JP2016154839A - X-ray ct apparatus and image processing device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an X-ray CT apparatus which can determine presence/absence of substances different from an assumed substance, and an image processing device.SOLUTION: According to an embodiment, an X-ray CT (Computed Tomography) apparatus comprises an acquisition part, a first generation part, a second generation part, a reconstruction part, a first comparison part and a first notification part. The acquisition part acquires projection data on the basis of spectrum showing an X-ray amount for each energy of a radiation having passed through a subject detected by a detector. The first generation part generates a first density image which is a density image of each of the plurality of substances selected as the substance existing in the subject, using the projection data. The second generation part generates a monochromatic image of a specific energy, using the first density image. The reconstruction part reconstructs the projection data corresponding to the specific energy to generate a reconstructed image. The first comparison part compares pixel values of the monochromatic image and the reconstructed image to each other. The first notification part notifies a result of the comparison performed by the first comparison part.SELECTED DRAWING: Figure 5

Description

  Embodiments described herein relate generally to an X-ray CT apparatus and an image processing apparatus.

  In recent years, development of silicon-based photomultipliers has become active, and radiation detection apparatuses such as X-ray CT (Computed Tomography) apparatuses using photomultipliers have been developed. In the X-ray CT apparatus, X-rays transmitted through the subject are detected, and a cross-sectional image (reconstructed image) of the subject having a CT value corresponding to the attenuation rate of the X-ray as a pixel value is reconstructed. Specifically, since the attenuation rate of X-rays when X-rays pass through a substance (subject) varies depending on the type of substance, such as bone or water, the X-ray intensity passing through the subject is Based on the projection data detected by the detector while circling the subject, the attenuation rate is reconstructed in the cross section of the subject, thereby visualizing the internal structure of the subject.

  Furthermore, in recent years, an X-ray CT apparatus that calculates the density of each substance from projection data has been put into practical use in order to grasp the inside of the subject in more detail. In order to calculate such density, the dual material CT device is used to switch the tube voltage of the X-ray tube to two types and project it twice because of the nature that the attenuation rate varies depending on the energy and the material density. There is a method for obtaining density images of two substances. X-rays contain photons of various energies, but the energy distribution is different when the tube voltage is different. In the above-described method, density images of two substances are obtained by the following two routes.

(1) Two types of tube voltage projection data → Two types of tube voltage attenuation rate images → Two substance density images (2) Two types of tube voltage projection data → X-ray transmission distances of two types of materials → 2 Material density image

  Here, the attenuation coefficient is an image (reconstructed image) having a pixel value of a linear attenuation coefficient that is an attenuation ratio per unit length of X-rays or a CT value that is a relative value of a linear attenuation coefficient such as air or water. An image having the density of the substance as a pixel value is referred to as a density image. In addition, since the linear attenuation coefficient is uniquely determined by the type, density, and photon energy of the material, it is possible to synthesize an attenuation rate image that assumes a specific energy from the obtained density of the two types of materials. Called an image. The contrast of the material of interest can be improved by adjusting the energy for synthesizing the monochrome image.

  However, in the above method, when there is a substance different from the two kinds of assumed substances, an error in the density of the obtained substance becomes large, but in the obtained density image and monochrome image, the occurrence of the error, that is, There is a problem that the existence of different substances cannot be determined.

JP 2011-172803 A

  The present invention has been made in view of the above, and an object of the present invention is to provide an X-ray CT apparatus and an image processing apparatus capable of determining the presence or absence of a substance different from an assumed substance.

  The X-ray CT apparatus of the embodiment includes an acquisition unit, a first generation unit, a second generation unit, a reconstruction unit, a first comparison unit, and a first notification unit. The acquisition unit acquires projection data based on a spectrum indicating the amount of X-rays for each energy of radiation that has passed through the subject detected by the detector. The first generation unit generates a first density image that is a density image of each of a plurality of substances selected as substances existing in the subject from the projection data. The second generation unit generates a monochrome image having a specific energy from the first density image. The reconstruction unit reconstructs projection data corresponding to specific energy to generate a reconstructed image. The first comparison unit compares the pixel values of the monochrome image and the reconstructed image. The first notification unit notifies the comparison result by the first comparison unit.

1 is an overall configuration diagram of an X-ray inspection apparatus according to a first embodiment. It is a figure explaining a sinogram. It is a figure which shows an example of the spectrum of the energy detected by the specific channel. It is a figure which shows the example of a subject sinogram. It is a figure which shows an example of the block configuration of the image processing part of 1st Embodiment. It is a figure which shows the example of the characteristic of the linear attenuation coefficient with respect to the energy of X-ray | X_line. It is a figure which shows the structural example of a substance specific priority table. 3 is a flowchart illustrating an example of an operation of an image processing unit according to the first embodiment. It is a figure which shows an example of the block configuration of the image process part of the modification of 1st Embodiment. It is a figure which shows an example of the block configuration of the 1st production | generation part of the image processing part of 2nd Embodiment. It is a figure explaining the relationship between projection data and a linear attenuation coefficient. It is a figure explaining the contribution of a pixel. It is a flowchart which shows an example of operation | movement of the image process part of 2nd Embodiment.

  Hereinafter, an X-ray CT apparatus and an image processing apparatus according to an embodiment of the present invention will be described in detail with reference to the drawings. Moreover, in the following drawings, the same code | symbol is attached | subjected to the same part. However, since the drawings are schematic, a specific configuration should be determined in consideration of the following description.

(First embodiment)
FIG. 1 is an overall configuration diagram of the X-ray inspection apparatus according to the first embodiment. An overview of the overall configuration of the X-ray inspection apparatus 1 will be described with reference to FIG.

  As shown in FIG. 1, an X-ray inspection apparatus 1 that is an example of an X-ray CT apparatus transmits X-rays that are an example of radiation to a subject 40 and detects it as a spectrum indicated by the number of photons for each energy. Thus, a spectral CT device, a photon counting CT device, or the like that obtains a cross-sectional image of the projected cross-section 41 of the subject 40 on the measurement range 42. As shown in FIG. 1, the X-ray inspection apparatus 1 includes a gantry device 10, a bed device 20, and a console device 30 (image processing device).

  The gantry device 10 is a device that irradiates and transmits the subject 40 with X-rays and detects the above-described spectrum. The gantry device 10 includes an X-ray tube 11, a rotating frame 12, a detector 13, an irradiation control unit 14, a gantry driving unit 15, and a data collection unit 16.

  The X-ray tube 11 is a vacuum tube that generates X-rays with a high voltage supplied from the irradiation control unit 14, and irradiates the subject 40 with the X-ray beam 11 a. The spectrum indicated by the number of photons for each X-ray energy irradiated from the X-ray tube 11 is determined by the tube voltage of the X-ray tube 11, the tube current, and the type of target (for example, tungsten) used for the radiation source. . When the X-rays irradiated from the X-ray tube 11 pass through the subject 40, the energy of the X-rays is attenuated according to the state of the substance constituting the subject 40 (the number of photons of each energy of the X-rays). ), And the number of photons of each energy is reduced to change the spectrum.

  The rotating frame 12 is a ring-shaped support member that supports the X-ray tube 11 and the detector 13 so as to face each other with the subject 40 interposed therebetween.

  The detector 13 is a detector that detects, for each channel, the number of photons for each energy of the X-ray beam 11 b that is an X-ray irradiated from the X-ray tube 11 and transmitted through the subject 40. That is, the detector 13 detects, for each channel, a spectrum indicated by the number of photons for each X-ray energy as shown in FIG. 3 described later. Here, it is assumed that the spectrum detected by the detector 13 may be hereinafter referred to as “detected spectrum”. As shown in FIG. 1, the detector 13 detects a spectrum for each view while rotating in the circumferential direction of the rotating frame 12. Here, the view means an angle when a spectrum is detected by the detector 13 at every predetermined angle out of 360 degrees in the circumferential direction of the rotating frame 12. That is, when the detector 13 detects a spectrum every 0.5 °, it is assumed that 1 view = 0.5 °. The detector 13 has a detection element array in which a plurality of detection elements are arranged in the channel direction (circumferential direction of the rotating frame 12) in the body axis direction (slice direction) of the subject 40 (Z-axis direction shown in FIG. 1). It is a two-dimensional array type detector arranged in a plurality of rows along. Note that the detection element array of the detector 13 may be configured by a combination of a photocounting type detection element and an integration type detection element. A plurality of sets of the X-ray tube 11 and the detector 13 may be installed.

