X-ray CT apparatus

Abstract

To reduce a data transmission amount in an X-ray CT apparatus.SOLUTION: An X-ray CT apparatus comprises an X-ray detector, a data collection unit, a rotating unit, a processing unit, and a reconstruction processing unit. The X-ray detector outputs output data corresponding to energy of X-ray photons. The data collection unit collects the output data of the X-ray detector and outputs count data for each of a plurality of energy bins. The rotating unit rotatably supports the detector and the data collection unit. The processing unit is provided on the rotating unit and generates data relating to a plurality of material compositions on the basis of the count data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in this specification and the drawings relate to an X-ray CT apparatus. [Background technology]

[0002] In a photon-counting X-ray CT system, the X-ray detector counts the number of incident X-ray photons within a set energy range using counters called energy bins. The counted data is transmitted from the detector unit in the rotating section to the fixed section, where the console performs data preprocessing and image reconstruction as necessary.

[0003] Increasing the number of energy bins improves the accuracy of energy information, a feature of photon-counting X-ray CT scanners. However, because there are limitations on the amount of data that can be transmitted from the rotating part of the gantry to the fixed part, the more energy bins there are, the more difficult it becomes to transmit all the data in real time. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-20057 [Patent Document 2] Japanese Patent Publication No. 2022-13686 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce the amount of data transferred in an X-ray CT apparatus. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of the configurations shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0006] An X-ray CT apparatus according to an embodiment includes an X-ray detector, a data acquisition unit, a rotation unit, a processing unit, and a reconstruction processing unit. The X-ray detector outputs output data according to the energy of X-ray photons. The data acquisition unit collects the output data from the X-ray detector and outputs count data for each of a plurality of energy bins. The rotation unit rotatably supports the detector and the data acquisition unit. The processing unit is provided on the rotation unit and generates data regarding a plurality of material compositions based on the count data. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of an X-ray CT apparatus according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating the configuration of a rotating part of the X-ray CT apparatus according to the first embodiment. [Figure 3] FIG. 3 is a flowchart illustrating the flow of processing performed by the X-ray CT apparatus according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating the processing according to the first embodiment. [Figure 5] FIG. 5 is a flowchart illustrating the process of step S300 in the first embodiment in more detail. [Figure 6] FIG. 6 is a flowchart illustrating the process of step S300 in the third embodiment in more detail. [Figure 7] FIG. 7 is a diagram illustrating the processing according to the third embodiment. [Figure 8] FIG. 8 is a diagram illustrating the processing in the fourth embodiment. [Figure 9] FIG. 9 is a flowchart illustrating the process of step S300 in the fourth embodiment in more detail. DETAILED DESCRIPTION OF THE INVENTION

[0008] (First embodiment) Hereinafter, an embodiment of an X-ray CT apparatus will be described in detail with reference to the drawings.

[0009] FIG. 1 is a diagram showing an example of the configuration of an X-ray CT apparatus 1 according to the first embodiment. The X-ray CT apparatus 1 is a photon-counting CT apparatus. That is, the X-ray CT apparatus 1 is an apparatus that can reconstruct X-ray CT image data with a high S / N ratio by counting X-ray photons that have passed through a subject P using a photon-counting detector rather than a conventional integral type (current mode measurement type) detector. As shown in FIG. 1, the X-ray CT apparatus 1 according to the first embodiment has a gantry 10, a bed 20, and a console 30.

[0010] The gantry 10 is a device that irradiates an object P with X-rays and collects data related to the X-rays that have passed through the object P. The gantry 10 includes an X-ray high-voltage device 11, an X-ray generator 12, an X-ray detector 13, a data acquisition circuit 14, a rotating frame 15, and a gantry control device 16. As shown in FIG. 1, the gantry 10 defines an orthogonal coordinate system consisting of an X-axis, a Y-axis, and a Z-axis. That is, the X-axis indicates the horizontal direction, the Y-axis indicates the vertical direction, and the Z-axis indicates the direction of the rotation center axis of the rotating frame 15 when the gantry 10 is not tilted.

[0011] The rotating frame 15 is an annular frame that supports the X-ray generator 12 and the X-ray detector 13 so that they face each other across the subject P, and is rotated at high speed in a circular orbit centered on the subject P by the gantry control device 16 described later.

