JP2024046604A - Medical image processing device and control method thereof, and medical image processing program - Google Patents

Abstract

[Problem] To make it easier to compare medical images obtained using different X-ray detection methods. [Solution] A medical image processing device acquires 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, processes the first data or a signal for acquiring the first data to generate third data similar to the second data, and aligns 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. [Selected Figure]

Description

This disclosure relates to a medical image processing device, a control method thereof, and a medical image processing program.

While CT devices using X-ray detectors with an integral X-ray detection method (integral method) are generally in widespread use, in recent years, CT devices using X-ray detectors with a photon-counting X-ray detection method (hereinafter referred to as photon-counting method) have also been put to practical use. Patent Document 1 discloses an X-ray CT device using a photon-counting method based on counting data of X-ray photons collected using signals detected by an X-ray detector. Compared to an X-ray CT device using an integral method based on integral data obtained by integrating signals detected by an X-ray detector over a predetermined time width, a photon-counting method X-ray CT device can obtain high-resolution images with a lower dose.

JP 2020-127635 A

For example, in follow-up observations, there are cases where it is necessary to compare medical images obtained using different X-ray detection methods, 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.

The disclosure herein provides techniques to make it easier to compare medical images obtained using different X-ray detection methods.

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 processing the first data or a signal for acquiring the first data to generate third data similar to the second 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.

Further, in a method for controlling a medical image processing apparatus according to an aspect of the present specification, first data obtained using a first X-ray detection method and second data obtained using a first X-ray detection method are used. an acquisition step of acquiring second data acquired using the X-ray detection method;
a generation step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data;
A position at which data based on the first data and data based on the second data are aligned based on a result of aligning data based on the second data and data based on the third data. A matching step is provided.

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.

According to the disclosure of this specification, it is possible to more easily compare images obtained by different X-ray detection methods.

1 is a diagram showing an example of the configuration of an X-ray CT apparatus according to an embodiment; 1 is a diagram for explaining an X-ray detector according to an embodiment; 5 is a flowchart showing medical image processing according to processing example 1. FIG. 1 is a flowchart showing medical image processing according to a processing example 1. 13 is a flowchart showing medical image processing according to a processing example 2. 7 is a flowchart showing medical image processing according to processing example 2. FIG. 12 is a flowchart illustrating medical image processing according to processing example 3. 12 is a flowchart illustrating medical image processing according to processing example 4. 13 is a flowchart showing a learning process according to a processing example 4. 13 is a flowchart showing medical image processing according to a processing example 5. 11A and 11B are diagrams showing display examples of tomographic images according to processing example 1. 11A and 11B are diagrams showing display examples of tomographic images according to processing example 1. 7 is a diagram illustrating a display example of information indicating a difference image or a difference area according to Processing Example 2. FIG. 13A and 13B are diagrams illustrating an example of display of information indicating a difference image or a difference region according to the processing example 2. FIG. 3 is a diagram illustrating a display example of an image data set in the embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the claimed invention. Although a plurality of features are described in the embodiments, not all of these features are essential to the invention, and the plurality of features may be arbitrarily combined. Furthermore, in the accompanying drawings, the same or similar components are designated by the same reference numerals, and redundant description will be omitted.

Below, embodiments of a medical image processing device, an X-ray CT device, and a processing program disclosed in this specification will be described in detail. Note that the medical image processing apparatus, X-ray CT system, and processing program according to the present application are not limited to the embodiments described below. Further, in the following description, an X-ray detector will be taken as an example of a radiation detector, and an X-ray CT apparatus will be taken as an example of a radiation diagnostic apparatus.

The X-ray CT apparatus described in the following embodiments is an apparatus capable of performing photon counting CT. In other words, the X-ray CT apparatus described below uses a photon-counting X-ray detector to count the number of photons generated by X-rays that have passed through the subject, thereby generating X-ray CT image data with a high signal-to-noise ratio. It is a reconfigurable device. Furthermore, the X-ray detector described in the following embodiments is a direct conversion type detector that directly converts X-ray photons into charges proportional to energy.

FIG. 1 is a diagram showing an example of the configuration of a photon counting type 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 device 10, a bed device 30, and a console device 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 device 30 is defined as the Z-axis direction. Further, the axial direction that is orthogonal to the Z-axis direction and horizontal to the floor surface is defined as the X-axis direction. Further, the axial direction that is orthogonal to the Z-axis direction and perpendicular to the floor surface is defined as the Y-axis direction. Although FIG. 1 includes a diagram in which the gantry apparatus 10 is drawn from a plurality of directions for explanation, it is assumed that the X-ray CT apparatus 1 of the embodiment has one gantry apparatus 10.

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.

