JP2024053288A - X-ray CT device, information processing method, and program - Google Patents

Abstract

[Problem] To efficiently adjust the contrast of an image generated by PCCT. [Solution] The X-ray CT apparatus according to the present embodiment includes an X-ray tube, a photon-counting detector, an acquisition section, a reconstruction section, an identification section, and a generation section. The X-ray tube irradiates an object with X-rays. The photon-counting detector includes a plurality of detection elements, and counts the photons contained in the X-rays. The acquisition section acquires an energy spectrum transmitted through the object for each of the plurality of detection elements. The reconstruction section reconstructs a plurality of energy images for each energy bin constituting the energy spectrum. The identification section identifies an energy bin to be displayed for each of the plurality of detection elements based on the plurality of energy images. The generation section generates a display image based on the energy bin to be displayed identified by the identification section. [Selected Figure] FIG.

Description

Embodiments of the present invention relate to an X-ray CT device, an information processing method, and a program.

Conventionally, photon counting computed tomography (PCCT) is known as an application of X-ray CT (Computed Tomography) that can estimate the type, atomic number, density, etc. of a substance contained in a subject. In PCCT, photons are counted in each energy bin and all energies are integrated, making it possible to generate an image similar to that of a conventional CT device (hereinafter also referred to as an integral image).

However, when adjusting the contrast of an integral image, the user must manually adjust the differences and weights for each energy bin, which can complicate the user's operations. Thus, there is room for improvement in terms of operability when it comes to adjusting the contrast of images generated by PCCT.

JP 2017-127638 A

One of the problems that the embodiments disclosed in this specification and the drawings attempt to solve is to efficiently adjust the contrast of images generated by PCCT. However, the problems that the embodiments disclosed in this specification and the drawings attempt to solve are not limited to the above problem. Problems that correspond to the effects of each configuration shown in the embodiments described below can also be positioned as other problems.

The X-ray CT apparatus of the embodiment includes an X-ray tube, a photon-counting detector, an acquisition unit, a reconstruction unit, an identification unit, and a generation unit. The X-ray tube irradiates an object with X-rays. The photon-counting detector includes multiple detection elements and counts photons contained in the X-rays. The acquisition unit acquires an energy spectrum transmitted through the object for each of the multiple detection elements. The reconstruction unit reconstructs multiple energy images for each energy bin constituting the energy spectrum. The identification unit identifies an energy bin to be displayed for each of the multiple detection elements based on the multiple energy images. The generation unit generates a display image based on the energy bin to be displayed identified by the identification unit.

FIG. 1 is a block diagram showing an example of the configuration of a photon counting X-ray CT apparatus according to the first embodiment. FIG. 2 is a diagram for explaining an example of a helical scan performed by the photon counting X-ray CT apparatus according to the first embodiment. FIG. 3 is a diagram for explaining an example of X-ray irradiation on a subject according to the first embodiment. FIG. 4 is a diagram illustrating an example of an irradiation spectrum according to the first embodiment. FIG. 5 is a diagram illustrating an example of the relationship between the transmission spectrum and the detection spectrum according to the first embodiment. FIG. 6 is a diagram illustrating an example of a corrected spectrum obtained by correcting a detected spectrum according to the first embodiment. FIG. 7 is a diagram showing an example of energy bins constituting the corrected spectrum according to the first embodiment. FIG. 8 is a diagram illustrating an example of a plurality of X-ray CT image data reconstructed for each energy bin according to the first embodiment. FIG. 9 is a diagram illustrating an example of processing for specifying pixels to be displayed according to the first embodiment. FIG. 10 is a flowchart showing an example of processing executed by the photon counting X-ray CT apparatus according to the first embodiment. FIG. 11 is a block diagram showing an example of the configuration of a photon counting X-ray CT apparatus according to the second embodiment. FIG. 12 is a diagram illustrating an example of a process for specifying an energy bin to be imaged according to the second embodiment. FIG. 13 is a flowchart showing an example of processing executed by the photon counting X-ray CT apparatus according to the second embodiment. FIG. 14 is an image diagram illustrating an example of a display image according to the second modification.

Below, embodiments of the X-ray CT device, information processing method, and program will be described in detail with reference to the drawings. In the following embodiments, parts with the same reference numerals perform similar operations, and duplicated descriptions will be omitted as appropriate.

For the sake of specificity, the X-ray CT device according to the embodiment will be described as a photon counting type X-ray CT device capable of performing photon counting CT (hereinafter referred to as a photon counting type X-ray CT (computed tomography) device). Note that the X-ray CT device according to the embodiment may have an integral type (current mode measurement method) X-ray detector in addition to the photon counting type detector.

First Embodiment
1 is a block diagram showing an example of the configuration of a photon counting X-ray CT apparatus 1 according to the first embodiment. As shown in FIG. 1, the photon counting X-ray CT apparatus 1 includes a gantry device 10, a bed device 30, and a console device 40.

In this embodiment, the rotation axis of the rotating frame 13 in a non-tilted state or the longitudinal direction of the tabletop 33 of the bed device 30 is defined as the Z-axis direction, the axial direction perpendicular to the Z-axis direction and horizontal to the floor surface is defined as the X-axis direction, and the axial direction perpendicular to the Z-axis direction and perpendicular to the floor surface is defined as the Y-axis direction. For convenience of explanation, multiple gantry devices 10 are drawn in FIG. 1, but the actual photon counting X-ray CT device 1 is configured with only one gantry device 10.

The gantry device 10 and the bed device 30 operate based on user operations via the console device 40, or on user operations via an operation unit provided on the gantry device 10 or the bed device 30. The gantry device 10, the bed device 30, and the console device 40 are connected to each other by wire or wirelessly so that they can communicate with each other.

The gantry device 10 is a device having an imaging system that irradiates X-rays onto the subject P and collects projection data from the detection data of the X-rays that have passed through the subject P.

The gantry device 10 has an X-ray tube 11 (X-ray generator), a photon counting detector 12, a rotating frame 13, an X-ray high voltage device 14, a control device 15, a bow-tie filter 16, a collimator 17, and a DAS (Data Acquisition System) 18.

The X-ray tube 11 is a vacuum tube that generates X-rays by irradiating thermoelectrons from a cathode (filament) to an anode (target) through the application of high voltage from the X-ray high voltage device 14 and the supply of filament current. X-rays are generated when the thermoelectrons collide with the target.

The X-rays generated at the tube focus in the X-ray tube 11 pass through the X-ray emission window in the X-ray tube 11, are shaped into a cone beam via the collimator 17, and are irradiated onto the subject P. The X-ray tube 11 may be, for example, a rotating anode type X-ray tube that generates X-rays by irradiating a rotating anode with thermoelectrons.

The photon counting detector 12 counts the photons of the X-rays generated by the X-ray tube 11. For example, the photon counting detector 12 outputs a pulse corresponding to the photons contained in the X-rays. Specifically, the photon counting detector 12 detects the X-rays irradiated from the X-ray tube 11 and passing through the subject P in photon units, and outputs an electrical signal corresponding to the amount of the X-rays to the DAS 18.

