JP7224829B2 - Medical image processing apparatus and method - Google Patents

Description

Embodiments of the present invention relate to medical image processing apparatus and methods.

An X-ray CT (Computed Tomography) apparatus removes scattered X-rays to improve contrast. As a technique for removing scattered X-rays, there is a technique using hardware such as placing a collimator plate in front of a detector to remove scattered X-rays. There is also a method using software to remove the influence of scattered X-rays by image processing.
When hardware is used to remove scattered X-rays, there are methods such as applying a two-dimensional collimator having a high ability to remove scattered X-rays or increasing the height of the collimator, but this leads to an increase in cost.
On the other hand, when the scattered X-ray correction process is performed by software, the calculation time becomes longer if the scattered X-ray removal capability is to be enhanced. Attempting to introduce a high-performance arithmetic processing unit in order to shorten the calculation time will eventually lead to an increase in cost.

U.S. Patent Application Publication No. 2018/0146935 U.S. Patent Application Publication No. 2018/0078221 U.S. Pat. No. 7,362,849

A problem to be solved by the present invention is to obtain a high-quality image while suppressing costs.

A medical image processing apparatus according to this embodiment includes an acquisition unit and a processing unit. The acquisition unit acquires first medical data to be processed based on hardware having a first ability to remove scattered radiation. The processing unit follows a trained model that receives first medical data and outputs second medical data based on a second scattered radiation removal ability higher than the first scattered radiation removal ability. Second medical data is generated from one medical data.

FIG. 1 is a block diagram showing an X-ray CT apparatus according to the first embodiment. FIG. 2 is a flow chart showing an operation example of the X-ray CT apparatus according to the first embodiment. FIG. 3 is a diagram showing the configuration of a scattered radiation removal grid that serves as a reference for determining the scattered radiation removal ability. FIG. 4 is a block diagram showing an example of a learning system that generates trained models. FIG. 5 is a diagram showing the concept of machine learning by the model learning device according to the first embodiment. FIG. 6 is a diagram illustrating the concept of using a machine-learned model according to the first embodiment. FIG. 7 is a block diagram of the medical image processing apparatus according to the second embodiment.

A medical image processing apparatus and method according to the present embodiment will be described below with reference to the drawings. In the following embodiments, it is assumed that parts denoted by the same reference numerals perform the same operations, and overlapping descriptions will be omitted as appropriate. An embodiment will be described below with reference to the drawings.

(First embodiment)
An X-ray CT (Computed Tomography) apparatus including a medical image processing apparatus according to this embodiment will be described below with reference to the block diagram of FIG. The X-ray CT apparatus 1 shown in FIG. 1 has a gantry device 10, a bed device 30, and a console device 40 that realizes processing of the medical image processing device. In FIG. 1, a plurality of gantry devices 10 are depicted for convenience of explanation.

In this embodiment, the rotation axis of the rotating frame 13 in the non-tilt state or the longitudinal direction of the top plate 33 of the bed apparatus 30 is the Z-axis direction, and the axial direction perpendicular to the Z-axis direction and horizontal to the floor surface is are defined as the X-axis direction, the axis direction perpendicular to the Z-axis direction, and the Y-axis direction as the axis direction perpendicular to the floor surface.

For example, the gantry device 10 and the bed device 30 are installed in a CT examination room, and the console device 40 is installed in a control room adjacent to the CT examination room. Note that the console device 40 does not necessarily have to be installed in the control room. For example, the console device 40 may be installed in the same room together with the gantry device 10 and the bed device 30 . In any case, the gantry device 10, the bed device 30, and the console device 40 are connected by wire or wirelessly so as to be able to communicate with each other.

The gantry device 10 is a scanning device having a configuration for X-ray CT imaging of the subject P. As shown in FIG. The gantry 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 data acquisition device 18 (hereinafter , DAS (Data Acquisition System) 18).

The X-ray tube 11 is a vacuum tube that generates X-rays by irradiating thermal electrons from a cathode (filament) to an anode (target) by applying a high voltage and supplying a filament current from an X-ray high voltage device 14. is. Specifically, X-rays are generated by thermal electrons colliding with a target. For example, the X-ray tube 11 is a rotating anode type X-ray tube that generates X-rays by irradiating a rotating anode with thermal electrons. The X-rays generated by the X-ray tube 11 are shaped into a cone beam through, for example, a collimator 17 and irradiated onto the subject P. FIG.

