Medical image processing device, method for controlling same, and medical image processing program

Abstract

To enable comparison between medical images obtained using different X-ray detection systems to be performed more easily.SOLUTION: A medical image processing device is configured to: acquire first data obtained using a first X-ray detection system and second data obtained using a second X-ray detection system different from the first X-ray detection system; process the first data or a signal for obtaining the first data to generate third data made to resemble the second data; and align data based on the first data with data based on the second data on the basis of the result of aligning the data based on the second data with data based on the third data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a medical image processing apparatus, a control method thereof, and a medical image processing program. [Background technology]

[0002] Generally, CT devices using X-ray detectors of an integral type X-ray detection method (integral method) are widespread, while in recent years, CT devices using X-ray detectors of a photon counting type X-ray detection method (hereinafter, photon counting method) are also being put to practical use. Patent Document 1 discloses an X-ray CT device of a photon counting method based on count data of X-ray photons collected using a signal detected by an X-ray detector. The X-ray CT device of the photon counting method can obtain a high-resolution image with a lower dose than an X-ray CT device of an integral method based on integral data obtained by integrating a signal detected by an X-ray detector over a predetermined time width. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-127635 A Summary of the Invention [Problem to be solved by the invention]

[0004] For example, in follow-up observations, there are cases where medical images obtained using different X-ray detection methods need to be compared, such as when comparing a CT image previously obtained using the integral method with a new CT image obtained using the photon counting method. However, it is difficult to properly compare medical images obtained using different X-ray detection methods, such as a CT image obtained using the photon counting method with a CT image obtained using the integral method. This is because the differences between the two medical images include a mixture of differences caused by improvements in image quality and differences caused by changes over time, such as changes in lesions, making it difficult to align the images obtained using both methods, and furthermore, the mixture of differences makes it difficult to recognize changes over time.

[0005] The disclosure herein provides techniques to make it easier to compare medical images obtained with different X-ray detection modalities. [Means for solving the problem]

[0006] A medical image processing apparatus according to an aspect of the present specification includes: an acquisition means for acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; A generating means for generating third data similar to the second data by processing the first data or a signal for acquiring the first data; and an alignment means for aligning the data based on the first data and the data based on the second data based on a result of aligning the data based on the second data and the data based on the third data.

[0007] Also, a method for controlling a medical image processing apparatus according to an aspect of the present specification includes: acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; A generating step of generating third data similar to the second data by processing the first data or a signal for acquiring the first data; and an alignment process of aligning the data based on the first data and the data based on the second data based on a result of aligning the data based on the second data and the data based on the third data.

[0008] Also, a medical image processing program according to an aspect of the present specification includes an acquisition step of acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; A generating step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data; and an alignment step of aligning the data based on the first data and the data based on the second data based on a result of aligning the data based on the second data and the data based on the third data. Effect of the Invention

[0009] The disclosure herein makes it easier to compare images obtained using different X-ray detection modalities. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of the configuration of an X-ray CT apparatus according to an embodiment. [Diagram 2] FIG. 2 is a diagram for explaining an X-ray detector according to the embodiment. [Figure 3A] 1 is a flowchart showing medical image processing according to a first processing example. [Figure 3B] 1 is a flowchart showing medical image processing according to a first processing example. [Figure 3C] 13 is a flowchart showing medical image processing according to a processing example 2. [Figure 3D] 13 is a flowchart showing medical image processing according to a processing example 2. [Figure 3E]13 is a flowchart showing medical image processing according to a processing example 3. [Figure 3F] 13 is a flowchart showing medical image processing according to a processing example 4. [Figure 3G] 13 is a flowchart showing a learning process according to a processing example 4. [Figure 3H] 13 is a flowchart showing medical image processing according to a processing example 5. [Figure 4A] FIG. 13 is a diagram showing a display example of a tomographic image according to the processing example 1. [Figure 4B] FIG. 13 is a diagram showing a display example of a tomographic image according to the processing example 1. [Figure 4C] 13A and 13B are diagrams showing a display example of information indicating a difference image or a difference region according to the processing example 2. [Figure 4D] 13A and 13B are diagrams showing a display example of information indicating a difference image or a difference region according to the processing example 2. [Diagram 5] FIG. 13 is a diagram showing a display example of an image data set according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the embodiments will be described in detail with reference to the attached drawings. Note that the following embodiments do not limit the invention according to the claims. Although the embodiments describe a number of features, not all of these features are essential to the invention, and the features may be combined in any manner. Furthermore, in the attached drawings, the same reference numbers are used for the same or similar configurations, and duplicated descriptions are omitted.

[0012] In the following, the embodiments of the medical image processing device, the X-ray CT device, and the processing program disclosed in this specification will be described in detail. Note that the medical image processing device, the X-ray CT system, and the processing program according to the present application are not limited to the embodiments shown below. In addition, in the following, an X-ray detector will be used as an example of the radiation detector, and an X-ray CT device will be used as an example of the radiation diagnostic device.

[0013] The X-ray CT device described in the following embodiments is a device capable of performing photon-counting CT. That is, the X-ray CT device described below is a device capable of reconstructing X-ray CT image data with a high signal-to-noise ratio by counting the number of photons generated by X-rays that have passed through a subject using a photon-counting X-ray detector. The X-ray detector described in the following embodiments is a direct conversion detector that directly converts X-ray photons into electric charges proportional to the energy.

[0014] FIG. 1 is a diagram showing an example of the configuration of a photon-counting X-ray CT apparatus 1 according to an embodiment. As shown in FIG. 1, the X-ray CT apparatus 1 according to the embodiment includes a gantry 10, a bed 30, and a console 40. In FIG. 1, the direction of the rotation axis of the rotating frame 13 in a non-tilted state or the longitudinal direction of the top plate 33 of the bed 30 is defined as the Z-axis direction. Also, the axial direction perpendicular to the Z-axis direction and horizontal to the floor surface is defined as the X-axis direction. Also, the axial direction perpendicular to the Z-axis direction and perpendicular to the floor surface is defined as the Y-axis direction. Note that, although FIG. 1 includes a diagram in which the gantry 10 is drawn from a plurality of directions for the purpose of explanation, the X-ray CT apparatus 1 according to the embodiment is assumed to have one gantry 10.

[0015] The gantry device 10 includes an X-ray tube 11, an X-ray detector 12, a rotating frame 13, an X-ray high voltage device 14, a control device 15, a wedge 16, a collimator 17, and a DAS 18. Note that DAS is an abbreviation for Data Acquisition System.

[0016] The X-ray tube 11 is a vacuum tube having a cathode (filament) that generates thermoelectrons and an anode (target) that generates X-rays upon impact of the thermoelectrons. The X-ray tube 11 generates X-rays to be irradiated onto the subject P by irradiating thermoelectrons from the cathode to the anode upon application of high voltage from the X-ray high voltage device 14. For example, the X-ray tube 11 may be a rotating anode type X-ray tube that generates X-rays by irradiating a rotating anode with thermoelectrons.

[0017] The rotating frame 13 is an annular frame that supports the X-ray tube 11 and the X-ray detector 12 facing each other and rotates the X-ray tube 11 and the X-ray detector 12 under the control of the control device 15. For example, the rotating frame 13 is a casting made of aluminum. Note that the rotating frame 13 can further support an X-ray high voltage device 14, a wedge 16, a collimator 17, a DAS 18, etc. in addition to the X-ray tube 11 and the X-ray detector 12. The rotating frame 13 can also further support various components not shown in FIG. 1.

[0018] The wedge 16 is a filter for adjusting the amount of X-rays irradiated from the X-ray tube 11. Specifically, the wedge 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. For example, the wedge 16 is a filter made of aluminum or the like processed to have a predetermined target angle and a predetermined thickness, and includes a wedge filter or a bowtie filter.