The X-ray tube 11 is a vacuum tube that has a cathode (filament) that generates thermoelectrons and an anode (target) that generates X-rays upon collision with the thermoelectrons. The X-ray tube 11 generates X-rays to irradiate the subject P by irradiating thermoelectrons from the cathode to the anode by applying a high voltage from the X-ray high voltage device 14 . For example, the X-ray tube 11 includes a rotating anode type X-ray tube that generates X-rays by irradiating a rotating anode with thermoelectrons.

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 cast from aluminum. Note that, in addition to the X-ray tube 11 and the X-ray detector 12, the rotating frame 13 can also support an X-ray high voltage device 14, a wedge 16, a collimator 17, a DAS 18, and the like. Additionally, the rotating frame 13 can further support various configurations not shown in FIG.

The wedge 16 is a filter for adjusting the amount of X-rays irradiated from the X-ray tube 11. Specifically, the wedge 16 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. It's a filter. For example, the wedge 16 is a filter processed from aluminum or the like to have a predetermined target angle and a predetermined thickness, and includes a wedge filter or a bow-tie filter.

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 a combination of a plurality of lead plates and the like. Note that the collimator 17 is sometimes called an X-ray diaphragm. Furthermore, although FIG. 1 shows a case in which the wedge 16 is disposed between the X-ray tube 11 and the collimator 17, a configuration in which the collimator 17 is disposed between the X-ray tube 11 and the wedge 16 is shown. It may be. In this case, the wedge 16 transmits and attenuates the X-rays irradiated from the X-ray tube 11 and whose irradiation range is limited by the collimator 17.

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

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 the 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, 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 the 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.

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 each 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 electrical signal (analog signal) each 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 multiple rows are arranged in the slice direction. The detection elements of the X-ray detector 12 can count the number of X-ray photons incident on the detection elements by counting the number of electrical signals (pulses). In addition, the energy value of the X-ray photon that caused the output of the signal can be measured by performing arithmetic processing on the signal.

Figure 2 is a schematic diagram showing the configuration of a portion of the X-ray detector 12 according to this embodiment. The X-ray detector 12 is a photon-counting detector, and as shown in Figure 2, has 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. Figure 2 shows one of the multiple detection elements that make up the X-ray detector 12.

The detection element 130 includes 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). Furthermore, each of the plurality of anode electrodes 133 corresponds to a detection pixel (also referred to as a "pixel"). When an X-ray photon is incident on the detection element 130, the detection element 130 directly converts the incident X-ray into a charge and outputs it to the ASIC 134 from the anode electrode 133 corresponding to the incident position of the X-ray.

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 results and/or the X-ray photon energy measurement results to the DAS 18 as digital data.

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. Capacitor 1341 accumulates the charge output by detection element 130. The amplifier circuit 1342 integrates and amplifies the charge collected in the capacitor 1341 in response to the X-ray photon incident on the detection element 130, and outputs the integrated charge as a pulse signal of electrical quantity. The pulse height or area of this pulse signal has a correlation with the energy of photons.

Amplification circuit 1342 includes, for example, an amplifier. The amplifier may be, for example, a single-end type amplifier or a differential type amplifier. In the case of a single-wire grounding type amplifier, the amplifier is grounded and amplifies the potential difference between the ground potential (ground) and the potential indicated by the electrical signal output by 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.

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 the multiple energy bands to be discriminated, and outputs the comparison result with the threshold to the downstream counter 1345. 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 the multiple energy bands, and outputs the generated digital data to the DAS 18.

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 that includes, 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 scintillator crystals that output a number of lights according to the incident X-ray energy. The grid is arranged on the X-ray incident side surface of the scintillator array and is composed of an X-ray shielding plate that has the function of absorbing scattered X-rays. The photosensor array has a function of converting the amount of light from the scintillator into an electrical signal according to the amount of light, and is composed of photosensors such as photomultiplier tubes. Here, the photosensor is, for example, a PD (Photodiode), an APD (Avalanche Photodiode), or a SiPM (Silicon photomultipliers).

Returning to FIG. 1, the DAS 18 generates detection data based on the count results input from the X-ray detector 12. The detected 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 channel direction as axes. The DAS 18 generates a sinogram in units of columns in the slice direction of the X-ray detector 12, for example. 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 X-rays irradiated from the X-ray tube 11 and transmitted through the subject P, discriminates the energy of the counted X-ray photons, and calculates the result of the counting process. do. The DAS 18 transfers the generated detection data to the console device 40. DAS18 is realized by a processor, for example.

The data generated by the DAS 18 is transmitted by optical communication from a transmitter having a light-emitting diode (LED) provided on the rotating frame 13 to a receiver having a photodiode (PD), and then transferred to the console device 40. The receiver is provided in 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. Furthermore, 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 data transmission method or a contact data transmission method may be used to transmit the data generated by the DAS 18.

The bed device 30 is a device on which the subject P to be imaged is placed and moved, and has 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.