The photon counting detector 12 has, for example, multiple detection element rows in which multiple detection elements are arranged in the channel direction along one arc centered on the focus of the X-ray tube 11. The photon counting detector 12 has, for example, a structure in which multiple detection element rows are arranged in the slice direction (row direction). The photon counting detector 12 is also called a main detector that detects X-rays that have passed through the subject P.

The photon counting detector 12 is specifically an indirect conversion detector having, for example, a grid, a scintillator array, and a photosensor array.

The scintillator array has multiple scintillators. The scintillator has scintillator crystals that output light with a photon quantity corresponding to the amount of incident X-rays. The grid is arranged on the X-ray incident side of the scintillator array and has an X-ray shielding plate that has the function of absorbing scattered X-rays. The optical sensor array has multiple optical sensor groups. The optical sensor group has multiple optical sensors.

Each of the multiple optical sensors has the function of amplifying the light received from the scintillator and converting it into an electrical signal. The optical sensor is, for example, an APD (Avalanche Photo-Diode) or a SiPM (Silicon Photo Multiplier). In other words, the optical sensor receives light from the scintillator and outputs an electrical signal (pulse) corresponding to the incident X-ray photons.

That is, each of the multiple optical sensors outputs a pulse corresponding to the photons contained in the X-rays. The multiple optical sensors correspond to multiple detection elements. In other words, the photon counting detector 12 has multiple detection elements.

The electrical signal output by each detection element is also called a detection signal. The peak value (voltage) of this electrical signal (pulse) correlates with the energy value of the X-ray photon. The photon counting detector 12 may be a direct conversion detector having a semiconductor element that converts the incident X-rays into an electrical signal. When the photon counting detector 12 is a direct conversion detector, the multiple electrodes in the semiconductor element correspond to the multiple detection elements.

The rotating frame 13 supports the X-ray tube 11 and the photon counting detector 12 so that they can rotate around a rotation axis. Specifically, the rotating frame 13 is an annular frame that supports the X-ray tube 11 and the photon counting detector 12 facing each other and rotates the X-ray tube 11 and the photon counting detector 12 using a control device 15, which will be described later.

The rotating frame 13 is rotatably supported by a fixed frame made of a metal such as aluminum. More specifically, the rotating frame 13 is connected to the edge of the fixed frame via bearings. The rotating frame 13 receives power from the drive mechanism of the control device 15 and rotates at a constant angular velocity around the rotation axis Z.

The rotating frame 13 further supports the X-ray tube 11 and the photon counting detector 12, as well as the X-ray high voltage device 14 and the DAS 18. The rotating frame 13 is housed in a roughly cylindrical housing in which an opening (bore) 131 that forms the imaging space is formed. The opening 131 roughly coincides with the FOV. The central axis of the opening 131 coincides with the rotation axis Z of the rotating frame 13.

The detection data generated by the DAS 18 is transmitted, for example, by optical communication from a transmitter having a light-emitting diode (LED) to a receiver having a photodiode provided in a non-rotating portion (e.g., a fixed frame) of the gantry 10, and then transferred to the console device 40. The method of transmitting the detection data from the rotating frame 13 to the non-rotating portion of the gantry 10 is not limited to the optical communication described above, and any method of non-contact data transmission may be used.

The X-ray high voltage device 14 has electrical circuits such as a transformer and a rectifier, and includes a high voltage generator that has the function of generating the high voltage to be applied to the X-ray tube 11 and the filament current to be supplied to the X-ray tube 11, and an X-ray control device that controls the output voltage according to the X-rays emitted by the X-ray tube 11.

The high voltage generator may be of the transformer type or the inverter type. The X-ray high voltage device 14 may be provided on the rotating frame 13 or on the fixed frame (not shown) side of the gantry device 10.

The control device 15 has a processing circuit having a CPU (Central Processing Unit) and the like, and a driving mechanism such as a motor and an actuator. The processing circuit has, as hardware resources, a processor such as a CPU or an MPU (Micro Processing Unit) and a memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory).

The control device 15 may also be implemented using an ASIC, a Field Programmable Gate Array (FPGA), other Complex Programmable Logic Devices (CPLDs), or Simple Programmable Logic Devices (SPLDs).

The control device 15 controls the X-ray high voltage device 14 and the DAS 18, etc., according to instructions from the console device 40. The processor realizes the above control by reading and executing the programs stored in the memory.

The control device 15 also has the function of receiving input signals from the console device 40 or an input interface attached to the gantry device 10 and controlling the operation of the gantry device 10 and the bed device 30.

For example, the control device 15 receives an input signal and performs control to rotate the rotating frame 13, control to tilt the gantry device 10, and control to operate the bed device 30 and the tabletop 33. Note that the control to tilt the gantry device 10 may be realized by the control device 15 rotating the rotating frame 13 around an axis parallel to the X-axis direction based on inclination angle (tilt angle) information input by an input interface attached to the gantry device 10.

The control device 15 may be provided in the gantry device 10 or in the console device 40. The control device 15 may be configured to directly incorporate the program into the circuitry of the processor, instead of storing the program in the memory. In this case, the processor realizes the above control by reading and executing the program incorporated in the circuitry.

The bowtie filter 16 is placed in front of the X-ray emission window in the X-ray tube 11. The bowtie filter 16 is a filter for adjusting the amount of X-rays emitted from the X-ray tube 11.

Specifically, the bowtie filter 16 is a filter that transmits and attenuates the X-rays irradiated from the X-ray tube 11 so that the X-rays irradiated from the X-ray tube 11 to the subject P have a predetermined distribution. The bowtie filter 16 is a filter made of processed aluminum so that it has a predetermined target angle and a predetermined thickness.

The collimator 17 is a lead plate or the like that focuses the X-rays that have passed through the bowtie filter 16 into the X-ray irradiation range 113, and a slit is formed by combining multiple lead plates or the like.

The DAS 18 has a plurality of counting circuits. Each of the plurality of counting circuits has an amplifier that performs an amplification process on the electrical signal output from each detection element of the photon counting detector 12, and an A/D converter that converts the amplified electrical signal into a digital signal, and generates detection data that is the result of a counting process using the detection signal of the photon counting detector 12.

The result of the counting process is data that assigns the number of X-ray photons to each energy bin. For example, the DAS 18 counts the photons (X-ray photons) derived from the X-rays irradiated from the X-ray tube 11 and transmitted through the subject P, and discriminates the energy of the counted photons to obtain the result of the counting process. The detection data generated by the DAS 18 is transferred to the console device 40.

Detection data is a set of data that includes the channel number of the detector pixel from which it was generated, the column number, the view number indicating the view (also called the projection angle) that was collected, and a value indicating the detected X-ray dose.