[0019] The collimator 17 narrows down the irradiation range of the X-rays that have passed through the wedge 16. The collimator 17 has a slit formed by combining a plurality of lead plates or the like. The collimator 17 may also be called an X-ray aperture. Although FIG. 1 shows a case in which the wedge 16 is disposed between the X-ray tube 11 and the collimator 17, the collimator 17 may be disposed between the X-ray tube 11 and the wedge 16. In this case, the wedge 16 transmits and attenuates the X-rays that are irradiated from the X-ray tube 11 and whose irradiation range is limited by the collimator 17.

[0020] X-ray high voltage device 14 has a high voltage generating unit that generates a high voltage to be applied to X-ray tube 11, and an X-ray control unit that controls an output voltage according to the X-rays generated by X-ray tube 11. The method of generating a high voltage by the high voltage generating unit may be, for example, a transformer method or an inverter method. X-ray high voltage device 14 may be provided on rotating frame 13, or may be provided on a fixed frame (not shown).

[0021] 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 control device 15 receives a signal from an input interface 43 of the console device 40 and controls the operation of the gantry device 10 and the bed device 30. For example, the control device 15 controls the rotation of the rotating frame 13, the tilt of the gantry device 10, the operation of the tabletop 33 by the bed device 30, and the like. For example, in order to tilt the gantry device 10, the control device 15 rotates the rotating frame 13 around an axis parallel to the X-axis direction according to inclination angle (tilt angle) information input from the input interface 43. The control device 15 may be provided in the gantry device 10 or in the console device 40.

[0022] The X-ray detector 12 is a photon-counting detector that outputs a signal capable of measuring the energy value of an X-ray photon every time an X-ray photon is incident. The X-ray photons detected by the X-ray detector 12 are, for example, X-ray photons irradiated from the X-ray tube 11 and transmitted through the subject P. The X-ray detector 12 has a plurality of detection elements that output one pulse of an electric signal (analog signal) every time an X-ray photon is incident. For example, the X-ray detector 12 has a structure in which a plurality of X-ray detection element rows (hereinafter also simply referred to as "detection elements") are arranged in the channel direction along one arc centered on the focus of the X-ray tube 11, and are arranged in a plurality of rows in the slice direction. The detection elements of the X-ray detector 12 can count the number of electric signals (pulses) to count the number of X-ray photons incident on the detection elements. In addition, the energy value of the X-ray photon that caused the output of the signal can be measured by performing a processing operation on the signal.

[0023] FIG. 2 is a schematic diagram showing a configuration of a part of the X-ray detector 12 according to this embodiment. The X-ray detector 12 is a photon-counting detector, and as shown in FIG. 2, includes a detection element 130 and an ASIC 134 that is connected to the detection element 130 and counts the X-ray photons detected by the detection element 130. Note that ASIC is an abbreviation for Application Specific Integrated Circuit. The X-ray detector 12 of this embodiment is a direct conversion type detector that directly converts incident X-ray photons into an electrical signal. FIG. 2 shows one detection element out of a plurality of detection elements that constitute the X-ray detector 12.

[0024] The detection element 130 has a semiconductor 131, a cathode electrode 132, and a plurality of anode electrodes 133. Here, the semiconductor 131 is a semiconductor such as CdTe (cadmium telluride) or CdZnTe (cadmium zinc telluride). Each of the plurality of anode electrodes 133 corresponds to a detection pixel (also called a "pixel"). When an X-ray photon is incident on the detection element 130, the detection element 130 directly converts the X-ray incident on the detection element 130 into an electric charge and outputs it to the ASIC 134 from the anode electrode 133 corresponding to the incident position of the X-ray.

[0025] One ASIC 134 is provided for each of the multiple anode electrodes 133 (i.e., each detection pixel). The ASIC 134 counts the number of incident X-ray photons for each detection pixel of the detection element 130 by discriminating the charge output by the detection element 130. The ASIC 134 also measures the energy of the counted X-ray photons by performing arithmetic processing based on the magnitude of each charge. The ASIC 134 outputs the X-ray photon counting result and / or the X-ray photon energy measurement result to the DAS 18 as digital data.

[0026] The ASIC 134 includes, for example, a capacitor 1341, an amplifier circuit 1342, a waveform shaping circuit 1343, a comparator circuit 1344, and a counter 1345. The capacitor 1341 accumulates the charge output by the detection element 130. The amplifier circuit 1342 integrates and amplifies the charge collected in the capacitor 1341 in response to the X-ray photons incident on the detection element 130, and outputs the result as a pulse signal of an electric quantity. The pulse height or area of ​​this pulse signal has a correlation with the energy of the photons.

[0027] The amplifier circuit 1342 includes, for example, an amplifier. The amplifier may be, for example, a single-ended amplifier or a differential amplifier. In the case of a single-ended amplifier, the amplifier is grounded and amplifies the potential difference between the ground potential and the potential indicated by the electrical signal output from the detection element 130. In the case of a differential amplifier, the positive input (+) of the amplifier is connected to the detection element 130 and the negative input (-) is grounded. The differential amplifier amplifies the potential difference between the potential indicated by the electrical signal from the detection element 130 input to the positive input and the ground potential indicated by the signal input to the negative input.

[0028] The waveform shaping circuit 1343 adjusts the frequency characteristics of the pulse signal output from the amplifier circuit 1342 and shapes the waveform of the pulse signal by applying a gain and an offset. The comparator circuit 1344 compares the pulse height or area of ​​the response pulse signal to the incident photons with a threshold value set in advance corresponding to a plurality of energy bands to be discriminated, and outputs the comparison result with the threshold value to the counter 1345 at the downstream stage. The counter 1345 counts the discrimination result of the waveform of the response pulse signal for each corresponding energy band, and outputs the photon count result to the DAS 18 as digital data. For example, the counter 1345 generates digital data indicating the count result of X-ray photons for each of a plurality of energy bands, and outputs the generated digital data to the DAS 18.

[0029] With the above-mentioned configuration, the X-ray detector 12 detects X-ray photons and obtains energy information. It goes without saying that a grid may be provided on the X-ray incident side of the detection element 130 in the above-mentioned X-ray detector 12. The X-ray detector 12 may also be an indirect conversion type photon counting detector including, for example, a grid, a scintillator array, and a photosensor array. The scintillator array includes a plurality of scintillators, and the scintillator is composed of a scintillator crystal that outputs a number of lights according to the energy of the incident X-rays. The grid is disposed on the surface of the scintillator array on the X-ray incident side, and is composed of an X-ray shielding plate having a function of absorbing scattered X-rays. The photosensor array has a function of converting into an electric signal according to the amount of light from the scintillator, and is composed of a photosensor such as a photomultiplier tube. Here, the photosensor is, for example, a PD (Photodiode), an APD (Avalanche Photodiode), or a SiPM (Silicon photomultipliers).

[0030] Returning to FIG. 1, the DAS 18 generates detection data based on the counting result input from the X-ray detector 12. The detection data is, for example, a sinogram. The sinogram is data in which the results of counting the X-ray photons incident on the detection element 130 at each position of the X-ray tube 11 are arranged in a two-dimensional orthogonal coordinate system with the view direction and the channel direction as axes. The DAS 18 generates a sinogram, for example, in units of rows in the slice direction of the X-ray detector 12. Here, the result of the counting process is data in which the number of X-ray photons is assigned to each energy bin. For example, the DAS 18 counts photons (X-ray photons) originating from the X-ray irradiated from the X-ray tube 11 and transmitted through the subject P, and discriminates the energy of the counted X-ray photons to obtain the result of the counting process. The DAS 18 transfers the generated detection data to the console device 40. The DAS 18 is realized, for example, by a processor.

[0031] The data generated by the DAS 18 is transmitted from a transmitter having a light emitting diode (LED) provided on the rotating frame 13 to a receiver having a photodiode (PD) by optical communication, and then transferred to the console device 40. The receiver is provided on a non-rotating part of the gantry 10, such as a fixed frame that rotatably supports the rotating frame 13. Note that the transmitter and receiver are not shown in FIG. 1. Also, the method of transmitting data from the rotating frame 13 to the non-rotating part of the gantry 10 is not limited to optical communication as described above. Any non-contact type data transmission method or a contact type data transmission method may be adopted for transmitting the data generated by the DAS 18.