The console device 40 has a memory 41, a display unit 42, an input interface 43, and a control unit 44. In this 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.

The memory 41 is realized, for example, by 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 device 1 to realize its functions. Note that the memory 41 may be realized by a group of servers (cloud) connected to the X-ray CT device 1 via a network.

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.

The input interface 43 functions as an instruction receiving section that receives various input operations from the user, converts the received input operations into electrical signals, and outputs the electrical signals to the control section 44 . Furthermore, for example, the input interface 43 receives input operations from the user such as reconstruction conditions when reconstructing CT image data, image processing conditions when generating post-processed images from CT image data, and the like. For example, the input interface 43 may include 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 that integrates a display screen and a touchpad, and an optical sensor. This can be realized by using a non-contact input unit, a voice input unit, etc. Note that when the input interface 43 is a touch screen, the input interface 43 can also function as the display section 42. Further, the input interface 43 may be provided in the gantry device 10. Furthermore, the input interface 43 may be configured with a tablet terminal or the like capable of wireless communication with the console device 40. Furthermore, the input interface 43 is not limited to one that includes physical operation parts such as a mouse and a keyboard. For example, the input interface 43 is configured to receive an electrical signal corresponding to an input operation from an external input device provided separately from the console device 40, and perform processing to output this electrical signal to the control unit 44. Good too.

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 a system control unit 441, a preprocessing unit 442, a reconstruction processing unit 443, an image processing unit 444, a scan control unit 445, and a display control unit 446. The functions executed by each functional unit of the control unit 44 shown in FIG. 1 are recorded in the memory 41 in the form of a computer-executable program, for example. The control unit 44 is, for example, a processor, and implements functions corresponding to each read program by reading each program from the memory 41 and executing them. In other words, the control section 44 in a state where each program is read out realizes each functional section shown in the control section 44 of FIG. 1. Note that in FIG. 1, the functions of a system control section 441, a preprocessing section 442, a reconstruction processing section 443, an image processing section 444, a scan control section 445, and a display control section 446 are realized by a single control section 44. However, the present disclosure is not limited thereto. For example, the control unit 44 may be configured by combining a plurality of independent processors, and each processor may implement each function by executing each program. Further, each function of the control unit 44 may be realized by being appropriately distributed or integrated into a single function unit or multiple function units.

The system control unit 441 controls various functions of the control unit 44 based on input operations received from the user via the input interface 43. The preprocessing unit 442 performs preprocessing such as logarithmic transformation 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 on the projection data generated by the preprocessing unit 442 using a filter correction back projection method, a successive approximation reconstruction method, etc., to obtain CT image data (volume data). generate. The reconstruction processing unit 443 stores the reconstructed CT image data in the memory 41.

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 the 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. The reconstruction processing unit 443 can also reconstruct CT image data of each of a plurality of energy components, for example.

Furthermore, the reconstruction processing unit 443 assigns a color tone according to the energy component to each pixel of the CT image data of each energy component, and generates image data in which a plurality of CT image data color-coded according to the energy component are superimposed. can be generated. Further, the reconstruction processing unit 443 can generate image data that allows identification of the substance, for example, using the K absorption edge unique to the substance. Other image data that can be generated by the reconstruction processing unit 443 include monochromatic X-ray image data, density image data, effective atomic number image data, and the like.

To reconstruct CT image data, projection data for 360° around the subject is required, and even in the half-scan method, projection data for 180° + fan angle is required. Either reconstruction method can be applied to this embodiment. For simplicity 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.

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 the user's input operation received via the input interface 43. do. The image processing unit 444 stores the converted image data in the memory 41. Further, the image processing unit 444 performs medical image processing that will be described later using processing examples 1 to 5.

The scan control unit 445 controls the CT scan performed by the gantry 10. For example, the scan control unit 445 controls the operation 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 positioning images (scanograms) and the main imaging (scan) for collecting images 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.

A tomographic image based on projection data acquired by the photon counting type X-ray detection method and a tomographic image based on projection data acquired by the integral type X-ray detection method by the X-ray CT apparatus 1 of the present embodiment having the above-described configuration. An example of processing for displaying an image will be described below. Note that 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. From now on, data acquired using the photon counting type X-ray detection method (the "data" described here includes images such as tomographic images) will be referred to as "data acquired using the photon counting method" and "PC type". Sometimes referred to as data. Similarly, data acquired by the integral type X-ray detection method may be referred to as data "obtained by the integral method" or "integral type" data. According to each processing example described below, the positional deviation and image quality difference between the tomographic image obtained by the photon counting method and the tomographic image obtained by the integral method are reduced, and it is possible to obtain a display suitable for medical diagnosis. can.