The X-ray detector 12 detects X-rays emitted from the X-ray tube 11 and passing through the subject P, and outputs an electrical signal corresponding to the X-ray dose to the DAS 18 . The X-ray detector 12 has, for example, a plurality of X-ray detection element arrays in which a plurality of X-ray detection elements are arranged in the channel direction along one circular arc centering on the focal point of the X-ray tube 11 . The X-ray detector 12 has, for example, a row structure in which a plurality of X-ray detection element rows each having a plurality of X-ray detection elements arranged in the channel direction are arranged in the slice direction (row direction).

Specifically, the X-ray detector 12 is, for example, an indirect conversion type detector having a grid, a scintillator array, and a photosensor array. The X-ray detector 12 is an example of a detection section.

The scintillator array has a plurality of scintillators. The scintillator converts incident X-rays into the number of photons corresponding to the intensity of the incident X-rays.
The grid has an X-ray shielding plate arranged on the surface of the scintillator array on the X-ray incident side and having a function of absorbing scattered X-rays. Note that the grid may also be called a collimator.

The photosensor array has a function of amplifying the light received from the scintillator and converting it into an electric signal, and has photosensors such as photomultiplier tubes (PMTs), for example.
The X-ray detector 12 may be a direct conversion type detector having a semiconductor element that converts incident X-rays into electrical signals.

The rotating frame 13 supports the X-ray generator and the X-ray detector 12 so as to be rotatable around the rotation axis. Specifically, the rotating frame 13 is an annular frame that supports the X-ray tube 11 and the X-ray detector 12 so as to face each other and rotates the X-ray tube 11 and the X-ray detector 12 by means of a control device 15, which will be described later. is. The rotating frame 13 is rotatably supported by a fixed frame (not shown) made of metal such as aluminum. Specifically, the rotating frame 13 is connected to the edges of the stationary frame via bearings. The rotating frame 13 receives power from the drive mechanism of the control device 15 and rotates around the rotation axis Z at a constant angular velocity.

In addition to the X-ray tube 11 and the X-ray detector 12, the rotating frame 13 further includes an X-ray high-voltage device 14 and a DAS 18 to support them. Such a rotating frame 13 is accommodated in a substantially cylindrical housing in which an opening (bore) 19 forming an imaging space is formed. The aperture approximately matches the FOV. The central axis of the opening coincides with the rotational axis Z of the rotating frame 13 . The detection data generated by the DAS 18 is provided in a non-rotating portion (for example, a fixed frame, not shown in FIG. 1) of the gantry device by optical communication from a transmitter having a light emitting diode (LED), It is transmitted to a receiver (not shown) having a photodiode and forwarded to the console device 40 . The method of transmitting the detected data from the rotating frame to the non-rotating portion of the gantry is not limited to the optical communication described above, and any method of non-contact data transmission may be adopted.

The X-ray high voltage device 14 has electric circuits such as a transformer and a rectifier, and has a function of generating a high voltage to be applied to the X-ray tube 11 and a filament current to be supplied to the X-ray tube 11. It has a generating device and an X-ray control device for controlling the output voltage according to the X-rays emitted by the X-ray tube 11 . The high voltage generator may be of a transformer type or an inverter type. Note that the X-ray high-voltage device 14 may be provided on a rotating frame 13 to be described later, or may be provided on a fixed frame (not shown) side of the gantry device 10 .

The control device 15 has a processing circuit having a CPU (Central Processing Unit) and the like, and drive mechanisms such as motors and actuators. The processing circuit has, as hardware resources, a processor such as a CPU or an MPU (Micro Processing Unit) and a memory such as a ROM (Read Only Memory) or a RAM (Random Access Memory). In addition, the control device 15 includes an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), and other complex programmable logic devices (Complex Programmable Logic Device: CPLD ), which may be implemented by a Simple Programmable Logic Device (SPLD). The control device 15 controls the X-ray high-voltage device 14, the DAS 18, etc. according to commands from the console device 40. FIG. The processor implements the control by reading and implementing the program stored in the memory.

The control device 15 also has a function of receiving an input signal from an input interface 43 (described later) attached to the console device 40 or the gantry device 10 and controlling the operations of the gantry device 10 and the bed device 30 . For example, the control device 15 receives an input signal and performs control to rotate the rotating frame 13 , control to tilt the gantry device 10 , and control to operate the bed device 30 and the tabletop 33 . The control for tilting the gantry device 10 is performed by the control device 15 rotating the frame about an axis parallel to the X-axis direction based on inclination angle (tilt angle) information input by the input interface 43 attached to the gantry device 10 . It is realized by rotating 13. Also, the control device 15 may be provided in the gantry device 10 or may be provided in the console device 40 . It should be noted that the control device 15 may be configured so as to directly incorporate the program into the circuit of the processor instead of storing the program in the memory. In this case, the processor implements the above control by reading and executing a program incorporated in the circuit.