[0032] The bed device 30 is a device on which the subject P to be imaged is placed and moved, and includes a base 31, a bed driving device 32, a top plate 33, and a support frame 34. The base 31 is a housing that supports the support frame 34 so that it can move in the vertical direction. The bed driving device 32 is a drive mechanism that moves the top plate 33 on which the subject P is placed, in the longitudinal direction of the top plate 33, and includes a motor, an actuator, etc. The top plate 33, which is provided on the upper surface of the support frame 34, is a plate on which the subject P is placed. Note that the bed driving device 32 may move the support frame 34 in the longitudinal direction of the top plate 33 in addition to the top plate 33.

[0033] The console device 40 includes a memory 41, a display unit 42, an input interface 43, and a control unit 44. In the present embodiment, the console device 40 is described as being separate from the gantry device 10, but the gantry device 10 may include the console device 40 or some of the components of the console device 40.

[0034] The memory 41 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 41 stores, for example, projection data and CT image data. Also, for example, the memory 41 stores a program for enabling a control unit included in the X-ray CT apparatus 1 to realize its functions. Note that the memory 41 may be realized by a server group (cloud) connected to the X-ray CT apparatus 1 via a network.

[0035] The display unit 42 displays various information. For example, the display unit 42 displays various images generated by the control unit 44, or displays a GUI (Graphical User Interface) for receiving various operations from the user. For example, the display unit 42 is a liquid crystal display or a CRT (Cathode Ray Tube) display. The display unit 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. The user is a person who uses the X-ray CT device 1, such as an operator or an examiner.

[0036] The input interface 43 functions as an instruction receiving unit that receives various input operations from a user, converts the received input operations into electrical signals, and outputs the electrical signals to the control unit 44. For example, the input interface 43 receives input operations from a user, such as reconstruction conditions when reconstructing CT image data and image processing conditions when generating a post-processed image from CT image data. For example, the input interface 43 can be realized by a mouse, a keyboard, a trackball, a switch, a button, a joystick, a touchpad that performs input operations by touching the operation surface, a touchscreen in which a display screen and a touchpad are integrated, a non-contact input unit using an optical sensor, a voice input unit, and the like. Note that, when the input interface 43 is a touchscreen, the input interface 43 can also function as the display unit 42. The input interface 43 may be provided in the gantry device 10. The input interface 43 may be configured by a tablet terminal or the like that can wirelessly communicate with the console device 40. The input interface 43 is not limited to only those that have physical operation parts such as a mouse and a keyboard. For example, the input interface 43 may be configured to receive an electrical signal corresponding to an input operation from an external input device provided separately from the console device 40 and to output this electrical signal to the control unit 44.

[0037] The control unit 44 controls the overall operation of the X-ray CT apparatus 1. The control unit 44 executes, for example, the functions of the system control unit 441, the pre-processing unit 442, the reconstruction processing unit 443, the image processing unit 444, the scan control unit 445, and the display control unit 446. The functions executed by the functional units of the control unit 44 shown in FIG. 1 are recorded in the memory 41 in the form of a program executable by a computer, for example. The control unit 44 is, for example, a processor, and realizes the functions corresponding to the programs read out by reading them from the memory 41 and executing them. In other words, the control unit 44 in a state in which the programs are read out realizes the functional units shown in the control unit 44 in FIG. 1. Note that, in FIG. 1, the case where the functions of the system control unit 441, the pre-processing unit 442, the reconstruction processing unit 443, the image processing unit 444, the scan control unit 445, and the display control unit 446 are realized by a single control unit 44 is shown, but the present disclosure is not limited to this. For example, the control unit 44 may be configured by combining a plurality of independent processors, and each processor may realize each function by executing each program. Furthermore, each function of the control unit 44 may be realized by being appropriately distributed or integrated into a single or multiple functional units.

[0038] The system control unit 441 controls various functions of the control unit 44 based on input operations received from a user via the input interface 43. The preprocessing unit 442 performs preprocessing such as logarithmic conversion processing, offset correction processing, inter-channel sensitivity correction processing, and beam hardening correction on the detection data output from the DAS 18 to generate projection data. The reconstruction processing unit 443 performs reconstruction processing using a filtered back projection method, an iterative reconstruction method, or the like on the projection data generated by the preprocessing unit 442 to generate CT image data (volume data). The reconstruction processing unit 443 stores the reconstructed CT image data in the memory 41.

[0039] Here, the projection data generated from the counting results obtained by the photon-counting X-ray CT device 1 contains information on the energy of X-rays attenuated by passing through the subject P. Therefore, the reconstruction processing unit 443 can reconstruct CT image data of a specific energy component, for example. Also, the reconstruction processing unit 443 can reconstruct CT image data of each of a plurality of energy components, for example.

[0040] The reconstruction processor 443 can also generate image data in which a color tone according to the energy component is assigned to each pixel of the CT image data of each energy component, and a plurality of CT image data color-coded according to the energy component are superimposed. The reconstruction processor 443 can also generate image data that allows identification of a substance, for example, by utilizing a K-absorption edge specific to the substance. Other image data that the reconstruction processor 443 can generate include monochromatic X-ray image data, density image data, and effective atomic number image data.

[0041] To reconstruct CT image data, projection data for 360° around the subject is required, and projection data for 180°+fan angle is also required in the half-scan method. Either reconstruction method can be applied to this embodiment. For ease of explanation, it is assumed below that a reconstruction (full-scan reconstruction) method is used in which CT image data is reconstructed using 360° of projection data obtained by the X-ray tube 11 and X-ray detector 12 going around the subject and capturing images.

[0042] The image processing unit 444 converts the CT image data generated by the reconstruction processing unit 443 into image data such as a tomographic image of an arbitrary cross section or a three-dimensional image based on an input operation of a user received via the input interface 43. The image processing unit 444 stores the converted image data in the memory 41. The image processing unit 444 also performs medical image processing which will be described later in processing examples 1 to 5.

[0043] The scan control unit 445 controls the CT scan performed by the gantry 10. For example, the scan control unit 445 controls the operations of the X-ray high voltage device 14, the X-ray detector 12, the control device 15, the DAS 18, and the bed driving device 32, thereby controlling the collection process of the counting results in the gantry 10. As an example, the scan control unit 445 controls the collection process of the projection data in the imaging for collecting the positioning image (scanogram) and the main imaging (scan) for collecting the image used for diagnosis. The display control unit 446 controls the various image data stored in the memory 41 to be displayed on the display unit 42.

[0044] A processing example for displaying a tomographic image based on projection data acquired by a photon-counting type X-ray detection method and a tomographic image based on projection data acquired by an integral type X-ray detection method by the X-ray CT device 1 of this embodiment having the above-mentioned configuration will be described below. The integral type X-ray detection method is an X-ray detection method that generates a CT image based on integral data obtained by integrating a signal detected by an X-ray detector over a predetermined time width. Hereinafter, data acquired by the photon-counting type X-ray detection method (the "data" described here includes images such as tomographic images) may be referred to as "photon-counting type acquired" data or "PC type" data. Similarly, data acquired by the integral type X-ray detection method may be referred to as "integral type acquired" data or "integral type" data. According to each processing example described below, the positional deviation and image quality difference between a tomographic image acquired by a photon-counting method and a tomographic image acquired by an integral method are reduced, and a display suitable for medical diagnosis can be obtained.

[0045] <Processing example 1> In the processing example 1, a signal for acquiring the first data is processed to generate third data so as to reduce a difference between the image quality of an image acquired based on the first data acquired by the X-ray CT device 1 using a photon counting method and the image quality of an image acquired based on the second data acquired in a past examination using an integral method. The generated third data is used for alignment and interpretation. Fig. 3A is a flowchart for explaining the processing by the image processing unit 444 and the display control unit 446 in the processing example 1.

