In this case, the tomographic image generating unit 64 generates voxels 91 corresponding to the slice plane 92 according to the specified interval h. j The absorption coefficient μ of the surrounding voxels 91 j The absorption coefficient μ of the tomographic image can be used to generate the tomographic image.

[0070] The tomographic image generating unit 64 outputs image data representing the generated multiple tomographic images to the display control unit 66.

[0071] The display control unit 66 has a function of displaying the multiple tomographic images generated by the tomographic image generating unit 64 on the display unit 58. The display destination of the tomographic images is not limited to the display unit 58. For example, the display destination may be an image reading device or the like external to the radiation image capturing system 1.

[0072] Next, the operation of the console 12 in tomosynthesis imaging will be described with reference to the drawings. After tomosynthesis imaging is performed by the mammography apparatus 10, the console 12 generates a tomographic image using multiple projection images obtained by tomosynthesis imaging, and displays the image on the display unit 58 or the like.

[0073] As an example, when the tomosynthesis imaging is completed, the mammography apparatus 10 of this embodiment outputs image data of the captured multiple projection images 80 to the console 12. The console 12 stores the image data of the multiple projection images 80 input from the mammography apparatus 10 in the memory unit 52.

[0074] After storing the image data of the multiple projection images 80 in the storage unit 52, the console 12 executes the image processing shown in Fig. 9. Fig. 9 shows a flowchart showing an example of the flow of image processing by the console 12 of this embodiment. As an example, the console 12 of this embodiment executes the image processing example shown in Fig. 9 by causing the CPU 50A of the control unit 50 to execute the image generating program 51 stored in the ROM 50B.

[0075] 9, the image acquisition unit 60 acquires a plurality of projection images. As described above, the image acquisition unit 60 of this embodiment acquires image data of the plurality of projection images from the storage unit 52.

[0076] In the next step S102, the optimization unit 62 optimizes a plurality of irradiation positions 19, which are the irradiation positions 19 of the radiation source 29 when the projection images obtained in the above step S100 were captured. t As described above, the optimization unit 62 optimizes the forward projection model 53 at the multiple irradiation positions 19. t In order to perform optimization processing for each pixel based on the projection image for each projection image, in this step, the irradiation position 19 corresponding to each projection image is t The method by which the optimization unit 62 acquires the irradiation position 19t corresponding to the projection image is not particularly limited. For example, the optimization unit 62 acquires the irradiation position 19t corresponding to the projection image from the mammography device 10. t For example, the projection image may be provided with information representing the irradiation position 19 as shooting information. t When information representing the projection position is attached, the projection position 19 is determined based on the shooting information attached to the acquired projection image. t Alternatively, information representing the above may be acquired.

[0077] In the next step S104, the optimization unit 62 performs an optimization process, the details of which will be described later, and performs the optimization process on the forward projection model 53 as described above. The optimization process on the forward projection model 53 by the optimization unit 62 is performed to obtain the absorption coefficient μ and the body motion amount θ t Derive.

[0078] In the next step S106, the tomographic image generating unit 64 generates a tomographic image of the breast, which is the subject U. As described above, the tomographic image generating unit 64 generates a plurality of tomographic images using the absorption coefficient μ obtained by the forward projection model 53 optimized in the above step S104.

[0079] In the next step S108, the display control unit 66 causes the display unit 58 to display the tomographic image generated in step S106. When the processing of step S108 ends, the image processing shown in Fig. 9 ends. Note that, in this embodiment, a tomographic image is generated in step S106, and the generated tomographic image is displayed in step S108. However, the generated radiographic image is not limited to a tomographic image, and the displayed radiographic image is not limited to a tomographic image.

[0080] For example, the tomographic image generating unit 64 may further generate a composite two-dimensional image by combining at least a part of the generated multiple tomographic images. Note that the method by which the tomographic image generating unit 64 generates the composite two-dimensional image is not particularly limited, and known methods such as the method described in U.S. Patent No. 8,983,156 or the method described in Japanese Patent Application Laid-Open No. 2014-128716 can be used.

[0081] The optimization process in step S104 of image processing will now be described in detail. Fig. 10 is a flowchart showing an example of the flow of the optimization process.

