Image processing device, operation method of image processing device, and operation program of image processing device

Abstract

To provide an image processing device, an operation method of an image processing device, and an operation program of an image processing device capable of displaying a tomographic image of a designated cross section in a shorter time than in the related art.SOLUTION: An image processing device includes a processor that performs image processing on a plurality of slice images which are output from a tomography apparatus and which represent an axial cross section orthogonal to a body axis of a subject, in which the processor acquires the plurality of slice images, and generates a tomographic image representing a designated cross section by using a function having pixel values of the plurality of slice images as parameters.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The technology of the present disclosure relates to an image processing device, an operating method for the image processing device, and an operating program. [Background technology]

[0002] Tomography devices, such as CT (Computed Tomography) devices and MRI (Magnetic Resonance Imaging) devices, are known for capturing cross-sectional images of a subject. These devices output multiple slice images representing axial sections perpendicular to the subject's body axis. Furthermore, a tomography image representing any cross-section of the subject can be obtained by generating an isotropic three-dimensional image with isotropic three-dimensional resolution based on the multiple slice images captured by the tomography device and then extracting a cross-sectional image representing the desired cross-section from the isotropic three-dimensional image. Such a cross-sectional image is called a multi-planar reconstruction (MPR) image.

[0003] The tomography apparatus described in Patent Document 1 also generates three-dimensional preparatory image data (corresponding to a three-dimensional image) from slice images, and acquires a tomographic image by specifying an arbitrary cross section for the generated three-dimensional preparatory image data. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-143735 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the process of generating a three-dimensional image from slice images places a heavy load on image processing, and is time-consuming, so it takes a long time to display a tomographic image of a specified cross section. Moreover, when such three-dimensional image data is generated based on all slice images within an imaging range set in the body axis direction, for example, the three-dimensional image data is generated after imaging by the tomographic imaging apparatus is completed. This takes even more time. Therefore, there has been a demand for a reduction in the time from when imaging by the tomographic imaging apparatus begins until a tomographic image of a specified cross section is displayed.

[0006] The technology according to the present disclosure provides an image processing device, an operating method for the image processing device, and an operating program that are capable of displaying a tomographic image of a specified cross section in a shorter time than conventional methods. [Means for solving the problem]

[0007] The image processing device according to the disclosed technology is an image processing device equipped with a processor that performs image processing on a plurality of slice images that are output by a tomographic imaging device and represent axial sections perpendicular to the body axis of the subject, and the processor acquires the plurality of slice images and generates a tomographic image that represents the specified section using a function that uses the pixel values of the plurality of slice images as parameters.

[0008] When the tomographic imaging apparatus outputs a plurality of slice images during imaging, it is preferable that the processor starts a process of generating a tomographic image using the plurality of slice images during imaging.

[0009] The function is preferably created according to the imaging conditions of the tomography imaging apparatus, which imaging conditions include at least the slice interval of the slice images.

[0010] It is preferable that the processor obtains the imaging conditions and creates the function before the tomography apparatus starts imaging.

[0011] When the body axis direction of the subject is the Z-axis direction and the two directions defining a cross section perpendicular to the body axis direction are the X-axis direction and the Y-axis direction, it is preferable that the function includes an isotropized data derivation function that derives isotropized data as pixel values of pixels whose resolution is isotropized in the X-axis direction, the Y-axis direction, and the Z-axis direction, and that the processor generates a tomographic image based on the isotropized data.

[0012] The cross section of the tomographic image is preferably any one of an axial cross section, a sagittal cross section, and a coronal cross section.

[0013] The processor preferably receives a designation of a slab thickness as the thickness of the tomographic image, and generates the tomographic image by weighting according to the slab thickness.

[0014] When the body axis direction of the subject is defined as the Z-axis direction, the width direction of a cross section perpendicular to the body axis direction is defined as the X-axis direction, and the height direction is defined as the Y-axis direction, it is preferable that the function includes a pixel value derivation function that derives pixel values of an inclined cross section tilted by rotating the axial cross section of the slice image around the X-axis, and the processor generates a tilt image, which is a tomographic image of the inclined cross section, using the pixel value derivation function.

[0015] When a plurality of tilt images arranged in the Z-axis direction are generated, it is preferable that the heights of the pixels in the Y-axis direction of the plurality of tilt images are the same.

[0016] Preferably, the processor receives a designation of a slab thickness as the thickness of the tilt image, and generates the tilt image by weighting according to the designated slab thickness.

[0017] The method of operating an image processing device according to the disclosed technology is an operating method of an image processing device that includes a processor that performs image processing on a plurality of slice images that are output by a tomographic imaging device and represent axial sections perpendicular to the body axis of the subject, in which the processor acquires the plurality of slice images and generates a tomographic image that represents the specified section using a function that uses the pixel values of the plurality of slice images as parameters.

[0018] The operating program of an image processing device according to the technology of the present disclosure is an operating program of an image processing device equipped with a processor that performs image processing on a plurality of slice images that are output by a tomographic imaging device and represent axial sections perpendicular to the body axis of the subject, and causes the processor to perform processing including acquiring a plurality of slice images and generating a tomographic image that represents a specified section using a function that uses pixel values of the plurality of slice images as parameters. [Effects of the Invention]

[0019] According to the technology of the present disclosure, a tomographic image of a specified cross section can be displayed in a shorter time than conventionally possible. [Brief explanation of the drawings]

[0020] [Figure 1] FIG. 1 is a diagram showing a CT device. [Figure 2] FIG. 1 is a diagram showing a schematic configuration of a CT device. [Figure 3] FIG. 2 is a diagram illustrating processing by a processor according to the first embodiment. [Figure 4] FIG. 10 is a diagram illustrating a conventional MPR image generation process using an isotropic three-dimensional image VD_ISO. [Figure 5] FIG. 10 is a diagram showing the procedure of a process for creating an MPR image generation function. [Figure 6] FIG. 10 is a diagram conceptually showing a process for creating a Z coordinate table. [Figure 7] FIG. 10 is a diagram showing the relationship between the size of the FOV and the isotropic Z coordinate. [Figure 8] FIG. 10 is a diagram conceptually illustrating a process for creating an isotropic data derivation function. [Figure 9] FIG. 10 is a diagram conceptually showing a process for creating a pixel value derivation function for an MPR image of an axial cross section. [Figure 10] FIG. 10 is a diagram conceptually showing a process for creating a pixel value derivation function for an MPR image of a sagittal section. [Figure 11] 10 is a diagram conceptually showing a process of creating a pixel value derivation function for an MPR image of a coronal section. FIG. [Figure 12]10 is a flowchart showing the processing procedure of an MPR image generation process. [Figure 13] FIG. 10 is a diagram illustrating processing by a processor according to the second embodiment. [Figure 14] FIG. 10 is a diagram showing the procedure of a process for creating an MPR image generation function. [Figure 15] FIG. 10 is a diagram conceptually illustrating a process for creating a coordinate conversion table. [Figure 16] FIG. 10 is a diagram showing a state in which the heights of pixels in a tilted image in the Y-axis direction are not aligned. [Figure 17] 10A and 10B are diagrams conceptually illustrating a process for creating a pixel value derivation function for a tilt image. [Figure 18] FIG. 10 is a diagram conceptually illustrating a process for creating a weight correction function. [Figure 19] 10 is a flowchart showing the processing procedure of tilt image generation processing. [Figure 20] FIG. 1 is a diagram illustrating an example in which an image display device functions as an image processing device. DETAILED DESCRIPTION OF THE INVENTION

[0021] [First embodiment] The CT device 11 shown in FIG. 1 is an example of a tomographic imaging device according to the technology of the present disclosure. As is well known, the CT device 11 uses radiation (e.g., X-rays) to capture an image of a subject H, an example of a subject, to obtain a tomographic image of the subject H. The CT device 11 is installed, for example, in an imaging room of a radiology department in a medical facility. The CT device 11 includes a gantry 16 and a console 17. The console 17 functions as an operation terminal and control device for operating the gantry 16. The console 17 is operated by an operator such as a diagnostic radiologist. The console 17 also functions as an image processing device that generates a tomographic image by performing image processing on data output from the gantry 16. The console 17 is an example of an "image processing device" according to the technology of the present disclosure. The console 17 also functions as an image display device that displays the generated tomographic image.