The view number may be the order in which the views were collected (collection time), or a number representing the rotation angle of the X-ray tube 11 (e.g., 1 to 1000). Each of the multiple counting circuits in the DAS 18 is realized, for example, by a group of circuits equipped with circuit elements capable of generating detection data.

The bed device 30 is a device for placing and moving the subject P to be scanned, and is equipped with a base 31, a bed driving device 32, a top plate 33, and a top plate support frame 34. The base 31 is a housing that supports the top plate support frame 34 so that it can move in the vertical direction. The bed driving device 32 is a motor or actuator that moves the top plate 33, on which the subject P is placed, in the longitudinal direction of the top plate 33.

The bed driving device 32 moves the top plate 33 under the control of the console device 40 or the control of the control device 15. The top plate 33, which is provided on the upper surface of the top plate support frame 34, is a plate on which the subject P is placed. Note that the bed driving device 32 may move the top plate support frame 34 in the longitudinal direction of the top plate 33 in addition to the top plate 33.

The console device 40 has a memory 41 (storage unit), a display 42 (display unit), an input interface 43 (input unit), and a processing circuit 44 (processing unit). Data communication between the memory 41, the display 42, the input interface 43, and the processing circuit 44 is performed via a bus (BUS).

The memory 41 is a storage device such as a hard disk drive (HDD), a solid state drive (SSD), or an integrated circuit storage device that stores various information. The memory 41 stores, for example, projection data and reconstructed image data.

In addition to HDDs and SSDs, memory 41 may be a drive device that reads and writes various information between portable storage media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), and flash memories, and semiconductor memory elements such as RAMs (Random Access Memory). The storage area of memory 41 may be located within photon counting X-ray CT device 1, or may be located within an external storage device connected via a network.

The memory 41 stores various programs according to this embodiment. For example, the memory 41 stores programs related to the execution of each of the system control function 441, the preprocessing function 442, the reconstruction processing function 443, the image processing function 444, the identification function 445, and the display image generation function 446 executed by the processing circuitry 44.

The display 42 displays various types of information. For example, the display 42 outputs medical images (CT images) generated by the processing circuitry 44, a GUI (Graphical User Interface) for receiving various operations from the user, etc.

As the display 42, for example, a liquid crystal display (LCD), a cathode ray tube (CRT) display, an organic electroluminescence display (OELD), a plasma display, or any other display can be used as appropriate.

The display 42 may be provided on the pedestal device 10. The display 42 may be a desktop type, or may be configured as a tablet terminal or the like capable of wireless communication with the console device 40 main body. The display 42 corresponds to a display unit.

The input interface 43 accepts various input operations from the user, converts the accepted input operations into electrical signals, and outputs them to the processing circuit 44. For example, the input interface 43 accepts from the user the collection conditions when collecting projection data, the reconstruction conditions when reconstructing a CT image, the image processing conditions when generating a post-processed image from a CT image, and the like.

As the input interface 43, for example, a mouse, keyboard, trackball, switch, button, joystick, touchpad, touch panel display, etc. can be used as appropriate.

In this embodiment, the input interface 43 is not limited to having physical operating parts such as a mouse, keyboard, trackball, switch, button, joystick, touchpad, and touch panel display.

For example, an example of the input interface 43 also includes an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs this electrical signal to the processing circuit 44.

The input interface 43 may also be provided in the pedestal device 10. The input interface 43 may also be configured as a tablet terminal or the like capable of wireless communication with the console device 40 main body. The input interface 43 corresponds to an input unit.

The processing circuit 44 controls the operation of the entire photon counting X-ray CT device 1 in response to the electrical input operation signals output from the input interface 43.

For example, the processing circuitry 44 has, as hardware resources, a processor such as a CPU, MPU, or GPU (Graphics Processing Unit), and memory such as ROM or RAM. The processing circuitry 44 executes a system control function 441, a pre-processing function 442, a reconstruction processing function 443, an image processing function 444, a specification function 445, and a display image generation function 446 by a processor that executes a program deployed in the memory.

The system control function 441 is an example of a display control unit. The pre-processing function 442 is an example of an acquisition unit. The reconstruction processing function 443 is an example of a reconstruction unit. The identification function 445 is an example of a identification unit. The display image generation function 446 is an example of a generation unit.

Note that each of the functions 441 to 446 is not limited to being realized by a single processing circuit. A processing circuit may be configured by combining multiple independent processors, and each processor may execute a program to realize each of the functions 441 to 446.

The system control function 441 controls each function of the processing circuit 44 based on the input operation received from the user via the input interface 43. Specifically, the system control function 441 reads out the control program stored in the memory 41, expands it on the memory in the processing circuit 44, and controls each part of the photon counting X-ray CT device 1 according to the expanded control program.

For example, the system control function 441 controls each part of the photon counting X-ray CT device 1 based on the input operation received from the user via the input interface 43, and executes a helical scan in which the rotating frame 13 is continuously rotated while the top plate 33 is moved to capture images.

For example, based on an input operation received from a user via the input interface 43, the system control function 441 executes a non-helical scan in which the rotating frame 13 rotates once around the subject P to capture an image, and then the top plate 33 on which the subject P is placed is shifted slightly and the rotating frame 13 rotates once again to capture an image.

Figure 2 is a diagram illustrating an example of a scan performed by the photon counting X-ray CT device 1 according to the first embodiment. As shown in Figure 2, the X-ray tube 11 irradiates the subject P with X-rays containing multiple energies while rotating continuously. In addition, during the irradiation of X-rays by the X-ray tube 11, the tabletop 33 on which the subject P is placed moves in the Z-axis direction.

The photon counting detector 12 detects the X-rays that have passed through the subject P in photon units. The photon counting detector 12 outputs an electrical signal corresponding to the amount of detected X-rays to the DAS 18. This causes the DAS 18 to generate detection data.

Returning to FIG. 1, the explanation will continue. The pre-processing function 442 acquires a detection spectrum for each of the multiple detection elements. For example, the pre-processing function 442 acquires the detection data output from the DAS 18. The detection data includes the detection spectrum (see FIG. 5).

The preprocessing function 442 also generates data that has undergone various preprocessing processes on the detected spectrum. In this specification, data before preprocessing is referred to as raw data, and data after preprocessing is referred to as projection data.

For example, the pre-processing function 442 performs processing to correct the distortion of the detected spectrum. In this embodiment, the corrected spectrum is referred to as the corrected spectrum (see FIG. 6).

The pre-processing function 442 also generates projection data for multiple energy bins based on the correction spectrum and the irradiation spectrum (see FIG. 3). For example, the pre-processing function 442 performs pre-processing such as dividing the correction spectrum by the irradiation spectrum, logarithmic conversion, offset correction, inter-channel sensitivity correction, and beam hardening correction on the correction spectrum for each of the multiple energy bins to generate projection data.