[0012] The X-ray generator 12 is a device that generates X-rays and irradiates the generated X-rays onto the subject P. The X-ray generator 12 has an X-ray tube (bulb) 12a, a wedge 12b, and a collimator 12c.

[0013] The X-ray tube 12a is a vacuum tube that receives a high voltage from the X-ray high voltage device 11 and irradiates thermoelectrons from a cathode (sometimes called a filament) toward an anode (target). The X-ray tube 12a irradiates the subject P with an X-ray beam as the rotating frame 15 rotates. That is, the X-ray tube 12a generates X-rays using the high voltage supplied from the X-ray high voltage device 11.

[0014] The X-ray tube 12a also generates an X-ray beam that spreads with a fan angle and a cone angle. For example, under the control of the X-ray high voltage generator 11, the X-ray tube 12a can continuously irradiate X-rays all around the subject P for full reconstruction, or continuously irradiate X-rays in an exposure range (180 degrees + fan angle) that allows half reconstruction for half reconstruction. Under the control of the X-ray high voltage generator 11, the X-ray tube 12a can also intermittently irradiate X-rays (pulsed X-rays) at a preset position (tube position).

[0015] The wedge 12b is an X-ray filter for adjusting the amount of X-rays emitted from the X-ray tube 12a. Specifically, the wedge 12b is a filter that transmits and attenuates the X-rays emitted from the X-ray tube 12a so that the X-rays irradiated from the X-ray tube 12a to the subject P have a predetermined distribution. For example, the wedge 12b is a filter made by processing aluminum to have a predetermined target angle and a predetermined thickness. The wedge is also called a wedge filter or a bow-tie filter.

[0016] The collimator 12c is made of a lead plate or the like and has a slit in part thereof. For example, the collimator 12c narrows down the irradiation range of the X-rays, the X-ray dose of which has been adjusted by the wedge 12b, by the control of the X-ray high voltage device 11, which will be described later, using the slit.

[0017] The X-ray source of the X-ray generator 12 is not limited to the X-ray tube 12a. For example, instead of the X-ray tube 12a, the X-ray generator 12 may be configured with a focus coil that focuses the electron beam generated from the electron gun, a deflection coil that electromagnetically deflects the electron beam, and a target ring that surrounds half the circumference of the subject P and generates X-rays by colliding with the deflected electron beam.

[0018] The X-ray high voltage device 11 is composed of electrical circuits such as a transformer and a rectifier, and is composed of a high-voltage generator that generates a high voltage to be applied to the X-ray tube 12a, and an X-ray control device that controls the output voltage according to the X-rays irradiated by the X-ray tube 12a. The high-voltage generator may be a transformer type or an inverter type. For example, the X-ray high voltage device 11 adjusts the tube voltage and tube current supplied to the X-ray tube 12a to adjust the amount of X-rays irradiated to the subject P. The X-ray high voltage device 11 is also controlled by a processing circuit 37 of the console 30.

[0019] The gantry control device 16 is composed of a processing circuit such as a CPU (Central Processing Unit) and a driving mechanism such as a motor and an actuator. The gantry control device 16 has a function of receiving input signals from an input interface 31 attached to the console 30 or an input interface attached to the gantry 10 and controlling the operation of the gantry 10. For example, the gantry control device 16 receives input signals and rotates the rotating frame 15, thereby controlling the rotation of the X-ray tube 12a and the X-ray detector 13 on a circular orbit centered on the subject P, controlling the tilt of the gantry 10, and controlling the operation of the bed 20 and the tabletop 22. The gantry control device 16 is controlled by a processing circuit 37 of the console 30.

[0020] The X-ray detector 13 is an example of a photon-counting detector (photon-counting detector) that is composed of multiple detection elements and outputs a signal corresponding to the number of counted X-ray photons (X-ray photon count). The X-ray detector 13 is composed of, for example, multiple X-ray detection element rows, in which multiple X-ray detection elements (also referred to as "sensors" or simply "detection elements") are arranged in the channel direction along an arc centered on the focal point of the X-ray tube 12a. The X-ray detector 13 has a structure in which multiple X-ray detection element rows, in which multiple X-ray detection elements are arranged in the channel direction, are arranged in the slice direction. Each X-ray detection element of the X-ray detector 13 detects X-rays irradiated from the X-ray generator 12 and passed through the subject P, and outputs an electrical signal (pulse) corresponding to the X-ray dose. The electrical signal output by each X-ray detection element is also referred to as a detection signal. The data acquisition circuit 14 (DAS: Data Acquisition System) is a circuit that collects the results of counting processing from each detection element of the X-ray detector 13 and generates detection data (projection data). In other words, the data acquisition circuitry 14 acquires the counting results from the X-ray detector 13. Here, the detected data is, for example, a sinogram. The data acquisition circuitry 14 is an example of a data acquisition unit.