[0022] As shown in FIG. 2, the gantry 16 is a main part of the CT device 11 and includes a gantry 18 and a bed device 19. In addition to a front view of the gantry 16, FIG. 2 also shows a side view of the gantry 16 within a rectangular dashed-line frame. The bed device 19 has a tabletop 19A on which a subject H can be placed in a supine position. The subject H is placed with his or her body axis aligned with the longitudinal direction of the tabletop 19A (the Z-axis direction of the gantry 16). The tabletop 19A is movable in the Z-axis direction. The gantry 18 has an overall annular shape and has a circular opening 18A in the center, the opening 18A having a diameter greater than the width of the tabletop 19A. During imaging, the tabletop 19A on which the subject H is placed moves in the Z-axis direction relative to the gantry 18 to enter the opening 18A. Imaging is performed while the tabletop 19A is moving relative to the gantry 18.

[0023] A radiation source 21, a detector 22, and a frame 23 are arranged inside the gantry 18. The radiation source 21 irradiates radiation toward the subject H. The detector 22 is a radiation detector that detects radiation that has passed through the subject H. The radiation that has passed through the subject H is attenuated by interactions (such as radiation absorption and scattering) with structures within the subject H's body, such as organs and bones. Each structure has its own unique attenuation coefficient for radiation, and the radiation that has passed through the structure carries intensity information that reflects the structure's attenuation coefficient. The detector 22 has a detection surface on which pixels are arranged two-dimensionally, and outputs a detection signal corresponding to radiation intensity information for each pixel within the detection surface. The detector 22 has an approximately arc-shaped configuration in accordance with the curvature of the gantry 18, and the detection surface is also curved.

[0024] The radiation source 21 and the detector 22 are disposed in opposing positions within the gantry 18, and rotate around the Z axis while maintaining their opposing orientation. The frame 23 is annular and rotatably supports the radiation source 21 and the detector 22. During imaging, the gantry 11 rotates the radiation source 21 and the detector 22 around the subject H on the tabletop 19A, and detects projection data PD at multiple positions in the circumferential direction around the Z axis corresponding to the body axis of the subject H, using the detector 22. During imaging, the tabletop 19A also moves in the Z axis direction in synchronization with the rotation of the radiation source 21 and the detector 22. This allows radiation projection data PD to be acquired at each position around the body axis of the subject H.

[0025] In the gantry 16, the Y axis represents the height direction and the X axis represents the width direction. As an example, in the bed device 19, the subject H is placed in a supine position with the head side facing the gantry 18. Therefore, in imaging, the subject H enters the gantry 18 head-first, and the projection data PD is output in order from the head side to the feet side.

[0026] The DAS (Data Acquisition System) 25 collects the detection signals output by the detector 22, generates projection data PD for each position around the Z axis based on the collected detection signals, and outputs the generated projection data PD to the console 17.

[0027] An irradiation field limiter 24 (also called a collimator) that limits the radiation irradiation field is disposed in front of the radiation source 21 in the irradiation direction. The irradiation field limiter 24 has an irradiation aperture whose outline is defined by a plurality of shielding plates that block radiation, and the size of the irradiation aperture can be changed by moving the shielding plates. Reference numeral 26 denotes a high-voltage generator that generates a high voltage to be supplied to the radiation source 21. The radiation source 21 and the detector 22 are electrically connected to the frame 23, for example, by a slip ring system, and power supply and data transmission / reception are performed via the slip ring. The slip ring system connection enables helical scan imaging of the radiation source 21 and the detector 22. The helical scan system is a system in which imaging is performed while the radiation source 21 and the detector 22 are rotated in one direction without reversing the rotation direction.

[0028] The gantry 16 is provided with a gantry control unit 27. Based on instructions from the console 17, the gantry control unit 27 controls the rotation of the radiation source 21 and the detector 22, the movement of the top plate 19A, and other components of the gantry 16.

[0029] The imaging conditions of the CT apparatus 11 are set through the gantry control unit 27 by operating the console 17. The imaging conditions include the radiation irradiation conditions of the radiation source 21, as well as the imaging range and slice interval. The radiation irradiation conditions include the tube voltage (unit: kV), tube current (unit: mA), and radiation irradiation time (unit: msec) applied to the radiation source 21. The product of the tube current and the irradiation time defines the total radiation dose, which is called the mAs value. The irradiation field is adjusted, for example, in the XZ plane by changing the size of the irradiation opening of the irradiation field limiter 24. Note that when the radiation emitted by the radiation source 21 is a cone beam, the width of the irradiation field in the Z-axis direction can also be adjusted by adjusting the width of the irradiation opening of the irradiation field limiter 24 in the Z-axis direction. The imaging range in the Z-axis direction, such as the whole body of the subject H or the area from the chest to the abdomen, is adjusted by changing the movement range of the top board 19A.

[0030] Furthermore, it is also possible to change the imaging range of a slice image SL (see FIG. 7 , etc.), which will be described later. The slice image SL is a tomographic image representing an XY plane, i.e., an axial cross section perpendicular to the body axis of the subject H, and is generated by image reconstruction based on the projection data PD, as will be described later. The imaging range of such a slice image SL in the XY plane is also called the field of view (FOV). For example, in an axial cross section of the chest of the subject H, the size of the FOV can be changed such that the FOV is a relatively large area that includes the entire chest, or a relatively small area, such as a portion of the chest. The radiation flux spreads from the focal point of the radiation source 21 toward the detector 22. Therefore, if the distance between the radiation source 21 and the detector 22 in the gantry 18 is constant, the area of the radiation flux that passes through the subject H can be narrowed by moving the subject H closer to the radiation source 21 by adjusting the height of the tabletop 19A. Because imaging is possible only for the region of the subject H's body through which radiation has passed, if the region through which radiation has passed is narrow, the FOV becomes small. Conversely, if the subject H is moved farther away from the radiation source 21, the region of the ray flux passing through the subject H becomes wider, and the FOV can be increased. In this way, the size of the FOV can be adjusted, for example, by adjusting the height of the tabletop 19A. On the other hand, since the number of pixels of the detector 22 is fixed, reducing the FOV increases the resolution of the captured slice images SL, while increasing the FOV decreases the resolution. In addition, it is also possible to adjust the distance the tabletop 19A moves in the Z-axis direction during one rotation of the radiation source 21 and the detector 22, i.e., the movement speed in the Z-axis direction. By adjusting the movement speed in the Z-axis direction, the slice spacing of the slice images SL can be adjusted. The FOV and slice spacing are also set as imaging conditions.

[0031] The console 17 includes a display 31, an input device 32, a storage 33, a communication unit 34, and a processor 36. The console 17 is configured, for example, based on a personal computer or the like, and its hardware configuration is similar to that of a general computer. The display 31 is, for example, a liquid crystal display, and displays an operation screen and captured slice images SL, etc. The input device 32 is a device through which an operator inputs operation instructions, and is configured by a keyboard, a mouse, etc.

[0032] The storage 33 is a data storage that stores various programs such as a control program that controls each part of the console 17. The various programs include an application program 37 that causes the processor 36 to function as a control device and image processing device of the CT device 11. Examples of the storage 33 include a hard disk drive (HDD) and a solid state drive (SSD). The storage 33 also temporarily stores projection data PD acquired from the gantry 16 and generated slice images SL. The application program 37 is an example of an "operating program" according to the technology of the present disclosure.

[0033] The communication unit 34 is a communication interface for communicating between the console 17 and external devices such as the gantry 16 and an external image DB (Data Base). The communication unit 34 is connected to a network (not shown) such as a LAN (Local Area Network) and / or a WAN (Wide Area Network), and performs transmission control in accordance with communication protocols defined by various wired or wireless communication standards.

[0034] The processor 36 functions as a control unit 36A that controls each unit of the console 17 and an image processing unit 36B that executes various types of image processing. The processor 36 is configured, for example, by a CPU (Central Processing Unit) and memory such as RAM (Random Access Memory). The CPU functions as the processor 36 by loading various programs, including an application program 37, from the storage 33 into the memory and executing the loaded programs. The processor 36 is an example of a "processor" according to the technology of the present disclosure. The console 17 having the processor 36 that executes image processing is an example of an "image processing device" according to the technology of the present disclosure.

[0035] The control unit 36A controls the gantry 16 via the gantry control unit 27 in accordance with instructions from the operator inputted from the input device 32. The setting of imaging conditions and the like is performed by the control unit 36A. The image processing unit 36B executes slice image generation processing and MPR image generation processing.