[0082] 10, the optimization unit 62 sets the three-dimensional model 90 in three-dimensional space. As described above with reference to FIG. 5, the optimization unit 62 creates voxels 91 of a predetermined size in a three-dimensional space in which it is assumed in advance that the subject U exists according to the imaging stand 24. j A three-dimensional model 90 is set up with voxels 91 as its constituent units. j The predetermined size is not particularly limited, but may be determined taking into consideration the size of the subject U, the processing load required for the optimization process of the forward projection model 53, and the like.

[0083] In the next step S132, the optimization unit 62 optimizes the absorption coefficient μ and the body motion amount θ t After setting these as initial values ​​of the forward projection model 53, the process proceeds to step S134. t is not particularly limited. t is, for example, the average absorption coefficient μ and the amount of body movement θ obtained experimentally. t may be applied.

[0084] In the next step S134, the optimization unit 62 performs optimization processing on the forward projection model 53 by solving the energy function of the forward projection model 53, and obtains the absorption coefficient μ and the body motion amount θ tAs described above, the forward projection model 53 can be expressed using the energy function of the above equation (6). Therefore, the optimization unit 62 performs optimization processing on the forward projection model 53 by solving the above equation (6), and derives the absorption coefficient μ and the body movement amount θ in the forward projection model 53 that has been optimized. t When step S134 is completed, the optimization process shown in Fig. 10 is completed, and the process proceeds to step S106 of the image processing shown in Fig. 9.

[0085] The optimization process by the optimization unit 62 in step S104 of the image processing is not limited to the above-described form. Modifications of the optimization process will be described below.

[0086] (Optimization process variation 1) The optimization process of this modification will be described with reference to Fig. 11. In the example shown in Fig. 11, in the first optimization, the optimization unit 62 optimizes a voxel 91_1 having a first size. j The optimization unit 62 uses the first three-dimensional model 90_1 and optimizes the first three-dimensional model 90_1 based on a predetermined absorption coefficient μ and a body motion amount θ t The first forward projection model 53_1 is optimized to obtain the absorption coefficient μ_1 and the body motion θ_1. t Derive.

[0087] In the second optimization, the optimization unit 62 optimizes the first voxel 91_1 j The second voxel, 91_2, is smaller in size than j The optimization unit 62 uses the second three-dimensional model 90_2 and optimizes the absorption coefficient μ_1 and the body motion amount θ_1 derived by the first forward projection model 53_1. t The second forward projection model 53_2 is optimized using the initial values ​​μ_2 and the body motion θ_2. t Derive.

[0088] In this manner, the optimization unit 62 of this modification optimizes the voxels 91 constituting the three-dimensional model 90 as the optimization process. jThe optimization process is repeated for the forward projection model 53 while reducing the size of the voxels 91 constituting the three-dimensional model 90 used in each optimization process. j The size of can be any size. For example, voxel 91 in the last optimization process for forward projection model 53 j The size of the voxel 91 in each optimization process is determined based on the number of times the optimization process is repeated and the processing load required for the optimization process. j The size of may be determined.

[0089] A flowchart showing an example of the flow of the optimization process in this modified example is shown in Fig. 12. The optimization process shown in Fig. 12 includes multiple optimization processes for the forward projection model 53.

[0090] In step S150 of FIG. 12, the optimization unit 62 sets a variable n, which indicates the number of times the optimization process is performed, to "1."

[0091] In the next step S152, the optimization unit 62 optimizes the n-th size voxel 91_n j The n-th three-dimensional model 90_n having the voxel 91_1 as a constituent unit is virtually set in a three-dimensional space in which the object U is assumed to exist. For example, in the case of the first optimization process, n=1, and a voxel 91_1 having a first size is set as shown in FIG. j A first three-dimensional model 90_1 is set, the first three-dimensional model 90_1 having the above as a constituent unit.

[0092] In the next step S154, the optimization unit 62 judges whether or not the variable n is "1". In other words, it judges whether or not the optimization process performed in the above step S152 is the first time. If the variable n is "1", the judgment in step S154 becomes positive, and the process proceeds to step S156. In step S156, the optimization unit 62 calculates a predetermined absorption coefficient μ and a body movement amount θ t As described above, the optimization unit 62 sets a predetermined absorption coefficient μ and a body motion amount θ as initial values ​​of the first forward projection model 53_1.t Set.