[0021] The console 30 is a device that accepts operations of the X-ray CT device 1 by an operator and reconstructs X-ray CT image data using sinograms (counting results) collected by the gantry 10. As shown in FIG. 1 , the console 30 has an input interface 31, a display 32, a memory 35, and a processing circuit 37.

[0022] The input interface 31 accepts various input operations from the operator, converts the accepted input operations into electrical signals, and outputs them to the processing circuitry 37. For example, the input interface 31 accepts from the operator acquisition conditions for acquiring projection data, reconstruction conditions for reconstructing X-ray CT image data, image processing conditions for generating image data (post-processed image data) from the X-ray CT image data, etc. For example, the input interface 31 is realized by a mouse, keyboard, trackball, switch, button, joystick, etc.

[0023] The display 32 displays various types of information. For example, the display 32 outputs an image (X-ray CT image) based on image data generated by the processing circuitry 37, a GUI (Graphical User Interface) for receiving various operations from an operator, etc. For example, the display 32 is configured by a liquid crystal display, a CRT (Cathode Ray Tube) display, etc.

[0024] The memory 35 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The memory 35 stores, for example, projection data and reconstructed image data. The memory 35 is an example of a storage unit.

[0025] The processing circuitry 37 executes, for example, a system control function 371, a preprocessing function 372, a reconstruction processing function 373, an image processing function 374, a scan control function 375, and a display control function 376. Here, for example, the processing functions executed by the system control function 371, the preprocessing function 372, the reconstruction processing function 373, the image processing function 374, the scan control function 375, and the display control function 376, which are components of the processing circuitry 37 shown in FIG. 1, are recorded in the memory 35 in the form of a computer-executable program. The processing circuitry 37 is realized, for example, by a processor. The processing circuitry 37 reads each program from the memory 35 and executes the read program to realize the function corresponding to each program. In other words, the processing circuitry 37 in a state in which each program has been read has each function shown in the processing circuitry 37 of FIG. 1. The system control function 371, preprocessing function 372, reconstruction processing function 373, image processing function 374, scan control function 375, and display control function 376 are examples of a system control unit, a preprocessing unit, a reconstruction processing unit, an image processing unit, a scan control unit, and a display control unit, respectively.

[0026] The system control function 371 controls various functions of the processing circuit 37 based on input operations received from an operator via the input interface 31 .

[0027] The pre-processing function 372 generates raw data by performing pre-processing such as logarithmic conversion, offset correction, inter-channel sensitivity correction, inter-channel gain correction, pile-up correction, response function correction, and beam hardening correction on the detection data output from the data acquisition circuit 14. Then, the pre-processing function 372 stores the raw data in the memory 35.

[0028] The reconstruction processing function 373 generates X-ray CT image data by performing reconstruction processing using a filtered back projection method, an iterative reconstruction method, or the like on the raw data generated by the preprocessing function 372. The reconstruction processing function 373 stores the reconstructed X-ray CT image data in the memory 35.

[0029] Here, the projection data generated from the sinogram (counting result) obtained by photon-counting CT includes information on the energy of X-rays attenuated by passing through the subject P. Therefore, the reconstruction processing function 373 can reconstruct X-ray CT image data of a specific energy component, for example. Furthermore, the reconstruction processing function 373 can reconstruct X-ray CT image data of each of a plurality of energy components, for example.

[0030] Furthermore, the reconstruction processing function 373, for example, assigns a color tone according to the energy component to each pixel of the X-ray CT image data of each energy component, and generates image data in which multiple X-ray CT image data color-coded according to the energy component are superimposed. Furthermore, the reconstruction processing function 373 can generate image data that enables identification of the substance, for example, by utilizing the K absorption edge specific to the substance. Other image data generated by the reconstruction processing function 373 include monochromatic X-ray image data, density image data, effective atomic number image data, etc.