[0036] 3 shows an overview of the processing of the processor 36 functioning as the image processing unit 36B. The slice image generation processing is a processing for generating a tomographic image by performing image reconstruction based on the projection data PD acquired from the gantry 16. In the slice image generation processing, the reconstructed tomographic image is a tomographic image representing an axial cross section perpendicular to the body axis (Z axis) of the subject H. Here, this tomographic image is referred to as a slice image SL. The slice image SL is an example of a "slice image" according to the technology of the present disclosure. The reconstruction of the slice image SL based on the projection data PD is performed by, for example, a filtered back projection method.

[0037] When imaging is performed in the CT device 11, a plurality of slice images SL are generated sequentially. For example, when projection data PD is output from the head side of the subject H as in this example, the projection data PD is output sequentially from the head side. Then, the console 17 executes reconstruction processing of the slice images SL sequentially starting from the projection data PD from the head side, and sequentially stores the generated slice images SL in the storage 33. Imaging by the CT device 11 ends when slice images SL of the entire imaging range in the body axis direction (Z-axis direction) are generated. A slice image group including a plurality of slice images SL is called a slice volume VOL. The slice volume VOL is made up of a plurality of slice images SL that are stored sequentially. During imaging, the slice volume VOL is made up of slice images SL of a portion of the imaging range, and after imaging is completed, it is made up of slice images SL of the entire imaging range.

[0038] In the MPR image generation process, first, a function generation process is executed to generate an MPR image generation function GF1 for generating an MPR image. The MPR image generation function GF1 is a function that uses slice images SL as input images and an MPR image Mp as output image. The MPR image generation function GF1 is an example of a function that uses pixel values of multiple slice images SL as parameters. The MPR image Mp is a tomographic image representing an arbitrarily specified cross-section of the subject H and is an example of a "tomographic image representing a specified cross-section" according to the technology of the present disclosure. In this example, in addition to the axial plane (AX), a sagittal plane (SAG), which is a vertical cross-section of the subject H, and a coronal plane (COR), which is a horizontal cross-section of the subject H, will be described as examples of cross-sections (see FIGS. 9 to 11). The primed X'-axis and Y'-axis represent the coordinate axes of the cross-section of the MPR image Mp. The X'-Y' plane changes depending on the direction of the specified cross-section and may not coincide with the XY plane of the slice images SL.

[0039] As shown in Fig. 4 as a conventional technique, an MPR image Mp is generally acquired by specifying an arbitrary cross section in an isotropic three-dimensional image VD_ISO and cutting out the specified arbitrary cross section. The isotropic three-dimensional image VD_ISO is generated by performing an isotropization process on a slice volume VOL including all slice images SL within the imaging range, thereby making the resolutions in the X-axis, Y-axis, and Z-axis directions uniform.

[0040] As described above, the resolution of the slice image SL in the X-axis and Y-axis directions varies depending on the FOV. For example, assume that the number of pixels in the X-axis and Y-axis directions of the slice image SL is 512 x 512. For the same number of pixels, the larger the FOV, the lower the resolution, and the narrower the FOV, the higher the resolution. For example, comparing an FOV of 320 mm with an FOV of 640 mm, the pixel spacing of the slice image SL is 320 mm / 512 = 0.625 and 640 mm / 512 = 1.25, respectively. The smaller the FOV, the smaller the pixel spacing and therefore the higher the resolution.

[0041] On the other hand, since the slice interval that defines the resolution in the Z-axis direction is generally longer than the pixel intervals in the X-axis and Y-axis directions, an interpolation process is performed on the slice images SL to match the pixel intervals in the X-axis and Y-axis directions. This is the isotropization process. The isotropized three-dimensional image VD_ISO is a three-dimensional image whose three-dimensional resolution is isotropized by interpolating the slice images SL based on all slice images SL in the imaging range, and is composed of isotropic voxels, which are pixels that are isotropized in three dimensions. If such an isotropized three-dimensional image VD_ISO is generated, it is possible to generate an MPR image Mp of any cross section. However, it takes time to generate the isotropized three-dimensional image VD_ISO, and it cannot be generated until all slice images SL in the imaging range have been output.

[0042] Therefore, the processor 36 according to the technique of the present disclosure uses the MPR image generation function GF1 to generate the MPR image Mp directly from the slice image SL without generating the isotropic three-dimensional image VD_ISO.

[0043] 3, processor 36 acquires imaging conditions (A) and tomographic image generation conditions (B) in order to create MPR image generation function GF1. These are set before imaging is performed in CT device 11. Processor 36 receives designation of imaging conditions (A) and tomographic image generation conditions (B) by, for example, operation by an operator via input device 32.

[0044] The imaging conditions (A) include A1: slice spacing, A2: FOV, and A3: number of pixels (X, Y). The tomographic image generation conditions (B) include B1: cross-sectional direction and position, and B2: slab thickness. The cross-sectional direction and position are the cross-sectional direction and position of the MPR image Mp to be generated. In this example, the cross-sectional direction is specified as an axial, sagittal, or coronal cross-section. Furthermore, for the cross-sectional position, for example, in the case of an axial cross-section MPR image Mp(AX), any position in the Z-axis direction is specified. In the case of a sagittal cross-section MPR image Mp(SAG), any position in the Z-axis direction and X-axis direction is specified. In the case of a coronal cross-section MPR image Mp(COR), any position in the Z-axis direction and Y-axis direction is specified.

[0045] 5 shows the processing procedure for creating the MPR image generation function GF1 (step S1200). In step S1210, processor 36 creates a Z-coordinate table based on the imaging condition (A). Then, in step S1220, processor 36 creates an isotropic data derivation function using the Z-coordinate table, and further, in step S1230, creates a pixel value derivation function Fmpr for the MPR image Mp based on the isotropic data derivation function.

[0046] FIG. 6 is a diagram conceptually illustrating the creation process of the Z-coordinate table in step S1210. First, the creation process of the Z-coordinate table in step S1210 will be described with reference to FIG. 6. The Z-coordinate table is a table showing the correspondence between SL position coordinates and isotropic Z coordinates. The SL position coordinates indicate the positions of multiple slice images SL in the Z-axis direction and are derived based on the slice spacing included in the imaging condition (A). In the SL position coordinates, point s is an arbitrary position, and point SLP indicates the position where a slice image SL exists. topZ is the position of the slice image SL located closest to the head among the reconstructed slice images SL, and btmZ is the position of the slice image SL located closest to the foot. In other words, it indicates the range of slice images SL that can be used to generate an MPR image Mp. In the example of FIG. 6, 32 slice images SL (#0 to #31) exist in the range from topZ to btmZ.

[0047] The isotropic Z coordinate is a Z coordinate with a scale set according to the resolution in the X-axis and Y-axis directions. In other words, the interval between the scales of the isotropic Z coordinate is the same as the pixel interval in the X-axis and Y-axis directions of the slice image SL. In the isotropic Z coordinate, point z is an arbitrary position on the scale.

[0048] As shown in Fig. 7, the scale interval of the isotropized Z coordinate changes depending on the size of the FOV. Comparing the case of FOV1 shown in Fig. 7(7A) with the case of FOV2, which is smaller than FOV1, shown in Fig. 7(7B), the scale interval is shorter for FOV2. As described above, the smaller the FOV, the higher the resolution, and the shorter the pixel intervals in the X-axis and Y-axis directions.

[0049] In the Z coordinate table creation process of step S1210, processor 36 first creates isotropized Z coordinates based on the FOV and number of pixels (X, Y) set as the imaging condition (A). Then, a table indicating the correspondence between SL position coordinates and each position z in the isotropized coordinates is created as a Z coordinate table. When the position of the MPR image Mp is specified in the isotropized Z coordinates, this Z coordinate table makes it possible to derive the corresponding point s in the SL position coordinates. As will be described later, the position of the MPR image Mp in the Z axis direction is specified based on the scale of the isotropized Z coordinates.

[0050] 8 is a diagram conceptually illustrating the process of creating an isotropic data derivation function in step S1220. The isotropic data derivation function is a function that derives an isotropic slice image SL_ISO at each z position of the isotropic Z coordinate. The isotropic slice image SL_ISO is a slice image interpolated at each z position of the isotropic Z coordinate based on the slice image SL. The isotropic data derivation function is a function that derives the pixel value tmp[z][p] of each pixel p of the isotropic slice image SL_ISO as isotropic data. Here, [z] indicates the position on the isotropic Z coordinate, and [p] indicates the position of the isotropic slice image SL_ISO in the XY plane.