  The irradiation control unit 14 is a device that generates a high voltage and supplies the generated high voltage to the X-ray tube 11.

  The gantry driving unit 15 is a device that rotationally drives the rotary frame 12 to rotationally drive the X-ray tube 11 and the detector 13 on a circular orbit around the subject 40. The gantry driving unit 15 is not limited to a configuration that rotationally drives both the X-ray tube 11 and the detector 13. For example, the detector 13 may be configured such that detection elements are arranged for one turn in the circumferential direction of the rotating frame 12, and the gantry driving unit 15 may be configured to rotate only the X-ray tube 11. .

  The data collection unit 16 is a device that collects spectrum data indicated by the number of photons for each energy detected for each channel by the detector 13. Then, the data collection unit 16 performs amplification processing or A / D conversion processing on each collected spectrum data and outputs the result to the console device 30. For example, the data collection unit 16 converts the data obtained by performing the above-described amplification processing or A / D conversion processing on the collected spectrum data for each energy band (energy bin) of a predetermined width (hereinafter, simply “for each energy”). Is output to the console device 30 as a sinogram (subject sinogram).

  The couch device 20 is a device on which the subject 40 is placed, and includes a couch driving device 21 and a top plate 22 as shown in FIG.

  The top plate 22 is a bed such as a bed on which the subject 40 is placed. The couch driving device 21 is a device that moves the subject 40 into the rotary frame 12 by moving the subject 40 placed on the top plate 22 in the body axis direction (Z-axis direction).

  The console device 30 is a device that receives an operation on the X-ray inspection apparatus 1 by an operator and reconstructs a cross-sectional image (restored image) from data collected by the gantry device 10. As shown in FIG. 1, the console device 30 includes an input device 31, a display device 32, a scan control unit 33, an image processing unit 34, an image storage unit 35, and a system control unit 36. .

  The input device 31 is a device for an operator who operates the X-ray inspection apparatus 1 to input various instructions, and is a device that transmits various commands input by the operation to the system control unit 36. The input device 31 is, for example, a mouse, a keyboard, a button, a trackball, or a joystick.

  The display device 32 displays a GUI (Graphical User Interface) for accepting an operation instruction from the operator via the input device 31, or displays a restored image (cross-sectional image) stored in the image storage unit 35 described later. It is. The display device 32 is, for example, a CRT (Cathode Ray Tube) display, an LCD (Liquid Crystal Display), an organic EL (Organic Electro-Luminescence) display, or the like.

  The scan control unit 33 is a processing unit that controls operations of the irradiation control unit 14, the gantry driving unit 15, the data collection unit 16, and the bed driving device 21. Specifically, the scan control unit 33 causes the X-ray scan to be executed by continuously or intermittently emitting X-rays from the X-ray tube 11 while rotating the rotary frame 12. For example, the scan control unit 33 performs helical scanning in which imaging is performed by continuously rotating the rotating frame 12 while moving the top plate 22, or imaging is performed by rotating the rotating frame 12 once around the subject 40, and then Then, the top plate 22 on which the subject 40 is placed is shifted by a predetermined amount, and the rotating frame 12 is rotated once again to perform non-helical scanning for imaging.

  The image processing unit 34 is a processing unit that reconstructs a cross-sectional image of the subject from the sinogram received from the data collection unit 16. Details of the block configuration and operation of the image processing unit 34 will be described later.

  The image storage unit 35 is a functional unit that stores a cross-sectional image (restored image) generated by the reconstruction processing by the image processing unit 34. The image storage unit 35 is, for example, a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk.

  The system control unit 36 is a processing unit that controls the entire X-ray inspection apparatus 1 by controlling operations of the gantry device 10, the couch device 20, and the console device 30. Specifically, the system control unit 36 controls the scan control unit 33 to control the spectrum data collection operation of the subject 40 by the gantry device 10 and the couch device 20. In addition, the system control unit 36 controls the image processing unit 34 to control the cross-sectional image reconstruction process. Further, the system control unit 36 reads the cross-sectional image from the image storage unit 35 and causes the display device 32 to display the cross-sectional image.

  In addition, although the sinogram for every predetermined energy band shall be produced | generated from the data of the collected spectrum by the data collection part 16, it is not limited to this. That is, the data collection unit 16 may transmit collected spectrum data to the image processing unit 34, and the image processing unit 34 may generate a sinogram for each energy band having a predetermined width from the spectrum data.

  FIG. 2 is a diagram illustrating a sinogram. FIG. 3 is a diagram illustrating an example of a spectrum of energy detected in a specific channel. FIG. 4 is a diagram illustrating an example of a subject sinogram. A spectrum detected by the sinogram and the detector 13 will be described with reference to FIGS.

  The data collection unit 16 of the gantry device 10 generates a sinogram from the spectrum indicated by the number of photons for each energy as shown in FIG. Here, the sinogram is data in which measured values for each view of the X-ray tube 11 and for each channel of the detector 13 are arranged as pixel values, like a sinogram 1001 shown in FIG. In the following description, it is assumed that a measured value for each view and for each channel is regarded as a pixel value, and a sinogram is handled as an image. Among these, a sinogram generated from a spectrum (see FIG. 3) in which X-rays irradiated from the X-ray tube 11 pass through the subject 40 and are detected by the detector 13 is referred to as a subject sinogram. A sinogram generated from a spectrum detected by the detector 13 with X-rays passing through only air without placing the subject 40 is referred to as an air sinogram. The pixel values of the subject sinogram and the air sinogram are, for example, the number of photons detected as a measurement value by the detector 13.

  In addition, since the detector 13 detects the spectrum indicated by the number of photons for each energy for each view and for each channel, the data acquisition unit 16 performs the X-ray scan for one round of the X-ray tube 11 to display the spectrum. As shown in FIG. 4, a subject sinogram 1011 for each energy can be obtained. In the example shown in FIG. 4, the spectrum is divided into four energy bands, and four object sinograms 1011a to 1011d are obtained for each energy band. In addition, although the example divided | segmented into four energy bands was shown in FIG. 4, it is not limited to this division | segmentation number. Further, from the viewpoint of improving the S / N ratio of the restored image (attenuation rate image) and the density image described later, it is desirable that the energy band used for reconstruction and estimation of the material density has a uniform number of photons. There is a case. In order to realize this, for example, there are the following two methods.

(Method 1) At the stage of generating a sinogram, the energy band is divided so that the number of photons is uniform.
(Method 2) First, it is finely divided (for example, divided every 1 [keV]), and the number of photons is added at the stage of reconstruction or estimation of material density.

  FIG. 5 is a diagram illustrating an example of a block configuration of the image processing unit according to the first embodiment. FIG. 6 is a diagram illustrating an example of characteristics of a linear attenuation coefficient with respect to X-ray energy. FIG. 7 is a diagram illustrating a configuration example of the substance identification priority table. The block configuration and the operation of each block of the image processing unit 34 of the present embodiment will be described with reference to FIGS.

  As shown in FIG. 5, the image processing unit 34 includes a projection data acquisition unit 341 (acquisition unit), a first generation unit 342, a second generation unit 343, a reconstruction unit 344, and a difference determination unit 345 (first 1 comparison unit, first determination unit), and change unit 346.

  The projection data acquisition unit 341 is a functional unit that receives and acquires a subject sinogram that is a sinogram of the subject 40 from the data collection unit 16 as projection data. Here, the subject sinogram acquired by the projection data acquisition unit 341 is a sinogram (sinogram for each energy) generated for each energy by the data collection unit 16 as described above.

The first generation unit 342 is a functional unit that sets a substance that may exist in the subject 40 and generates a density image for each set substance using the subject sinogram received from the projection data acquisition unit 341. is there. Hereinafter, the density in the density image will be described as indicating the mass of a specific substance contained per unit volume (for example, [mg / cm ³ ] is used as the unit). As a substance to be set, when the subject 40 is a human body or an animal, water, bone, fat, and a contrast agent are injected into the subject 40, and the contrast agent, calcium, thrombus, and blood vessels in the plaque portion of the blood vessel It is envisaged that the fibers of the walls, etc., as well as metals in the body such as stents.