[0031] Furthermore, as an application of X-ray CT, there is a technology for discriminating the type, abundance, density, etc. of materials contained in the subject P by utilizing the fact that each material has different X-ray absorption characteristics. This is called material decomposition. For example, the reconstruction processing function 373 performs material decomposition on the projection data to obtain material decomposition information. Then, the reconstruction processing function 373 reconstructs material decomposition image data that indicates a material-decomposed image using the material decomposition information that is the result of the material decomposition.

[0032] The image processing function 374 converts the X-ray CT image data generated by the reconstruction processing function 373 into various image data such as tomographic image data of an arbitrary cross section or three-dimensional image data obtained by rendering processing, using a known method, based on an input operation received from the operator via the input interface 31. The image processing function 374 stores the converted various image data in the memory 35.

[0033] The scan control function 375 controls the CT scan performed on the gantry 10. For example, the scan control function 375 controls the operations of the X-ray high voltage device 11, the X-ray detector 13, the gantry control device 16, the data acquisition circuitry 14, and the bed driving device 21, thereby controlling the start, execution, and end of a scan on the gantry 10.

[0034] The display control function 376 controls the display 32 to display images based on various image data stored in the memory 35 .

[0035] Next, the configuration of the rotating unit 100 according to the embodiment will be described with reference to FIG. 2. FIG. 2 shows the configuration of the rotating unit 100 according to the embodiment. The rotating unit 100 is a rotating part of the X-ray CT apparatus 1, including a rotating frame 15, which is an annular frame that supports the X-ray generator 12 and the X-ray detector 13 so that they face each other across the subject P and rotates at high speed on a circular orbit centered on the subject P, and the X-ray detector 13. In addition, in this embodiment, the rotating unit 100 itself includes a data acquisition circuit 14, a processing circuit 17, and a memory 18 in order to reduce the amount of data transmitted from the rotating unit 100 to a fixed part of the X-ray CT apparatus 1 (i.e., a part fixed in the X-ray CT apparatus 1, such as the gantry 10), as will be described later. As an example, the X-ray detector 13, the data acquisition circuit 14, the processing circuit 17, and the memory 18 are installed on the rotating frame 15.

[0036] The memory 18 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc., and stores various data. The memory 18 is an example of a storage unit.

[0037] In the first embodiment, each processing function performed by the processing circuitry 17 is stored in the memory 18 in the form of a program executable by a computer. The processing circuitry 150 is a processor that realizes the function corresponding to each program by reading the program from the memory 18 and executing it. In other words, the processing circuitry 17 in a state where each program has been read has each corresponding function. The processing circuitry 17 is an example of a processing unit.

[0038] The term "processor" used in the above description refers to circuits such as a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes its functions by reading and executing programs stored in memory 18.

[0039] 1, which is a function for reconstructing an image, has been described below as being provided in the processing circuitry 37 of the console 30, but the embodiment is not limited to this. The reconstruction processing unit may be disposed in the fixed part of the X-ray CT apparatus 1, or, as another example, the processing circuitry 17 of the rotating part 100 may be provided with the reconstruction processing function.

[0040] Next, the background of the embodiment will be described.

[0041] In the photon-counting X-ray CT scanner 1, the X-ray detector 13 is a counter called an energy bin, which counts the number of incident X-ray photons within a set energy range. The counted data is transmitted from the detector unit in the rotating part 100 to the fixed part, where the console 30 performs data preprocessing and image reconstruction as necessary.

[0042] Increasing the number of energy bins improves the accuracy of energy information, which is a feature of photon-counting X-ray CT scanners. However, since there is a limit to the amount of data that can be transmitted from the rotating part 100 of the gantry to the fixed part, the more energy bins there are, the more restrictions there are on transmitting all data in real time.

[0043] Based on this background, the X-ray CT apparatus according to the embodiment includes an X-ray detector 13, a data acquisition circuit 14, a rotating unit 100, a processing circuit 17 as a processing unit, and a reconstruction processing function 373 as a reconstruction processing unit. The X-ray detector 13 outputs output data according to the energy of X-ray photons irradiated from the X-ray tube 12a. The data acquisition circuit 14 collects the output data from the X-ray detector 13 and outputs count data for each of a plurality of energy bins. The rotating unit 100 rotatably supports the detector and the data acquisition unit. The processing circuit 17 is provided in the rotating unit 100 and generates data regarding a plurality of material compositions based on the count data.