[0051] In the process of creating an isotropic data derivation function in step S1220, processor 36 first sets a range in the SL position coordinates corresponding to each position z according to the slab thickness of the isotropic slice image SL_ISO and the Z coordinate table. This range is defined by point Sb on the topZ side and point Se on the btmZ side, and is a selection range for selecting slice images SL to be used to derive pixel values tmp[z]″p] of the isotropized slice image SL_ISO. The isotropized slice image SL_ISO is a slice image that interpolates an area where no slice images SL exist. Therefore, the pixel values tmp[z]″p] of the isotropized slice image SL_ISO are derived by linear interpolation from pixel values of multiple slice images SL that exist in the vicinity. The selection range defines the slice images SL to be used for interpolation. The width of this selection range is set in advance according to the interval between scale marks on the isotropized Z coordinate. In other words, the approximate number of slice images SL to be used for interpolation for one z position is set in advance. In this example, since the selection range includes two slice images SL (Smin and Smax), two slice images SL are used for interpolation. Of course, the number of slice images SL to be used for interpolation is arbitrary and may be three or more.

[0052] In the example shown in FIG. 8, the processor 36 identifies the position of the SL position coordinates corresponding to each position z of the isotropic Z coordinates based on the Z coordinate table. The position corresponding to the z position is set as ztbl[z-topZ]. The points moved equal distances to the topZ side and the btmZ side in the SL position coordinates from this position are points Sb and Se, respectively. The range of points Sb and Se includes Smin(SLP) on the topZ side and Smax(SLP) on the btmZ side. The SLP in parentheses indicates that slice images SL exist at the positions of Smin and Smax. By specifying points Sb and Se, two slice images SL to be used for interpolation are selected.

[0053] Then, in the pixel value interpolation process, processor 36 determines the weights to be applied to the pixel values of each of slice images SL of Smin and Smax from an isosceles triangle with the z position as the vertex and the line connecting points Sb and Se as the base. The isosceles triangle represents the distribution of weights of pixel values of the slice images SL to be used. rb is a weighting coefficient by which the pixel value of slice image SL of Smin is multiplied, and re is a weighting coefficient by which the pixel value of slice image SL of Smax is multiplied. The maximum value of the weighting coefficient is "1." Comparing the weighting coefficients rb and re, rb, which is closer to the z position in the Z-axis direction, is larger. Processor 36 uses the weighting coefficients rb and re derived in this way to determine the weights of the pixel values of each of slice images SL of Smin and Smax, and calculates pixel values tmp[z] "p] of the isotropic slice image SL_ISO.

[0054] Conceptually, the isotropic data derivation function performs this processing to derive the pixel value tmp[z]``p] as isotropic data. The pixel value tmp[z]``p] is the pixel value of a pixel whose resolution is isotropic in the X-axis, Y-axis, and Z-axis directions, where the body axis direction is the Z-axis direction and the two directions defining the cross section orthogonal to the body axis direction are the X-axis and Y-axis directions. This is data equivalent to the pixel value of an isotropic voxel in the isotropic three-dimensional image VD_ISO.

[0055] 8, the isotropic data derivation function is expressed by, for example, Equation (1) under the following conditions: First, the ranges of x, y, and z of the isotropic slice image SL_ISO are as follows: 0≦x <imageWidh 0≦y <imageHight topZ ≦ z ≦ btmZ In equation (1), [p] indicates the position of the isotropic slice image SL_ISO in the XY plane, and is defined by the component [x] in the X-axis direction and the component [y] in the Y-axis direction.

[0056]

number

[0057] Here, in formula (1), "vol" means the pixel value of the slice image SL included in the slice volume VOL. For example, vol[Smin][p] is the pixel value of each pixel p in the XY plane of the slice image SL of Smin at the SL position coordinates. vol[Smax][p] is the pixel value of each pixel p in the XY plane of the slice image SL of Smax at the SL position coordinates. The definitions of the other symbols are as follows: rb=Smin-Sb re=Se-Smax Smin = Ceil(Sb) Smax=floor(Se) Sb=ztbl[z-topZ]-1 Se=ztbl[z-topZ]+1

[0058] For example, suppose the SL position coordinate of ztbl[z-topZ] is "2.3." Then, from the formulas for Sb and Se, Sb is "1.3" and Se is "3.3." Because the slice image SL is used for interpolation, to find the position (SLP) of the slice image SL near Sb and Se, Smix is determined by rounding up "1.3" in Sb to the integer value "2." Meanwhile, Se's "3.3" is rounded down to the integer value "3," which determines Smax. The weighting coefficients rb and re for the pixel values of these slice images SL are determined according to the distance from the z position, so rb = 2 - 1.3 = 0.7 and re = 3.3 - 3 = 0.3. The sum of 70% of the pixel value of Smin and 30% of the pixel value of Smax is the value of tmp[z][p] at z = 2.3. Here, to obtain an accurate pixel value, it is necessary to divide by the number of slice images SL used in order to calculate the arithmetic average of the pixel values of the slice images SL of Smin and Smax. However, as will be described later, tmp[z'[p] is data that is integrated into the pixel value derivation function Fmpr of the MPR image Mp. Therefore, tmp[z'[p] is used without being divided by the number of slice images SL.

[0059] In this example, the slab thickness, which is the thickness of the isotropic slice image SL_ISO in the Z-axis direction, is "0," so no slice image SL exists between Smin and Smax. Therefore, the second term including Σ in equation (1) is "0." However, if the slab thickness is greater than "0" and a slice image SL exists between Smin and Smax, the second term will be greater than "0." If the slab thickness is greater than "0," the isosceles triangle representing the distribution of weighting coefficients will be a trapezoid with an upper base the length of which is the slab thickness. The weighting coefficient for the pixel values of the slice image SL defined in the second term will be the maximum value of "1."

[0060] FIG. 9 is a diagram conceptually illustrating the process of generating the pixel value derivation function Fmpr for the MPR image Mp in step S1230. The pixel value derivation function Fmpr shown in FIG. 9 is a function that derives the pixel value output[p'] of pixel p' in the MPR image Mp(AX) of the axial section (AX). In the MPR image Mp(AX) of the axial section (AX), the X'-Y' plane represents the cross section, and the C axis represents the thickness direction of the slab thickness Slb_Th. In the MPR image Mp(AX) of the axial section (AX), the C axis corresponds to the isotropized Z coordinate. The C axis is represented as C(Z) because it corresponds to the isotropized Z coordinate. The position of the MPR image Mp(AX) is specified in the isotropized Z coordinate. Ci is the specified position of the cross section of the MPR image Mp(AX) and is specified from a position corresponding to the scale of the isotropized Z coordinate.

[0061] The method for deriving pixel values of the MPR image Mp(AX) is substantially the same as the method for deriving pixel values of the isotropized slice image SL_ISO shown in FIG. 8. That is, the processor 36 derives the pixel value output[p'] of each pixel p' of the MPR image Mp(AX) by linearly interpolating the pixel values of the isotropized slice image SL_ISO corresponding to the specified position Ci. The trapezoid indicated by the dotted line on the C(Z) axis is similar to the isosceles triangle shown as the distribution of weighting coefficients of the isotropized data derivation function in FIG. 8. In FIG. 9, the trapezoid is a trapezoid because the slab thickness Slb_Th is greater than "0." The trapezoid has equidistant widths on both the topZ and btmZ sides centered on the specified position Ci. On the C(Z) axis, the range defined by Cb and Ce is the selection range of the isotropized slice image SL_ISO used for interpolation, similar to Sb and Se shown in FIG. 8. The slab thickness Slb_Th is specified as a tomographic image generation condition (B), and the selection range is set according to the specified slab thickness Slb_Th. qb and qe are weighting coefficients by which the pixel values of the isotropic slice image SL_ISO of Cmin and Cmax are multiplied.

[0062] Conceptually, the pixel value derivation function Fmpr of the MPR image Mp(AX) performs such processing to derive the pixel value output[p'].