[0093] On the other hand, in step S154, if the variable n is not 1, a negative determination is made, and the process proceeds to step S158. In other words, if the optimization performed in step S152 is the second or later, the process proceeds to step S158. In step S158, the optimization unit 62 optimizes the absorption coefficient μ_n-1 and the body motion amount θ obtained by the (n-1)th forward projection model 53n-1. t _n-1 as the initial values ​​of the n-th forward projection model 53, and then the process proceeds to step S160. Specifically, in the case of the second optimization process, the variable n is "2", and as described above, the optimization unit 62 sets the absorption coefficient μ_1 and the body motion amount θ_1 as the initial values ​​of the second forward projection model 53_2. t Set.

[0094] In step S160, the optimization unit 62 performs optimization processing on the n-th forward projection model 53_n by solving the energy function of the forward projection model 53_n, and obtains the absorption coefficient μ_n and the body motion amount θ_n t As described above, the n-th forward projection model 53_n can be expressed using the energy function of the above equation (6). Therefore, the optimization unit 62 performs optimization processing on the n-th forward projection model 53_n by solving the above equation (6), and derives the absorption coefficient μ_n and the body movement amount θ_n in the forward projection model 53_n that has been optimized. t Derive:

[0095] In the next step S162, the optimization unit 62 determines whether or not to end the optimization process shown in FIG. j The number of times the optimization process is repeated while reducing the size of is predetermined. In other words, the maximum value of the variable n at the optimum point is predetermined. Therefore, the optimization unit 62 judges whether or not to end the optimization process depending on whether the currently set variable n is the predetermined maximum value. If the optimization process is not to be ended, the judgment in step S162 is negative, and the process proceeds to step S164.

[0096] In step S164, the optimization unit 62 adds 1 to the variable n (n=n+1), and then returns to step S152 to repeat the processes of steps S152 to S162.

[0097] On the other hand, if the optimization process is to be ended, the determination in step S162 becomes positive, the optimization process shown in FIG. 12 is ended, and the process proceeds to step S106 of the image processing shown in FIG.

[0098] In this manner, according to the console 12 of this modification, the optimization process is carried out by j The optimization of the forward projection model 53_n is repeated while reducing the size of the voxel 91. In other words, the optimization process is performed on the low-resolution forward projection model 53_n, and then the optimization process is performed on the high-resolution forward projection model 53_n. j By increasing the size of the voxels 91 that make up the three-dimensional model 90, j The number of voxels can be reduced. j By reducing the number of the forward projection models 53 and performing the optimization process for the forward projection models 53, the processing time and processing load required for the optimization process can be reduced. In addition, the absorption coefficient μ and the body motion amount θ obtained by the optimization process for the low-resolution forward projection model 53_n can be reduced. t Since the optimization process is performed on the high-resolution forward projection model 53_n using the initial value, the processing time and processing load required for the optimization process on the high-resolution forward projection model 53_n can be reduced. t The accuracy of derivation can be improved.

[0099] (Variation 2 of the optimization process) The optimization process of this modified example will be described with reference to Fig. 13. The optimization unit 62 of this modified example performs optimization process on a forward projection model 53 using a three-dimensional model 90 that is virtually set in a three-dimensional space corresponding to a feature region 94 of the subject U, out of the three-dimensional space in which the subject U is disposed.

[0100] That is, the optimization unit 62 of this modification sets the three-dimensional model 90 in a part of the three-dimensional space in which the subject U is placed. Thus, the characteristic region 94 in which the three-dimensional model 90 is provided in this modification is smaller than the region in which the three-dimensional model 90 is provided in the above embodiment. Therefore, it is preferable that the characteristic region 94 is a region including a characteristic structure 96. The characteristic structure 96 may be, for example, a structure including a feature point in a radiation image representing the subject U. Also, the characteristic structure 96 may be, for example, a structure in which the feature amount of an image representing the structure is equal to or greater than a threshold value. Specific examples of such characteristic structure 96 include at least one of mammary glands and calcification when the subject U is a breast.

[0101] The optimization unit 62 of this modification optimizes the forward projection model 53 using the three-dimensional model 90 set for the feature region 94 to obtain the body movement amount θ t Furthermore, the optimization unit 62 derives the derived body movement amount θ t The total body movement of the subject U is θ t Then, optimization processing is performed on the forward projection model 53 using a three-dimensional model 90 that is virtually set in a three-dimensional space in which the entire subject U exists, and the absorption coefficient μ is derived.