<Processing example 1>
In processing example 1, the image quality is acquired based on the first data obtained by the photon counting method by the X-ray CT apparatus 1, and the second data obtained by the integral method in a past examination. The third data is generated by processing the signal for acquiring the first data so as to reduce the difference in image quality between the two images. The generated third data is used for position alignment and image interpretation. FIG. 3A is a flowchart illustrating processing by the image processing unit 444 and display control unit 446 in processing example 1.

In S101, the image processing unit 444 uses the first data acquired using the first X-ray detection method and the second X-ray detection method that is an X-ray detection method different from the first X-ray detection method. second data obtained using the method. In addition, in this example, the first data and the second data are acquired in examinations on different dates and times, and the first data is obtained using a photon counting type CT apparatus (hereinafter referred to as a PC-type CT apparatus) in the current examination. This is the first projection data (hereinafter referred to as PC type projection data) acquired in the above. Further, the second data is second projection data (hereinafter referred to as integral type projection data) acquired by an integral type CT apparatus (hereinafter referred to as integral type CT apparatus) in a past examination. The X-ray CT device 1 is an example of a PC-type CT device. Note that the integral projection data may be data stored in the memory of the console device 40 (which may be the memory 41 or other memory), or may be data stored in a server connected to the console device 40. It may also be data stored in an external device.

In S102, the image processing unit 444 generates volume data by performing back projection 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 obtains the PC type volume data and the integral type volume data by performing reconstruction processing on each of the PC type projection data and the integral type projection data using the filtered back projection method. The PC type volume data is an example of data based on the first data (PC type projection data in this example). Further, the integral volume data is an example of data based on the second data (integral projection data in this example).

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 the projection data acquired by the integral method from the signal (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 the 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 preprocessing 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 using the 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 preprocessing 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.

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

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), Search for corresponding feature points in the other volume data. Possible feature points include SIFT, HOG, and SURF. Furthermore, characteristic parts of the image may be extracted as feature points by performing edge detection processing or the like. Further, template matching, that is, SSD (Sum of Squared Difference), normalized correlation, etc. can be used to search for corresponding feature points. Then, the image processing unit 444 transforms the two volumes 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 corresponding feature points is minimized. Align the data. At this time, if the positions of the feature points are significantly different, a triangular mesh is formed with the feature points as lattice points, and alignment is performed using nonlinear transformation such as local affine transformation, which applies affine transformation to each triangular mesh. It's okay to be beaten. Examples of nonlinear transformation include Free-form deformation (FFD) using B-splines. This conversion amount is used as the above-mentioned positional deviation amount.

In S105, the image processing unit 444 generates a tomographic image of the same cross-sectional position from the aligned PC type volume data and integral type volume data. 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. 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-sections at the same position generated in S105 on the display unit 42.

FIGS. 4A and 4B show schematic diagrams when displaying cross-sectional images of the same position of PC type volume data and integral type volume data. FIG. 4A is an example of a screen that simultaneously displays a PC-type tomographic image of a predetermined cross-section in PC-type volume data and an integral-type tomographic image at the same position as the predetermined cross-section in integral-type volume data. In the example screen of FIG. 4A, a PC type tomographic image is displayed on the right side and an integral type tomographic image is displayed on the left side. In this way, when two tomographic images are displayed simultaneously, the two tomographic images are displayed in pairs (displayed in parallel) with a positional relationship such as horizontal or vertical. At this time, the two tomographic images may be displayed on the same screen or may be displayed on separate screens. Furthermore, the timings at which the display of the two tomographic images starts or ends may be different. Alternatively, as shown in FIG. 4B, a stack display may be used in which two tomographic images are displayed individually by switching pages. Since the two tomographic images displayed in FIGS. 4A and 4B are properly aligned, the user can easily confirm changes over time in the region of interest, such as a lesion. Further, at this time, a tomographic image (hereinafter referred to as a pseudo tomographic image) of a cross section of the pseudo volume data at the above position (same position as the PC type tomographic image and the integral type tomographic image) may be displayed. For example, in the parallel display as shown in FIG. 4A, the PC type tomographic image may be replaced with a pseudo tomographic image, and the pseudo tomographic image and the integral type tomographic image may be displayed in parallel. Alternatively, in stack display (switching display) as shown in FIG. 4B, the PC type tomographic image may be replaced with a pseudo tomographic image, and the pseudo tomographic image and the integral type tomographic image may be switched and displayed. This allows the user to compare past tomographic images and current tomographic images with similar image quality.

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

Further, there are cases in which the data obtained from past examinations is only an integral tomographic image acquired by an integral CT apparatus. In this case, since integral projection data and integral volume data cannot be obtained, instead of positioning using volume data, a corresponding PC type tomographic image is obtained from information such as the tomographic position of the integral tomographic image, and the tomographic Images can be aligned with each other. Therefore, the data based on the first data and the data based on the second data become a PC type tomographic image and an integral type tomographic image, respectively. Further, a pseudo tomographic image is used as data (data based on the third data) used for positioning the PC type tomographic image and the integral type tomographic image. The processing in this case will be described below with reference to the flowchart in FIG. 3B.