[0046] In S101, the image processor 444 acquires first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method that is an X-ray detection method different from the first X-ray detection method. In this example, the first data and the second data are acquired in examinations at different dates and times, and the first data is first projection data (hereinafter, PC type projection data) acquired by a CT device of a photon counting method (hereinafter, PC type CT device) in a current examination. The second data is second projection data (hereinafter, integral type projection data) acquired by a CT device of an integral method (hereinafter, integral type CT device) in a past examination. The X-ray CT device 1 is an example of a PC type CT device. The integral type projection data may be data stored in a memory (which may be the memory 41 or another memory) of the console device 40, or may be data stored in an external device such as a server connected to the console device 40.

[0047] In S102, the image processing unit 444 generates volume data by performing backprojection processing and reconstruction processing on each of the PC type projection data and the integral type projection data using the reconstruction processing unit 443. In this example, the image processing unit 444 acquires PC type volume data and integral type volume data by performing reconstruction processing by a filtered backprojection method on each of the PC type projection data and the integral type projection data. The PC type volume data is an example of data based on the first data (PC type projection data in this example). The integral type volume data is an example of data based on the second data (integral type projection data in this example).

[0048] In S103, the image processing unit 444 processes the signal for acquiring the first data to generate third data similar to the second data. In this example, the image processing unit 444 generates third projection data (hereinafter, pseudo projection data) similar to projection data acquired by the integral method from a signal (a signal for acquiring PC type projection data) detected by the X-ray detector 12 in the current examination. At this time, the image processing unit 444 functions as a data generating unit. Then, the image processing unit 444 generates third volume data (hereinafter, pseudo volume data) that is data based on the third data by performing back projection processing and reconstruction processing on the pseudo projection data using the reconstruction processing unit 443. Here, the signal detected by the X-ray detector 12 is detection data output from the DAS 18, and is a signal used to generate projection data (PC type projection data) of the photon counting method. The pseudo volume data can be generated, for example, as follows. First, the DAS 18 outputs detection data including independent information on the number of photons and the energy value. The pre-processing unit 442 obtains the number of photons and the energy value from the detection data, and calculates the integral value of the product of these. The image processing unit 444 generates pseudo projection data using the integral value, and generates pseudo volume data by performing reconstruction processing by a filtered back projection method using the reconstruction processing unit 443. In this way, pseudo volume data similar to volume data obtained by an integral type X-ray CT device is generated. Note that, although the pre-processing unit 442 calculates the integral value in the above, the DAS 18 may calculate the integral value and output it as part of the detection data.

[0049] In S104, the image processing unit 444 aligns the data based on the first data with the data based on the second data based on the result of aligning the data based on the second data with the data based on the third data. More specifically, the image processing unit 444 first aligns the integral type volume data acquired in S102 with the pseudo volume data acquired in S103. Next, the image processing unit 444 aligns the PC type volume data with the integral type volume data based on the alignment result (for example, the amount of positional deviation between the integral type volume data and the pseudo volume data).

[0050] The alignment of the two volume data is performed, for example, as follows. The image processing unit 444 extracts feature points (preferably a plurality of feature points) in one of the two volume data to be aligned (PC-type volume data and integral-type volume data), and searches for corresponding feature points in the other volume data. SIFT, HOG, SURF, etc. are possible feature points. Also, a characteristic part of an image may be extracted as a feature point by performing edge detection processing or the like. Also, template matching, that is, SSD (Sum of Squared Difference), normalized correlation, etc., may be used to search for corresponding feature points. Then, the image processing unit 444 aligns the two volume data by performing affine transformation on one of the volume data using the least squares method or the like so that the difference in the positions of the corresponding feature points is minimized. At this time, if the positions of the feature points are significantly different, alignment may be performed using a nonlinear transformation such as local affine transformation in which a triangular mesh is formed with the feature points as lattice points and an affine transformation is performed on each triangular mesh. The nonlinear transformation includes, for example, free-form deformation (FFD) using B-spline. The amount of transformation is used as the above-mentioned displacement amount.

[0051] In S105, the image processing unit 444 generates a tomographic image at the same cross-sectional position from the PC type volume data and the integral type volume data after the alignment. Hereinafter, a tomographic image obtained from the PC type volume data is referred to as a PC type tomographic image, and a tomographic image obtained from the integral type volume data is referred to as an integral type tomographic image. Note that the cross-sectional position for generating the tomographic image can be specified by the user via the input interface 43. In S106, the display control unit 446 displays the two tomographic images of the cross-section at the same position generated in S105 on the display unit 42.

[0052] 4A and 4B are schematic diagrams showing the display of cross-sectional images of the same position of the PC type volume data and the integral type volume data. FIG. 4A is an example of a screen that simultaneously displays a PC type cross-sectional image of a predetermined cross-section in the PC type volume data and an integral type cross-sectional image of the same position as the predetermined cross-section in the integral type volume data. In the example of the screen in FIG. 4A, the PC type cross-sectional image is displayed on the right side, and the integral type cross-sectional image is displayed on the left side. In this way, when two cross-sectional images are displayed simultaneously, the two cross-sectional images are displayed in pairs (parallel display) with a positional relationship such as left and right or up and down. In this case, the two cross-sectional images may be displayed on the same screen, or may be displayed on different screens. In addition, the timing of starting or ending the display of each of the two cross-sectional images may be different. Alternatively, as shown in FIG. 4B, the two cross-sectional images may be displayed as a stack in which the two cross-sectional images are displayed individually by switching pages. Since the two cross-sectional images displayed in FIG. 4A and FIG. 4B are appropriately aligned, the user can easily check the change over time of a site of interest such as a lesion. At this time, a tomographic image (hereinafter referred to as a pseudo tomographic image) of a cross section at the above-mentioned position (the same position as the PC type tomographic image and the integral type tomographic image) of the pseudo volume data may be displayed. For example, in a parallel display as shown in FIG. 4A, the PC type tomographic image may be replaced with the pseudo tomographic image, and the pseudo tomographic image and the integral type tomographic image may be displayed in parallel. Alternatively, in a stack display (switching display) as shown in FIG. 4B, the PC type tomographic image may be replaced with the pseudo tomographic image, and the pseudo tomographic image and the integral type tomographic image may be switched between. This allows the user to compare a past tomographic image with a current tomographic image with similar image quality.

[0053] In this example, PC type projection data and integral type projection data are acquired as the first and second data in S101, and PC type volume data and integral type volume data are generated as data based on the first and second data in S102, but this is not limited to this. In the present disclosure, when "data based on a-th data" (a is a natural number) is described, the "data based on a-th data" may be a-th data or data generated from a-th data. Therefore, for example, if integral type volume data is acquired as the second data from the outside, only PC type projection data, which is the first data, is acquired in S101. Then, PC type volume data is generated as data based on the first data in S102, and the integral type volume data acquired above is used as it is for the data based on the second data. Also, if the image processing unit 444 acquires PC type volume data as the first data and integral type volume data as the second data from the outside, acquisition of projection data and generation of volume data are skipped. Then, the data based on the first data is the acquired PC type volume data, and the data based on the second data is the acquired integral type volume data. In either case, in S103, a signal (a signal detected by the X-ray detector 12) for acquiring the first data (PC type projection data or PC type volume data) is processed to generate pseudo projection data, which is third data similar to the projection data acquired by the integral method. Then, back projection processing and reconstruction processing are performed on the generated pseudo projection data to generate pseudo volume data, which is data based on the third data.

[0054] Also, there are cases where data obtained in past examinations are only integral tomographic images acquired by an integral CT device. In this case, since integral projection data and integral volume data are not obtained, instead of alignment using volume data, a corresponding PC tomographic image can be acquired from information on the tomographic position of the integral tomographic image, and alignment can be performed between the tomographic images. Therefore, data based on the first data and data based on the second data are a PC tomographic image and an integral tomographic image, respectively. Also, a pseudo tomographic image is used as data (data based on the third data) used to align the PC tomographic image and the integral tomographic image. Hereinafter, the processing in this case will be described with reference to the flowchart in FIG. 3B.