[0102] In this manner, the optimization unit 62 of this modified example performs optimization processing on a forward projection model 53 using a three-dimensional model 90 that is virtually set in a characteristic region 94 that includes a characteristic structure 96, which is a portion of the three-dimensional space in which the subject U is located.

[0103] A flowchart showing an example of the flow of the optimization process of this modification is shown in Fig. 14. The optimization process shown in Fig. 14 differs from the optimization process shown in Fig. 10 in that it includes steps S130A and S130B instead of step S130, and includes steps S136 and S138 after step S134.

[0104] In step S130A of FIG. 14, the optimization unit 62 derives a feature region 94 in which the three-dimensional model 90 is to be placed. In this modification, as an example, an image analysis or computer-aided diagnosis (CAD) algorithm is applied to a tomographic image obtained by reconstructing the projection image acquired in step S100 (see FIG. 9) of the image processing by a back projection method such as the FBP (Filter Back Projection) method or the iterative reconstruction method, and the influence of body movement is not corrected. A characteristic structure 96 having an image feature amount equal to or greater than a threshold is identified, and a region of a predetermined size including the identified characteristic structure 96 is derived as the feature region 94. Note that the method by which the optimization unit 62 derives the feature region 94 is not particularly limited. For example, a tomographic image obtained by reconstructing the projection image as described above may be displayed on the display unit 58, and a characteristic structure 96 designated by the user using the operation unit 56 for the displayed tomographic image may be acquired.

[0105] In the next step S130B, the optimization unit 62 optimizes the feature region 94 by dividing the voxels 91 into a predetermined size as described above. j A three-dimensional model 90 is set up with the above as a building block.

[0106] In the next step S132, the optimization unit 62 optimizes the absorption coefficient μ and the body motion amount θ as described above. t After setting as the initial value of the forward projection model 53, the process proceeds to step S134.

[0107] In the next step S134, the optimization unit 62 performs optimization processing on the forward projection model 53 by solving the energy function of the above equation (6) as described above, and obtains the absorption coefficient μ and the body motion amount θ in the forward projection model 53 that has been optimized. t Derive:

[0108] In the next step S136, the optimization unit 62 optimizes voxels 91 of a predetermined size. j A three-dimensional model 90 having the above as a constituent unit is reset to a three-dimensional space including the area in which the subject U exists.

[0109] In the next step S138, the optimization unit 62 calculates the body movement amount θ t Specifically, the optimization unit 62 optimizes the amount of body movement by t The forward projection model 53 is optimized by solving the energy function of the above equation (6) using the absorption coefficient μ as a parameter, and the absorption coefficient μ and the body movement amount θ in the optimized forward projection model 53 are t The amount of body movement θ t is the θ derived in step S134 above. t The absorption coefficient μ derived in step S134 may be applied to the absorption coefficient μ in the feature region 94. When step S138 is completed, the optimization process shown in Fig. 14 is completed, and the process proceeds to step S106 of the image processing shown in Fig. 9.

[0110] In this manner, according to the console 12 of this modified example, the body movement amount θ obtained by performing optimization processing on the forward projection model 53 using the three-dimensional model 90 set in the feature region 94, which is a part of the three-dimensional space in which the subject U is placed, is calculated. t Using the above, optimization processing is performed on the forward projection model 53 using the three-dimensional model 90 set in the three-dimensional space including the entire object U. By setting the three-dimensional model 90 in a partial area of ​​the three-dimensional space in which the object U is placed, the voxels 91 constituting the three-dimensional model 90 are j The number of voxels can be reduced. j By reducing the number of elements and performing optimization processing on the forward projection model 53, the processing time and processing load required for the optimization processing can be reduced.

[0111] As described above, the console 12 of each of the above embodiments has a plurality of irradiation positions 19 with different irradiation angles α. tThe console 12 includes a CPU 50A. The CPU 50A acquires the multiple projection images, and processes the multiple projection images obtained by irradiating the subject U with radiation R from each of the radiation sources 29. The CPU 50A acquires the multiple projection images, and calculates, as parameters, the multiple voxels 91 virtually set in the three-dimensional space in which the subject U is placed. j A voxel 91 of a three-dimensional model 90 with j The absorption coefficient μ assigned to each irradiation position 19 t Path X of radiation R emitted from t i Voxel 91 intersects with 3D model 90 j Intersection length w t ij and the amount of body movement of the subject U, θ t For a forward projection model 53 having a plurality of irradiation positions 19 t An optimization process is performed based on the projected images for each image, and a tomographic image of the subject U is generated using the optimized parameters.