The detection spectrum and irradiation spectrum will be described below with reference to Figs. 3 to 6. Fig. 3 is a diagram for explaining an example of X-ray irradiation of a subject P according to the first embodiment. Note that the vertical axis of Fig. 3 represents the slice direction, and the horizontal axis represents the channel direction. Fig. 4 is a diagram for explaining an example of an irradiation spectrum 50 according to the first embodiment.

As shown in FIG. 3, assume that X-rays a1 are irradiated from the X-ray tube 11 to the detection element 12a of the photon counting detector 12. In this case, as shown in FIG. 4, the spectrum of X-rays in region XA in X-rays a1 corresponds to the irradiation spectrum 50. Note that the area above region XA is an air region, and the attenuation of X-rays can be ignored.

The irradiation spectrum 50 is determined by the high voltage and current supplied to the X-ray tube 11, the type of target (e.g., tungsten) used in the radiation source, and the type and thickness of the wedge. For this reason, the irradiation spectrum 50 is obtained by precise actual measurements and highly accurate simulations. In this embodiment, the irradiation spectrum 50 is stored in advance in the memory 41.

In addition, in this embodiment, the spectrum of X-rays from when they pass through the subject P until they reach the detection element 12a is referred to as the transmission spectrum 52. FIG. 5 is a diagram for explaining an example of the relationship between the transmission spectrum 52 and the detection spectrum 54 according to the first embodiment. For example, as shown in FIG. 5, the spectrum of X-rays in region XB of X-rays a1 irradiated from the X-ray tube 11 to the detection element 12a corresponds to the transmission spectrum 52. In FIG. 5, the transmission spectrum 52 is represented by a dotted line.

The transmission spectrum 52 is determined by the composition of the material present in the path along which the X-rays pass through the subject P and the irradiation spectrum 50 irradiated onto the subject P.

In addition, in this embodiment, the spectrum of X-rays detected by the detection element 12a is referred to as the detection spectrum 54. Specifically, the spectrum of X-rays detected by the photon counting detector 12 corresponds to the detection spectrum 54. In FIG. 5, the detection spectrum 54 is represented by a solid line. The detection spectrum 54 is included in the detection data generated by the DAS 18.

Here, the irradiation spectrum 50 irradiated from the X-ray tube 11 to the subject P is attenuated by passing through the subject P. This attenuation depends on the substance contained in the subject P. Therefore, the transmission spectrum 52, which is the spectrum of the X-rays that have passed through the subject P, is a waveform that is attenuated according to the substance contained in the subject P. In other words, theoretically, the waveform detected by the photon counting detector 12 should be the waveform shown in the transmission spectrum 52.

However, as shown in FIG. 5, the detection spectrum 54 actually detected by the photon counting detector 12 has a waveform that is a distorted version of the transmission spectrum 52. It is known that this spectral distortion is caused by the response characteristics of the photon counting detector 12.

The response characteristics of the photon counting detector 12 are, in detail, the response characteristics of each of the detection elements provided in the photon counting detector 12. The response characteristics of the detection elements are factors that cause distortion in the transmission spectrum 52 of the X-rays incident on the detection elements. The response characteristics of the detection elements are, for example, the probability of escape, fluorescence, crosstalk, and scattering occurring for each energy of the X-rays incident on the detection element, and the variation in the detected energy.

Therefore, in this embodiment, the pre-processing function 442 performs processing to correct the detection spectrum 54, which has a waveform that is a distorted version of the transmission spectrum 52. Since the processing to correct the distorted spectrum can be performed using known processing as appropriate, a description thereof will be omitted.

Fig. 6 is a diagram illustrating an example of a corrected spectrum 56 obtained by correcting the detection spectrum 54 according to the first embodiment. As shown in Fig. 6, the pre-processing function 442 acquires the corrected spectrum 56 obtained by correcting the detection spectrum 54 in Fig. 5 as an energy spectrum transmitted through the subject P. The pre-processing function 442 performs the above processing for each detection element of the photon counting detector 12. The pre-processing function 442 performs pre-processing such as logarithmic conversion processing on the acquired corrected spectrum 56 to generate projection data.

Returning to FIG. 1, the explanation will be continued. The reconstruction processing function 443 performs reconstruction processing on the projection data generated by the preprocessing function 442 using a filtered back projection method (FBP method), an iterative reconstruction method, reconstruction using AI, or the like to generate CT image data. The reconstruction processing function 443 stores the reconstructed CT image data in the memory 41.

The projection data generated from the counting results obtained by photon counting CT contains information on the energy of X-rays attenuated by passing through the subject P. Therefore, the reconstruction processing function 443 can reconstruct X-ray CT image data of a specific energy component, for example. The reconstruction processing function 443 can also reconstruct X-ray CT image data of each of a plurality of energy components, for example.

Therefore, for example, the reconstruction processing function 443 reconstructs X-ray CT image data for each energy bin that constitutes the correction spectrum 56. The X-ray CT image data in this case is an example of an energy image.

Figure 7 is a diagram showing an example of energy bins constituting the correction spectrum 56 according to the first embodiment. In the example of Figure 7, the correction spectrum 56 is composed of energy bin1 (b1), energy bin2 (b2), energy bin3 (b3), energy bin4 (b4), energy bin5 (b5), and energy bin6 (b6).

In the example of FIG. 7, the reconstruction processing function 443 reconstructs X-ray CT image data (hereinafter also referred to as reconstructed images) based on each of the energy bins 1 to 6. FIG. 8 is a diagram illustrating an example of a plurality of X-ray CT image data reconstructed for each energy bin according to the first embodiment. As shown in FIG. 8, in the example of FIG. 7, the reconstruction processing function 443 reconstructs a reconstructed image BI1 corresponding to energy bin1. Similarly, the reconstruction processing function 443 reconstructs reconstructed images BI2 to BI6 corresponding to each of the energy bins 2 to 6.

The reconstruction processing function 443 can also generate an integral image by integrating the total energy, for example, by accumulating energy bin1 to bin6.

Returning to FIG. 1, the explanation will be continued. The image processing function 444 performs various image processing on the reconstructed image data (volume data) in response to, for example, a user instruction via the input interface 43. As this image processing can be performed by any known processing as appropriate, the explanation will be omitted.

The identification function 445 identifies the energy bin to be displayed for each of the multiple detection elements based on the multiple reconstructed image data reconstructed for each energy bin. For example, the identification function 445 calculates a statistical value of the concentration value (CT value) of the pixel of the multiple reconstructed image data reconstructed for each energy bin. Then, based on the calculated statistical value, the identification function 45 identifies the reconstructed image data to be used to generate the display image for the detection element corresponding to the pixel.

Examples of CT value statistics include maximum values, minimum values, and average values. In this embodiment, the identification function 445 identifies the energy bin to be displayed based on the statistical value selected by the user from the maximum values, minimum values, and average values. Note that in this embodiment, the statistical values of the CT values are the maximum values, minimum values, and average values, but the statistical values of the CT values are not limited to these. The statistical value of the CT values may be, for example, the median, the mode, the 75th percentile value, etc.