[0044] This allows for the transfer of data from the rotating part to the stationary part in real time while utilizing more energy bin data.

[0045] Next, the processing according to the embodiment will be described in detail with reference to Figures 3 to 5. Figure 3 is a diagram illustrating the flow of processing performed by the X-ray CT apparatus 1 in the first embodiment.

[0046] First, in step S100, the X-ray detector 13 outputs to the data acquisition circuitry 14 output data corresponding to the energy of the X-ray photons irradiated from the X-ray tube 12a.

[0047] Next, in step S200, the data collection circuit 14 collects output data from the X-ray detector 13 and outputs count data for each of a plurality of energy bins. Figure 4 shows a schematic diagram of the count data output by the data collection circuit 14. The data collection circuit 14 collects output data from the X-ray detector 13 and outputs count data 40 to 44 for, for example, six energy bins, Bin1 to Bin6, which are a plurality of energy bins.

[0048] Next, in step S300, the processing circuitry 17 provided on the rotating unit 100 that rotatably supports the X-ray detector 13 and the data acquisition circuitry 14 generates data on a plurality of material compositions (basis materials) based on the count data 40-45 output in step S200, generating data on the plurality of material compositions. Here, the data on the plurality of material compositions is, for example, the thicknesses of the plurality of materials. As an example, the plurality of materials are water and calcium. As another example, the plurality of materials are water, calcium, and an iodine contrast agent. The plurality of materials may also include contrast agents other than iodine contrast agents, stones, etc.

[0049] That is, based on the count data 40 to 45 output in step S200, the processing circuit 17 calculates, for example, data 47 representing the thickness of calcium and data 46 representing the thickness of water as data relating to a plurality of material compositions.

[0050] The details of this processing are shown in Figure 5. Figure 5 is a flowchart illustrating in more detail the processing in step S300 of Figure 3 in the first embodiment.

[0051] In step S310A, the processing circuitry 17 acquires a lookup table indicating the relationship between the count data for each energy bin and the thicknesses of multiple basis materials from the memory 18 connected to the processing circuitry 17. Next, the processing circuitry 17 compares the lookup table indicating the relationship between the count data for each energy bin and the thicknesses of multiple basis materials with the count data for each energy bin acquired in step S200.

[0052] Here, a lookup table between count data for each energy bin and thicknesses of a plurality of basis materials is created, for example, as follows.

[0053] When the multiple basis substances are water and calcium, the count data is expressed by the following formula (1).

[0054]

number

[0055] where E is the energy, w(E) is the energy spectrum of the incident X-ray, R(E) is the energy response of the detector, and μ is the linear attenuation coefficient (μ Ca is the linear attenuation coefficient of calcium, μ water is the linear attenuation coefficient of water), d is the transmission distance (d Ca is the calcium permeation distance, d water is the permeation distance of water). If the permeation distances of calcium and water are known, the processing circuit 17 can calculate the count data for each energy bin by substituting these values ​​into the right side of equation (1).

[0056] To explain the flow of creating the lookup table, prior to imaging, the processing circuitry 17 determines possible combinations of reference materials and their thicknesses, and creates a lookup table of energy bin outputs for the reference materials and their thicknesses. Since the lookup table only requires the relative intensity of the output for each energy bin to be known, it is sufficient to be able to calculate the output ratio for each energy bin. The processing circuitry 17 stores the created lookup table in memory 18 connected to the processing circuitry 17.

[0057] Next, in step S320A, processing circuitry 17 outputs estimated values ​​of thicknesses of the multiple basis materials based on the comparison results of step S310A. As one example, processing circuitry 17 uses the thicknesses of the multiple basis materials in the lookup table data whose energy bin count data is closest to the count data for each energy bin acquired in step S200 as the estimated values ​​of thicknesses of the multiple basis materials to be output in step S320A. As another example, processing circuitry 17 selects multiple pieces of lookup table data whose energy bin count data is closest to the count data for each energy bin acquired in step S200, and interpolates the thickness data of the basis materials in these pieces of data to estimate the values ​​of the multiple basis materials to be output in step S320A. In this way, processing circuitry 17 generates data regarding the multiple material configurations by performing interpolation processing with reference to a lookup table that shows the relationship between the count data 40 to 45 for each energy bin and the thickness data of the multiple basis materials.