[0112] According to the above-described configuration of the console 12 of each of the above-described embodiments, the forward projection model 53 is used to calculate the body movement amount θ t Since the influence of structures other than the structure used for the correction can be suppressed, the body movement of the subject U can be corrected with high accuracy. As a result, the console 12 of each of the above embodiments can provide high-quality tomographic images with high accuracy.

[0113] In the above embodiments, the optimization unit 62 performs the optimization process for the forward projection model 53 by making the pixel value of each pixel of the pseudo projection image closer to the pixel value of the corresponding pixel of the projection image without obtaining the T images themselves that are the pseudo projection images obtained by the forward projection model 53. However, the method of the optimization process for the forward projection model 53 is not limited to this embodiment. The optimization process for the forward projection model 53 may be performed by sequentially obtaining T pseudo projection images by the forward projection model 53 and making each of the obtained T pseudo projection images closer to the corresponding T projection images.

[0114] In addition, the amount of body movement θ tWhen is relatively large, the optimization process for the forward projection model 53 may be insufficient, or the image quality of the tomographic image generated using the forward projection model 53 may be degraded. For example, when the subject moves significantly during tomosynthesis imaging, the amount of body movement θ of the subject breast may be large. t In such a case, it is preferable to re-capture the projection image, for example. Therefore, the body movement amount θ t If the difference exceeds a preset threshold, a warning may be issued.

[0115] In the above embodiment, the console 12 is an example of the image processing device of the present disclosure, but a device other than the console 12 may have the functions of the image processing device of the present disclosure. In other words, some or all of the functions of the image acquisition unit 60, the optimization unit 62, the tomographic image generation unit 64, and the display control unit 66 may be provided by a device other than the console 12, such as the mammography device 10 or an external device. The image processing device of the present disclosure may also be configured by a plurality of devices. For example, some of the functions of the image processing device may be provided by a device other than the console 12.

[0116] In the above embodiment, a breast is applied as an example of a subject of the present disclosure, and a mammography device 10 is applied as an example of a radiation image capturing device of the present disclosure, but the subject is not limited to a breast, and the radiation image capturing device is not limited to a mammography device. For example, the subject may be a chest or abdomen, and the radiation image capturing device may be a radiation image capturing device other than a mammography device.

[0117] In the above embodiment, the following various processors can be used as the hardware structure of the processing unit that executes various processes, such as the image acquisition unit 60, the optimization unit 62, the tomographic image generation unit 64, and the display control unit 66. As described above, the above various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacture, such as an FPGA (Field Programmable Gate Array), a dedicated electric circuit, which is a processor having a circuit configuration designed specifically for executing specific processes, such as an ASIC (Application Specific Integrated Circuit), etc.

[0118] A single processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, multiple processing units may be configured with a single processor.

[0119] As an example of configuring multiple processing units with one processor, first, there is a form in which one processor is configured with a combination of one or more CPUs and software, and this processor functions as multiple processing units, as represented by computers such as client and server. Second, there is a form in which a processor is used to realize the functions of the entire system including multiple processing units with one IC (Integrated Circuit) chip, as represented by a system on chip (SoC). In this way, the various processing units are configured using one or more of the above various processors as a hardware structure.

[0120] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements.

[0121] In the above embodiments, the photographing program 41 is pre-stored (installed) in the ROM 40B, and the image generating program 51 is pre-stored (installed) in the ROM 50B, but the present invention is not limited to this. Each of the photographing program 41 and the image generating program 51 may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a USB (Universal Serial Bus) memory. Each of the photographing program 41 and the image generating program 51 may be downloaded from an external device via a network. [Explanation of symbols]