  First, the characteristic of the linear attenuation coefficient with respect to the X-ray energy of a substance will be described with reference to FIG. In FIG. 6, as an example of the characteristic of the linear attenuation coefficient with respect to the X-ray energy, the characteristics of iodine and calcium, which are a kind of contrast agent, and water are shown. Specifically, in FIG. 6, the density of iodine is 20 [mg / cm 3], the density of calcium is 100 [mg / cm 3], and the density of water is 100 [%]. ] Is shown. As shown in FIG. 6, as the energy increases, the linear attenuation coefficient becomes smaller continuously in principle for any substance. However, the linear attenuation coefficient increases discontinuously when it exceeds the energy at which the photoelectric effect occurs, such as the K absorption edge, as in the characteristics of iodine in FIG. The energy of the K absorption edge varies depending on the element. In the case of iodine, it is about 33 [keV] as shown in FIG. Thus, the characteristic of the linear attenuation coefficient with respect to energy differs depending on the substance.

As described below, the first generation unit 342 calculates the density for each set substance by using the above-described characteristics of the linear attenuation coefficient with respect to the X-ray energy of the substance, and generates a density image. The linear attenuation coefficient of the coordinates (x, y) of the attenuation rate image (restored image, reconstructed image) of the energy E of X-ray is μ (x, y, E), and the coordinate (x, y) of the density image of the substance M Ρ (x, y, M), the linear attenuation coefficient when the substance M of energy E is 100 [%] in density (μ) _M (E), and the density when the substance M is 100 [%] in density Is (ρ) _M , the linear attenuation coefficient μ (x, y, E) is expressed by the following equation (1).

The linear attenuation coefficient (μ) _M (E) and the density (ρ) _M in Equation (1) are known values as the theoretical values of the substance M. Further, (μ) _M (E) / (ρ) _M in the formula (1) corresponds to a so-called mass attenuation coefficient. Specifically, the first generation unit 342 first sets a specific energy band, receives an object sinogram of the set energy band from the projection data acquisition unit 341, and calculates an attenuation rate sinogram from the received object sinogram. Generate. Specifically, the first generation unit 342 calculates an attenuation rate for each view and for each channel in the subject sinogram of the set energy band, and generates an attenuation rate sinogram using the attenuation rate as a pixel value. As the energy band to be set, for example, 30 to 32 [keV], 34 to 36 [keV], 60 to 62 [keV] or the like is selected. In addition, the energy band to be set may be a single energy, but if the energy band is a group of a plurality of continuous energies, the number of photons increases, so that the reconstruction accuracy can be improved. As a calculation method of the attenuation rate, when the number of photons of X-rays emitted from the X-ray tube 11 is known, attenuation rate = (channel from X-ray tube 11 and its view) for each view and for each channel. The attenuation rate is calculated as: (number of photons irradiated in step) / (number of photons transmitted through the subject 40 and detected by the detector 13 in the channel and the view). On the other hand, when the number of photons of X-rays emitted from the X-ray tube 11 is unknown, the first generation unit 342 inputs the spectrum detected by the detector 13 without arranging the subject 40 in advance, An air sinogram is generated from the spectrum. Then, the attenuation rate is calculated as attenuation rate = (number of photons in the air sinogram (pixel value)) / (number of photons in the subject sinogram (pixel value)) for each view and for each channel. When the number of photons when the subject 40 is arranged is A, and the number of photons when the subject 40 is not arranged is B, for example, log (B / A) is calculated and this is expressed in the attenuation rate sinogram. It may be a pixel value (attenuation rate).

  Next, the first generation unit 342 reconstructs the generated attenuation rate sinogram by a well-known technique such as a back projection method or a successive approximation method, and obtains a linear attenuation coefficient μ (x, y, E). . Since the line attenuation coefficient varies depending on the type and density of the substance that transmits X-rays, the structure inside the subject 40 can be recognized by visualizing the distribution with a reconstructed image.

  As described above, when the back projection method is adopted as the reconstruction method, first, the measurement values detected by the detector 13 in a certain view are written in the entire image to be reconstructed, and this is performed in all the views. In this case, since the value remains even where the subject 40 does not exist, a blurred image is obtained. However, the edge is emphasized to cancel out the blur by enhancing the edge by a filter process that reduces the artifact by enhancing the edge. Thus, a clear reconstructed image is obtained. The filter processing method may be either a method of performing Fourier transform and executing on the frequency domain, or a method of performing convolution (convolution operation) in real space. A method of correcting a reconstructed image using a filter in this way is particularly called a filter-corrected back projection method (FBP (Filtered Back Projection) method).

  When adopting the successive approximation method as a reconstruction method, first, a provisional image is prepared in advance and X-rays are irradiated in each view. When the pixel value of the temporary image is smaller than the measured value actually detected by the detector 13, the pixel value of the temporary image is increased. Conversely, when the pixel value of the temporary image is larger than the measured value actually detected by the detector 13, the pixel value of the temporary image is decreased. By repeating this operation, the reconstructed image is obtained by changing the pixel value of the temporary image so as to be equal to the pixel value of the true cross-sectional image. As the successive approximation method, there are various methods such as an OS-EM (Order Subset Expansion Maximization) method and an ML-EM (Maximum Likelihood Extraction Maximization) method.

  Next, the first generation unit 342 uses the calculated linear attenuation coefficient μ (x, y, E), and the simultaneous equations in which only the density ρ (x, y, M) is unknown according to the above equation (1). And the density ρ (x, y, M) is calculated as a solution for each coordinate (x, y) by making the set number of energy bands equal to the set number of substances. Then, the first generation unit 342 generates a density image in which the calculated density ρ (x, y, M) is arranged as a pixel value for each coordinate (x, y). The first generation unit 342 sends the generated density image to the second generation unit 343.

In general, since the obtained linear attenuation coefficient μ (x, y, E) includes an error, the number of energy bands to be set is made larger than the number of substances to be set to increase the number of equations, By using the least square method or the like, an error in the density ρ (x, y, M) can be reduced. Moreover, since the linear attenuation coefficient μ (x, y, E) is an average value in the set energy band, the linear attenuation coefficient (μ) _M (E) is also an average value in the energy band.

  If a substance that does not actually exist in the subject 40 is set as the substance set by the first generation unit 342, the density of the nonexistent substance is calculated as 0, and the density of the existing substance is calculated correctly. Is ideal, but in reality, an error also occurs in the calculated density due to a measurement error and a calculation error. In particular, as the number of unknown substances increases, the density error increases. Therefore, first, it is possible to obtain the density of main substances with high accuracy by excluding the trace amount of substances that are unlikely to exist or even if they exist, by minimizing the number of substances. it can.

The second generation unit 343 substitutes the density ρ of the density image received from the first generation unit 342 into the right side of the above-described formula (1), and specifies specific energy (hereinafter sometimes referred to as “difference comparison energy”). And the linear attenuation coefficient μ (x, y, E) of the difference comparison energy is calculated using (μ) _M (E) / (ρ) _M of the set difference comparison energy. Then, the second generation unit 343 generates a monochrome image in which the calculated line attenuation coefficient μ (x, y, E) is arranged as a pixel value for each coordinate (x, y). The second generation unit 343 sends the generated monochrome image to the difference determination unit 345.

  Note that the difference comparison energy set by the second generation unit 343 may match the energy set by the first generation unit 342.

  The reconstruction unit 344 is a functional unit that reconstructs the subject sinogram received from the projection data acquisition unit 341 and generates a reconstructed image. Specifically, the reconstruction unit 344 first receives the subject sinogram of the difference comparison energy set by the second generation unit 343 from the projection data acquisition unit 341, and generates the attenuation rate sinogram from the received subject sinogram. To do. The generation method of the attenuation rate sinogram by the reconstruction unit 344 is the same as the generation method of the attenuation rate sinogram by the first generation unit 342 described above.

  Then, the reconstruction unit 344 reconstructs the generated attenuation rate sinogram by a well-known technique such as a back projection method or a successive approximation method, and generates a reconstructed image. The reconstruction unit 344 sends the generated reconstruction image to the difference determination unit 345. Since the reconstructed image generated by the reconstructing unit 344 is generated based on the subject sinogram of the differential comparison energy that is specific energy, that is, the subject sinogram based on the energy having a small number of photons, it may include noise. However, the line attenuation coefficient that is the pixel value can be regarded as a correct value.