Figure 9 is a diagram illustrating an example of a process for identifying pixels to be displayed according to the first embodiment. In Figure 9, pixel BP1 represents one pixel of reconstructed image BI1. Similarly, pixel BP2 represents one pixel of reconstructed image BI2, pixel BP3 represents one pixel of reconstructed image BI3, pixel BP4 represents one pixel of reconstructed image BI4, pixel BP5 represents one pixel of reconstructed image BI5, and pixel BP6 represents one pixel of reconstructed image BI6.

In addition, pixel BP2 in reconstructed image BI2 to pixel BP6 in reconstructed image BI6 represent pixels at pixel positions corresponding to the pixel position of pixel BP1 in reconstructed image BI1. For ease of explanation, the following explanation will be given assuming that pixels BP1 to BP6 correspond to detection element 12a shown in FIG. 3.

For example, if the user selects the minimum value as the statistical value, the identification function 445 compares the CT values of pixels BP1 to BP6. Then, the identification function 445 identifies the pixel with the smallest CT value among pixels BP1 to BP6. For example, if pixel BP6 has the smallest CT value, the identification function 445 identifies pixel BP6 of reconstructed image BI6 as the pixel of the reconstructed image to be used to generate the image for display.

For example, if the user selects the maximum value as the statistical value, the identification function 445 identifies the pixel with the maximum CT value among pixels BP1 to BP6. For example, if the user selects the average value as the statistical value, the identification function 445 calculates the average value of the CT values of pixels BP1 to BP6, and identifies the pixel showing this CT value as the pixel to be used in generating the image for display. The identification function 445 also performs the same process as above for all pixels (detection elements).

Returning to FIG. 1, the explanation will be continued. The display image generating function 446 generates a display image based on the energy bin of the display target identified by the identifying function 445. For example, the display image generating function 446 generates the display image by synthesizing pixels of the reconstructed image used to generate the display image, which is identified for each detection element by the identifying function 445.

For example, suppose that the identification function 445 identifies pixel BP6 of reconstructed image BI6 for detection element 12a as the pixel of the reconstructed image to be used to generate the display image.

In this case, as shown in FIG. 9, for detection element 12a, the display image generating function 446 uses pixel BP6 of reconstructed image BI6 as the pixel for generating the display image. The display image generating function 446 also performs similar processing for the other detection elements. Then, the display image generating function 446 synthesizes the pixels used for each of the multiple detection elements to generate the display image FI.

The display image FI generated by the display image generation function 446 is displayed, for example, on a display 42 by the system control function 441.

For example, when the minimum value is selected as the statistical value of the CT value, the display image FI generated by the display image generation function 446 is an image that emphasizes the parts absorbed in the low energy band. Also, when the maximum value is selected as the statistical value of the CT value, the display image FI generated by the display image generation function 446 is an image that emphasizes the parts absorbed in the high energy band.

For example, when the average value is selected as the statistical value of the CT value, the display image FI generated by the display image generation function 446 is the average of all energy bands, and therefore is an integral image similar to a normal CT image.

For example, if the median is selected as the statistical value of the CT value, the display image generation function 446 rearranges BP1 to BP6 in order of the number of detections and displays the pixel at the center. In this case, the display image FI generated by the display image generation function 446 is an image in which the low energy side, high energy side, and medium energy side are different depending on the pixel.

Note that, although one pixel is used for one detection element in the above, multiple pixels may be used. For example, in the examples of Figures 9 and 10, if the user selects the minimum value as the statistical value and uses two pixels, the identification function 445 identifies the pixel with the smallest CT value and the pixel with the second smallest CT value among pixels BP1 to BP6.

In this case, the display image generating function 446 generates a composite pixel by, for example, superimposing the pixel with the smallest CT value on the pixel with the second smallest CT value. The display image generating function 446 executes this process for all detection elements to generate a display image. By employing multiple pixels in this manner, the proportion of components due to noise in the display image can be reduced. In other words, the photon counting X-ray CT device 1 according to the first embodiment can prevent degradation of the image quality of the display image.

Next, the process executed by the photon counting X-ray CT device 1 according to the first embodiment will be described. FIG. 10 is a flowchart showing an example of the process executed by the photon counting X-ray CT device 1 according to the first embodiment.

First, the pre-processing function 442 acquires a detection spectrum for each of the multiple detection elements (step S1). For example, the pre-processing function 442 acquires the detection spectrum output from the DAS 18.

Next, the pre-processing function 442 generates projection data from the detection spectrum acquired in step S1 (step S2). For example, the pre-processing function 442 performs processing to correct distortion in the detection spectrum. In addition, for example, the pre-processing function 442 performs pre-processing such as logarithmic conversion processing, offset correction processing, inter-channel sensitivity correction processing, and beam hardening correction on the distortion-corrected correction spectrum to generate projection data.

Next, the reconstruction processing function 443 generates reconstructed X-ray image data for each energy bin based on the projection data generated in step S2 (step S3). For example, the reconstruction processing function 443 reconstructs reconstructed image data for each energy bin that constitutes the correction spectrum 56.

Next, the identification function 445 calculates statistical values of the CT values for the multiple reconstructed image data reconstructed in step S3 for each of the multiple detection elements (step S4). For example, the identification function 445 calculates the maximum CT value of the corresponding pixel of the reconstructed image data for each of the multiple detection elements. Note that the identification function 445 may calculate the minimum, average, median, 75% tile value, etc. of the CT value as the statistical value.

Next, the identification function 445 identifies pixels to be used to generate the display image from among the pixels of the multiple reconstructed image data reconstructed in step S3 based on the statistical value calculated in step S4 (step S5). For example, if a maximum value is calculated as the statistical value in step S4, the identification function 445 identifies the pixel of the reconstructed image data showing the maximum CT value from among the pixels of the multiple reconstructed image data reconstructed in step S3 as the pixel to be used to generate the display image.

Next, the display image generating function 446 generates a display image based on the pixels to be used to generate the display image identified in step S5 (step S6). For example, the display image generating function 446 generates the display image by synthesizing the pixels to be used to generate the display image identified for each of the multiple detection elements.

Next, the system control function 441 controls the display 42 to display the display image generated in step S6 (step S7), and ends this process.

As described above, the photon counting X-ray CT device 1 according to the first embodiment generates reconstructed image data for each energy bin, and identifies the energy bin to be displayed for each of the multiple detection elements based on the multiple reconstructed image data generated, and generates an image for display based on the energy bin.

Since the CT value of the pixel of the reconstructed X-ray CT image data changes depending on the energy bin to be displayed, it is possible to generate a display image with adjusted contrast by changing the conditions for identifying the energy bin to be displayed. In other words, the photon counting X-ray CT device 1 according to the first embodiment can efficiently adjust the contrast of the image generated by PCCT.