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

<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 region is used for display. FIG. 3C is a flowchart for explaining the processing example 2.

S201 to S205 are the same as S101 to S105 of Processing Example 1 (FIG. 3A). 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. Further, the integral type tomographic image is a tomographic image obtained from integral volume data generated based on integral type projection data acquired by an integral method in a past examination.

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 that represents the difference between the integral-type CT tomographic image and the pseudo tomographic image. In this embodiment, as an example of an image that represents the difference, a difference image that identifiably displays the area (difference area) that is the difference between the integral-type CT tomographic image and the pseudo tomographic image is generated. 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, for example, an image in which information indicating the difference area is reflected in the PC-type tomographic image, as in FIG. 4D. Note that, as another example of an image that represents the difference, an image that represents 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. In this case, for example, as shown in FIG. 4C, the PC type tomographic image (the image on the left side of the figure) and the difference image (the image on the right side of the figure) may be displayed side by side, 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, if 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.

As described above, in processing example 2, it is possible to generate an image showing changes over time in which the influence of differences in X-ray detection methods is reduced. As a result, changing portions of the region of interest such as lesions are extracted, and unchanged portions are less likely to be extracted as differences, making it easier for doctors and technicians to diagnose.

As mentioned in Processing Example 1, the data obtained from past examinations using an integral CT device is only integral tomographic images, and integral projection data and integral volume data cannot be obtained. There may also be cases where alignment cannot be achieved. The processing in that case will be explained with reference to the flowchart of FIG. 3D. The processing from S211 to S215 in FIG. 3D is similar to the processing from S111 to S115 in Processing Example 1 (FIG. 3B). In S216, the image processing unit 444 generates a difference image from the pseudo tomographic image aligned in S215 and the integral tomographic image. In S217, the display control unit 446 performs display using the difference image, similar to S208.

<Processing example 3>
In processing example 3, the first data (integral type tomographic image) acquired using the integral method is processed to improve the image quality of the second data (PC type tomographic image) acquired using the photon counting method. Generate similar third data (pseudo tomographic image). In FIG. 3B of Processing Example 1 and FIG. 3D of Processing Example 2, the process of performing alignment using a pseudo tomographic image when volume data cannot be aligned with each other has been described. In these processes, in Processing Examples 1 and 2, a pseudo tomographic image used for alignment or generation of a difference image was obtained from pseudo volume data. On the other hand, in processing example 3, a pseudo tomographic image used to align the PC type tomographic image and the integral type tomographic image and to generate a difference image is generated from the integral type tomographic image. More specifically, in processing example 3, the image quality of integral tomographic images acquired in past examinations is improved through image processing, and the image quality is comparable (similar) to tomographic images acquired by the photon counting method. A tomographic image is generated and used as a 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 and the PC tomographic image and generate a difference image.

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

In S303, the image processing unit 444 improves the image quality (e.g., graininess or sharpness) of the integral 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 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) is 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 obtained. 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.

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 from the past examination and the PC type tomographic image from 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 alignment. The display process is similar to the display process described in S208 and S217. In addition, by replacing the integral type tomographic image with a pseudo tomographic image and displaying it together with the PC type tomographic image, the user can compare a tomographic image based on a past examination and a tomographic image based on a current examination, which have similar image quality, thereby improving diagnostic efficiency.

Note that in Processing Example 3, image processing is performed on the integral type tomographic image to generate a pseudo tomographic image close to the image quality of the PC type tomographic image, but the present invention is not limited to this. A process that reduces at least one of graininess and sharpness (for example, image blurring) is performed on the PC-type tomographic image to generate a pseudo tomographic image that is close to the quality of the tomographic image obtained by the integral method. It is clear that it is also good. In this case, in S305, a difference image between the pseudo tomographic image and the integral tomographic image is generated. Furthermore, in this case, by replacing the PC type tomographic image with a pseudo tomographic image and displaying it together with the integral type tomographic image, the user can compare past and current tomographic images with similar image quality.

<Processing example 4>
In Processing Example 3, a configuration was described in which a pseudo tomographic image in which the image quality of an integral type tomographic image is brought close to that of a PC type tomographic image is obtained by image processing. In processing example 4, a configuration will be described in which, using AI, a pseudo tomographic image is obtained in which the image quality of an integral type tomographic image is made close to the image quality of a tomographic image obtained by a photon counting method. More specifically, by inputting integral type tomographic images obtained in past examinations to the trained model, a pseudo tomographic image with image quality similar to a PC type tomographic image is obtained. Then, the PC type tomographic image and the integral type tomographic image are aligned using the pseudo tomographic image, and a difference image between the pseudo tomographic image and the PC type tomographic image is generated. Here, the trained model is obtained by machine learning using a pair of a pseudo tomographic image similar to an integral tomographic image and a PC type tomographic image (a tomographic image obtained from a photon counting CT device) as training data. It is a learning model.