  The difference determination unit 345 obtains a difference (first difference) that is a comparison result between the monochrome image generated by the second generation unit 343 and the reconstructed image generated by the reconstruction unit 344, and determines the difference. It is a functional part to do.

  When the density is correctly calculated by the first generation unit 342, a monochrome image of the difference comparison energy generated by the second generation unit 343 using the density, and the difference comparison energy generated by the reconstruction unit 344 The difference in pixel value from the reconstructed image is almost zero. On the other hand, when the density calculated by the first generation unit 342 is incorrect, the monochrome image and the reconstructed image are different images and a difference is generated.

  Therefore, the difference determination unit 345 generates the first generation unit 342 when the sum of absolute values of differences between the pixel values of the entire monochrome image and the reconstructed image is equal to or less than a predetermined value (first predetermined value). The density of the obtained density image is determined to be sufficiently high. On the other hand, if the sum of the absolute values of the differences is larger than the predetermined value, the difference determination unit 345 determines that the density accuracy of the density image is insufficient, and obtains the density again by the first generation unit 342 (hereinafter referred to as “the density image”). , Reprocessing information including information indicating that it is necessary) is generated and sent to the changing unit 346.

  Although the difference determination unit 345 calculates the sum of absolute values of pixel values, the present invention is not limited to this. For example, another error measure such as the sum of squares of pixel values is used. May be.

  Further, the difference determination unit 345 calculates the difference between the pixel values of the entire monochrome image and the reconstructed image. However, the present invention is not limited to this, and there is a region of interest such as a blood vessel in the image. In this case, a difference may be obtained for the pixel value in the attention area.

  Further, the difference determination unit 345 obtains a difference for each area or pixel of the monochrome image and the reconstructed image, and includes in the reprocessing information whether or not it is necessary to reprocess each area or each pixel. Also good.

  The comparison result (for example, difference information) between the monochrome image and the reconstructed image obtained by the difference determination unit 345 is displayed on the display device 32 (an example of the first notification unit), for example. Also good. In this case, the method of notifying the comparison result is not limited to displaying on the display device 32. For example, the comparison result may be notified by voice from an unillustrated audio output device (an example of a first notification unit), and the comparison result is indicated by lighting or blinking of a lamp of a lamp display device (an example of a first notification unit). It is good also as what notifies.

  The changing unit 346 is a functional unit that changes the material for calculating the density or the energy band for obtaining the linear attenuation coefficient μ in accordance with the reprocessing information received from the difference determining unit 345. Specifically, the changing unit 346 generates change information for changing the material for calculating the density or the setting of the energy band for obtaining the linear attenuation coefficient μ, and sends the change information to the first generating unit 342. The first generation unit 342 changes the material setting or the energy band setting for obtaining the linear attenuation coefficient μ according to the change information received from the changing unit 346, and calculates the density of each material after the setting change again. . The second generation unit 343 generates a monochrome image again from the density image generated by the first generation unit 342. Then, the difference determination unit 345 obtains a difference between the monochrome image generated again by the second generation unit 343 and the reconstructed image generated by the reconstruction unit 344, and determines the difference. The series of operations described above are repeated while changing the setting of the substance and energy band by the changing unit 346 until it is determined that the density accuracy is sufficiently high, or until a predetermined number of times is reached.

  For example, assuming that the thrombus or fat does not exist in the plaque portion and the density has been calculated by setting only another substance by the first generation unit 342, the changing unit 346 previously calculates the thrombus or fat. Is generated as a substance whose density is to be calculated. In addition, for example, if it is assumed that no metal exists in advance, the changing unit 346 generates change information for changing the setting of the metal as a substance for calculating the density. In addition, the change unit 346 is, for example, a change for changing the setting to an energy band in which the relative magnitude relationship of the linear attenuation coefficient of the substance set by the first generation unit 342 is different in order to improve the density calculation accuracy. Generate information. The change of the energy band of the linear attenuation coefficient μ by the changing unit 346 may be performed according to a predetermined pattern, for example.

  Note that when the changing unit 346 additionally sets a substance whose density is calculated according to the reprocessing information received from the difference determination unit 345, for example, the priority order indicated by the substance specifying priority table 2000 (priority information) in FIG. According to the above, additional substances may be set. The substance specification priority table 2000 may be stored in advance in a storage unit such as the image storage unit 35 (see FIG. 1), for example. For example, the first generation unit 342 refers to the substance identification priority table 2000 and assumes that substances assumed as substances contained in the subject 40 are water and iodine having priority levels 1 and 2. Suppose that the density image is generated by setting, but the difference determination unit 345 determines that the density accuracy is insufficient. In this case, the changing unit 346 generates change information for additional setting by referring to the substance identification priority table 2000, assuming that the next highest priority calcium is included in the subject 40, and 1 is sent to the generation unit 342. According to the change information, the first generation unit 342 assumes that the substances included in the subject 40 are water, iodine, and calcium, and calculates the density of each substance again. In the above description, the changing unit 346 has described the operation of additionally setting the substance whose density is to be calculated. Similarly, it is also possible to refer to the substance specifying priority table 2000 or the like and delete and set a substance having a low priority. Good. Further, as shown in FIG. 7, the substance specification priority table 2000 is in a table format, but may be information in any format as long as the information associates the substance with the priority.

  Moreover, the change of the setting of the energy band which calculates | requires the substance which calculates the density by the change part 346, or the linear attenuation coefficient (micro | micron | mu) is good also as an operator with respect to the input device 31 is good.

  In addition, when the reprocessing information received from the difference determination unit 345 includes information indicating whether or not reprocessing is required for each part of the image or for each pixel, the changing unit 346 needs to be reprocessed. Alternatively, change information for calculating the density again may be generated for each pixel in the same manner as described above.

  Further, although the difference comparison energy is set by the second generation unit 343, the set difference comparison energy is not limited to one. That is, the second generation unit 343 sets N (N> 1) difference comparison energies, the second generation unit 343 generates N monochrome images, and the reconstruction unit 344 A reconstructed image may be generated. Thereby, the difference determination unit 345 can use the difference of each of the N sets of the same difference comparison energy, and can confirm the density accuracy in detail with more energy.

  The second generation unit 343 generates a monochrome image while continuously switching the magnitude of the difference comparison energy, and the reconstruction unit 344 generates a reconstructed image while continuously switching the difference energy, The difference determination unit 345 may obtain a difference between the monochrome image and the reconstructed image for each difference comparison energy that is continuously switched. In this case, when the difference increases discontinuously at a certain energy, there is a high possibility that a substance having the energy at the K absorption edge is unexpectedly present, so the changing unit 346 is used to additionally set the substance. The change information is generated, and the first generation unit 342 may additionally set the substance and calculate the density again. Here, the case where the difference increases discontinuously at a certain energy may be, for example, a case where the amount of change in the difference exceeds a predetermined value (second predetermined value). Since the K absorption edge is known by the substance, there is a high possibility that a substance specified when the K absorption edge is detected is included in the subject 40, so that the density of the substance can be obtained with high accuracy. Become.

  Further, the projection data acquisition unit 341, the first generation unit 342, the second generation unit 343, the reconstruction unit 344, the difference determination unit 345, and the change unit 346 shown in FIG. 5 conceptually show functions. However, it is not limited to such a configuration. For example, a plurality of functional units illustrated as independent functional units in FIG. 5 may be configured as one functional unit. On the other hand, the function of one functional unit in FIG. 5 may be divided into a plurality of units and configured as a plurality of functional units.

  FIG. 8 is a flowchart illustrating an example of the operation of the image processing unit according to the first embodiment. The overall operation of the image processing by the image processing unit 34 of the first embodiment will be described with reference to FIG.

<Step S11>
The projection data acquisition unit 341 receives and acquires a subject sinogram that is a sinogram of the subject 40 generated by the data collection unit 16 as projection data. Then, the process proceeds to step S12.