[0063] 9, the pixel value derivation function Fmpr of the MPR image Mp(AX) is expressed by equation (2) under the following conditions, for example: The conditions are as follows: First, the ranges of x', y', and cp of the MPR image Mp(AX) are as follows: cp is the position of the isotropic slice image SL_ISO that exists within the range corresponding to the slab thickness Slb_Th in the isotropic Z coordinate corresponding to the C(Z) axis. 0≦x' <imageWidh 0≦y' <imageHight topZ ≦ cp ≦ btmZ In equation (2), [p'] indicates the position [x'][y'] of the MPR image Mp(AX) in the X'-Y' plane.

[0064]

number

[0065] Here, in equation (2), "tmp" is the pixel value of the isotropized slice image SL_ISO calculated from the isotropized data derivation function. For example, tmp[Cmin][p'] is the pixel value of each pixel p' in the XY plane of the isotropized slice image SL_ISO of Cmin in the isotropized Z coordinate. tmp[Cmax][p'] is the pixel value of each pixel p' in the XY plane of the isotropized slice image SL_ISO of Cmax in the isotropized Z coordinate. The definitions of the other symbols are as follows: qb=Cmin-Cb re=Ce-Cmax Cmin=Ceil(Cb) Cmax=floor(Ce) Cb=Ci-ΔT / 2-1 Ce=Ci+ΔT / 2+1 ΔT=Slb_Th / PS

[0066] qb and qe correspond to rb and re in the isotropized data derivation function and are weighting coefficients by which the pixel values of Cmin and Cmax are multiplied. Like rb and re, qb and qe are calculated according to the weight distribution represented by a trapezoid. ΔT is the slab thickness Slb_Th in millimeters divided by the pixel spacing PS, and is the thickness equivalent to the slab thickness Slb_Th adjusted to the scale units of the isotropized Z coordinate.

[0067] The pixel value derivation function Fmpr includes tmp in equation (2), and the isotropized data derivation function is integrated. After creating the isotropized data derivation function, the processor 36 creates the pixel value derivation function Fmpr according to the slab thickness Slb_Th specified as the tomographic image generation condition (B).

[0068] FIG. 10 is a conceptual diagram illustrating the process of creating a pixel value derivation function Fmpr that derives the pixel value output[p'] of pixel p' in an MPR image Mp(SAG) of a sagittal plane (SAG). This is essentially the same as the example of an axial plane (AX) shown in FIG. The following mainly explains the differences. In the MPR image Mp(SAG), the X'-Y' plane represents the cross section, and the C axis represents the thickness direction of the slab thickness Slb_Th. In the case of an MPR image Mp(SAG) of a sagittal plane (SAG), the C axis corresponds to the isotropic X coordinate. The position of the MPR image Mp(SAG) is specified on the C(X) axis, which corresponds to the isotropic X coordinate. Ci is the specified position of the cross section of the MPR image Mp(SAG), and is specified from a position corresponding to the scale of the isotropic X coordinate.

[0069] Then, processor 36 determines a selection range defined by Cb and Ce on the C(X) axis based on the designated position Ci and the slab thickness Slb_Th. The weighting coefficients by which pixel values of the isotropic slice image SL_ISO are multiplied are determined from the weight distribution of a trapezoid defined by Cb, Ce, and the designated position Ci.

[0070] In the case of the MPR image Mp(SAG) of the sagittal section (SAG), unlike the case of the axial section (AX), the directions of the isotropic Z coordinate and the slab thickness Slb_Th are different, so the ranges of topZ and btmZ are defined in the width direction (Y' axis direction) of the X'-Y' plane.

[0071] 10, the pixel value derivation function Fmpr of the MPR image Mp(SAG) is expressed by equation (3) under the following conditions, for example: The conditions are as follows: First, the ranges of x', y', and cp of the MPR image Mp(SAG) are as follows: where cp is the pixel position of the isotropized slice image SL_ISO within the range corresponding to the slab thickness Slb_Th in the isotropized X coordinate corresponding to the C(X) axis. 0≦cp <imageWidh 0≦x' <imageHight topZ ≦ y' ≦ btmZ In equation (3), [p'] indicates the position [x'][y'] of the MPR image Mp(SAG) in the X'-Y' plane.

[0072]

number

[0073] Equation (3) also includes "tmp", the output value of the isotropization data derivation function, and the isotropization data derivation function is integrated. The definitions of each symbol in equation (3) are as follows, and are the same as those in equation (2). ΔT is the thickness equivalent to the slab thickness Slb_Th adjusted to the unit of the scale of the isotropization X coordinate. qb=Cmin-Cb re=Ce-Cmax Cmin=Ceil(Cb) Cmax=floor(Ce) Cb=Ci-ΔT / 2-1 Ce=Ci+ΔT / 2+1 ΔT=Slb_Th / PS

[0074] FIG. 11 is a conceptual diagram illustrating the process of creating a pixel value derivation function Fmpr that derives the pixel value output[p'] of pixel p' in an MPR image Mp(COR) of a coronal section (COR). This is essentially the same as the example of a sagittal section (SAG) shown in FIG. 10. The following mainly explains the differences. In the MPR image Mp(COR), the X'-Y' plane represents the cross section, and the C axis represents the thickness direction of the slab thickness Slb_Th. In the case of an MPR image Mp(COR) of a coronal section (COR), the C axis corresponds to the isotropic Y coordinate. The position of the MPR image Mp(COR) is specified on the C(Y) axis, which corresponds to the isotropic Y coordinate. Ci is the specified position of the cross section of the MPR image Mp(COR), and is specified from a position corresponding to the scale of the isotropic Y coordinate.

[0075] Then, similarly to the case of the sagittal plane (SAG), processor 36 determines a selection range defined by Cb and Ce on the C(Y) axis based on the designated position Ci and the slab thickness Slb_Th. The weighting coefficients by which the pixel values of the isotropic slice image SL_ISO are multiplied are determined from the weight distribution of a trapezoid defined by Cb, Ce, and the designated position Ci.

[0076] In the case of the MPR image Mp(COR) of the coronal section (COR), as in the sagittal section (SAG), the directions of the isotropic Z coordinate and the slab thickness Slb_Th are different, so the ranges of topZ and btmZ are defined in the width direction (Y' axis direction) of the X'-Y' plane.

[0077] In the example shown in FIG. 11 , the pixel value derivation function Fmpr of the MPR image Mp(COR) is expressed by, for example, equation (4) under the following conditions: Equation (4) is similar to equation (3) for the sagittal plane (SAG). By devising a way to define the X'-axis and Y'-axis of the cross section of the MPR image Mp(COR), equation (3) for the sagittal plane (SAG) and equation (4) for the coronal plane are unified. The conditions differ from those for the sagittal plane (SAG). The conditions are as follows: First, the ranges of x', y', and cp for the MPR image Mp(COR) are as follows: Here, cp is the pixel position of the isotropized slice image SL_ISO within the range corresponding to the slab thickness Slb_Th in the isotropized Y coordinate corresponding to the C(Y) axis. 0≦x' <imageWidh 0≦cp <imageHight topZ ≦ y' ≦ btmZ In equation (4), [p'] indicates the position [x'][y'] of the MPR image Mp(COR) in the X'-Y' plane.

[0078]

number

[0079] Equation (4) also includes "tmp", the output value of the isotropization data derivation function, and the isotropization data derivation function is integrated. The definitions of each symbol in equation (4) are as follows, and are the same as those in equation (3). ΔT is the thickness equivalent to the slab thickness Slb_Th adjusted to the unit of the scale of the isotropization Y coordinate. qb=Cmin-Cb re=Ce-Cmax Cmin=Ceil(Cb) Cmax=floor(Ce) Cb=Ci-ΔT / 2-1 Ce=Ci+ΔT / 2+1 ΔT=Slb_Th / PS

[0080] The operation of the above configuration will be described with reference to the flowchart of FIG. 12 showing the processing procedure of the MPR image generation process. When performing imaging with the CT device 11, the processor 36 of the console 17 waits for acquisition of the imaging conditions (A) and the tomographic image generation conditions (B) in step S1100. As explained in FIG. 2, the imaging conditions (A) include the slice interval, FOV, and number of pixels (X, Y). The tomographic image generation conditions (B) include the direction and position of the cross section of the MPR image Mp and the slab thickness Slb_Th.

[0081] In step S1100, if the imaging conditions (A) and the tomographic image generating conditions (B) are acquired (Y in step S1100), the processor 36 proceeds to step S1200.