[0122] 1 Radiography system 10 Mammography equipment 12 Console 191-197, 19 t Irradiation position 20 Radiation detector, 20A detection surface twenty one i Pixels 24 Imaging Table, 24A Imaging Surface 28 Radiation Department 29 Radiation source 33 Arm section 34 Foundation 35 Shaft 36 Compression Unit 38 Compression Plate 39 Support part 40A, 50A CPU, 40B, 50B ROM, 40C, 50C RAM 41 Shooting Program 42, 52 Storage section 44, 54 I / F section 46, 56 Operation section 47 Source moving part 49, 59 Bus 51 Image Generation Program 53 forward projection model, 53_1 first forward projection model, 53_2 second forward projection model 58 Display section 60 Image acquisition unit 62 Optimization Department 64 Tomographic image generation unit 66 Display control unit 90 3D model, 90_1 1st 3D model, 90_2 2nd 3D model 911, 91 j Voxel, 91_1 j First voxel, 91_2 j Second Voxel 921~926 Fault Plane 94 Feature Areas 96 Characteristic Structures CL normal D. Dotted line H Height h interval R radiation, RC radiation axis U Subject w t ij Cross Length X t i route α, β angles μ, μ_1, μ_2 absorption coefficients θ t , θ_1 t , θ_2 t Amount of body movement

Claims

1. 1. An image processing device that processes a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, comprising: At least one processor; The processor, acquiring the plurality of projection images; optimizing a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from an irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, for each of the plurality of irradiation positions based on the projection image; generating a tomographic image of the subject using the parameters that have been optimized; When the amount of body movement derived by performing the optimization process exceeds a preset threshold, a warning is issued. Image processing device.

2. The processor, The tomographic image is generated using the absorption coefficients of the forward projection model that has been subjected to the optimization process. The image processing device according to claim 1 .

3. The processor, As the optimization process, pixel values ​​of a plurality of pseudo projection images obtained by the forward projection model through pseudo projection from the plurality of irradiation positions are made to approach pixel values ​​of the plurality of projection images.

3. The image processing device according to claim 1 or 2.

4. The processor, The optimization process is performed by deriving the absorption coefficient and the amount of body movement that bring the pixel values ​​of the pseudo projection image closer to the pixel values ​​of the plurality of projection images. The image processing device according to claim 3 .

5. The processor, deriving the amount of body movement based on a forward projection model using a three-dimensional model that is virtually set in a three-dimensional space corresponding to a characteristic region of the subject out of a three-dimensional space in which the subject is disposed, as the three-dimensional model; The tomographic image is generated using the derived body movement amount and a forward projection model using a three-dimensional model virtually set in a three-dimensional space in which the subject is placed. The image processing device according to any one of claims 1 to 4.

6. The characteristic region is a region including a structure having a feature amount equal to or greater than a threshold value. The image processing device according to claim 5 .

7. the subject is a breast, The structure is at least one of a calcification and a mammary gland. The image processing device according to claim 6.

8. The processor, performing an optimization process on a first forward projection model using voxels of a first size; The absorption coefficient and the amount of body movement of the first forward projection model that has been subjected to the optimization process are set as initial values, and an optimization process is performed on a second forward projection model that uses voxels of a second size that is smaller than the first size. The image processing device according to any one of claims 1 to 7.

9. The processor, Reduce the size of the voxels used and repeat the optimization process. The image processing device according to claim 8.

10. The processor, The forward projection model is estimated using an energy function defined by the absorption coefficient, the intersection length, and the amount of body motion. The image processing device according to any one of claims 1 to 9.

11. A radiation source that generates radiation; a radiation image capturing apparatus that performs tomosynthesis imaging by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles and capturing a projection image of the subject for each of the irradiation positions; An image processing device according to any one of claims 1 to 10; A radiation imaging system comprising:

12. 1. An image processing method for processing a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, the method comprising: acquiring the plurality of projection images; optimizing a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from an irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, for each of the plurality of irradiation positions based on the projection image; generating a tomographic image of the subject using the parameters that have been optimized; When the amount of body movement derived by performing the optimization process exceeds a preset threshold, a warning is issued. An image processing method in which the processing is performed by a computer.

13. An image processing program for processing a plurality of projection images obtained by irradiating a subject with radiation from a radiation source from each of a plurality of irradiation positions having different irradiation angles, the program comprising: At least one processor; The processor, acquiring the plurality of projection images; optimizing a forward projection model having parameters including an absorption coefficient assigned to each voxel of a three-dimensional model having a plurality of voxels as constituent units virtually set in a three-dimensional space in which the subject is disposed, an intersection length for each voxel where a path of radiation irradiated from an irradiation position intersects with the three-dimensional model, and a body movement amount of the subject, for each of the plurality of irradiation positions based on the projection image; generating a tomographic image of the subject using the parameters that have been optimized; When the amount of body movement derived by performing the optimization process exceeds a preset threshold, a warning is issued. An image processing program that causes a computer to carry out the processing.

Images