<Step S12>
The first generation unit 342 sets a specific energy band, receives an object sinogram of the set energy band from the projection data acquisition unit 341, and generates an attenuation rate sinogram from the received object sinogram. Next, the first generation unit 342 reconstructs the generated attenuation rate sinogram by a well-known technique such as a back projection method or a successive approximation method, and obtains a linear attenuation coefficient μ (x, y, E). . Next, the first generation unit 342 uses the calculated linear attenuation coefficient μ (x, y, E), and the simultaneous equations in which only the density ρ (x, y, M) is unknown according to the above equation (1). And the density ρ (x, y, M) is calculated as a solution for each coordinate (x, y) by making the set number of energy bands equal to the set number of substances. Then, the first generation unit 342 generates a density image in which the calculated density ρ (x, y, M) is arranged as a pixel value for each coordinate (x, y). The first generation unit 342 sends the generated density image to the second generation unit 343. Then, the process proceeds to step S13.

<Step S13>
The second generation unit 343 assigns the density ρ of the density image received from the first generation unit 342 to the right side of the above equation (1), sets the difference comparison energy, and sets the difference comparison energy (μ). _M (E) / (ρ) Using _M , the linear attenuation coefficient μ (x, y, E) of the difference comparison energy is calculated. Then, the second generation unit 343 generates a monochrome image in which the calculated line attenuation coefficient μ (x, y, E) is arranged as a pixel value for each coordinate (x, y). The second generation unit 343 sends the generated monochrome image to the difference determination unit 345.

  The reconstruction unit 344 receives the subject sinogram of the difference comparison energy set by the second generation unit 343 from the projection data acquisition unit 341, and generates an attenuation rate sinogram from the received subject sinogram. Then, the reconstruction unit 344 reconstructs the generated attenuation rate sinogram by a well-known technique such as a back projection method or a successive approximation method, and generates a reconstructed image. The reconstruction unit 344 sends the generated reconstruction image to the difference determination unit 345. Then, the process proceeds to step S14.

<Step S14>
The difference determination unit 345 obtains a difference between the monochrome image generated by the second generation unit 343 and the reconstructed image generated by the reconstruction unit 344, and determines the difference. For example, the difference determination unit 345 generates the first generation unit 342 when the sum of the absolute values of the differences between the pixel values of the entire monochrome image and the reconstructed image is equal to or less than a predetermined value (step S14: Yes). It is determined that the density of the obtained density image has sufficiently high accuracy, and the image processing ends. On the other hand, when the sum of the absolute values of the differences is larger than the predetermined value (step S14: No), the difference determination unit 345 determines that the density accuracy of the density image is insufficient, and the first generation unit 342 Reprocessing information including information indicating that reprocessing is necessary is generated and sent to the changing unit 346, and the process proceeds to step S15.

<Step S15>
The changing unit 346 changes the material for calculating the density or the energy band setting for obtaining the linear attenuation coefficient μ in accordance with the reprocessing information received from the difference determining unit 345. Specifically, the changing unit 346 generates change information for changing the material for calculating the density or the setting of the energy band for obtaining the linear attenuation coefficient μ, and sends the change information to the first generating unit 342. Then, the process returns to step S12.

  The series of operations in steps S12 to S15 described above are repeated while changing the substance and energy band settings by the changing unit 346 until it is determined that the density accuracy is sufficiently high (step S14). As described above, it may be repeated until the predetermined number of times is reached.

  As described above, the second generation unit 343 generates a monochromatic image by calculating the linear attenuation coefficient μ of the difference comparison energy that is specific energy, and the reconstruction unit 344 performs the subject sinogram of the difference comparison energy. Then, a reconstructed image in which the line attenuation coefficient that is a pixel value can be regarded as correct is generated, and the difference determination unit 345 determines a difference between the monochrome image and the reconstructed image, and matches the monochrome image and the reconstructed image. The degree is to be judged. As a result, it can be determined that the linear attenuation coefficient, which is a pixel value of a monochrome image having a large difference, is not correct, that is, the density of the density image is not accurately calculated, and the substance assumed to be included in the subject 40 Can determine the presence or absence of different substances. Further, when it is determined that the composition of the substance assumed to be included in the subject 40 is different, another substance is added or deleted, or the setting of the energy band for obtaining the linear attenuation coefficient μ is changed. The correct density image can be generated.

<Modification>
FIG. 9 is a diagram illustrating an example of a block configuration of an image processing unit according to a modification of the first embodiment. With reference to FIG. 9, the block configuration and the operation of each block of the image processing unit 34 a according to the modification of the present embodiment will be described focusing on differences from the image processing unit 34 of the first embodiment. In the first embodiment, when the difference between the monochrome image and the reconstructed image is larger than a predetermined value, the change unit 346 automatically calculates the density according to the reprocessing information of the difference determination unit 345, Or the operation | movement which produces | generates the change information for changing the setting of the energy band which calculates | requires the linear attenuation coefficient (micro | micron | mu) was demonstrated. In this modification, an operation in which an operator manually generates change information will be described. The configuration of the X-ray inspection apparatus according to this modification is a configuration in which the image processing unit 34 shown in FIG. 1 is replaced with an image processing unit 34a.

  As illustrated in FIG. 9, the image processing unit 34a includes a projection data acquisition unit 341, a first generation unit 342, a second generation unit 343, a reconstruction unit 344, and a difference calculation unit 345a (first calculation unit). And. Furthermore, the X-ray inspection apparatus according to this modification includes an input unit 311 and a display unit 321 (an example of a first notification unit). The operations of the projection data acquisition unit 341, the first generation unit 342, the second generation unit 343, and the reconstruction unit 344 of the image processing unit 34a are the projection data acquisition unit 341 of the image processing unit 34 illustrated in FIG. The operations are the same as those of the first generation unit 342, the second generation unit 343, and the reconstruction unit 344.

  The difference calculation unit 345 a is a functional unit that obtains a difference that is a comparison result between the monochrome image generated by the second generation unit 343 and the reconstructed image generated by the reconfiguration unit 344. For example, the difference calculation unit 345a obtains a difference between pixel values of each pixel constituting the monochrome image and the reconstructed image, generates a difference image having each difference as a pixel value, and transmits the difference image to the display unit 321.

  The display unit 321 is a functional unit that displays difference information (for example, a difference image) that is a comparison result between the monochrome image and the reconstructed image obtained by the difference calculation unit 345a. The display unit 321 is realized by the display device 32 illustrated in FIG.

  The input unit 311 changes the setting of the energy band in which the operator who has confirmed the difference information between the monochrome image displayed on the display unit 321 and the reconstructed image calculates the density or the linear attenuation coefficient μ. This is a functional unit for inputting operations. The input unit 311 transmits the change information input by the operation to the first generation unit 342. For example, the operator confirms the difference image displayed on the display unit 321, and manually inputs, via the input unit 311, a portion where the accuracy of density is to be increased, such as a portion where the difference is large in the region of interest. The input unit 311 transmits the operation input information to the first generation unit 342 as change information. The input unit 311 is realized by the input device 31 illustrated in FIG.

  As described above, the operator confirms the difference information between the monochrome image and the reconstructed image on the display unit 321 and manually inputs the change information via the input unit 311. Thus, the operator's idea can be reflected in the process of changing the setting of the energy band for obtaining the substance contained in the subject 40 or the linear attenuation coefficient μ, and the density accuracy can be improved in accordance with the operator's idea. Can be improved.

  The comparison result (for example, difference information) between the monochrome image and the reconstructed image obtained by the difference calculation unit 345a is displayed on the display unit 321 to the operator. The notification method is not limited to display on the display unit 321. For example, the comparison result may be notified by voice from an unillustrated audio output device (an example of a first notification unit), and the comparison result is indicated by lighting or blinking of a lamp of a lamp display device (an example of a first notification unit). It is good also as what notifies.

(Second Embodiment)
The image processing unit of the present embodiment will be described focusing on differences from the image processing unit 34 of the first embodiment. In the first embodiment, the operation of obtaining the attenuation rate sinogram and the linear attenuation coefficient from the subject sinogram and generating the density image of the substance from the linear attenuation coefficient and the set substance has been described. In the present embodiment, an operation for generating a density image directly from the attenuation rate sinogram will be described.

  FIG. 10 is a diagram illustrating an example of a block configuration of the first generation unit of the image processing unit according to the second embodiment. FIG. 11 is a diagram for explaining the relationship between the projection data and the linear attenuation coefficient. FIG. 12 is a diagram illustrating the pixel contribution. The block configuration and the operation of each block of the first generation unit 342a of the image processing unit of the present embodiment will be described with reference to FIGS.