Wedge 16 is a filter for adjusting the dose of X-rays emitted from 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 is a filter that For example, the wedge 16 (wedge filter, bow-tie filter) is a filter processed from aluminum to have a predetermined target angle and a predetermined thickness.

The collimator 17 is a lead plate or the like for narrowing down the irradiation range of the X-rays transmitted through the wedge 16, and a slit is formed by combining a plurality of lead plates or the like. Note that the collimator 17 may also be called an X-ray diaphragm.

The DAS 18 reads the electrical signal from the X-ray detector 12 and generates digital data (hereinafter also referred to as detection data) regarding the X-ray dose detected by the X-ray detector 12 based on the read electrical signal. The detection data is a set of data indicating the channel number and row number of the X-ray detection element from which it was generated, the view number indicating the acquired view (also called projection angle), and the integral value of the detected X-ray dose. be. The DAS 18 is implemented by, for example, an ASIC (Application Specific Integrated Circuit) equipped with circuit elements capable of generating detection data. The detected data are transferred to the console device 40 .

For example, DAS 18 includes a preamplifier, variable amplifier, integrator circuit and A/D converter for each detector pixel. The preamplifier amplifies the electric signal from the X-ray detection element of the connection source with a predetermined gain. A variable amplifier amplifies the electrical signal from the preamplifier with a variable gain. An integrator circuit integrates the electrical signal from the preamplifier over one view period to generate an integrated signal. The crest value of the integral signal corresponds to the X-ray dose value detected by the X-ray detection element of the connection source over one view period. The A/D converter analog-to-digital converts the integration signal from the integration circuit to generate detection data.

The bed device 30 is a device for placing and moving a subject P to be scanned, and includes a base 31 , a bed driving device 32 , a top board 33 and a support frame 34 .

The base 31 is a housing that supports the support frame 34 so as to be vertically movable.
The bed driving device 32 is a motor or actuator that moves the table 33 on which the subject P is placed in the longitudinal direction of the table 33 . The bed driving device 32 moves the tabletop 33 under the control of the console device 40 or the control device 15 . For example, the bed driving device 32 moves the top plate 33 in a direction orthogonal to the subject P so that the body axis of the subject P placed on the top plate 33 coincides with the central axis of the opening of the rotating frame 13 . do. Further, the bed driving device 32 may move the top board 33 along the body axis direction of the subject P according to the X-ray CT imaging performed using the gantry device 10 . The bed drive device 32 generates power by driving at a rotational speed according to the duty ratio of the drive signal from the control device 15 and the like. The bed driving device 32 is realized by a motor such as a direct drive motor or a servo motor, for example.

A top plate 33 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 42 , an input interface 43 and a processing circuit 44 . Data communication between the memory 41, the display 42, the input interface 43, and the processing circuit 44 is performed via a bus (BUS). Note that the console device 40 is described as being separate from the gantry device 10 , but the console device 40 or a part of each component of the console device 40 may be included in the gantry device 10 .

The memory 41 is a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an integrated circuit storage device that stores various information. The memory 41 stores projection data and reconstructed image data, for example. The memory 41 can be connected to portable storage media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), flash memories, semiconductor memory devices such as RAMs (Random Access Memory), etc., in addition to HDDs and SSDs. It may also be a driving device that reads and writes various information with. Also, the storage area of the memory 41 may be in the X-ray CT apparatus 1 or in an external storage device connected via a network. For example, the memory 41 stores data of CT images and display images. The memory 41 also stores a control program according to this embodiment.

The display 42 displays various information. For example, the display 42 outputs a medical image (CT image) generated by the processing circuit 44, a GUI (Graphical User Interface) for accepting various operations from the operator, and the like. For example, the display 42 may be, for example, a liquid crystal display (LCD: Liquid Crystal Display), a CRT (Cathode Ray Tube) display, an organic EL display (OELD: Organic Electro Luminescence Display), a plasma display, or any other arbitrary display. , is enabled. Also, the display 42 may be provided on the gantry device 10 . The display 42 may be of a desktop type, or may be configured by a tablet terminal capable of wireless communication with the main body of the console device 40, or the like.