Figure 3F is a flowchart explaining image processing according to processing example 4. S401 to S402 are similar to S301 to S302 in processing example 3 (Figure 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) possessed by 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.

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 the 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 obtained 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.

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. A GAN (generative adversarial network) may also 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 uses a loss function to calculate the error between the output data from the neural network and the teacher data. In addition, the update unit updates the connection weighting coefficient between the nodes of the neural network based on the error obtained by the error detection unit so that the error is reduced. The update unit updates the connection weighting coefficient using, for example, an error backpropagation method. The error backpropagation method is a method of adjusting the connection weighting coefficient between the nodes of each neural network so that the above error is reduced.

Note that a GPU may be used for machine learning of a learning model and estimation using a learned model. Increasing parallel processing using the GPU enables more efficient calculations and is therefore effective when learning is performed multiple times using a learning model (for example, deep learning). Specifically, when a learning program including a learning model is executed, learning is performed by the CPU and GPU working together to perform calculations. Note that the processing of the learning section may be performed only by the CPU or GPU. Furthermore, when performing estimation using a trained model, a GPU may be used as in the case of learning. Through such machine learning, the machine learning engine generates a learned model that outputs a pseudo tomographic image based on the integral tomographic image. Furthermore, trained models can be generated for each imaging condition such as the number of views, tube current, and slice thickness for the same region.

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 similar to S304. In S405, the image processing unit 444 acquires a difference image between the aligned pseudo tomographic image and the PC type tomographic image. This process is similar to 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 similar to S306.

<Processing example 5>
In processing examples 2 to 4, by calculating 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, the integral type of the past examination is calculated. The difference area between the PC type tomographic image and the PC type tomographic image of the current examination was calculated. In processing example 5, when an ROI (region of interest) is set in one of the acquired integral tomographic images and the PC type tomographic image, processing is performed to reflect the ROI at the same position in the other tomographic image. explain. Note that the region set by the ROI may be an analysis region (a region to be analyzed). FIG. 3H is a flowchart illustrating the processing of the image processing unit 444 and display control unit 446 in processing example 5.

S501 to S506 are the same as S101 to S106 in Processing Example 1 (FIG. 3A). Through 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, the first ROI) on the PC type tomographic image displayed on the display unit 42 to measure the size of a lesion 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 the 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.

In S508, the image processing unit 444 calculates the position on the integral type tomographic image corresponding to the first ROI on the PC type tomographic image set by the user, and calculates the position on the integral type tomographic image corresponding to that position (this can also be expressed as setting the corresponding region). Then, the display control unit 446 displays information indicating the second ROI (information indicating the 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 displaying graphs and numerical values of the measurement values and analysis values measured by each ROI, it is possible to display them in a distinguishable manner corresponding 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 a distinguishable manner, such as by displaying them in different display forms. 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 tomographic image may be displayed in different colors.

Note that in processing example 5, the second ROI is set on the integral type tomographic image based on the position information regarding the first ROI set on the PC type tomographic image, but the present invention is not limited to this. . For example, the first ROI may be set on the integral type tomographic image, and the second ROI may be set on the PC type tomographic image based on the position information. At this time, the first ROI set on the integral tomographic image may be a third ROI that has already been set in the past, and in such a case, as shown in FIG. An area on the PC-type tomographic image corresponding to the third ROI that has already been set in the integral-type tomographic image is specified and displayed in a superimposed manner as information indicating the fourth ROI. In addition, in this state, if the user newly sets a first ROI on the PC-type tomographic image, information indicating the third ROI corresponding to the ROI of the integral-type tomographic image and the newly set first ROI are added. The information indicating the ROI may be displayed in a distinguishable manner (for example, displayed in different display formats).

Furthermore, the first to fourth ROIs may be reflected between the tomographic images after alignment shown in processing examples 3 and 4. For example, in an integral tomographic image and a PC tomographic image aligned using the method of processing example 3, it is possible to reflect the first ROI set in the PC tomographic image as a second ROI in the integral tomographic image. can. Similarly, in the aligned integral type tomographic image and PC type tomographic image, the third ROI set in the integral type tomographic image is set as the fourth ROI in the PC type tomographic image based on the alignment result. Can be set.

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 be obtained on different dates and times. For example, the data may be obtained on the same day by the integral CT device and the PC CT device. 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 with two or more types of tube voltage, it can be compared in a similar 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 obtained by CT imaging using two types of X-rays with different tube voltages from the signal for acquiring a set of PC-type projection data, and compare it in the same way 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).