[0055] In S111, the image processing unit 444 acquires an integral tomographic image, which is the second data. The integral tomographic image may be stored in the memory (which may be the memory 41 or another memory) of the console device 40, or may be stored in an external device such as a server connected to the console device 40. In S112, the image processing unit 444 acquires a PC tomographic image corresponding to the cross-sectional position of the integral tomographic image as the first data, based on the information of the cross-sectional position of the integral tomographic image acquired in S111. As described above, the PC tomographic image is obtained from PC volume data generated from PC projection data obtained from the X-ray CT device 1 in the current examination. In S113, the image processing unit 444 generates pseudo volume data by processing a signal of the photon counting method. This process is the same as S103. In S114, the image processing unit 444 acquires a cross-sectional image corresponding to the cross-sectional position of the PC tomographic image acquired in S112 from the pseudo volume data, as a pseudo tomographic image. In S115, the image processing unit 444 performs alignment between the integral type tomographic image acquired in S111 and the PC type tomographic image acquired in S112 using the pseudo tomographic image acquired in S114. For alignment between the tomographic images, for example, a method of extracting feature points similar to the above-mentioned alignment of volume data, a method using a value indicating a correlation of a part or all of the tomographic images, etc. can be used. Then, based on the alignment result, the image processing unit 444 performs alignment between the PC type tomographic image acquired in S112 and the integral type tomographic image acquired in S111. In S116, the display control unit 446 displays the PC type tomographic image and the integral type tomographic image aligned in S115. As in the above-mentioned S106, a display using a pseudo tomographic image may be performed, such as displaying a pseudo tomographic image instead of the PC type tomographic image.

[0056] <Processing example 2> In the processing example 1, a PC type tomographic image and an integral type tomographic image at a predetermined cross-sectional position are acquired and displayed from the PC type volume data and the integral type volume data aligned using the pseudo volume data generated from the pseudo projection data. In the processing example 2, a difference image between the tomographic images is further generated, and the difference image or the difference area is used for display. FIG. 3C is a flowchart explaining the processing example 2.

[0057] S201 to S205 are the same as S101 to S105 (FIG. 3A) in Processing Example 1. As described above, the PC type tomographic image is a tomographic image obtained from PC type volume data generated based on PC type projection data acquired by the photon counting method in the current examination. Also, the integral type tomographic image is a tomographic image obtained from integral type volume data generated based on integral type projection data acquired by the integral method in the past examination.

[0058] In S206, the image processing unit 444 generates a tomographic image (pseudo tomographic image) at the same cross-sectional position as that at which the PC type tomographic image and the integral type tomographic image were generated from the pseudo volume data generated in S203. Then, in S207, the image processing unit 444 generates an image showing the difference between the integral type CT tomographic image and the pseudo tomographic image. In this embodiment, as an example of an image showing the difference, a difference image is generated in which a region (difference region) which is the difference between the integral type CT tomographic image and the pseudo tomographic image is identifiably displayed. The difference image may be, for example, an image in which the difference between each pixel value of the integral type CT tomographic image and the pseudo tomographic image is calculated, as in the image on the right side of FIG. 4C, or may be, for example, an image in which information indicating the difference region is reflected in the PC type tomographic image, as in FIG. 4D. Note that, as another example of an image showing the difference, an image showing the ratio of each pixel value between both tomographic images may be generated. In S208, the display control unit 446 displays the difference image generated in S207 on the display unit 42. At this time, for example, as shown in Fig. 4C, the PC type tomographic image (the image on the left side in the figure) and the difference image (the image on the right side in the figure) may be displayed in parallel, or as shown in Fig. 4D, the difference image may be displayed superimposed on the information PC type tomographic image showing the difference region. In addition, in S207, when the brightness difference between the first tomographic image and the second tomographic image is large, the image processing unit 444 may adjust the brightness value of the pseudo tomographic image before generating the difference image or calculating the difference region. Of course, the displays described in S106 (display of the PC type tomographic image, the integral type tomographic image, and the pseudo tomographic image) may be used in combination.

[0059] As described above, in processing example 2, it is possible to generate an image showing changes over time with reduced effects from differences in X-ray detection methods. This allows changed areas in the region of interest, such as lesions, to be extracted, while unchanged areas are less likely to be extracted as differences, making it easier for doctors and technicians to make diagnoses.

[0060] As described in the processing example 1, it may be assumed that the data obtained in the past examination by the integral CT device is only an integral tomographic image, and the integral projection data and the integral volume data are not obtained, and alignment using the volume data cannot be performed. The processing in this case will be described with reference to the flowchart in FIG. 3D. The processing in S211 to S215 in FIG. 3D is the same as that in S111 to S115 in the processing example 1 (FIG. 3B). In S216, the image processing unit 444 generates a difference image from the pseudo tomographic image and the integral tomographic image aligned in S215. In S217, the display control unit 446 performs display using the difference image, as in S208.

[0061] <Processing example 3> In the processing example 3, the first data (integral type tomographic image) acquired using the integral method is processed to generate the third data (pseudo tomographic image) having image quality similar to that of the second data (PC type tomographic image) acquired using the photon counting method. In FIG. 3B of the processing example 1 and FIG. 3D of the processing example 2, the process of performing alignment using the pseudo tomographic image when alignment between volume data is not possible has been described. In these processes, in the processing examples 1 and 2, the pseudo tomographic image used for performing alignment or generating a difference image is acquired from the pseudo volume data. In contrast, in the processing example 3, the pseudo tomographic image used for performing alignment between the PC type tomographic image and the integral type tomographic image and generating a difference image is generated from the integral type tomographic image. More specifically, in the processing example 3, the image quality of the integral type tomographic image acquired in the past examination is improved by image processing to generate a tomographic image having image quality comparable (similar) to that of a tomographic image acquired using the photon counting method, and the generated image is used as the pseudo tomographic image. The image processing unit 444 uses the pseudo tomographic image thus generated from the integral tomographic image to align the integral tomographic image with the PC tomographic image and generate a difference image.

[0062] FIG. 3E is a flowchart for explaining image processing according to Processing Example 3. S301 to S302 are the same as S111 to S112 (S211 to S212). In S301, the image processing unit 444 acquires an integral type tomographic image, which is the first data. The integral type tomographic image may be stored in a memory (which may be the memory 41 or another memory) of the console device 40, or may be stored in an external device such as a server connected to the console device 40. In S302, the image processing unit 444 acquires a PC type tomographic image, which is the second data corresponding to the cross-sectional position of the integral type tomographic image, based on the information of the cross-sectional position of the integral type tomographic image acquired in S301.

[0063] In S303, the image processing unit 444 improves the image quality (e.g., graininess or sharpness) of the integral type tomographic image acquired in S301 by image processing, and generates a pseudo tomographic image, which is the third data. The pseudo tomographic image, which is the third data, has an image quality similar to that of a tomographic image acquired by a photon counting type X-ray detection method. For example, the image processing unit 444 performs noise reduction processing on the integral type tomographic image acquired in S301 to improve the graininess of the image, and performs image restoration processing to improve the sharpness of the image, thereby obtaining a pseudo tomographic image. For the noise reduction processing, for example, a linear filter processing such as a low-pass filter such as a Gaussian filter may be used, or a nonlinear filter processing having image structure preservation properties such as an epsilon filter or a bilateral filter may be used. In addition, as another noise reduction processing, a structure preserving type noise reduction processing such as NLmeans or BM3D may be used. In addition, a deconvolution processing may be used for the image restoration processing. When performing deconvolution processing, the MTF (Modulation Transfer Function) of a PC type tomographic image (a tomographic image of a photon counting type X-ray detection method) and an integral type tomographic image (a tomographic image of an integral type X-ray detection method) are measured in advance. Then, an inverse filter process is performed on the integral type tomographic image so that the MTF matches the MTF of the tomographic image of the PC type X-ray detection method to generate a tomographic image. Another image restoration process is a method using Wiener filter processing. By using Wiener filter processing, it is possible to perform image restoration processing while suppressing deterioration of the graininess of the image. This allows a tomographic image (hereinafter referred to as a pseudo tomographic image) whose image quality is similar to that of the PC type tomographic image to be acquired. Note that, in improving the image quality of the integral type tomographic image (image processing for making the image quality similar to that of the PC type tomographic image), both graininess and sharpness may be improved, or either one of them may be improved.