The input interface 43 receives various input operations from the operator, converts the received input operations into electrical signals, and outputs the electrical signals to the processing circuit 44 . For example, the input interface 43 receives acquisition conditions for acquiring projection data, reconstruction conditions for reconstructing CT images, image processing conditions for generating post-processed images from CT images, and the like from the operator. . As the input interface 43, for example, a mouse, keyboard, trackball, switch, button, joystick, touch pad, touch panel display, etc. can be used as appropriate. In addition, in the present embodiment, the input interface 43 is not limited to physical operation components such as a mouse, keyboard, trackball, switch, button, joystick, touch pad, and touch panel display. For example, the input interface 43 includes an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the device and outputs the electrical signal to the processing circuit 44. . The input interface 43 may be provided on the gantry device 10 . Also, the input interface 43 may be composed of a tablet terminal or the like capable of wireless communication with the main body of the console device 40 .

The processing circuit 44 controls the operation of the entire X-ray CT apparatus 1 according to the electric signal of the input operation output from the input interface 43 . For example, the processing circuit 44 has, as hardware resources, processors such as a CPU, MPU, and GPU (Graphics Processing Unit), and memories such as a ROM and a RAM. The processing circuit 44 executes a system control function 441, a preprocessing function 442, a reconstruction processing function 443, an acquisition function 444, a correction processing function 445, and a display control function 446 by means of a processor that executes programs developed in memory. Note that each function (system control function 441, preprocessing function 442, reconstruction processing function 443, acquisition function 444, correction processing function 445, and display control function 446) is not limited to being realized by a single processing circuit. A processing circuit may be configured by combining a plurality of independent processors, and each function may be realized by each processor executing a program.

The system control function 441 controls each function of the processing circuit 44 based on input operations received from the operator via the input interface 43 . Specifically, the system control function 441 reads the control program stored in the memory 41, develops it on the memory in the processing circuit 44, and controls each part of the X-ray CT apparatus 1 according to the developed control program. . For example, the processing circuit 44 controls each function of the processing circuit 44 based on an input operation received from the operator via the input interface 43 . For example, the system control function 441 acquires a two-dimensional positioning image of the subject P for determining the scan range, imaging conditions, and the like. A positioning image is also called a scanogram or a scout image. The system control function 441 is an example of a system control section.

A preprocessing function 442 generates data by performing 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 . Data before preprocessing (detection data) and data after preprocessing may be collectively referred to as projection data.

A reconstruction processing function 443 performs reconstruction processing on the projection data generated by the preprocessing function 442 using a filtered back projection (FBP) method, an iterative reconstruction method, or the like. to generate CT image data.

Acquisition function 444 acquires medical data. Medical data is, for example, CT image data or projection data captured by the X-ray CT apparatus 1 . Acquisition function 444 is an example of an acquisition unit.

The correction processing function 445 executes scattered radiation correction processing on the medical data acquired by the acquisition function 444 to generate medical data from which scattered radiation components have been removed. The correction processing function 445 is an example of a processing unit.

The display control function 446 is a process for controlling the display 42 so as to display information on the progress or result of processing in each function or process of the processing circuit 44 .

The processing circuit 44 also performs scan control processing and image processing.
The scan control process is a process of controlling various operations related to X-ray scanning, such as causing the X-ray high-voltage device 14 to supply a high voltage and causing the X-ray tube 11 to emit X-rays.
In the image processing, the CT image data generated by the reconstruction processing function 443 is transformed into tomographic image data or three-dimensional image data of an arbitrary cross section by a known method based on the input operation received from the operator via the input interface 43. This is the process of converting to Note that the generation of the three-dimensional image data may be directly performed by the reconstruction processing function 443 .

The processing circuit 44 is not limited to being included in the console device 40, and may be included in an integrated server that collectively processes data acquired by a plurality of medical image diagnostic apparatuses.
Although the console device 40 has been described as executing a plurality of functions with a single console, the plurality of functions may be executed by separate consoles. For example, the functions of the processing circuit 44 such as the preprocessing function 442 and the reconstruction processing function 443 may be distributed.

Next, an operation example of the X-ray CT apparatus 1 according to the first embodiment will be described with reference to the flowchart of FIG.
In step S201, positioning imaging (positioning scanning) of the subject P is performed.
In step S202, the main imaging (main scan) of the subject is performed. As for steps S201 and S202, a general scan may be executed, so a detailed description thereof will be omitted.

In step S203, the acquisition function 444 causes the processing circuit 44 to acquire the first medical data to be processed obtained by the main scan. Here, the first medical data is medical data captured based on hardware having the first scattered radiation removal ability. Specifically, the medical data captured based on the hardware having the n-th (n is an integer) anti-scattering ability is an X-ray image provided with an anti-scattering grid having the n-th anti-scattering ability. It includes projection data (or sinogram data) detected by a detector, CT image data reconstructed based on the projection data, and calculated projection data generated by applying forward transformation or the like to the CT image data.