The photon counting X-ray CT device 1 according to the first embodiment also identifies the energy bin to be displayed for each of the multiple detection elements based on the statistical values of the CT values of the pixels that constitute the reconstructed image data.

As a result, for example, when the statistical value is a minimum value, an image can be generated that emphasizes the parts absorbed in the low energy band. Also, for example, when the statistical value is a maximum value, an image can be generated that emphasizes the parts absorbed in the high energy band. Also, for example, when the statistical value is an average value, an integral image similar to that of normal CT can be generated. Also, for example, when the statistical value is a median value, an image can be generated in which the low energy side, high energy side, and medium energy side differ depending on the pixel.

Therefore, if the photon counting X-ray CT device 1 according to the first embodiment is configured so that the user can select the type of statistical value, the user can adjust the contrast of the generated display image, for example, simply by selecting a statistical amount according to the part that the user wants to emphasize.

Second Embodiment
In the first embodiment, an energy bin to be displayed is specified for each of a plurality of detection elements based on a plurality of reconstructed image data reconstructed for each energy bin. In the second embodiment, an energy bin to be displayed is specified for each of a plurality of detection elements from a statistical value based on an energy spectrum transmitted through the subject P.

The following mainly describes the differences from the above-described embodiments, and omits detailed descriptions of the commonalities with the contents already described. Furthermore, each embodiment described below may be implemented individually or in appropriate combination.

First, the configuration of the photon counting X-ray CT device 1a according to the second embodiment will be described. FIG. 11 is a block diagram showing an example of the configuration of the photon counting X-ray CT device 1a according to the second embodiment.

The photon counting X-ray CT device 1a has a gantry device 10, a bed device 30, and a console device 40a. The console device 40a also has a memory 41, a display 42, an input interface 43, and a processing circuit 44a.

The processing circuit 44a also executes a system control function 441, a preprocessing function 442a, a reconstruction processing function 443a, an image processing function 444, and a specification function 445a by a processor that executes a program deployed in memory. The reconstruction processing function 443a is an example of a reconstruction unit. The specification function 445a is an example of a calculation unit and a specification unit.

First, the identification function 445a will be described. The identification function 445a identifies the energy bin to be imaged for each of the multiple detection elements. For example, the identification function 445a calculates a statistical value based on the energy spectrum transmitted through the subject. Then, the identification function 445a identifies the energy bin to be imaged based on the statistical value.

The process of identifying energy bins to be imaged will be described below with reference to FIG. 12. FIG. 12 is a diagram illustrating an example of the process of identifying energy bins to be imaged according to the second embodiment. In the example of FIG. 12, similar to FIG. 7, the energy bins constituting the correction spectrum 56 of the detection element 12a in FIG. 3 are shown. Also, similar to FIG. 7, the correction spectrum 56 is composed of energy bin 1 (b1) to energy bin 6 (b6).

The specific function 445a calculates statistical values of the photon count numbers for energy bin 1 to energy bin 6. For example, the specific function 445a calculates the maximum, minimum, and average values of the photon count numbers. Note that, as in the first embodiment, the statistical values to be calculated may be selectable by the user.

The statistical value of the photon count number is not limited to the maximum value, minimum value, and average value. For example, the statistical value of the photon count number may be the median value, the mode value, the 75th percentile value, etc. In the example of FIG. 12, a case where the minimum value is calculated as the statistical value of the photon count number is described as an example.

The identification function 445a calculates the photon count number of energy bin 6 as the minimum value of the photon count numbers of energy bin 1 to energy bin 6 because the photon count number of energy bin 6 is the smallest among the photon count numbers of energy bin 1 to energy bin 6. Then, as shown in FIG. 12, the identification function 445a identifies energy bin 6 as the energy bin to be used as the imaging target for the detection element 12a.

Returning to FIG. 11, the explanation will be continued. The reconstruction processing function 443a performs image reconstruction processing for each of the multiple detection elements based on the photon count number of the energy bin identified by the identification function 445a.

For example, the reconstruction processing function 443a reconstructs image data from projection data relating to the energy bins identified for each of the multiple detection elements by the identification function 445a. The reconstructed X-ray CT image data is displayed on the display 42 by the system control function 441.

For example, if the minimum value is selected as the statistical value of the photon count number, the reconstructed image reconstructed by the reconstruction processing function 443a will be an image that emphasizes the parts absorbed in the low energy band.

Also, for example, if the maximum value is selected as the statistical value, the reconstructed image reconstructed by the reconstruction processing function 443a will be an image that emphasizes the parts absorbed in the high energy band.

Also, for example, when the average value is selected as the statistical value, the reconstructed image reconstructed by the reconstruction processing function 443a becomes an integral image similar to a normal CT image.

Also, for example, if the statistical value is the median, an image can be generated in which the low energy side, high energy side, and medium energy side differ depending on the pixel.

Therefore, the user can adjust the contrast of the reconstructed image, for example, by simply selecting a statistical value according to the part they want to emphasize.

Note that in the above, the reconstruction processing function 443a uses one energy bin as the imaging target, but multiple energy bins may be used as the imaging target.

For example, in the example of FIG. 12, if the user selects the minimum value as the statistical value and employs two energy bins, the identification function 445a identifies, among energy bin 1 to energy bin 6, energy bin 6 with the smallest photon count number and energy bin 1 with the second smallest photon count number as the energy bins to be employed as the imaging target.

By using multiple energy bins as the energy bins to be imaged, the ratio of noise to the signal can be reduced, and the decrease in the S/N ratio can be suppressed. In other words, the photon counting X-ray CT device 1a according to the second embodiment can prevent deterioration of the image quality of the reconstructed image data.

Next, the process executed by the photon counting X-ray CT device 1a according to the second embodiment will be described. FIG. 13 is a flowchart showing an example of the process executed by the photon counting X-ray CT device 1a according to the second embodiment. Steps S11 and S12 are similar to steps S1 and S2 in FIG. 10, and therefore will not be described.

After the pre-processing function 442 generates the projection data, the identification function 445a calculates statistical values of the photon count numbers for multiple energy bins (step S13). For example, the identification function 445a calculates the maximum photon count number for multiple corresponding energy bins for each of multiple detection elements. The identification function 445a may also calculate the minimum or average photon count number as a statistical value.

Next, the identification function 445a identifies an energy bin to be imaged for each of the multiple detection elements (step S14). For example, if the identification function 445a has calculated a maximum value as a statistical value in step S13, the identification function 445a identifies, for each of the multiple detection elements, the energy bin that shows the maximum photon count number among the multiple corresponding energy bins, as the energy bin to be used as the imaged object.

Next, the reconstruction processing function 443a performs image reconstruction for each of the multiple detection elements based on the photon count number of the energy bin identified in step S14 (step S15). For example, the reconstruction processing function 443a reconstructs reconstruction image data from projection data related to the energy bin identified for each of the multiple detection elements.

Next, the system control function 441 controls the display 42 to display the reconstructed image data reconstructed in step S15 (step S16), and ends this process.