[0058] Although the example of the multiple basis substances has been described as two types of basis substances, water and calcium, the embodiment is not limited thereto, and the multiple basis substances may be three or more types of basis substances. As an example, the multiple basis substances may be water, calcium, and iodine, which is an element related to the contrast agent.

[0059] Returning to FIG. 3 , in step S400, the processing circuit 17 transmits the data related to the plurality of material compositions output in step S300 from the rotating unit 100 to the fixed unit, or transmits it to the console 30 via the fixed unit. Here, the amount of data related to the plurality of material compositions output in step S300 is smaller than the amount of count data for each energy bin acquired in step S200. For example, in the case of FIG. 4 , there are six energy bins, so the number of data acquired in step S200 is six. Meanwhile, two data sets, namely, the water thickness and the calcium thickness, are output in step S300. Therefore, in this example, the amount of data transmitted is one-third of the original data. This makes it possible to reduce the amount of data transmitted from the rotating unit to the fixed unit, etc., in the X-ray CT device 1.

[0060] Next, in step S500, the processing circuitry 37, using the reconstruction processing function 373, performs reconstruction processing based on the data regarding the plurality of material configurations transmitted in step S400 to generate a reconstructed image. As an example, the processing circuitry 37 arranged in the console 30 of the X-ray CT apparatus 1 generates a reconstructed image using, for example, a filtered back projection method or an iterative approximation method, using the reconstruction processing function 373 as a reconstruction unit. As an example, the processing circuitry 37 generates a plurality of reference material images as reconstructed images using the reconstruction processing function 373. As an example, the processing circuitry 37 generates a reference material image related to water and a reference material image related to calcium as reconstructed images using the reconstruction processing function 373.

[0061] Furthermore, although the reconstruction unit has been described as being arranged on the console 30 of the X-ray CT apparatus 1, the embodiment is not limited to this. The reconstruction unit may be arranged on a fixed part of the X-ray CT apparatus 1. In this case, the reconstruction unit arranged on the fixed part of the X-ray CT apparatus 1 performs reconstruction processing based on the data on the multiple material compositions transmitted in step S400, generates a reconstructed image, and then transfers the generated reconstructed image to the console 30.

[0062] As described above, in the first embodiment, the processing circuitry 17 of the rotating unit 100 of the X-ray CT apparatus 1 generates data on a plurality of material compositions based on count data for each energy bin by referring to a lookup table. This makes it possible to reduce the amount of data transmitted from the rotating unit 100 to the fixed unit, etc.

[0063] (Second embodiment) In the first embodiment, the processing circuitry 17 of the rotating unit 100 of the X-ray CT scanner 1 generates data relating to a plurality of material compositions by referring to a lookup table. However, the embodiment is not limited to this. In step S300, the processing circuitry 17 of the rotating unit 100 of the X-ray CT scanner 1 may generate data relating to a plurality of material compositions using a neural network (AI).

[0064] Specifically, in the training stage, the neural network is trained using count data for each energy bin as input and thickness data for multiple basis materials as output. This neural network training does not need to be performed by the processing circuitry 17 of the rotating unit 100, but is typically performed by a predetermined processing circuit, such as the processing circuitry 37 of the console 30, or an external processing circuit. Once the neural network training is complete, the processing circuit that performed the training transmits the trained neural network to the processing circuitry 17. The processing circuitry 17 stores the trained neural network in the memory 18 of the rotating unit 100.

[0065] In step S300, the processing circuitry 17 of the rotating unit 100 retrieves the trained model from the memory 18. The processing unit then generates data related to multiple material configurations using the trained neural network, which has been trained using count data for each energy bin as input and thickness data for multiple basis materials as output. In step S400, the processing circuitry 17 transmits the output data related to the multiple material configurations to the fixed unit. In step S500, the processing circuitry 37 performs reconstruction processing using the reconstruction processing function 373 based on the data related to the multiple material configurations transmitted in step S400 to generate reconstructed images. As an example, the processing circuitry 37 generates multiple reference material images as reconstructed images using the reconstruction processing function 373. As an example, the processing circuitry 37 generates a reference material image related to water and a reference material image related to calcium as reconstructed images using the reconstruction processing function 373.