In step S204, the correction processing function 445 causes the processing circuit 44 to perform processing based on the second scatter removal ability, which is higher than the first scatter removal ability, from the first medical data to be processed according to a learned model described later. Generate second medical data. In other words, second medical data to which scattered radiation correction has been performed with higher precision (higher scattered radiation removal rate) than the first medical data to be processed is generated. This completes the operation example of the X-ray CT apparatus 1 .

Next, the configuration of the scattered radiation removal grid, which serves as a reference for determining the scattered radiation removal performance, will be described with reference to FIG.
FIG. 3 shows the anti-scattering grid 301 viewed from the Z-axis direction, and the scintillator array 302 arranged behind the anti-scattering grid 301 . The anti-scatter grid 301 is provided on the X-ray detector 12 and rotates together with the X-ray detector 12 around the Z-axis. FIG. 3 shows the anti-scatter grid 301 when the X-ray detector 12 is positioned at the lowest (180 degrees) position about the Z-axis.

In the scattered radiation removing grid 301, grid plates 3011 for absorbing scattered radiation are arranged at predetermined intervals. A so-called primary X-ray that has passed through the subject P enters the X-ray detector 12 in the space 3012 provided between the two grid plates 3011 . The space 3012 may be formed simply by air, or may be formed by arranging an intermediate substance such as fiber or aluminum that transmits X-rays.

The ability of the anti-scatter grid 301 to remove scattered radiation varies depending on the degree of division of the grid. For example, a two-dimensional anti-scatter grid is finer than a one-dimensional anti-scatter grid, and therefore has a higher ability to remove scattered radiation.

In addition, without being limited to changing the number of dimensions, the scattered radiation removing ability of the anti-scattering grid 301 is determined by the height H of the grid plate, the width W of the grid plate 3011, and the interval (pitch) Pi of the grid plate 3011 (in other words, , the length of the intermediate material 5012 in the X-axis direction) can be defined as a reference (parameter). For example, as the height H of the grid plate 3011 increases, more scattered radiation can be shielded, so that the scattered radiation removal performance increases. As the width W of the grid plate 3011 increases, more scattered radiation can be absorbed, so the ability to remove scattered radiation increases. In addition, the narrower the pitch Pi of the grid plate 3011, the higher the ratio of the primary X-rays incident on the space 3012, so that the ability to remove scattered radiation increases.

Furthermore, the more the grid plate 3011 is made of a material having a higher radiation (X-ray) shielding ability, the higher the ability to remove scattered radiation. For example, materials such as tungsten, molybdenum, and lead, which have larger atomic weights than copper and nickel, have high X-ray shielding ability.
In addition, the above criteria may be combined to consider the ability to remove scattered radiation. For example, the larger the grid ratio (also referred to as the aspect ratio), which is the ratio of the height H to the pitch Pi, the higher the ability to remove scattered radiation. .

Next, a method of generating a trained model used by the correction processing function 445 will be described with reference to FIG.
FIG. 4 is a block diagram showing an example of a medical information processing system that generates trained models. The medical information processing system shown in FIG. 4 includes an X-ray CT apparatus 1 , a learning data storage device 50 and a model learning device 52 .

The learning data storage device 50 stores learning data including multiple learning samples. For example, the learning data storage device 50 is a computer with a built-in mass storage device. The learning data storage device 50 may also be a mass storage device communicatively connected to a computer via a cable or communication network. As the storage device, an HDD (Hard Disk Drive), an SSD (Solid State Drive), an integrated circuit storage device, or the like can be used as appropriate.

The model learning device 52 generates a trained model 411 by causing the model to perform machine learning according to a model learning program based on the learning data stored in the learning data storage device 50 . In this embodiment, a neural network, deep learning, random forest, kernel regression, or the like is assumed as a machine learning algorithm, but other machine learning algorithms are also possible. The model learning device 52 is a computer such as a workstation having processors such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit).

The model learning device 52 and the learning data storage device 50 may be communicably connected via a cable or a communication network. Also, the learning data storage device 50 may be installed in the model learning device 52 . In these cases, learning data is supplied from the learning data storage device 50 to the model learning device 52 . Note that the model learning device 52 and the learning data storage device 50 do not have to be communicably connected. In this case, the learning data is supplied from the learning data storage device 50 to the model learning device 52 via the portable storage medium storing the learning data.

The X-ray CT apparatus 1 and the model learning apparatus 52 may be communicably connected via a cable or a communication network. A trained model 411 generated by the model learning device 52 is supplied to the X-ray CT apparatus 1 and the trained model 411 is stored in the memory 41 . Note that the X-ray CT apparatus 1 and the model learning apparatus 52 do not necessarily have to be communicably connected. In this case, the trained model 411 is supplied from the model learning device 52 to the X-ray CT apparatus 1 via a portable storage medium or the like in which the trained model 411 is stored.