[0064] In S304, the image processing unit 444 aligns the PC type tomographic image (data based on the second data) and the integral type tomographic image (data based on the first data) using the pseudo tomographic image (data based on the third data) generated in S303. In this example, the "data based on the third data" is the "third data", and both are the same pseudo tomographic image. The alignment process is the same as S115, and for example, the pseudo tomographic image and the integral type tomographic image are aligned using a method of extracting feature points or a method using a value indicating correlation, similar to the alignment of volume data described in Processing Example 1. Then, the image processing unit 444 aligns the PC type tomographic image and the integral type tomographic image based on the alignment result. Next, in S305, the image processing unit 444 obtains a difference image between the aligned pseudo tomographic image and the PC type tomographic image. The difference image represents the difference between the integral type tomographic image by the past examination and the PC type tomographic image by the current examination. Then, in S306, the display control unit 446 performs display using the integral type tomographic image, the PC type tomographic image, and the difference image after the alignment. The display process is the same as the display process described in S208 and S217. In addition, by replacing the integral type tomographic image with the pseudo tomographic image and displaying it together with the PC type tomographic image, the user can compare the tomographic image based on the past examination and the tomographic image based on the current examination, which have similar image quality, and the diagnostic efficiency is improved.

[0065] In the processing example 3, the integral type tomographic image is subjected to image processing to generate a pseudo tomographic image having an image quality similar to that of the PC type tomographic image, but the present invention is not limited to this. It is clear that a pseudo tomographic image having an image quality similar to that of a tomographic image obtained by the integral method may be generated by performing a process for reducing at least one of graininess and sharpness (for example, a process for blurring the image) on the PC type tomographic image. In this case, in S305, a difference image between the pseudo tomographic image and the integral type tomographic image is generated. In addition, in this case, by replacing the PC type tomographic image with the pseudo tomographic image and displaying it together with the integral type tomographic image, the user can compare past and present tomographic images with similar image quality.

[0066] <Processing example 4> In the processing example 3, a configuration is described in which a pseudo tomographic image with the image quality of an integral tomographic image being made closer to that of a PC tomographic image by image processing is obtained. In the processing example 4, a configuration is described in which a pseudo tomographic image with the image quality of an integral tomographic image being made closer to that of a tomographic image obtained by a photon counting method is obtained by using AI. More specifically, an integral tomographic image obtained in a past examination is input to the trained model to obtain a pseudo tomographic image with image quality similar to that of a PC tomographic image. Then, the pseudo tomographic image is used to align the PC tomographic image and the integral tomographic image, and a difference image between the pseudo tomographic image and the PC tomographic image is generated. Here, the trained model is a learning model obtained by machine learning using a pair of a pseudo tomographic image made similar to the integral tomographic image and a PC tomographic image (a tomographic image obtained from a CT device using a photon counting method) as teacher data.

[0067] 3F is a flowchart for explaining image processing according to processing example 4. S401 to S402 are similar to S301 to S302 in processing example 3 (FIG. 3E). In S403, the image processing unit 444 inputs the integral type tomographic image, which is the first data acquired in S401, to a trained model stored in a storage unit (memory) (not shown) of the control unit 44, and obtains a pseudo tomographic image, which is the third data. The pseudo tomographic image obtained here is an image quality improved from the integral type tomographic image to an image quality similar to that of a PC type tomographic image.

[0068] Here, the construction process of the trained model will be described with reference to FIG. 3G. FIG. 3G is a flowchart for explaining the construction process of the trained model in the processing example 4. In S411, the image processing unit 444 acquires PC type volume data generated from the PC type projection data. In S412, the image processing unit 444 generates pseudo volume data (pseudo integral type volume data) based on a signal detected when acquiring the PC type projection data acquired in S411. The procedure for generating the pseudo volume data is the same as S103 in the processing example 1 (FIG. 3A). That is, the image processing unit 444 acquires the integral value of the product of the number of photons and the energy from the DAS18 (or the preprocessing unit 442), acquires pseudo projection data (pseudo integral type projection data) similar to the projection data obtained from the integral type CT device, and generates pseudo volume data from the pseudo projection data. In S414, the image processing unit 444 acquires a pair of a PC type tomographic image obtained from the PC type volume data acquired in S411 and a pseudo tomographic image obtained from the pseudo volume data at the same cross-sectional position as training data. That is, training data is acquired in which a pair of tomographic images at the same cross-sectional position generated from each of the PC type volume data and the pseudo volume data is acquired. In S415, the image processing unit 444 generates a trained model by providing (training) the training data acquired in S414 to the machine learning engine. At this time, a large number of training data can be acquired by obtaining pairs of tomographic images at a large number of cross-sectional positions from the PC type volume data and the pseudo volume data.

[0069] The machine learning engine is preferably a regression type using a convolutional neural network. This is because it is possible to make one image similar to the image quality of the other image. In addition, known networks such as Unet, Residual Net, and Dense Net can be used as the network. In addition, something like a GAN (generative adversarial network) may be used. Furthermore, the machine learning engine may include an error detection unit and an update unit. The error detection unit obtains an error between the output data output from the output layer of the neural network according to the input data input to the input layer and the teacher data. The error detection unit calculates the error between the output data from the neural network and the teacher data using a loss function. In addition, the update unit updates the coupling weighting coefficient between the nodes of the neural network, etc., based on the error obtained by the error detection unit, so that the error is reduced. The update unit updates the coupling weighting coefficient, etc., using, for example, an error backpropagation method. The error backpropagation method is a method of adjusting the coupling weighting coefficient between the nodes of each neural network so that the above-mentioned error is reduced.

[0070] A GPU may be used for machine learning of the learning model and estimation using the learned model. Increasing parallel processing by the GPU enables more efficient calculations, and is therefore effective when learning is performed multiple times using the learning model (e.g., deep learning). Specifically, when a learning program including the learning model is executed, the CPU and the GPU work together to perform calculations to perform learning. The processing of the learning unit may be performed only by the CPU or the GPU. Also, when making an estimation using the learned model, the GPU may be used in the same way as when learning. By such machine learning, the machine learning engine generates a learned model that outputs a pseudo tomographic image based on an integral tomographic image. Furthermore, a learned model can be generated for each imaging condition, such as the number of views, tube current, and slice thickness, for the same part.

[0071] Returning to FIG. 3F, in S404, the image processing unit 444 aligns the PC type tomographic image (data based on the second data) and the integral type tomographic image (data based on the first data) using the pseudo tomographic image (data based on the third data). This process is the same as S304. In S405, the image processing unit 444 obtains a difference image between the aligned pseudo tomographic image and the PC type tomographic image. This process is the same as S305. In S406, the display control unit 446 displays the PC type tomographic image, the integral type tomographic image, and the difference image. This process is the same as S306.

[0072] <Processing example 5> In the processing examples 2 to 4, the difference between the integral type tomographic image acquired in the past examination and the pseudo tomographic image corresponding to the PC type tomographic image acquired in the current examination is calculated to calculate the difference region between the integral type tomographic image of the past examination and the PC type tomographic image of the current examination. In the processing example 5, when an ROI (region of interest) is set in one of the acquired integral type tomographic image and the PC type tomographic image, the ROI is reflected at the same position in the other tomographic image. The region set by the ROI may be the analysis region (region to be analyzed). FIG. 3H is a flowchart explaining the processing of the image processing unit 444 and the display control unit 446 in the processing example 5.

[0073] S501 to S506 are the same as S101 to S106 in the processing example 1 (FIG. 3A). By the above processing, the PC type volume data (data based on the first data) and the integral type volume data (data based on the second data) are aligned based on the pseudo volume data (data based on the third data). Then, the aligned PC type tomographic image and the integral type tomographic image at the same cross-sectional position are displayed. The user can set a region of interest (hereinafter, a first ROI) on the PC type tomographic image displayed on the display unit 42 in order to measure the size of a lesion site such as a tumor. In S507, the display control unit 446 receives the setting of the first ROI by the user through the input interface 43, which is an instruction receiving unit, and superimposes and displays information indicating the first ROI (information indicating the first region) on the PC type tomographic image displayed on the display unit 42. Note that in this example, an example of displaying a frame on the PC type tomographic image as information indicating the first ROI will be described.