[0066] Furthermore, in the above-described embodiment, a case where data relating to a plurality of substance configurations is generated using a neural network has been described, but the embodiment is not limited thereto, and processing circuitry 17 may generate data relating to a plurality of substance configurations using machine learning. As an example, processing circuitry 17 may generate data relating to a plurality of substance configurations using PCA, linear regression, decision tree, gradient boosting, or the like. Furthermore, in the second embodiment, as in the first embodiment, the data relating to a plurality of substance configurations may be data relating to three or more types of substances.

[0067] As described above, in the second embodiment, the processing circuitry 17 generates data relating to multiple material configurations using a neural network or machine learning, which makes it possible to more flexibly reduce the amount of data transmitted from the rotating part 100 to the fixed part, etc.

[0068] (Third embodiment) In the first and second embodiments, the thickness of a reference material is calculated as data relating to a plurality of material compositions. However, the embodiments are not limited to this. In the third embodiment, the effective atomic number is calculated as data relating to a plurality of material compositions instead of the thickness of a reference material.

[0069] In the third embodiment, the processes other than step S300 in Fig. 3 are the same as those in the first embodiment, and a redundant description of the processes other than step S300 will be omitted.

[0070] FIG. 6 illustrates in more detail the process in step S300 of FIG. 3 in the third embodiment.

[0071] In step S310B, processing circuit 17 compares the count data for each energy bin from memory 18 connected to processing circuit 17 with a lookup table showing the relationship between effective atomic numbers and their thicknesses, i.e., the thicknesses when converted into materials with the effective atomic numbers.

[0072] Here, the flow of creating the lookup table will be explained. Prior to imaging, the processing circuitry 17 determines possible combinations of effective atomic numbers and their thicknesses, and creates a lookup table of energy bin outputs for the effective atomic numbers and their thicknesses. The processing circuitry 17 then stores the created lookup table in memory 18 connected to the processing circuitry 17.

[0073] Next, in step S320B, processing circuitry 17 outputs estimates of thicknesses of multiple basis materials based on the comparison results of step S310A. Specifically, processing circuitry 17 generates effective atomic numbers and their thickness estimates as data related to multiple material compositions. That is, in the third embodiment, the data related to multiple material compositions includes effective atomic numbers. For example, processing circuitry 17 references count data for each energy bin 40-45 and a lookup table showing the relationship between effective atomic numbers and their thicknesses. As shown in FIG. 7, processing circuitry 17 generates effective atomic number 48 and thickness 49 converted to the material with that effective atomic number as data related to multiple material compositions. Based on this data, processing circuitry 17 can generate an image of any reference material based on the generated effective atomic number and thickness data.

[0074] As described above, in the third embodiment, the processing circuitry 17 generates data including effective atomic numbers as data relating to a plurality of material compositions. This makes it possible to reduce the amount of data transmitted from the rotating unit 100 to the fixed unit, etc., in a manner different from the first and second embodiments.

[0075] (Fourth embodiment) In the first and second embodiments, the case where thicknesses of materials of a plurality of materials are used as data relating to a plurality of material compositions has been described, while in the third embodiment, the case where effective atomic numbers, etc. are used as data relating to a plurality of material compositions has been described. In the fourth embodiment, the case where photoelectric effect data, Compton scattering data, and data for a predetermined tube voltage are used as data relating to a plurality of material compositions will be described.

[0076] Using Figure 8, we will explain the significance of using photoelectric effect data and Compton scattering data as data related to multiple material compositions. Figure 8 is a schematic diagram showing which processes are dominant in each region when photon energy is plotted on the horizontal axis and effective atomic number is plotted on the vertical axis. Here, region 50 is a region typically used in X-ray CT. Looking at Figure 8, it can be seen that the photoelectric effect is dominant in region 52, Compton scattering is dominant in region 51, and the ratio of the photoelectric effect to Compton scattering in the count data changes as the effective atomic number changes. Therefore, the processing circuitry 17 calculates data corresponding to the frequency of the photoelectric effect (photoelectric effect data or photoelectric effect image) and data corresponding to the frequency of Compton scattering (Compton scattering data or photoelectric effect data). In addition, the processing circuitry 17 calculates data for a specified tube voltage, e.g., 120 kVp image data, which is data equivalent to data obtained from a typical integral detector, and transmits these three data to the fixed unit. For example, if the number of energy bins is six, the amount of data transmitted to the fixed unit is three, so the amount of data transmitted from the rotating unit 100 to the fixed unit or the like can be reduced.