A trained model 411 is a parameterized synthesized function obtained by synthesizing a plurality of functions. A parameterized composite function is defined by a combination of multiple adjustable functions and parameters. Trained model 411 can be any parameterized composite function that meets the above requirements.

Note that the trained model 411 according to the first embodiment is generated by machine-learning a multi-layered network (also simply referred to as a model) before machine learning using a neural network represented by a deep neural network (DNN). . Note that the trained model 411 is not limited to a neural network, and may be generated by learning a model using the machine learning algorithm described above. Also, the trained model 411 may be realized by a lookup table (LUT) instead of a synthetic function with parameters.

Next, the concept of model learning by the model learning device 52 will be described with reference to FIG.
The model learning device 52 may perform machine learning on the multi-layered network 410, which is a learning program, using the learning data. A trained model 411 is installed in the console device 40 of the X-ray CT apparatus 1 . Also, the learned model 411 may be updated when the X-ray CT apparatus 1 is repaired or software is updated.

At the time of model learning of the trained model 411, for example, at the time of shipment from the factory, etc., medical data obtained by actually imaging the subject P using an apparatus equipped with hardware having low scattering radiation elimination ability is used as input data, and the scattering radiation elimination performance is high. Learning data is used in which correct data (output data) is medical data obtained by actually photographing the subject P by a hardware-implemented device. At this time, a phantom, a deceased patient, a living animal, or a dead animal may be used as the subject P in addition to a patient, a healthy person, and the like. The input data and the correct data may be not only measured data, but also data generated by simulation, or data generated by processing measured data.
It may be difficult to distribute hardware with high scattered radiation removal ability as a general-purpose device from the viewpoint of manufacturing cost and material durability. Therefore, by manufacturing a device that implements hardware with high scattered ray removal performance, and by generating a trained model using medical data acquired based on the device as correct data, hardware with high scatter removal performance can be manufactured. Data-driven insights can also be applied to general-purpose instruments with low anti-scatter but durable hardware implementations.

Here, the relationship between the high and low scattered ray removal ability may be such that the input data and the correct data are compared, and the correct data has a higher scattered ray removal ability than the input data.
Specifically, as learning data, medical data captured using a one-dimensional anti-scatter grid is used as input data, and medical data captured using a two-dimensional anti-scatter grid is used as correct data. Just do it.

Moreover, when the dimensionality of the anti-scattering grid for the correct data is higher than that for the input data, of course, even when the input data and the correct data are photographed by the anti-scattering grid of the same dimension, as shown in FIG. Training data can be generated by changing the parameters of the anti-scatter grid.

For example, if medical data captured using an anti-scatter grid with a higher grid height (grid plate height) than the anti-scatter grid used to capture the input data is used as correct data, good. Alternatively, medical data captured using an anti-scatter grid having a thicker grid plate than the anti-scatter grid used to capture the input data may be used as the correct data. Alternatively, medical data captured using an anti-scatter grid having a larger grid ratio than the grid used to capture the input data may be used as the correct data. Alternatively, correct medical data captured using an anti-scatter grid generated using a material with a higher radiation (X-ray) shielding capability than the anti-scatter grid used to capture the input data. It can be used as data.

In the above example, both the input data and the correct data are different in the anti-scattering ability of the anti-scattering grid, that is, the difference in hardware performance is learned. In addition, medical data subjected to scattered radiation correction by software may be used as the correct data. Specifically, for example, as learning data, medical data captured using a one-dimensional anti-scatter grid is used as input data, and for medical data captured using a two-dimensional anti-scatter grid, Furthermore, medical data that has undergone scattered radiation correction processing using software may be used as correct data.

As a result, when using the trained model 411, which will be described later, the medical data output from the trained model 411 does not need to be subjected to scattered radiation correction processing by separate software. can be omitted, and the overall calculation time related to the process can be shortened. As a result, efficiency of processing can be improved.

On the other hand, input data may be generated from correct data. For example, the quality of medical data captured using a two-dimensional anti-scatter grid is simulated so that it has the same level of anti-scatter ability as that of medical data captured using a one-dimensional anti-scatter grid. lower the In other words, the scattered radiation component included in the medical data is increased. Specifically, a simulation is performed to calculate the difference in the scattered radiation components between the ability to remove scattered radiation by a one-dimensional grid for removing scattered radiation and the elimination of scattered radiation by a two-dimensional grid for eliminating scattered radiation. Synthesize with the correct data. By doing so, it is possible to generate medical data with increased influence of scattered radiation. In this way, by generating medical data based on a low anti-scattering power as input data from medical data based on a two-dimensional anti-scattering grid with a high anti-scattering power, learning can be performed simply by obtaining correct data. Data can be easily generated.