  The image processing unit of the present embodiment has a configuration in which the first generation unit 342 of the image processing unit 34 of the first embodiment shown in FIG. 5 is replaced with a first generation unit 342a shown in FIG. That is, the first generation unit 342a is a functional unit that, like the first generation unit 342, receives the subject sinogram from the projection data acquisition unit 341, generates a density image, and outputs the density image to the second generation unit 343. . As illustrated in FIG. 10, the first generation unit 342a includes an update value calculation unit 3421 (calculation unit, second comparison unit), a determination unit 3422 (second determination unit), and a density image generation unit 3423 (update unit, A fourth generation unit), an image storage unit 3424, and a virtual projection unit 3425 (third generation unit, fifth generation unit).

  The update value calculation unit 3421 is a difference (a difference (a provisional projection data)) between the attenuation rate sinogram generated from the subject sinogram received from the projection data acquisition unit 341 and the virtual projection sinogram (provisional projection data) generated by the virtual projection unit 3425. (Second difference) is calculated, and an update value for each pixel is generated so that the difference becomes small.

  Specifically, the update value calculation unit 3421 first sets a specific energy band, receives an object sinogram of the set energy band from the projection data acquisition unit 341, and calculates an attenuation rate sinogram from the received object sinogram. Generate. The calculation method of the attenuation rate which is the pixel value of the attenuation rate sinogram is the same as the method described above in the first embodiment. When the number of photons when the subject 40 is arranged is A, and the number of photons when the subject 40 is not arranged is B, for example, log (B / A) is calculated and this is expressed in the attenuation rate sinogram. The pixel value (attenuation rate) may be used.

  Next, the update value calculation unit 3421 receives the virtual projection sinogram from the virtual projection unit 3425, and calculates the virtual projection sinogram and the attenuation rate sinogram for each channel, view, and energy (energy band) by the following equation (2). The difference D is calculated. That is, the update value calculation unit 3421 calculates, for each pixel, the difference D from the virtual projection sinogram for the set attenuation rate sinogram of each energy band.

D = (pixel value of virtual projection sinogram) − (pixel value of attenuation rate sinogram)
... (2)

When the difference D calculated by the update value calculation unit 3421 is D> 0, the density and mass of the substance set by the density image generation unit 3423 described later and the linear attenuation coefficient are all positive values. If the pixel value of the provisional density image generated by the density image generation unit 3423 described later is decreased, the difference D becomes smaller. The update value calculation unit 3421, for example, for each pixel of the provisional density image, the contribution degree in the channel and view, and (μ) _M (E) / (ρ) _M (the above-described equation) at the energy for each substance. A value obtained by multiplying the difference D by a separately adjusted parameter (see (1)) is calculated for each substance as an updated value (> 0). Then, as described later, the density image generation unit 3423 subtracts the update value calculated by the update value calculation unit 3421 from the pixel value of the provisional density image for each substance.

  On the other hand, when the difference D calculated by the update value calculation unit 3421 is D <0, if the pixel value of the provisional density image generated by the density image generation unit 3423 described later is increased, the difference D becomes smaller. The updated value calculation unit 3421 calculates an updated value (<0) for each substance, as described above. Then, as described later, the density image generation unit 3423 subtracts the update value calculated by the update value calculation unit 3421 from the pixel value of the provisional density image for each substance. In this case, since the update value is a negative value, the pixel value of the provisional density image increases.

  Furthermore, when the difference D calculated by the update value calculation unit 3421 is D = 0, the virtual projection sinogram and the attenuation rate sinogram (the pixel values thereof) match, and therefore the update value calculation unit 3421 does not calculate the update value. In this case, the update value calculation unit 3421 sets the update value to 0.

  The update value calculation unit 3421 sends the calculated update value to the determination unit 3422. When the update value calculation unit 3421 receives change information from the change unit 346 (see FIG. 5), the update value calculation unit 3421 changes the set energy band, for example, according to the change information, and changes the setting from the projection data acquisition unit 341 again. The subject sinogram in the energy band is received and the above-described updated value is calculated.

  The determination unit 3422 is a functional unit that determines whether or not the update value calculated by the update value calculation unit 3421 is equal to or less than a predetermined value. When the update value is equal to or less than the predetermined value (third predetermined value), it can be determined that the pixel value of the provisional density image generated by the density image generation unit 3423 described later has approached the correct density. Also, the determination unit 3422 sends the determination result for the update value and the update value received from the update value calculation unit 3421 to the density image generation unit 3423. Actually, since the update value can take a positive or negative value as described above, the absolute value of the update value may be determined. The determination unit 3422 determines whether or not the update value is equal to or less than the predetermined value. However, the determination unit 3422 is not limited to this, and the number of determinations (that is, update processing by the density image generation unit 3423 described later) It may be determined whether the number of times has reached a predetermined number.

  The density image generation unit 3423 reads and acquires a provisional density image (hereinafter referred to as “provisional density image”) stored in the image storage unit 3424, and receives the provisional density image from the determination unit 3422. It is a functional unit that sequentially updates with update values. Specifically, the density image generation unit 3423 first sets a substance that may exist in the subject 40, and reads and acquires an initial provisional density image from the image storage unit 3424 for each set substance. As an initial provisional density image, for example, an image having all pixel values as constant values is used. Next, the density image generation unit 3423 updates the provisional density image by subtracting the update value received from the determination unit 3422 from the pixel value of the provisional density image. Then, the density image generation unit 3423 stores the updated provisional density image in the image storage unit 3424 and sends it to the virtual projection unit 3425. Further, when the determination result received from the determination unit 3422 indicates that the update value is equal to or less than the predetermined value, the density image generation unit 3423 sets the updated provisional density image as the formal density image as the second generation unit 343 ( (See FIG. 5). In addition, when the density image generation unit 3423 receives the change information from the change unit 346 (see FIG. 5), for example, according to the change information, the setting of the substance that may exist in the subject 40 is changed, and again, Update processing is performed on the initial provisional density image.

  The image storage unit 3424 is a functional unit that stores the initial provisional density image and the updated provisional density image as described above. The image storage unit 3424 is realized by a storage device (not shown), for example. Note that the image storage unit 3424 may be realized by the image storage unit 35 shown in FIG.

  The virtual projection unit 3425 is a functional unit that generates a virtual projection sinogram from the provisional density image for each substance received from the density image generation unit 3423 for each channel, view, and energy (energy band) that is the same as the attenuation rate sinogram described above. is there.

  Here, the linear attenuation coefficient μ (x, y, E) of the reconstructed image reconstructed from the attenuation rate sinogram of each energy (energy band) is calculated using the density ρ (x, y, M) as described above. Calculated by equation (1).

In addition, the channel is α, the view is β, the number of photons of the X-ray energy E when the subject 40 is placed is I _d (α, β, E), and the X-ray energy E when the subject 40 is not placed. 11 is assumed to be I ₀ (α, β, E), the pixel value log (I ₀ (α, β, E) / I _d (α, β, E)) of the virtual projection sinogram is shown in FIG. The integral along the path of the projection beam s shown (represented here as s), and is represented by the following equation (3).

Substituting the linear attenuation coefficient μ (x, y, E) shown in the above equation (1) into this equation (3), the following equation (4) is obtained.

The virtual projection unit 3425 calculates the pixel value log (I ₀ (α ₀ ) of the virtual projection sinogram from the density ρ (x, y, M), which is the pixel value of the provisional density image for each set substance M, using Equation (4). , Β, E) / _Id (α, β, E)) is calculated, and a virtual projection sinogram is generated for each channel, view, and energy (energy band) that is the same as the above-described attenuation rate sinogram. That is, for each channel, view, and energy E, the virtual projection unit 3425 first integrates the density of each substance M along the path of the projection beam s determined by the channel and view, and the substance M has a concentration of 100 [ %], The value obtained by multiplying (μ) _M (E) / (ρ) _M is added for all substances M.