[0074] In S508, the image processing unit 444 calculates a position on the integral type tomographic image corresponding to the first ROI on the PC type tomographic image set by the user, and calculates a position on the integral type tomographic image corresponding to the position (it can also be expressed as performing corresponding region setting). Then, the display control unit 446 displays information indicating the second ROI (information indicating a second region corresponding to the first region, a frame in this example) superimposed on the integral type tomographic image. Since the integral type volume data and the PC type volume data have been aligned in S503, the position at which the second ROI is set can be easily calculated. This makes it possible to analyze the same position and measure changes over time, for example, in follow-up observation. A display example of the information indicating the first ROI and the information indicating the second ROI is shown in FIG. 5. At this time, for example, if an ROI (third ROI) has already been set in the integral type tomographic image, the information indicating the already set third ROI and the information indicating the second ROI may be displayed in different display forms, such as displaying them in different colors. By displaying in different display forms in this way, the user can more easily distinguish between the ROI set in the past and the ROI set this time. In addition, when graphs or numerical values ​​of the measurement values ​​and analysis values ​​measured by each ROI are displayed, the display can be made identifiable according to the display form of each ROI. Furthermore, information indicating a manually set ROI and information indicating an ROI set by the control unit 44 based on an ROI on a tomographic image to be compared may be displayed in different display forms, so as to be identifiable. Specifically, for example, information regarding an ROI that is manually drawn and set on an integral tomographic image by a user and information regarding a second ROI that is automatically set on an integral tomographic image based on a first ROI set on a PC-type tomographic image may be displayed in different colors.

[0075] In the above processing example 5, the second ROI is set on the integral tomographic image based on the position information on the first ROI set on the PC tomographic image, but the present invention is not limited to this. For example, the first ROI may be set on the integral tomographic image, and the second ROI may be set on the PC tomographic image based on the position information. In this case, the first ROI set on the integral tomographic image may be the third ROI already set in the past, and in such a case, as shown in FIG. 5, the area on the PC tomographic image corresponding to the third ROI already set on the integral tomographic image by the past examination is specified and displayed superimposed as information indicating the fourth ROI. In addition, in this state, when the user newly sets the first ROI on the PC tomographic image, the information indicating the third ROI corresponding to the ROI of the integral tomographic image and the information indicating the newly set first ROI may be displayed in a distinguishable manner (for example, displayed in different display forms).

[0076] The first to fourth ROIs may be reflected between the tomographic images after the alignment shown in the processing examples 3 to 4. For example, in the integral type tomographic image and the PC type tomographic image aligned by the method of the processing example 3, the first ROI set in the PC type tomographic image can be reflected as the second ROI in the integral type tomographic image. Similarly, in the aligned integral type tomographic image and the PC type tomographic image, the third ROI set in the integral type tomographic image can be set as the fourth ROI in the PC type tomographic image based on the alignment result.

[0077] In the above processing examples 1 to 5, the data obtained from the integral CT device and the data obtained from the PC CT device are assumed to be data obtained on different dates and times, assuming follow-up observation, but it is not essential that the data are obtained on different dates and times. For example, the data may be obtained by the integral CT device and the PC CT device on the same day. In the above processing examples, the projection data and the volume data may be part of the data obtained by the CT device. The volume data may be partial volume data corresponding to a specific organ such as the heart. In the above processing examples 1 to 5, the data obtained from the integral CT device obtained in the past examination and the data obtained from the PC CT device obtained in the current examination are compared, but the present disclosure is not limited to this. For example, even if the integral CT image obtained in the past examination is a dual energy CT image obtained by performing imaging at two or more types of tube voltage, the comparison can be performed in the same manner. As described above, photon energy information can be obtained from the photon counting type X-ray detector 12. Therefore, it is possible to generate a pseudo dual energy CT image similar to a functional image acquired by performing CT imaging using two types of X-rays with different tube voltages from a signal for acquiring a set of PC type projection data, and compare it in the same manner as in the above processing examples 1 to 5. Examples of functional images include an effective atomic number image, a virtual monochromatic X-ray image, a virtual non-contrast image, and a material decomposition image (an image in which contrast agent, bone, water, etc. are separated).

[0078] In addition, the medical image processing device of the present disclosure may be capable of one of the processes of the processing examples 1 to 5, or may be capable of a plurality of processes. For example, the user may be able to select the processes of S111 to S114 of the processing example 1 and the processes of S401 to S403 of the processing example 4. More specifically, the control unit 44 can select either a first method of acquiring a PC type tomographic image (first data) and an integral type tomographic image (second data), acquiring pseudo volume data similar to the integral type volume data from a signal detected by the PC method, and acquiring a pseudo tomographic image (third data) corresponding to the position of the PC type tomographic image, or a second method of acquiring a pseudo tomographic image (fourth data) similar to a PCCT image by image processing from the integral type tomographic image (second data). In this case, an example of an operation of the selection instruction performed by the user is an operation on a switch button for switching to the other method, which is displayed on a screen displaying the results obtained by one of the first and second methods. Of course, the operation of selecting and instructing is not limited to this, and may be an operation of selecting the first method or the second method from a button or pull-down menu displayed on the screen before displaying the inspection results. Note that, for the subsequent process of aligning data based on the first data and data based on the second data using the third data, S115 to S116 or S404 to S406 are automatically selected based on the selected method.

[0079] As described above, according to the above processing examples 1 to 5, it is possible to reduce the difference in image quality between a tomographic image based on projection data acquired by a photon-counting type X-ray detection method and a tomographic image based on projection data acquired by an integral type X-ray detection method. This makes it possible to more accurately align the tomographic images and facilitate comparisons such as observation of changes over time in the same subject, thereby reducing the burden on doctors and technicians and barriers to device replacement.

[0080] The disclosed technology can also be realized by executing the following process. That is, the disclosed technology can also be realized by supplying software (medical image processing program) that realizes one or more functions of the various embodiments described above to a system or device via a network or a storage medium, and having a computer (or a CPU, MPU, etc.) of the system or device read and execute the medical image processing program. The computer has one or more processors or circuits, and may include a network of separate computers or separate processors or circuits to read and execute computer-executable instructions. In this case, the processor or circuit may include a central processing unit (CPU), a microprocessing unit (MPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), or a field programmable gateway (FPGA). The processor or circuit may also include a digital signal processor (DSP), a data flow processor (DFP), or a neural processing unit (NPU).