[0077] Fig. 9 shows the flow of processing performed by the X-ray CT apparatus 1 according to the fourth embodiment in step S300 of Fig. 3. The processing other than step S300 is the same as that in the first embodiment, and therefore repeated explanation will be omitted.

[0078] In step S310C, the processing circuitry 17 acquires a lookup table indicating the relationship between count data for each energy bin, photoelectric effect data (photoelectric effect image), Compton scattering data (Compton scattering data), and data for a predetermined tube voltage (e.g., a 120 kVp image) from the memory 18 connected to the processing circuitry 17. Next, the processing circuitry 18 acquires the count data for each energy bin. Next, the processing circuitry 17 compares the lookup table with the count data for each energy bin acquired in step S200.

[0079] To create the lookup table, the processing circuitry 17 converts the count data for each energy bin into data on the frequency of the photoelectric effect and data on the frequency of Compton scattering, based on a theoretical curve such as that shown in FIG. 8, for possible combinations of count data for each energy bin before imaging. The processing circuitry 17 also converts the count data for each energy bin into data for a predetermined tube voltage, such as a 120 kVp image. In this way, the processing circuitry 17 creates a lookup table and stores the created lookup table in memory 18 connected to the processing circuitry 17.

[0080] Next, in step S320A, the processing circuitry 37 generates photoelectric effect data (photoelectric effect image), Compton scattering data (Compton scattering data), and data for a predetermined tube voltage (120 kVp image) based on the comparison result of step S310A, and transmits them to a fixed unit, etc. The processing circuitry 37 reconstructs an X-ray CT image based on the transmitted data using the reconstruction processing function 373. The processing circuitry 37 can generate an image of any reference material based on the photoelectric effect image, Compton scattering image, and 120 kVp image.

[0081] In the above-described embodiment, the processing circuitry 17 outputs data on multiple material compositions for each X-ray detector 13 and transmits the data to the fixed unit, etc. However, the embodiment is not limited to this. As an example, the processing circuitry 17 in the rotating unit 100 may have an image reconstruction function, aggregate data acquired from multiple X-ray detectors 13, perform image reconstruction, generate a photoelectric effect image, a Compton scattering image, and a 120 kVp image, and transmit the generated images to the fixed unit, etc.

[0082] According to at least one of the embodiments described above, the amount of data transfer can be reduced.

[0083] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0084] 13 X-ray detector 14 Data collection circuit 17 Processing circuit 18 Memory 30 Console

Claims

1. an X-ray detector that outputs output data according to the energy of X-ray photons; a data acquisition unit that collects output data from the X-ray detector and outputs count data for each of a plurality of energy bins; a rotating unit that rotatably supports the detector and the data collecting unit; a processing unit provided in the rotating unit, the processing unit generating data relating to a plurality of material compositions based on the count data; and a reconstruction processing unit that performs reconstruction processing based on the data on the plurality of material configurations; An X-ray CT device comprising:

2. The X-ray CT apparatus according to claim 1 , wherein the reconstruction processing unit is disposed on a fixed portion of the X-ray CT apparatus.

3. The X-ray CT apparatus according to claim 1 , wherein the reconstruction processing unit is disposed on a console of the X-ray CT apparatus.

4. The X-ray CT apparatus according to claim 1 , wherein the data relating to the plurality of material configurations is thicknesses of the plurality of materials.

5. 5. The X-ray CT apparatus according to claim 4, wherein the plurality of substances are water and calcium.

6. 5. The X-ray CT apparatus according to claim 4, wherein the plurality of substances are water, calcium, and an iodine contrast agent.

7. 2. The X-ray CT apparatus according to claim 1, wherein the processing unit generates data regarding the plurality of material configurations by referencing a lookup table showing a relationship between count data for each energy bin and thickness data of a plurality of basis materials and performing interpolation processing.

8. 2. The X-ray CT apparatus according to claim 1, wherein the processing unit generates data regarding the plurality of material configurations using a trained neural network that has been trained using count data for each energy bin as input and thickness data of a plurality of basis materials as output.

9. 2. The X-ray CT apparatus according to claim 1, wherein the data relating to the plurality of material compositions includes effective atomic numbers.

10. 2. The X-ray CT apparatus according to claim 1, wherein the data relating to the plurality of material compositions are photoelectric effect data, Compton scattering data, and data at a predetermined tube voltage.

Images