  Actually, since the provisional density image is discrete data, the integration along the path of the projection beam s is performed by filling each of the pixels 1111 constituting the density image 1101 as shown in FIG. The area of the overlapping portion 1112 between the projection beam s reaching the channel and the pixel 1111 is defined as the contribution of the pixel (normalized in the projection beam s as necessary). Then, the virtual projection unit 3425 sets a value obtained by adding a value obtained by multiplying the pixel value by the contribution degree for the pixel on which the projection beam s overlaps in the density image 1101 as an integral value of the density ρ.

  The virtual projection unit 3425 sends the generated virtual projection sinogram to the update value calculation unit 3421.

  Note that the pixel value is not updated for each channel, view, and energy pair. For example, the pixel value may be updated with an updated value collected for all channels in a certain view and certain energy pair. For example, these channels can be processed in parallel, and the processing time can be shortened. Similarly, the same effect can be obtained by summarizing views and energy.

  Further, the comparison result (for example, difference information) between the attenuation rate sinogram and the virtual projection sinogram obtained by the update value calculation unit 3421 is displayed by, for example, the display device 32 (an example of the second notification unit). May be. In this case, the method of notifying the comparison result is not limited to displaying on the display device 32. For example, the comparison result may be notified by voice from an unillustrated voice output device (an example of a second notification unit), and the comparison result is indicated by lighting or blinking of a lamp of a lamp display device (an example of a second notification unit). It is good also as what notifies. For example, the update value calculation unit 3421 that has received a sinogram of specific energy obtains an update value, the determination unit 3422 makes a determination, the density image generation unit 3423 updates the provisional density image with the update value, and the virtual projection unit 3425. The comparison result obtained by the update value calculation unit 3421 after the repetitive operation of generating the virtual projection sinogram by a predetermined number of times may be displayed on the display device 32. In this case, the operator who has confirmed the comparison result displayed on the display device 32 changes the setting of the energy band of the substance for calculating the density or the sinogram via the input device 31, and then the above-described repetitive processing is continued. Or the like.

  Further, the update value calculation unit 3421, the determination unit 3422, the density image generation unit 3423, the image storage unit 3424, and the virtual projection unit 3425 illustrated in FIG. 10 conceptually illustrate functions, and have such a configuration. It is not limited. For example, a plurality of functional units illustrated as independent functional units in FIG. 10 may be configured as one functional unit. On the other hand, the function of one functional unit in FIG. 10 may be divided into a plurality of functions and configured as a plurality of functional units.

  FIG. 13 is a flowchart illustrating an example of the operation of the image processing unit according to the second embodiment. The operation of density image generation processing by the first generation unit 342a of the image processing unit of the second embodiment will be mainly described with reference to FIG. Of the image processing performed by the image processing unit, processes other than the density image processing performed by the first generation unit 342a are the same as the image processing performed by the image processing unit 34 of the first embodiment.

<Step S21>
The projection data acquisition unit 341 (see FIG. 5) receives and acquires a subject sinogram that is a sinogram of the subject 40 generated by the data collection unit 16 (see FIG. 1) as projection data. The update value calculation unit 3421 sets a specific energy band, receives a subject sinogram of the set energy band from the projection data acquisition unit 341, and generates an attenuation rate sinogram from the received subject sinogram. Then, the process proceeds to step S22.

<Step S22>
The density image generation unit 3423 sets a substance that may exist in the subject 40, and reads (acquires) an initial provisional density image from the image storage unit 3424 for each set substance. The density image generation unit 3423 sends the acquired provisional density image to the virtual projection unit 3425. Then, the process proceeds to step S23.

<Step S23>
From the density ρ (x, y, M) that is the pixel value of the provisional density image for each set substance, the virtual projection unit 3425 calculates the pixel value log (I ₀ ( [alpha], [beta], E) / _Id ([alpha], [beta], E)) is calculated, and a virtual projection sinogram is generated for each channel, view, and energy (energy band) that is the same as the above-described attenuation rate sinogram. The virtual projection unit 3425 sends the generated virtual projection sinogram to the update value calculation unit 3421. Then, the process proceeds to step S24.

<Step S24>
The update value calculation unit 3421 receives the virtual projection sinogram from the virtual projection unit 3425, and calculates the difference D between the virtual projection sinogram and the attenuation rate sinogram for each channel, view, and energy (energy band) according to the above equation (2). calculate. That is, the update value calculation unit 3421 calculates, for each pixel, the difference D from the virtual projection sinogram for the set attenuation rate sinogram of each energy band. Next, the update value calculation unit 3421, for example, (μ) _M (E) / (ρ) _M (for each pixel of the provisional density image, the contribution in the channel and view, and the energy for each substance. A value obtained by multiplying the difference D by the above-described equation (1)) and a separately determined adjustment parameter is calculated for each substance as an update value. The update value calculation unit 3421 sends the calculated update value to the determination unit 3422. Then, the process proceeds to step S25.

<Step S25>
The determination unit 3422 determines whether or not the update value calculated by the update value calculation unit 3421 is equal to or less than a predetermined value. When the update value is equal to or less than the predetermined value, it can be determined that the pixel value of the provisional density image generated by the density image generation unit 3423 has approached the correct density. Also, the determination unit 3422 sends the determination result for the update value and the update value received from the update value calculation unit 3421 to the density image generation unit 3423. When the updated value is equal to or smaller than the predetermined value (step S25: Yes), the process proceeds to step S27, and when larger than the predetermined value (step S25: No), the process proceeds to step S26.

<Step S26>
The density image generation unit 3423 reads out and acquires the provisional density image stored in the image storage unit 3424, and sequentially updates the provisional density image with the update value received from the determination unit 3422. Specifically, the density image generation unit 3423 updates the provisional density image by subtracting the update value received from the determination unit 3422 from the pixel value of the provisional density image. Then, the density image generation unit 3423 stores the updated provisional density image in the image storage unit 3424 and sends it to the virtual projection unit 3425. Then, the process returns to step S23.

<Step S27>
When the determination result received from the determination unit 3422 indicates that the update value is equal to or less than the predetermined value, the density image generation unit 3423 officially displays the updated provisional density image (provisional density image read from the image storage unit 3424). It outputs to the 2nd production | generation part 343 (refer FIG. 5) as a density image.

  Until the density of the provisional density image obtained by updating the series of operations in steps S23 to S26 described above is determined to be a correct value (step S25), the update value calculation unit 3421 calculates the update value, and the density image generation unit. The update of the provisional density image by 3423 is repeated. As described above, it may be repeated until the predetermined number of times is reached.

  As described above, the virtual projection unit 3425 generates a virtual projection sinogram using the equation (4) from the provisional density image received from the density image generation unit 3423, and the update value calculation unit 3421 attenuates the virtual projection sinogram. A process based on the successive approximation method in which an update value is calculated based on the difference from the rate sinogram, and the density image generation unit 3423 updates the provisional density image with the update value calculated by the update value calculation unit 3421. I do. When the determination unit 3422 determines that the update value (absolute value) calculated by the update value calculation unit 3421 is equal to or less than a predetermined value, the density image generation unit 3423 has the correct pixel value of the updated provisional density image. The density is determined to be a density, and the updated provisional density image is output as a formal density image. As a result, the density image can be directly obtained from the attenuation rate sinogram without obtaining the line attenuation coefficient, so that the generated error can be reduced as compared with the case of obtaining the line attenuation coefficient in the middle.

  Further, when generating a reconstructed image composed of linear attenuation coefficients from the sinogram and further generating a density image from the reconstructed image, it is necessary to store both the reconstructed image and the density image in the storage means. In this embodiment, since the density image is directly obtained from the sinogram, it is only necessary to store the density image, so the capacity of the storage means can be reduced.

  In each of the above-described embodiments, the X-ray inspection apparatus 1 is described as a spectral CT apparatus or a photon counting CT apparatus. However, the present invention is not limited to this. For example, a dual energy CT apparatus may be used as the X-ray inspection apparatus 1. In the case of a dual energy CT system, the subject sinogram and attenuation rate sinogram are generated in two energy bands of X-rays irradiated at high and low tube voltages, and the two energies used to calculate the density of the two substances. The accuracy of the density image can be determined by setting the band to an energy band determined by the tube voltage and the difference comparison energy to be either or both of the energy bands determined by the tube voltage. When the difference is large, the accuracy of the density image may be improved by changing the type of the substance. A multi-energy CT apparatus can also be used as the X-ray inspection apparatus 1.