[0082] In step S1200, the processor 36 acquires the imaging conditions (A) and the tomographic image generation conditions (B) before the CT device 11 starts imaging, and generates an MPR image generation function GF1. The processor 36 generates the MPR image generation function GF1 in the procedure shown in FIG. 5 based on the imaging conditions (A) and the tomographic image generation conditions (B). More specifically, the MPR image generation function GF1 includes the Z coordinate table shown in FIG. 6, the isotropic data derivation function shown in FIG. 8, and the pixel value derivation function Fmpr shown in FIGS. 9 to 11. The processor 36 generates these in step S1200. The imaging conditions (A) of the CT device 11 include at least the slice spacing, and the processor 36 generates the MPR image generation function GF1 according to the imaging conditions (A).

[0083] Then, when imaging is started in step S1300, the processor 36 acquires projection data PD in order from the head side of the subject H, and starts generating slice images SL based on the acquired projection data PD.

[0084] In step S1400, the processor 36 waits for acquisition of the necessary slice images SL according to the tomographic image generation conditions (B). If the designated position Ci of the MPR image Mp is on the head side of the subject H, the necessary slice images SL can be acquired relatively quickly. When the necessary slice images SL are acquired in step S1400, the processor 36 proceeds to step S1500.

[0085] In step S1500, the processor 36 uses the created MPR image generation function GF1 and inputs the slice images SL to generate an MPR image Mp meeting the specified conditions. In this way, when the CT device 11 outputs multiple slice images SL during imaging, the processor 36 starts the process of generating the MPR image Mp during imaging.

[0086] Then, in step S1600, the processor 36 displays the MPR image Mp on the display 31.

[0087] Thus, the console 17 having the processor 36 is an example of an image processing device equipped with a processor that performs image processing on a plurality of slice images SL that are output by the CT device 11 (an example of a tomographic imaging device) and represent axial sections (AX) perpendicular to the body axis of the subject H (an example of a test object). The processor 36 acquires the plurality of slice images SL and generates an MPR image Mp, which is an example of a tomographic image representing a specified cross section, using an MPR image generation function GF1, which is an example of a function that uses pixel values of the plurality of slice images SL as parameters.

[0088] Therefore, compared to the conventional method of generating an isotropic three-dimensional image VD_ISO (see FIG. 4) in which the three-dimensional resolution is isotropized based on all slice images SL in the imaging range and then extracting a tomographic image representing a specified cross section from the generated isotropic three-dimensional image VD_ISO, a tomographic image such as an MPR image Mp representing the specified cross section can be acquired in a shorter time. That is, by using a function such as the MPR image generation function GF1, which directly inputs the slice images SL and outputs a tomographic image such as an MPR image Mp, a tomographic image representing the specified cross section can be acquired without going through the process of generating an isotropic three-dimensional image. Therefore, the acquisition time from the start of imaging in the tomography apparatus to the acquisition of a tomographic image can be shortened compared to the conventional method.

[0089] Furthermore, as shown in steps S1400 and S1500 of FIG. 12 , when the CT apparatus 11 outputs multiple slice images SL during imaging, the processor 36 according to the technology of the present disclosure starts a process for generating a tomographic image, such as an MPR image Mp, during imaging using the multiple slice images SL. As described above, starting the process for generating a tomographic image during imaging further shortens the time required to acquire the tomographic image. Here, “during imaging” refers to the period from the start of imaging of a specified imaging range in the subject's body axis direction until imaging of the entire imaging range is completed. In the above example, for example, if the imaging range is the entire body of the subject H, this refers to the period from the start of imaging from the subject H's head until imaging of the entire imaging range down to the feet is completed. Furthermore, as shown in step S1400, for example, the processor 36 can start generating an MPR image Mp without waiting for the end of imaging when a slice image SL necessary to generate an MPR image Mp for the specified position Ci is output.

[0090] Furthermore, a function, such as the MPR image generation function GF1, is created according to the imaging conditions of the CT device 11, including the slice spacing of the slice images SL. Therefore, the processor 36 can create an appropriate function according to the imaging conditions including the slice spacing.

[0091] Furthermore, the processor 36 acquires the imaging conditions and creates a function such as the MPR image generation function GF1 before the tomographic imaging apparatus starts imaging. Therefore, compared to acquiring the imaging conditions after imaging starts and creating a function, a tomographic image of a specified cross section such as the MPR image Mp can be acquired in a shorter time. Note that instead of creating a function for each imaging, for example, multiple functions corresponding to different slice intervals may be prepared in advance, and a function may be selected according to the slice interval set as an imaging condition.

[0092] The MPR image generation function also includes an isotropic data derivation function that derives isotropic data as pixel values of pixels whose resolution is isotropized in the X-axis, Y-axis, and Z-axis directions. The processor generates a tomographic image such as the MPR image Mp based on the isotropic data. This results in an MPR image Mp equivalent to an MPR image extracted from the isotropic three-dimensional image VD_ISO. Such an MPR image Mp is useful because it is frequently used.

[0093] In the above example, the cross section of the MPR image Mp, which is an example of a tomographic image, is one of an axial plane (AX), a sagittal plane (SAG), and a coronal plane (COR). These planes are useful because they are frequently used, and in addition, the MPR image generation function GF1 can be created more easily than when generating other planes. Note that the cross section of the MPR image Mp may be an oblique plane or another plane in any other direction, in addition to the planes in the above example. In that case, a function corresponding to the plane in the other direction is created.

[0094] The processor 36 also accepts a slab thickness specification as the thickness of the MPR image Mp, which is an example of a tomographic image, and performs weighting according to the slab thickness to generate the MPR image Mp. Since weighting according to the slab thickness is performed, a tomographic image that accurately reflects information about the subject H can be obtained compared to when no weighting is performed.

[0095] [Second embodiment] 13 to 19 is an example in which a tilt image DT is generated as a tomographic image representing a specified cross section using a tilt image generation function GF2 that uses pixel values of a slice image SL as a parameter. The tilt image DT is a tomographic image representing a tilted cross section obtained by rotating the axial cross section of the slice image SL around the X axis, where the body axis direction is the Z axis direction, the width direction of the cross section perpendicular to the body axis direction is the X axis direction, and the height direction is the Y axis direction.

[0096] Gantry tilt radiography, in which radiography is performed by physically tilting the gantry 18, is known. By tilting the gantry 18, the radiation irradiation direction also tilts with respect to the body axis, causing the radiation to pass through the subject H at an angle. This results in a slice image SL that is tilted with respect to the body axis of the subject H. The slice image SL obtained by gantry tilt radiography is called a tilt image because the cross section is tilted. However, the mechanism for rotating the gantry 18 is complex and large-scale, which results in a very high cost.

[0097] Therefore, in the second embodiment, a tilt image DT is generated by image processing based on slice images SL representing cross sections perpendicular to the body axis. Processor 36 creates a tilt image generation function GF2 for generating tilt image DT based on imaging conditions (A) and tomographic image generation conditions (B). As in the first embodiment, imaging conditions (A) include A1: slice spacing, A2: FOV, and A3: number of pixels (X, Y). Tomographic image generation conditions (B) include B2: slab thickness and B3: tilt angle.

[0098] 14 shows the processing procedure for creating the tilt image generation function GF2 (step S2200). In step S2210, processor 36 creates a coordinate conversion table. Then, in step S2220, processor 36 creates a pixel value derivation function Fdt for the tilt image DT, and in step S2230, processor 36 creates a pixel value derivation function Fdt for the tilt image DT.

[0099] Fig. 15 is a diagram conceptually showing the process of creating a coordinate conversion table in step S2210. The coordinate conversion table is a table that converts the position of pixel P in slice image SL into the position of pixel Pt in tilt image DT, as shown in Fig. 15 (15A). In Fig. 15 (15A), a thick-lined circle with dotted hatching represents pixel P, and a thin-lined circle without hatching represents pixel Pt.

[0100] More specifically, the coordinate conversion table is a table for performing linear conversion by setting a tilt center CTR and rotating pixel P around the X axis with the set tilt center CTR as the center of rotation, as shown in (15A) of Fig. 15. The coordinate conversion table is created, for example, based on a rotation determinant that rotates a point in the YZ plane around the X axis with the origin as the center, as shown in the following equation (5).

[0101]

number

[0102] By performing coordinate transformation using equation (5), the processor 36 rotates the slice image SL of the axial section as shown in (15B) of FIG. 15 around the X-axis by the tilt angle ω as shown in (15C) of FIG. 15 to generate a tilt image DT representing a tilted section.