Next, the concept of using the trained model 411 machine-learned in FIG. 5 will be described with reference to FIG.
When using the trained model 411 , the medical data to be processed captured by the X-ray CT apparatus 1 is input to the trained model 411 . The trained model 411 outputs medical data from which scattered radiation components have been removed from the input medical data to be processed. Specifically, for example, first medical data captured by an X-ray CT apparatus 1 having a one-dimensional anti-scatter grid is input to the trained model 411, and two-dimensional scattering data is obtained from the first medical data. Second medical data is generated as acquired based on the line removal grid.

The medical data may be CT image data as described above, or may be projection data. If the medical data is CT image data, the CT image data is input to the trained model 411, and CT image data from which scattered radiation components have been removed from the input CT image data is output. If the medical data is projection data, the projection data is input to the trained model 411, and CT image data obtained based on the scattered radiation elimination ability higher than that of the projection data is output.

Projection data may be output as the output of the trained model 411 . That is, the projection data from which the scattered radiation component has been removed from the input projection data is output. Projection data, which is the output of the trained model 411, can be subjected to existing reconstruction processing such as reconstruction processing by the reconstruction processing function 443, for example. Therefore, for example, if the medical image processing apparatus according to the present embodiment is mounted on the console device of an X-ray CT apparatus that has already been deployed in a hospital, etc., the ability to remove scattered radiation will be higher than that of the X-ray CT apparatus that has been deployed. CT images can be generated that are obtained based on high anti-scatter power.

According to the first embodiment described above, at the time of learning, correct data generated by an X-ray CT apparatus for correct data creation, which implements high-quality and high-performance hardware regarding the ability to remove scattered radiation, Generate a trained model. If the trained model is used with an X-ray CT apparatus having a lower ability to remove scattered radiation than the X-ray CT apparatus for creating the correct data, highly accurate correction of scattered radiation can be performed even with an X-ray CT apparatus having a lower ability to remove scattered radiation. The applied medical data can be output. In other words, even an X-ray CT apparatus whose scattered ray removal ability is inferior to that of the apparatus for correct data preparation generates medical data subjected to scattered ray correction processing with a scattered ray removal ability equivalent to that of the X-ray CT apparatus for correct answer data preparation. can do.
That is, according to the X-ray CT apparatus according to the present embodiment, by using a trained model, a CT image with more improved contrast based on a higher scattered radiation removal ability than the configuration of an actual X-ray CT apparatus can be generated. Therefore, it is possible to obtain a high-quality image while suppressing costs.

(Second embodiment)
The scattered radiation correction process according to the above-described embodiments is not limited to being performed in the console device 40 of the X-ray CT apparatus 1, and may be performed in, for example, a medical image processing apparatus included in a workstation.

A medical image processing apparatus that executes scattered radiation correction processing according to the second embodiment will be described with reference to the block diagram of FIG.
Medical image processing apparatus 700 includes processing circuitry 720 , storage 740 and communication interface 760 . Also, signal exchange is performed via the bus 780 .

Processing circuitry 720 includes an acquisition function 722 and a correction processing function 724 . The acquisition function 722 acquires projection data or CT image data as medical data from the X-ray CT apparatus 1 via the communication interface 760 . The correction processing function 724 performs processing similar to that of the above-described embodiment, so detailed description thereof will be omitted here.
The storage 740 is, for example, a memory, and stores the trained model 411 and the like.
A communication interface 760 exchanges data with the X-ray CT apparatus 1 .

According to the second embodiment described above, the medical image processing apparatus executes the scattered radiation correction process shown in the first embodiment, so that the user can operate the X-ray CT apparatus 1 while viewing the console screen. Alternatively, the scattered radiation correction process can be performed in a separate room from the X-ray CT apparatus 1 .

According to at least one embodiment described above, it is possible to obtain a high-quality image while suppressing costs.

The X-ray CT apparatus includes a Rotate/Rotate-Type (3rd generation CT) in which the X-ray tube and detector are rotated around the subject P as a unit, and a large number of X-ray detectors arrayed in a ring. There are various types such as Stationary/Rotate-Type (4th generation CT) in which the element is fixed and only the X-ray tube rotates around the subject P, and any type can be applied to this embodiment.