  Further, the image processing devices (console devices 30) of the above-described embodiments and modifications are configured using a computer. That is, the console device 30 includes a control device such as a CPU (Central Processing Unit) (scan control unit 33 and system control unit 36 in FIG. 1), and a storage such as a ROM (Read Only Memory) or a RAM (Random Access Memory). A device, an external storage device such as an HDD (Hard Disk Drive) or a CD drive (image storage unit 35 in FIG. 1), an input device such as a keyboard or a mouse (input device 31 in FIG. 1), and a display such as a display Device (display device 32 in FIG. 1).

  Here, as described above, the projection data acquisition unit 341, the first generation unit 342, the second generation unit 343, the reconstruction unit 344, the difference determination unit 345 and the change unit 346, the update value calculation unit 3421, the determination unit When at least one of 3422, the density image generation unit 3423, and the virtual projection unit 3425 is realized by a program, the program executed by the console device 30 is a file in an installable format or an executable format and is a CD- The program is recorded on a computer-readable recording medium such as a ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk) and provided as a computer program product.

  Further, the program executed by the image processing device (console device 30) according to each of the above-described embodiments and modifications is stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. You may comprise as follows. The program executed by the image processing device (console device 30) according to each of the above-described embodiments and modifications may be provided or distributed via a network such as the Internet. Further, the above program may be provided by being incorporated in advance in a ROM or the like.

  The program executed by the image processing apparatus (console device 30) according to each of the above-described embodiments and modifications includes the above-described projection data acquisition unit 341, first generation unit 342, second generation unit 343, and reconstruction unit. 344, a module configuration including at least one of a difference determination unit 345 and a change unit 346, an update value calculation unit 3421, a determination unit 3422, a density image generation unit 3423, and a virtual projection unit 3425. As the hardware, the CPU reads out and executes the program from the above-described storage medium, and the above-described functional units are loaded onto the main storage device and generated. Note that some or all of the functional units of the above-described image processing apparatus may be realized by a hardware circuit instead of a program that is software.

  Although several embodiments and modifications of the present invention have been described, these embodiments and modifications are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments and modifications can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 1 X-ray inspection apparatus 10 Base apparatus 11 X-ray tube 11a, 11b X-ray beam 12 Rotating frame 13 Detector 13a Channel 14 Irradiation control part 15 Base drive part 16 Data collection part 20 Bed apparatus 21 Bed drive apparatus 22 Top plate 30 Console Device 31 Input device 32 Display device 33 Scan control unit 34, 34a Image processing unit 35 Image storage unit 36 System control unit 40 Subject 41 Projection cross section 42 Measurement range 311 Input unit 321 Display unit 341 Projection data acquisition unit 342, 342a First Generation unit 343 Second generation unit 344 Reconfiguration unit 345 Difference determination unit 345a Difference calculation unit 346 Change unit 1001 sinogram 1011, 1011a to 1011d subject sinogram 1101 density image 1111 pixel 1112 overlapped part 2000 substance specific priority Buru 3421 updating value calculating unit 3422 determination unit 3423 density image generating unit 3424 image storage unit 3425 virtual projection portion s projection beam

Claims (17)

An acquisition unit for acquiring projection data based on a spectrum indicating an amount of X-rays for each energy of radiation that has passed through a subject detected by a detector;
A first generation unit that generates a first density image that is a density image of each of a plurality of substances selected as substances existing in the subject from the projection data;
A second generator for generating a monochrome image of a specific energy from the first density image;
A reconstruction unit that reconstructs the projection data corresponding to the specific energy to generate a reconstructed image;
A first comparison unit that compares pixel values of the monochrome image and the reconstructed image;
A first notifying unit for notifying a comparison result by the first comparing unit;
X-ray CT apparatus provided with   Based on the comparison result, the first generation unit adds a new substance to the plurality of substances or changes to a plurality of substances in which at least one of the plurality of substances is different from the projection data. The X-ray CT apparatus according to claim 1, wherein a second density image different from the first density image is generated. The first comparison unit calculates a first difference as the comparison result for the pixel values of the monochrome image and the reconstructed image,
A first determination unit configured to determine the first difference;
The X-ray CT apparatus according to claim 2, wherein the first generation unit generates the second density image based on a determination result for the first difference by the first determination unit. An input unit for receiving operation inputs;
Further,
The X-ray CT apparatus according to claim 2, wherein the first generation unit generates the second density image based on the operation input information received by the input unit based on the comparison result. The first determination unit determines whether a value based on the first difference is greater than a first predetermined value;
The X-ray CT apparatus according to claim 3, wherein the first generation unit generates the second density image when a value based on the first difference is larger than the first predetermined value by the first determination unit.   A changing unit that changes the selected substance based on the determination result or changes the energy corresponding to the projection data for generating the second density image; The X-ray CT apparatus according to claim 3, further provided.   The first generation unit changes the substance to be selected based on the information of the operation input, or changes energy corresponding to the projection data for generating the second density image, and The X-ray CT apparatus according to claim 4, which generates a two-density image.   The changing unit refers to priority order information that associates a substance assumed to exist in the subject and a priority order, and sets the priority order in the priority order information as the substance to be selected by the first generation unit. The X-ray CT apparatus according to claim 6, wherein an additional change is made from a high substance.   The X-ray CT apparatus according to claim 3, wherein the first determination unit calculates the first difference for the entire image between the monochrome image and the reconstructed image.   The X-ray CT apparatus according to claim 3, wherein the first determination unit calculates the first difference for each pixel or each region for the monochrome image and the reconstructed image. The second generation unit generates the monochrome image for each of the plurality of specific energies from the first density image,
The reconstruction unit reconstructs the projection data corresponding to each of the plurality of specific energies to generate the reconstructed image;
The X-ray CT apparatus according to claim 3, wherein the first determination unit calculates the first difference between the plurality of monochrome images and the reconstructed image corresponding to each of the monochrome images. The second generation unit generates the monochrome image while continuously switching the magnitude of the specific energy,
In the change unit, the change amount of the first difference calculated by the first determination unit exceeds a second predetermined value in accordance with continuous switching of the magnitude of the specific energy by the second generation unit. The X-ray CT apparatus according to claim 6, wherein the first generation unit is configured to select a substance having the specific energy whose change amount exceeds the second predetermined value as the K absorption edge. The first generator is
An update unit for updating a provisional density image that is a provisional density image of each of the plurality of substances;
A third generation unit that generates provisional projection data, which is provisional projection data for each of a plurality of energies, from the provisional density image;
A calculation unit that calculates a second difference between pixel values of the projection data acquired by the acquisition unit and the provisional projection data, and calculates an update value based on the second difference;
A second determination unit for determining the update value;
Have
The update unit updates the provisional density image with the update value calculated by the calculation unit, and the provisional density when the absolute value of the update value is equal to or less than a third predetermined value by the second determination unit. The X-ray CT apparatus according to claim 1, wherein an image is output as the first density image. An acquisition unit for acquiring projection data based on a spectrum indicating an amount of X-rays for each energy of radiation that has passed through a subject detected by a detector;
A fourth generation unit configured to generate a density image of each of a plurality of substances selected as substances existing in the subject based on the projection data;
A fifth generation unit that generates provisional projection data, which is provisional projection data for each of a plurality of energies, from the density image;
A second comparison unit that compares the projection data corresponding to each of the plurality of energies with the provisional projection data;
X-ray CT apparatus provided with   The X-ray CT apparatus according to claim 14, further comprising a second notification unit that notifies a comparison result by the second comparison unit. An X-ray tube that irradiates the radiation around the subject;
A detector for detecting the energy of the radiation emitted from the X-ray tube;
The X-ray CT apparatus according to any one of claims 1 to 15, further comprising: An acquisition unit that acquires projection data based on a spectrum indicating an amount of X-rays for each energy of radiation that has passed through the subject;
A first generation unit that generates a first density image that is a density image of each of a plurality of substances selected as substances existing in the subject from the projection data;
A second generator for generating a monochrome image of a specific energy from the first density image;
A reconstruction unit that reconstructs the projection data corresponding to the specific energy to generate a reconstructed image;
A first comparison unit that compares pixel values of the monochrome image and the reconstructed image;
A first notifying unit for notifying a comparison result by the first comparing unit;
An image processing apparatus.

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