[0103] However, as shown in (15A) of FIG. 15, coordinate transformation is performed so that the heights of pixels Pt in the Y-axis direction are uniform in multiple tilt images DT arranged in the Z-axis direction. For example, if multiple slice images SL are simply tilted around the tilt center CTR, as shown in FIG. 16, pixels P arranged in the Z-axis direction in the slice images SL become pixels Pt arranged in a direction tilted upward and to the right with respect to the Z-axis in the tilt images DT. Furthermore, in gantry tilt imaging in which the gantry 18 is tilted, the gantry 18 moves in the Z-axis direction in an inclined position, and the detector 22 has a width. Therefore, the heights of pixels Pt in the Y-axis direction change stepwise according to the width of the detector 22. Since such a change in the height of pixels Pt in the Y-axis direction may be undesirable in terms of visibility, etc., the heights of pixels Pt in the Y-axis direction are uniform in the tilt images DT according to the technology disclosed herein. As an example, the heights of pixels Pt in the Y-axis direction are constant.

[0104] As shown in (15A) of FIG. 15, the slice spacing SI of the slice image SL is the same as the spacing in the direction perpendicular to the two tilted tilt axes of the tilt image DT. The spacing between the two tilt axes in the Z-axis direction is 1 / cosω times wider than the slice spacing SI. Furthermore, the pixel spacing PS of two pixels P adjacent in the Y-axis direction of the slice image SL is the same as the pixel spacing PS of two pixels Pt adjacent in the tilt axis direction in the tilt image DT. The coordinate conversion table is set to satisfy these conditions. As explained in the first embodiment, the pixel spacing PS is calculated based on the FOV and the number of pixels (X, Y) set as the imaging condition (A).

[0105] 17 is a diagram conceptually illustrating the process of creating the pixel-value derivation function Fdt in step S2220. The pixel value of pixel Pt in tilt image DT is found by linear interpolation according to the distance d from the pixel values of four neighboring pixels P arranged to surround pixel Pt. If the distance between each of the four pixels P and pixel Pt is d and the weighting coefficient of the pixel values of the four pixels is W, then, as shown in the graph representing the relationship between d and w, the smaller d is, the larger the weighting coefficient W is. In other words, the closer the distance to pixel Pt, the greater the weight of the pixel value of pixel P. The pixel-value derivation function Fdt is created in accordance with these conditions.

[0106] When the slab thickness Slb_Th of the tilt image DT is "0", generation of the tilt image DT may be completed by simply performing coordinate transformation and linear interpolation of pixel values using the pixel value derivation function Fdt. However, when the slab thickness Slb_Th is greater than "0", generating the tilt image DT by weighting according to the slab thickness Slb_Th will result in a tilt image DT that accurately reflects the information of the subject H.

[0107] Step S2230 is a process for creating a weight correction function for weighting according to the slab thickness Slb_Th. FIG. 18 is a diagram conceptually illustrating the process for creating the weight correction function in step S2230. In FIG. 18, pixel Pt_i is the pixel Pt that is the target of weight correction according to the slab thickness Slb_Th. The weight correction method shown in FIG. 18 is the same as the weighting process shown in FIGS. 9 to 11 of the first embodiment. That is, using the pixel values of multiple pixels Pt arranged in the thickness direction of the slab thickness Slb_Th, each pixel value is multiplied by a weight coefficient according to the distance from the pixel Pt_i to be corrected, thereby correcting the pixel value of the pixel Pt_i to be corrected. The range defined by Pt_b and Pt_e is a selection range of pixels Pt to be used for correction, and is set according to the slab thickness Slb_Th. Pixels Pt_min and Pt_max are the pixels Pt located at both ends of the selection range. qb and qe are weighting coefficients that set the weights of pixels Pt_min and Pt_max. Processor 36 generates such a weight correction function based on slab thickness Slb_Th in step S2230.

[0108] The operation of the above configuration will be described with reference to the flowchart of the tilt image generation process shown in Fig. 19. When performing imaging with the CT device 11, the processor 36 of the console 17 waits for acquisition of the imaging conditions (A) and the tomographic image generation conditions (B) in step S2100. As explained in Fig. 13, the imaging conditions (A) include the slice interval, FOV, and number of pixels (X, Y). The tomographic image generation conditions (B) include the slab thickness Slb_Th and the tilt angle ω.

[0109] In step S2100, if the imaging conditions (A) and the tomographic image generating conditions (B) are acquired (Y in step S2100), the processor 36 proceeds to step S2200.

[0110] In step S2200, the processor 36 generates a tilt image generation function GF2. The processor 36 generates the tilt image generation function GF2 in the procedure shown in Fig. 13 based on the imaging conditions (A) and the tomographic image generation conditions (B). More specifically, the tilt image generation function GF2 includes the coordinate conversion table shown in Fig. 15, the pixel value derivation function Fdt by four-point interpolation shown in Fig. 17, and the weight correction function shown in Fig. 18. In step S2200, the processor 36 generates these. In this way, the processor 36 generates the tilt image generation function GF2 according to the imaging conditions (A) of the CT device 11 including the slice interval SI.

[0111] Then, when imaging is started in step S2300, the processor 36 acquires projection data PD in order from the head side of the subject H, and starts generating slice images SL based on the acquired projection data PD.

[0112] In step S2400, the processor 36 waits for acquisition of the necessary slice images SL according to the tomographic image generation conditions (B). If the designated position of the tilt image DT is on the head side of the subject H, the necessary slice images SL can be acquired relatively quickly. When the necessary slice images SL are acquired in step S2400, the processor 36 proceeds to step S2500.

[0113] In step S2500, the processor 36 uses the created tilt image generation function GF2 and inputs the slice image SL to generate a tilt image DT according to specified conditions such as the tilt angle ω. In this way, when the CT device 11 outputs a plurality of slice images SL during imaging, the processor 36 starts the process of generating the tilt image DT during imaging.

[0114] Then, in step S2600, processor 36 displays tilt image DT on display 31.

[0115] In this way, the processor 36 generates a tilt image DT representing a tilted section tilted by rotating the axial section of the slice image SL around the X axis using the tilt image generation function GF2 including the pixel value derivation function Fdt. By using the tilt image generation function GF2, the tilt image DT can be obtained at a lower cost than when gantry tilt imaging is performed.

[0116] Furthermore, when processor 36 generates a plurality of tilt images DT arranged in the Z-axis direction, the heights of pixels Pt in the Y-axis direction of the plurality of tilt images DT are uniform. Therefore, the visibility of the tilt images DT is better than when the heights of pixels Pt in the Y-axis direction are not uniform, as shown in FIG.

[0117] The processor 36 receives a specification of the slab thickness Slb_TH as the thickness of the tilt image DT, and generates the tilt image DT by weighting according to the specified slab thickness Slb_TH. As described above, by weighting, the tilt image DT that accurately reflects the information of the subject H can be obtained.

[0118] The processor 36 may execute the MPR image generation process shown in the first embodiment in addition to the tilt image generation process.

[0119] Furthermore, as shown in the above embodiment, the "function" according to the technology of the present disclosure may be in the form of table data or an arithmetic expression.

[0120] [Third embodiment] In the above embodiment, the console 17 has been described as an example of an image processing device that performs image processing for generating an MPR image and a tilt image. However, as shown in FIG. 20 , an image display device 13 separate from the console 17 may function as the image processing device. In this case, for example, slice images SL output by the CT device 11 are temporarily stored in an image DB 12. The image DB 12 is, for example, a PACS (Picture Archiving and Communication System). The image DB 12 stores slice images SL of the subject H output from the CT device 11 and delivers the stored slice images SL to the image display device 13 that has requested the image display. The image display device 13 has a processor similar to the processor 36 and performs image processing such as generating an MPR image and a tilt image based on the delivered slice images SL. For example, the image display device 13 is disposed in each department in a medical facility and used by doctors in the department.

[0121] In this case, the tomographic image generating conditions (B) are specified by a doctor in the medical department. Furthermore, the image display device 13 acquires the imaging conditions (A) set in the CT device 11 from the CT device 11 via the console 17. The image display device 13 executes image processing such as MPR image generating processing and tilt image generating processing based on the imaging conditions (A) and the tomographic image generating conditions (B).

[0122] In the above embodiment, an example has been shown in which image processing such as MPR image generation processing is performed based on slice images SL output during imaging by the CT device 11, but image processing such as MPR image generation processing may also be performed after imaging is completed. Even in this case, the process of generating the isotropic three-dimensional image VD_ISO is not required, and the effect of being able to execute the MPR image generation processing or tilt image generation processing in a short time can be obtained.