[0081] The disclosure of this specification includes the following medical image processing device, a control method for a medical image processing device, and a medical image processing program. (Item 1) an acquisition means for acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; A generating means for generating third data similar to the second data by processing the first data or a signal for acquiring the first data; and a registration means for registering data based on the first data and data based on the second data based on a result of registering data based on the second data and data based on the third data. (Item 2) 2. The medical image processing device according to item 1, characterized in that the processing of the first data or the signal for acquiring the first data is processing for reducing the difference in image quality between an image based on the first data and an image based on the second data. (Item 3) 2. The medical image processing device according to item 1, characterized in that the first data is data based on count data of X-ray photons collected using a signal detected by an X-ray detector, and the second data is data based on integrated data obtained by integrating the signal detected by the X-ray detector over a predetermined time width. (Item 4) 2. The medical image processing device according to item 1, characterized in that the first data is data based on integrated data obtained by integrating a signal detected by an X-ray detector over a predetermined time width, and the second data is data based on count data of X-ray photons collected using the signal detected by the X-ray detector. (Item 5) 4. The medical image processing device according to item 3, wherein the generating means generates the third data based on an integral value obtained by integrating the product of the number and energy of photons contained in the count data detected by an X-ray detector. (Item 6) 2. The medical image processing device according to item 1, wherein the first data and the second data are both projection data, or both volume data, or one is projection data and the other is volume data. (Item 7) 2. The medical image processing apparatus according to item 1, wherein at least one of the first data and the second data is a tomographic image. (Item 8) 4. The medical image processing device according to item 3, wherein the generating means generates the third data by applying image processing to the first data to reduce graininess or sharpness. (Item 9) 4. The medical image processing device according to item 3, wherein the generating means generates the third data by applying image processing to the first data to improve graininess or sharpness. (Item 10) The medical image processing device described in item 3, characterized in that the generation means generates the third data from the first data by using a trained model obtained by learning using as training data a pair of a first image acquired from data acquired using the second X-ray detection method and a third image acquired from data acquired using the second X-ray detection method and in which the image quality of the first image is similar to that of the second image acquired from data acquired using the first X-ray detection method. (Item 11) 11. The medical image processing apparatus according to any one of items 1 to 10, further comprising a display control means for displaying on a display unit a first image obtained from data based on the first data and a second image obtained from data based on the second data after the alignment. (Item 12) Item 12. The medical image processing apparatus according to item 11, wherein the display control means displays the first image and the second image in parallel on the display unit or switches between them. (Item 13) 11. The medical image processing apparatus according to any one of items 1 to 10, further comprising a means for generating an image representing a difference between a third image obtained from data based on the third data after the alignment and a second image obtained from data based on the second data after the alignment. (Item 14) Item 14. The medical image processing apparatus according to item 13, wherein the image representing the difference is a difference image representing a difference region between the third image and the second image. (Item 15) Item 15. The medical image processing device according to item 14, wherein the difference image is a first image obtained from data based on the first data after the alignment, or an image in which information representing the difference region is superimposed on the second image. (Item 16) Item 12. The medical image processing device according to item 11, further comprising a region setting means for setting, as a second region, a region on the second image corresponding to a first region set on the first image. (Item 17) Item 17. The medical image processing apparatus according to item 16, further comprising an instruction receiving means for receiving an instruction to set the first region on the first image. (Item 18) Item 17. The medical image processing apparatus according to item 16, characterized in that the display control means displays information indicating the first region on the first image and information indicating the second region on the second image by superimposing them on each other. (Item 19) The medical image processing device described in item 16, characterized in that the display control means displays information indicating the second region set by the region setting means and information indicating the region set by a user by drawing on the second image in a distinguishable manner. (Item 20) 20. The medical image processing apparatus according to item 19, wherein the display control means is characterized in that the area drawn and set on the second image by the user is an area set in a previous examination. (Item 21) 11. The medical image processing apparatus according to any one of items 1 to 10, wherein the first data and the second data are data acquired from different X-ray detectors at different dates and times. (Item 22) The generating means is capable of generating fourth data similar to the first data by processing the second data or a signal for acquiring the second data, 2. The medical image processing apparatus according to item 1, wherein the generating means has an instruction receiving means for receiving a selection instruction for generating either the third data or the fourth data. (Item 23) an acquisition step of acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; a data generating step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data; and a registration process for registering data based on the first data and data based on the second data based on a result of registering data based on the second data and data based on the third data. (Item 24) an acquisition step of acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method; a data generating step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data; and a registration step of aligning data based on the first data and data based on the second data based on a result of aligning data based on the second data and data based on the third data.

[0082] The invention is not limited to the above-described embodiments, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0083] 1: X-ray CT device, 10: stand device, 30: bed device, 40: console device, 12: X-ray detector, 18: DAS, 44: control unit, 441: system control unit, 442: pre-processing unit, 443: reconstruction unit, 444: image processing unit, 445: scan control unit, 446: display control unit

Claims

1. An acquisition means for acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method, A generation means that processes the first data or a signal for acquiring the first data to generate a third data similar to the second data, A medical image processing apparatus comprising: alignment means for aligning data based on the first data and data based on the second data based on the result of aligning data based on the second data and data based on the third data.

2. The medical image processing apparatus according to claim 1, characterized in that the processing of the first data or the signal for acquiring the first data is a process for reducing the difference in image quality between an image based on the first data and an image based on the second data.

3. The medical image processing apparatus according to claim 1, characterized in that the first data is data based on counting data of X-ray photons collected using a signal detected by an X-ray detector, and the second data is data based on integral data obtained by integrating the signal detected by the X-ray detector over a predetermined time width.

4. The medical image processing apparatus according to claim 1, characterized in that the first data is data based on integral data obtained by integrating a signal detected by an X-ray detector over a predetermined time width, and the second data is data based on counting data of X-ray photons collected using the signal detected by the X-ray detector.

5. The medical image processing apparatus according to claim 3, characterized in that the generation means generates the third data based on an integral value obtained by integrating the product of the number of photons and their energy contained in the counting data detected by the X-ray detector.

6. The medical image processing apparatus according to claim 1, characterized in that both the first data and the second data are projection data, or both are volume data, or one is projection data and the other is volume data.

7. The medical image processing apparatus according to claim 1, characterized in that at least one of the first data and the second data is a tomographic image.

8. The medical image processing apparatus according to claim 3, characterized in that the generation means generates the third data by applying image processing to the first data to reduce granularity or sharpness.

9. The medical image processing apparatus according to claim 3, characterized in that the generation means generates the third data by applying image processing to the first data to improve granularity or sharpness.

10. The medical image processing apparatus according to claim 3, wherein the generation means generates the third data from the first data using a trained model obtained by training using a pair of a first image obtained from data acquired using the second X-ray detection method and a third image obtained from data acquired using the second X-ray detection method and made similar in quality to the second image obtained from data acquired using the first X-ray detection method as training data.

11. The medical image processing apparatus according to claim 1, further comprising a display control means for displaying a first image obtained from data based on the first data after the alignment, and a second image obtained from data based on the second data, on a display unit.

12. The medical image processing apparatus according to claim 11, characterized in that the display control means displays the first image and the second image in parallel on the display unit, or switches between them for display.

13. The medical image processing apparatus according to claim 1, further comprising means for generating an image representing the difference between a third image obtained from data based on the third data after alignment and a second image obtained from data based on the second data after alignment.

14. The medical image processing apparatus according to claim 13, characterized in that the image representing the difference is a difference image representing the difference region between the third image and the second image.

15. The medical image processing apparatus according to claim 14, characterized in that the difference image is a first image obtained from data based on the first data after alignment, or an image in which information representing the difference region is superimposed on the second image.

16. The medical image processing apparatus according to claim 11, further comprising region setting means for setting a region on the second image that corresponds to a first region set in the first image as a second region.

17. The medical image processing apparatus according to claim 16, further comprising an instruction receiving means for receiving an instruction to set the first region on the first image.

18. The medical image processing apparatus according to claim 16, characterized in that the display control means superimposes information indicating the first region onto the first image and information indicating the second region onto the second image.

19. The medical image processing apparatus according to claim 16, characterized in that the display control means displays in a manner that allows for the identification of information indicating a second region set by the region setting means and information indicating a region set by drawing on the second image by the user.

20. The medical image processing apparatus according to claim 19, characterized in that the region drawn and set on the second image by the user is a region set in a previous examination.

21. The medical image processing apparatus according to claim 1, characterized in that the first data and the second data are data acquired from different X-ray detectors at different times.

22. The generation means is capable of processing the second data or a signal for acquiring the second data to generate a fourth data similar to the first data. The medical image processing apparatus according to claim 1, characterized in that the generation means has an instruction receiving means that receives a selection instruction to generate either the third data or the fourth data.

23. An acquisition step of acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method, A data generation step that processes the first data or a signal for acquiring the first data to generate a third data similar to the second data, A control method for a medical image processing apparatus, characterized by comprising: an alignment step of aligning data based on the first data and data based on the second data based on the result of aligning data based on the second data and data based on the third data.

24. An acquisition step of acquiring first data acquired using a first X-ray detection method and second data acquired using a second X-ray detection method different from the first X-ray detection method, A data generation step involves processing the first data or a signal for acquiring the first data to generate a third data similar to the second data, A medical image processing program that causes a computer to perform an alignment step of aligning data based on the first data and data based on the second data based on the result of aligning data based on the second data and data based on the third data.

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