As described above, the photon counting X-ray CT device 1a according to the second embodiment calculates statistical values based on the energy spectrum transmitted through the subject P, identifies the energy bin to be imaged for each of the multiple detection elements based on the calculated statistical values, and performs reconstruction processing of the reconstructed image data based on the photon count number of the identified energy bin.

Here, the CT value of the pixel of the reconstructed image data that is finally reconstructed changes depending on which energy bin is used to perform the reconstruction process. Therefore, by changing the statistical value used to identify the energy bin to be imaged, it is possible to generate reconstructed image data with adjusted contrast. In other words, the photon counting X-ray CT device 1 according to the second embodiment can efficiently adjust the contrast of images generated by PCCT.

The photon counting X-ray CT device 1 according to the second embodiment also identifies the energy bin to be imaged for each of the multiple detection elements based on the statistical values of the photon count numbers of the corresponding multiple energy bins.

As a result, for example, when the statistical value of the photon count number is a minimum value, reconstructed image data that ultimately emphasizes the portion absorbed in the low energy band is reconstructed, making it possible to generate a display image that emphasizes the portion absorbed in the low energy band. Also, for example, when the statistical value of the photon count number is a maximum value, reconstructed image data that ultimately emphasizes the portion absorbed in the high energy band is reconstructed, making it possible to generate a display image that emphasizes the portion absorbed in the high energy band. Also, for example, when the statistical value of the photon count number is an average value, reconstructed image data that is an average across all energy bands is reconstructed, making it possible to generate a display image similar to a normal CT image.

Therefore, for example, by configuring the photon counting X-ray CT device 1 according to the second embodiment so that the user can select the type of statistical value of the photon count number, the user can adjust the contrast of the reconstructed image data by simply selecting the statistical amount.

The above-described embodiment can be modified as appropriate by changing a portion of the configuration or function of each device. Therefore, several modified examples of the above-described embodiment will be described below as other embodiments. Note that the following will mainly describe the differences from the above-described embodiment, and detailed descriptions of the points in common with the contents already described will be omitted. The modified examples described below may be implemented individually or in appropriate combination.

(Variation 1)
In the above-described first and second embodiments, a description has been given of a form in which the generated display image or the reconstructed image data (hereinafter also referred to as a contrast-adjusted image) is directly displayed on the display 42. However, the system control function 441 may superimpose the contrast-adjusted image on the integral image and display it on the display 42 or the like.

In addition, the display image generating function 446 may generate a display image by superimposing a contrast adjustment image on an integral image. In this case, the system control function 441 may display the superimposed image generated by the display image generating function 446 on the display 42, etc.

This makes it possible to obtain results similar to those achieved by adjusting the contrast of the integral image by changing the conditions for identifying the energy bin to be displayed (imaged). In addition, by superimposing the integral image and the display object, the effects of noise can be reduced, thereby improving the image quality of the displayed image.

(Variation 2)
In the above-described first and second embodiments, a contrast image is generated (reconstructed) for the entire subject P. However, a contrast image may be generated (reconstructed) for only a specific part (e.g., the heart) of the subject P.

In this modified example, for example, the system control function 441 accepts input from a user specifying the range to be targeted for generating (reconstructing) a contrast image on a scanogram generated by scanogram photography (also called positioning photography or positioning scan). Then, each function of the processing circuit 44 (44a) executes processing related to generating (reconstructing) a contrast image only for the specified target range.

The system control function 441 may automatically determine the target range from the captured scan image, for example, by using a data table that associates the scan image with the target range.

In addition, in this modified example, the system control function 441 superimposes a contrast image in which only the target range is drawn on the integral image and displays it on the display 42. The display image generation function 446 may generate a display image in which a contrast image in which only the target range is drawn is superimposed on the integral image.

Furthermore, for example, each function of the processing circuit 44 (44a) may generate (reconstruct) a contrast image based on a statistical value different from that of the target range for an area other than the target range. For example, when each function of the processing circuit 44 (44a) generates (reconstructs) a contrast image based on a minimum value for the target range, it may generate (reconstruct) a contrast image based on a maximum value for an area outside the target range.

In this case, the system control function 441 may combine a contrast image based on the maximum value in which only the outside of the target range is depicted, and a contrast image based on the minimum value in which only the target range is depicted, and display the result on the display 42.

Here, FIG. 14 is an image diagram explaining an example of a display image (reconstructed image) according to Modification Example 2. Display image (reconstructed image) II in FIG. 14 shows an example of a display image (reconstructed image) showing a specific cross section of subject P.

In FIG. 14, each function of the processing circuit 44 (44a) generates (reconstructs) a contrast image based on the minimum value for the target range area TA of the subject P. Also, each function of the processing circuit 44 (44a) generates (reconstructs) a contrast image based on the maximum value for the out-of-target range area OA. Then, each function of the processing circuit 44 (44a) displays a display image (reconstructed image) II that is a combination of the two on the display 42.

As a result, for the target range area TA, the parts absorbed in the low energy band are emphasized, and for the outside target range OA, the parts absorbed in the low energy band are less noticeable. Therefore, in the above example, each function of the processing circuit 44 (44a) can draw an image in which the parts absorbed in the low energy band are more emphasized for the target range area TA.

Note that the above is just one example, and the combination of the statistical values used to generate (reconstruct) the display image (reconstructed image) in the target range area TA and the statistical values used to generate (reconstruct) the display image (reconstructed image) in the outside target range area OA is not limited to the above.

For example, a contrast image based on the minimum value may be generated (reconstructed) for the target range area TA, and a contrast image based on the median value may be generated (reconstructed) for the out-of-target range area OA. Also, for example, a contrast image based on the maximum value may be generated (reconstructed) for the target range area TA, and a contrast image based on the median value may be generated (reconstructed) for the out-of-target range area OA.

The photon counting X-ray CT device 1 according to this modified example can adjust the contrast only for the area of interest of the subject P. Furthermore, the photon counting X-ray CT device 1 according to this modified example can generate (reconstruct) a display image (reconstructed image) that further emphasizes the area of interest of the subject P.

(Variation 3)
In the above-described first and second embodiments, a contrast image based on predetermined statistics is generated (reconstructed) and displayed on the display 42. However, a list for selecting statistics may be displayed on the display 42, and the corresponding contrast image may be switched and displayed according to the selection of the statistics by the user.

In this modified example, for example, the system control function 441 causes the display 42 to display, together with the display image (or reconstructed image data), a list for selecting a statistic to be used to identify an energy bin from "maximum value," "minimum value," and "average value." Note that the image displayed together with the list may be an integral image.

For example, when the system control function 441 receives an instruction from the user to select "minimum value," the identification function 445 (445a) identifies the energy bin of the display object (image object) based on the minimum value of the photon count number for each of multiple detection elements.