[0123] In the above embodiment, the CT device 11 is used as an example of the tomographic imaging device, but an MRI device may also be used. Furthermore, the radiation is not limited to X-rays, and may be gamma rays.

[0124] Furthermore, in the above embodiment, the hardware structure of the processor 36 of the console 17 or the processor of the image display device 13 may be any of the various processors listed below. The various processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as various processing units, as well as dedicated electrical circuits, such as a PLD (Programmable Logic Device) whose circuit configuration can be changed after manufacture, such as an FPGA (Field-Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing specific processing.

[0125] The various processes described above may be executed by one of these various processors, or may be executed by a combination of two or more processors of the same or different types (for example, a plurality of FPGAs, or a combination of a CPU and an FPGA). Furthermore, a plurality of processing units may be configured by a single processor. An example of configuring a plurality of processing units by a single processor is a form in which a processor is used that realizes the functions of an entire system including a plurality of processing units by a single IC (Integrated Circuit) chip, such as a System on Chip (SOC).

[0126] In this way, the various processing units are configured as hardware structures using one or more of the various processors described above.

[0127] Furthermore, as the hardware structure of these various processors, more specifically, an electric circuit combining circuit elements such as semiconductor elements can be used. do.

[0128] In addition to the operating program of the CT device 11 or the image display device 13, the technology disclosed herein also extends to a computer-readable storage medium (such as a USB memory or a DVD (Digital Versatile Disc)-ROM (Read Only Memory)) that non-temporarily stores the operating program.

[0129] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0130] From the above description, the technology described in the following supplementary paragraphs can be understood.

[0131] [Additional note 1] An image processing device including a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, The processor Acquire multiple slice images, Generates a tomographic image representing a specified cross section using a function that uses pixel values of multiple slice images as parameters. Image processing device. [Additional note 2] When a tomography apparatus outputs multiple slice images during imaging, The processor Using multiple slice images, start the process of generating a tomographic image during imaging Item 1. An image processing device according to claim 1. [Additional note 3] The function is generated according to the imaging conditions of the tomographic imaging apparatus, which include at least the slice interval of the slice images. Item 1 or 2. An image processing device according to item 1 or 2. [Additional note 4] The processor Before the tomography device starts taking images, obtain the imaging conditions and create a function. Item 2 or 3. The image processing device according to item 2 or 3. [Additional note 5] When the body axis direction of the subject is the Z axis direction, and the two directions defining the cross section perpendicular to the body axis direction are the X axis direction and the Y axis direction, the function includes an isotropic data derivation function that derives isotropic data as pixel values of pixels whose resolutions are isotropic in the X-axis direction, the Y-axis direction, and the Z-axis direction; The processor generates a tomographic image based on the isotropized data. Item 4. The image processing device according to any one of items 1 to 4. [Additional note 6] The slices of the tomographic image can be axial, sagittal, or coronal. Item 6. An image processing device according to item 5. [Additional note 7] The processor receives a designation of the slab thickness as the thickness of the tomographic image, and generates the tomographic image by weighting according to the slab thickness. Item 7. The image processing device according to item 5 or 6. [Additional note 8] When the body axis direction of the subject is the Z axis direction, the width direction of the cross section perpendicular to the body axis direction is the X axis direction, and the height direction is the Y axis direction, the function includes a pixel value derivation function for deriving pixel values of an inclined section obtained by rotating an axial section of the slice image around the X axis, The processor generates a tilt image, which is a tomographic image of the tilted cross section, using the pixel value derivation function. 8. The image processing device according to any one of claims 1 to 7. [Additional note 9] In the case where a plurality of tilt images arranged in the Z-axis direction are generated, The pixel heights of multiple tilt images are aligned in the Y-axis direction Item 9. The image processing device according to item 8. [Additional Note 10] The processor receives a designation of a slab thickness as the thickness of the tilt image, and generates a tilt image by weighting according to the designated slab thickness. Item 9. The image processing device according to item 7 or 8. [Additional Note 11] 1. A method for operating an image processing device having a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, the method comprising: The processor Acquire multiple slice images, Generates a tomographic image representing a specified cross section using a function that uses pixel values of multiple slice images as parameters. A method for operating an image processing device. [Additional Note 12] An operating program for an image processing device including a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, the operating program comprising: acquiring multiple slice images; A processor is caused to execute a process including generating a tomographic image representing a specified cross section using a function having pixel values of a plurality of slice images as parameters. An operating program for an image processing device.

[0132] In this specification, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0133] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0134] 11 CT device 12 Image DB 13 Image display devices 16 Mounting stand 17 Console 18 Gantry 18A opening 19 Bed Device 19A Top plate 21 Radiation source 22 Detector 23 frames 24 Irradiation field limiter 26 High voltage generator 27 Mounting control unit 31 Display 32 Input Devices 33 Storage 34 Communications Department 36 processors 36A Control Unit 36B Image processing unit 37 Application Programs DT Tilt Image Fdt Pixel value derivation function Fmpr pixel value derivation function GF1 MPR image generation function GF2 tilt image generation function H. Subject Mp, Mp(AX), Mp(SAG), Mp(COR) MPR image P, Pt pixels PD projection data PS pixel spacing SI slice interval SL slice image SL_ISO Isotropic slice image SL SLP point Sb point Se point VD_ISO Isotropic 3D image VOL Slice volume W weighting factor rb, re, qb, qe weighting coefficients

Claims

1. An image processing device including a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, The processor: acquiring a plurality of said slice images; A tomographic image representing a specified cross section is generated using a function that uses pixel values of the plurality of slice images as parameters. Image processing device.

2. When the tomography imaging apparatus outputs a plurality of slice images during imaging, The processor: Using the plurality of slice images, a process of generating the tomographic image is started during the imaging. The image processing device according to claim 1 .

3. The function is generated according to imaging conditions of the tomographic imaging apparatus, the imaging conditions including at least the slice interval of the slice images. The image processing device according to claim 1 .

4. The processor: Before the tomographic imaging apparatus starts imaging, the imaging conditions are acquired and the function is created. The image processing device according to claim 3 .

5. When the body axis direction of the subject is defined as the Z-axis direction, and two directions defining a cross section perpendicular to the body axis direction are defined as the X-axis direction and the Y-axis direction, the function includes an isotropy data derivation function that derives isotropy data as pixel values of pixels whose resolutions are isotropized in the X-axis direction, the Y-axis direction, and the Z-axis direction; The processor generates the tomographic image based on the isotropized data. The image processing device according to claim 1 .

6. The cross section of the tomographic image is one of an axial cross section, a sagittal cross section, and a coronal cross section. The image processing device according to claim 5 .

7. The processor receives a designation of a slab thickness as the thickness of the tomographic image, and generates the tomographic image by performing weighting according to the slab thickness. The image processing device according to claim 5 .

8. When the body axis direction of the subject is defined as the Z-axis direction, the width direction of a cross section perpendicular to the body axis direction is defined as the X-axis direction, and the height direction is defined as the Y-axis direction, the function includes a pixel value derivation function that derives pixel values of an inclined cross section obtained by rotating the axial cross section of the slice image around an X axis, The processor generates a tilt image, which is the tomographic image of the tilted cross section, using the pixel value derivation function. The image processing device according to claim 1 .

9. In the case where a plurality of tilt images arranged in the Z-axis direction are generated, The heights of the pixels of the plurality of tilt images in the Y-axis direction are uniform. The image processing device according to claim 8 .

10. The processor receives a designation of a slab thickness as the thickness of the tilt image, and generates the tilt image by performing weighting according to the designated slab thickness. The image processing device according to claim 8 .

11. 1. A method for operating an image processing device having a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, the method comprising: The processor: acquiring a plurality of said slice images; A tomographic image representing a specified cross section is generated using a function that uses pixel values of the plurality of slice images as parameters. A method for operating an image processing device.

12. An operating program for an image processing device including a processor that performs image processing on a plurality of slice images that are output by a tomography device and represent axial cross sections perpendicular to a body axis of a subject, the operating program comprising: acquiring a plurality of said slice images; and causing the processor to execute a process including generating a tomographic image representing a specified cross section using a function having pixel values of the plurality of slice images as parameters. An operating program for an image processing device.

Images