Furthermore, the medical image processing apparatus of the present disclosure may be capable of performing one of processing examples 1 to 5, or may be capable of performing a plurality of processes. For example, the user may be able to select between the processing in S111 to S114 of the first processing example and the processing in S401 to S403 in the fourth processing example. More specifically, the control unit 44 acquires a PC-type tomographic image (first data) and an integral-type tomographic image (second data), and converts the signals detected by the PC method into similar to integral-type volume data. The first method is to obtain a pseudo tomographic image (third data) corresponding to the position of the PC type tomographic image by acquiring pseudo volume data, and the PCCT is performed by image processing from the integral type tomographic image (second data). Either the second method of acquiring a pseudo tomographic image (fourth data) similar to the image can be selected. At this time, the selection instruction operation performed by the user includes, for example, a switch to switch to the other method displayed on a screen displaying the results obtained by one of the first and second methods. Examples include button operations. Of course, the selection instruction operation is not limited to this, and may be an operation of selecting the first method or the second method from buttons or pull-downs displayed on the screen before displaying the test results. Note that the subsequent step of aligning the data based on the first data and the data based on the second data using the third data is performed in S115 to S116 or S404 to S404 based on the selected method. S406 is automatically selected.

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 using a photon-counting X-ray detection method and a tomographic image based on projection data acquired using an integral X-ray detection method. This makes it possible to more accurately align these tomographic images and facilitate comparisons such as observing changes over time in the same subject, thereby reducing the burden on doctors and technicians and barriers to replacing equipment.

Further, the disclosed technology is also realized by performing the following processing. That is, the disclosed technology supplies software (medical image processing program) that implements one or more functions of the various embodiments described above to a system or device via a network or a storage medium, and a computer of the system or device. It can also be realized by a process in which (or a CPU, MPU, etc.) reads and executes a medical image processing program. A computer has one or more processors or circuits and may include separate computers or a network of separate processors or circuits for reading and executing computer-executable instructions. The processor or circuit may include a central processing unit (CPU), microprocessing unit (MPU), graphics processing unit (GPU), application specific integrated circuit (ASIC), or 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).

The disclosure of this specification includes the following medical image processing apparatus, method for controlling a medical image processing apparatus, and medical image processing program.
(Item 1)
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. an acquisition means to acquire;
generating means for processing the first data or a signal for acquiring the first data to generate third data similar to the second data;
A position at which data based on the first data and data based on the second data are aligned based on a result of aligning data based on the second data and data based on the third data. A medical image processing device comprising: a matching means.
(Item 2)
The processing of the first data or the signal for acquiring the first data is processing for reducing a difference in image quality between an image based on the first data and an image based on the second data. The medical image processing device according to item 1, characterized in that:
(Item 3)
The first data is data based on counting data of X-ray photons collected using the signal detected by the X-ray detector, and the second data is data based on the count data of X-ray photons collected using the signal detected by the X-ray detector. The medical image processing device according to item 1, wherein the data is based on integral data obtained by integrating over a time width.
(Item 4)
The first data is data based on integral data obtained by integrating a signal detected by the X-ray detector over a predetermined time width, and the second data is collected using the signal detected by the X-ray detector. The medical image processing device according to item 1, wherein the data is based on X-ray photon count data.
(Item 5)
The generation means generates the third data based on an integral value obtained by integrating the product of the number and energy of photons included in the count data detected by the X-ray detector. The medical image processing device according to item 3.
(Item 6)
Item 1, wherein the first data and the second data are both projection data, or both are volume data, or one is projection data and the other is volume data. The medical image processing device described in .
(Item 7)
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 apparatus according to item 3, wherein the generating means generates the third data by applying image processing to reduce graininess or sharpness to the first data.
(Item 9)
The medical image processing apparatus according to item 3, wherein the generating means generates the third data by applying image processing to improve graininess or sharpness to the first data. .
(Item 10)
The generating means includes a first image acquired from data acquired using the second X-ray detection method and a first image acquired from data acquired using the second X-ray detection method; Learning using as training data a pair with a third image in which the image quality of the first image is similar to the image quality of the second image obtained from the data obtained using the first X-ray detection method. 4. The medical image processing apparatus according to item 3, wherein the third data is generated from the first data using a learned model obtained by the method.
(Item 11)
Display control 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. The medical image processing apparatus according to any one of items 1 to 10, further comprising means.
(Item 12)
12. The medical image processing apparatus according to item 11, wherein the display control means displays the first image and the second image on the display section in parallel or in a switched manner.
(Item 13)
represents 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 The medical image processing apparatus according to any one of items 1 to 10, further comprising means for generating an image.
(Item 14)
14. The medical image processing apparatus according to item 13, wherein the image representing the difference is a difference image representing a difference area between the third image and the second image.
(Item 15)
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 area is displayed superimposed on the second image. 15. The medical image processing device according to item 14.
(Item 16)
The medical device according to item 11, further comprising an area setting means for setting an area on the second image, which corresponds to a first area set in the first image, as a second area. Image processing device.
(Item 17)
17. The medical image processing apparatus according to item 16, further comprising instruction receiving means for receiving an instruction to set the first area on the first image.
(Item 18)
Item 16, wherein the display control means superimposes and displays information indicating the first area on the first image and information indicating the second area on the second image. The medical image processing device described.
(Item 19)
The display control means displays information indicating the second area set by the area setting unit and information indicating the area set by drawing on the second image by the user in a distinguishable manner. The medical image processing device according to item 16, characterized by:
(Item 20)
20. The medical image processing apparatus according to item 19, wherein the display control means draws and sets an area on the second image by the user as an area set in a past examination.
(Item 21)
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 generation means can process the second data or a signal for acquiring the second data to generate fourth data similar to the first data,
2. The medical image processing apparatus according to item 1, wherein the generation means includes instruction reception means for accepting a selection instruction for generating either the third data or the fourth data.
(Item 23)
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. an acquisition process to acquire;
a data generation step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data;
A position at which data based on the first data and data based on the second data are aligned based on a result of aligning data based on the second data and data based on the third data. A method for controlling a medical image processing apparatus, comprising: an alignment step.
(Item 24)
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. an acquisition step to acquire;
a data generation step of processing the first data or a signal for acquiring the first data to generate third data similar to the second data;
A position at which data based on the first data and data based on the second data are aligned based on a result of aligning data based on the second data and data based on the third data. A medical image processing program comprising: a matching step.