Next, the display image generation function 446 (or the reconstruction processing function 443a) generates (reconstructs) a display image (or a reconstructed image) based on the energy bin. Then, the system control function 441 displays on the display 42 the display image (or the reconstructed image) based on the "minimum value" in place of the image that had been displayed up until that point.

For example, in the above state, if the system control function 441 receives an instruction from the user to select the "maximum value", the same process as above is executed. As a result, the display image (or reconstructed image) based on the "maximum value" is displayed on the display 42 instead of the display image (or reconstructed image) based on the "minimum value".

In addition, the system control function 441 may receive display instructions from the user, such as "superimposing a contrast image on an integral image" or "displaying a contrast image based on two or more energy bins."

According to this modified example, the user can adjust the contrast of the displayed image simply by selecting a statistic while looking at the display 42.

(Variation 4)
In the above-described first and second embodiments, a form has been described in which the processing circuit 44 (44a) of the console device 40 (40a) has a system control function 441, a pre-processing function 442, a reconstruction processing function 443 (443a), an image processing function 444, a specification function 445 (445a), and a display image generation function 446.

However, all or part of these functions may be performed by a computer such as a workstation connected to the photon counting X-ray CT device 1 (1a) via a network.

According to at least one of the embodiments described above, contrast adjustment of images generated by PCCT can be performed efficiently.

Although several embodiments of the present invention 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, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

Reference Signs List 1, 1a Photon counting X-ray CT device 10 Mount device 11 X-ray tube 12 Photon counting detector 13 Rotating frame 14 X-ray high voltage device 15 Control device 16 Bowtie filter 17 Collimator 18 DAS (Data Acquisition System)
30 Bed device 31 Base 32 Bed driving device 33 Top plate 34 Top plate support frame 40, 40a Console device 41 Memory 42 Display 43 Input interface 44, 44a Processing circuit 441 System control function 442 Pre-processing function 443, 443a Reconstruction processing function 444 Image processing function 445, 445a Identification function 446 Display image generation function

Claims (15)

an X-ray tube that irradiates an object with X-rays;
a photon-counting detector including a plurality of detection elements and counting photons contained in the X-rays;
an acquisition unit that acquires an energy spectrum transmitted through the subject for each of the plurality of detection elements;
a reconstruction unit that reconstructs a plurality of energy images for each energy bin that constitutes the energy spectrum;
an identifying unit that identifies an energy bin to be displayed for each of the plurality of detection elements based on the plurality of energy images;
a generation unit that generates a display image based on the energy bin of the display object identified by the identification unit;
An X-ray CT apparatus comprising: the identifying unit identifies the energy bin to be displayed for each of the plurality of detection elements based on a statistical value of the CT values of the plurality of energy images;
The X-ray CT apparatus according to claim 1. The statistical values include at least one of a maximum value, a minimum value, a mean value, a median value, a mode value, and a 75th percentile value.
The X-ray CT apparatus according to claim 2. The identification unit identifies a plurality of energy bins to be displayed for each of the plurality of detection elements based on the statistical value.
The X-ray CT apparatus according to claim 2. The identification unit identifies an energy bin to be displayed for each of the plurality of detection elements based on the statistical value selected by a user.
The X-ray CT apparatus according to claim 2. A display control unit that displays the display image generated by the generation unit on a display unit,
The reconstruction unit reconstructs an integral image by integrating all energy,
The display control unit causes the display image to be superimposed on the integral image.
6. The X-ray CT apparatus according to claim 1. an X-ray tube that irradiates an object with X-rays;
a photon-counting detector including a plurality of detection elements and counting photons contained in the X-rays;
an acquisition unit that acquires an energy spectrum transmitted through the subject for each of the plurality of detection elements;
A calculation unit for calculating a statistical value based on the energy spectrum;
an identification unit that identifies an energy bin of an imaging object based on the statistical value for each of the plurality of detection elements;
a reconstruction unit that performs image reconstruction for each of the plurality of detection elements based on the count of the energy bin identified by the identification unit;
An X-ray CT apparatus comprising: The statistical values include at least one of a maximum, a minimum, a mean, a median, a mode, and a 75th percentile value of the photon count number of the energy bin.
The X-ray CT apparatus according to claim 7. The identification unit identifies energy bins of a plurality of imaging objects for each of the plurality of detection elements based on the statistical value.
The X-ray CT apparatus according to claim 7. the identifying unit identifies an energy bin of an imaging target for each of the plurality of detection elements based on the statistical value selected by a user;
The X-ray CT apparatus according to claim 7. A display control unit that displays the reconstructed image reconstructed by the reconstruction unit on a display unit,
The reconstruction unit reconstructs an integral image by integrating all energy,
The display control unit causes the reconstructed image to be superimposed on the integral image.
11. The X-ray CT apparatus according to claim 7. 1. An information processing method using an X-ray CT apparatus including an X-ray tube that irradiates an object with X-rays and a photon-counting detector that includes a plurality of detection elements and counts photons contained in the X-rays,
an acquisition step of acquiring an energy spectrum transmitted through the subject for each of the plurality of detection elements;
a reconstruction step of reconstructing a plurality of energy images for each energy bin constituting the energy spectrum;
a step of identifying an energy bin to be displayed for each of the plurality of detection elements based on the plurality of energy images;
a generating step of generating a display image based on the energy bins of the display object identified in the identifying step;
An information processing method comprising: 1. An information processing method using an X-ray CT apparatus including an X-ray tube that irradiates an object with X-rays and a photon-counting detector that includes a plurality of detection elements and counts photons contained in the X-rays,
an acquisition step of acquiring an energy spectrum transmitted through the subject for each of the plurality of detection elements;
calculating a statistical value based on the energy spectrum;
identifying an energy bin of an image object for each of the plurality of detector elements based on the statistical value;
a reconstruction step of performing image reconstruction for each of the plurality of detector elements based on the count of the energy bins identified in the identification step;
An information processing method comprising: A computer of an X-ray CT apparatus including an X-ray tube that irradiates an object with X-rays and a photon-counting detector that includes a plurality of detection elements and counts photons contained in the X-rays,
an acquisition step of acquiring an energy spectrum transmitted through the subject for each of the plurality of detection elements;
a reconstruction step of reconstructing a plurality of energy images for each energy bin constituting the energy spectrum;
a step of identifying an energy bin to be displayed for each of the plurality of detection elements based on the plurality of energy images;
a generating step of generating a display image based on the energy bins of the display object identified in the identifying step;
A program that executes the following. A computer of an X-ray CT apparatus including an X-ray tube that irradiates an object with X-rays and a photon-counting detector that includes a plurality of detection elements and counts photons contained in the X-rays,
an acquisition step of acquiring an energy spectrum transmitted through the subject for each of the plurality of detection elements;
calculating a statistical value based on the energy spectrum;
identifying an energy bin of an image object for each of the plurality of detector elements based on the statistical value;
a reconstruction step of performing image reconstruction for each of the plurality of detector elements based on the count of the energy bins identified in the identification step;
A program that executes the following.

Images