Note that hardware for generating X-rays is not limited to the X-ray tube 11 . For example, in place of the X-ray tube 11, a focus coil for converging the electron beam generated from the electron gun, a deflection coil for electromagnetic deflection, and the deflected electron beam surrounding the half circumference of the subject P collide with each other to emit X-rays. X-rays may be generated using a fifth generation system including a target ring to be generated.

Furthermore, in the present embodiment, both a single-tube type X-ray CT apparatus and a so-called multi-tube type X-ray CT apparatus in which a plurality of pairs of X-ray tubes and detectors are mounted on a rotating ring can be used. Applicable.

In addition, each function according to the embodiment can also be realized by installing a program for executing the above processing in a computer such as a workstation and deploying them on the memory. At this time, the program that allows the computer to execute the above method can be distributed by being stored in a storage medium such as a magnetic disk (hard disk, etc.), optical disk (CD-ROM, DVD, etc.), semiconductor memory, or the like. .

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

Reference Signs List 1 X-ray CT apparatus 10 Mounting device 11 X-ray tube 12 X-ray detector 13 Rotating frame 14 X-ray high voltage device 15 Control device 16 Wedge 17 Collimator 18 Data acquisition device (DAS)
19 aperture (bore)
30 bed device 31 base 32 bed drive device 33 top board 34 support frame 40 console device 41 memory 42 display 43 input interface 44,720 processing circuit 50 learning data storage device 52 model learning device 301 anti-scatter grid 302 scintillator array 410 multilayer network 411 trained model 441 system control function 442 preprocessing function 443 reconstruction processing function 444, 722 acquisition function 445, 724 correction processing function 446 display control function 700 medical image processing apparatus 740 storage 760 communication interface 780 bus 3011 grid board 3012 space

Claims (9)

an acquisition unit that acquires first medical data to be processed based on hardware having a first ability to remove scattered radiation;
The first medical data to be processed according to a trained model that receives first medical data and outputs second medical data based on a second scattered radiation removal power higher than the first scattered radiation removal power. a processing unit that generates second medical data from
with
The first medical data is medical data acquired based on a one-dimensional anti-scatter grid,
wherein the second medical data is medical data acquired based on a two-dimensional anti-scatter grid;
Medical image processing equipment. an acquisition unit that acquires first medical data to be processed based on hardware having a first ability to remove scattered radiation;
The first medical data to be processed according to a trained model that receives first medical data and outputs second medical data based on a second scattered radiation removal power higher than the first scattered radiation removal power. a processing unit that generates second medical data from
with
The first medical data is medical data acquired based on a one-dimensional or two-dimensional anti-scatter grid,
The second medical data is medical data acquired based on a two-dimensional anti-scatter grid and subjected to scattered radiation correction processing by software.
Medical image processing equipment. wherein the first medical data is medical data obtained by increasing the scattered radiation component contained in the second medical data ;
The medical image processing apparatus according to claim 1 or 2 . The second medical data is medical data acquired based on an anti-scatter grid having a higher grid height than the anti-scatter grid used to acquire the first medical data.
The medical image processing apparatus according to any one of claims 1 to 3 . The second medical data is medical data acquired based on an anti-scatter grid having a thicker grid plate than the anti-scatter grid used to acquire the first medical data.
The medical image processing apparatus according to any one of claims 1 to 4 . The second medical data is medical data acquired based on an anti-scatter grid having a larger grid ratio than the anti-scatter grid used to acquire the first medical data.
The medical image processing apparatus according to any one of claims 1 to 5 . The second medical data is acquired based on an anti-scatter grid generated using a material having a higher radiation shielding ability than the anti-scatter grid used to acquire the first medical data. is the data,
The medical image processing apparatus according to any one of claims 1 to 6 . obtaining first medical data to be processed based on hardware having a first anti-scatter capability;
The first medical data to be processed according to a trained model that receives first medical data and outputs second medical data based on a second scattered radiation removal power higher than the first scattered radiation removal power. A medical image processing method for generating second medical data from
The first medical data is medical data acquired based on a one-dimensional anti-scatter grid,
wherein the second medical data is medical data acquired based on a two-dimensional anti-scatter grid;
Medical image processing method . obtaining first medical data to be processed based on hardware having a first anti-scatter capability;
The first medical data to be processed according to a trained model that receives first medical data and outputs second medical data based on a second scattered radiation removal power higher than the first scattered radiation removal power. A medical image processing method for generating second medical data from
The first medical data is medical data acquired based on a one-dimensional or two-dimensional anti-scatter grid,
The second medical data is medical data acquired based on a two-dimensional anti-scatter grid and subjected to scattered radiation correction processing by software.
Medical image processing method.

Images