The invention is not limited to the embodiments described above, and various changes and modifications can be made without departing from the spirit and scope of the invention. Therefore, the following claims are hereby appended to disclose the scope of the invention.

1: X-ray CT device, 10: gantry device, 30: bed device, 40: console device, 12: X-ray detector, 18: DAS, 44: control section, 441: system control section, 442: preprocessing section, 443: Reconstruction unit, 444: Image processing unit, 445: Scan control unit, 446: Display control unit

Claims (24)

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 processing the first data or a signal for acquiring the first data to generate third data similar to the second 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. The medical image processing device according to claim 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. The first data is data based on counting data of X-ray photons collected using the signal detected by the X-ray detector, and the second data is data based on the count data of X-ray photons collected using the signal detected by the X-ray detector. The medical image processing apparatus according to claim 1, wherein the data is based on integral data obtained by integrating over a time width. The first data is data based on integral data obtained by integrating a signal detected by the X-ray detector over a predetermined time width, and the second data is collected using the signal detected by the X-ray detector. The medical image processing apparatus according to claim 1, wherein the data is based on count data of X-ray photons. The medical image processing device according to claim 3, characterized in that 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. A claim characterized in that the first data and the second data are both projection data, or both are volume data, or one is projection data and the other is volume data. 1. The medical image processing device according to 1. The medical image processing apparatus according to claim 1, wherein at least one of the first data and the second data is a tomographic image. The medical image processing device according to claim 3, characterized in that the generating means generates the third data by applying image processing to the first data to reduce graininess or sharpness. 4. Medical image processing according to claim 3, wherein the generating means generates the third data by applying image processing to improve graininess or sharpness to the first data. Device. The medical image processing device according to claim 3, characterized in that the generating means generates the third data from the first data 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 having image quality similar to that of the second image acquired from data acquired using the first X-ray detection method. The medical image processing device according to claim 1, 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. 12. The medical image processing apparatus according to claim 11, wherein the display control means displays the first image and the second image in parallel or in a switched manner on the display unit. The medical image processing device according to claim 1, further comprising a means for generating an image representing the 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. The medical image processing apparatus according to claim 13, wherein the image representing the difference is a difference image representing a difference area between the third image and the second image. The medical image processing device according to claim 14, characterized in that 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. The medical image processing device according to claim 11, further comprising a region setting means for setting, as a second region, a region on the second image that corresponds to a first region set on the first image. The medical image processing device according to claim 16, further comprising an instruction receiving means for receiving an instruction to set the first region on the first image. The medical image processing device according to claim 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 the information on the first image and the information on the second image. The medical image processing device according to claim 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 the user by drawing on the second image in a distinguishable manner. The medical image processing device according to claim 19, characterized in that the display control means is characterized in that the area drawn and set by the user on the second image is an area set in a previous examination. The medical image processing device according to claim 1, characterized in that the first data and the second data are data acquired from different X-ray detectors at different dates and times. The generation means can process the second data or a signal for acquiring the second data to generate fourth data similar to the first data,
The medical image processing apparatus according to claim 1, wherein the generation means includes instruction reception means for accepting a selection instruction for generating either the third data or the fourth data. . 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. an acquiring step of acquiring first data acquired using a first X-ray detection technique and second data acquired using a second X-ray detection technique different from the first X-ray detection technique;
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.

Images