Dynamic image analysis apparatus, method, and program

Abstract

To quantitatively evaluate, in terms of micro, a spot of a lung such as a lung structure by a dynamic image obtained by dynamic imaging with a less exposure.SOLUTION: A dynamic image analysis apparatus in one embodiment of a disclosure comprises: an acquisition unit which acquires a dynamic image of an imaging object by dynamic imaging; and a calculation unit which calculates, from the dynamic image, two displacement amount data on a region obtained by dividing a static image constituting the dynamic image and variation data on the density of the region.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a dynamic image analysis device, method, and program. [Background technology]

[0002] Dynamic imaging is performed by a radiation generator repeatedly emitting radiation pulses at a frequency (pulse period) of multiple times per unit time (e.g., 15 times per second) for a predetermined time (duration) while an emission command is being issued, and a radiation detection device reads out the amount of charge generated in accordance with the radiation dose received through the subject as a signal value (intensity). Dynamic imaging captures dynamic images consisting of multiple (series of) still images captured at different times, each captured at a pulse period. The period at which still images are captured is called the frame rate, and is equal to the period of the radiation pulses. Physicians diagnose diseases based on the captured dynamic images. Physicians can perform diagnoses based on the movement of the lungs and heart by performing dynamic imaging of organs such as the lungs and heart. Furthermore, physicians can perform diagnoses based on the movement of joints by performing dynamic imaging of bones.

[0003] As a method for quantitatively evaluating the movement of the lungs as a whole (macroscopically), such as the lung fields, an index value indicating the change in the lung fields is calculated from dynamic images of the chest, and the softness of the lung fields is evaluated based on the calculated index value (for example, Patent Document 1).

[0004] Furthermore, by improving the accuracy of estimating the volume of a moving subject in a radiographic image, the accuracy of estimating the subject's function evaluation index, which is estimated based on the subject's volume, is improved. The volume of the lung field is estimated based on the frame images of each extracted set, and the respiratory function index of the lung field is estimated based on the estimated volume (for example, Patent Document 2). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2017-176202 [Patent Document 2] Japanese Patent Application Publication No. 2019-122449 Summary of the Invention [Problem to be solved by the invention]

[0006] Currently, in the treatment of emphysema (emphysematous COPD), respiratory function tests are used to diagnose and assess the progression of the disease. Furthermore, chest CT imaging is commonly used as a detailed examination. Chest CT scans can confirm the progression of emphysema by quantitatively assessing the areas and volume of dark areas caused by destruction of lung structures such as alveoli.

[0007] However, CT scans involve a high amount of radiation exposure, especially since detailed evaluation of emphysema requires CT scans in two phases, inhalation and exhalation, which increases radiation exposure.

[0008] It is necessary to quantitatively evaluate (microscopically) localized lung deformations associated with respiratory movement using dynamic images obtained by dynamic photography with low radiation exposure, for example, to evaluate localized deformations and the quantification of deformations. [Means for solving the problem]

[0009] A dynamic image analysis device in one embodiment of the present disclosure includes an acquisition unit that acquires a dynamic image of a subject by dynamic photography, and a calculation unit that calculates, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images that constitute the dynamic image, and change amount data relating to the concentration of the regions.

[0010] A dynamic image analysis method in one embodiment of the present disclosure includes an acquisition step of acquiring a dynamic image of a subject by dynamic photography, and a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images that constitute the dynamic image, and change amount data relating to the density of the regions.

[0011] A dynamic image analysis program in one embodiment of the present disclosure causes a computer to execute an acquisition step of acquiring a dynamic image of a subject by dynamic photography, and a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images that constitute the dynamic image, and change amount data relating to the density of the regions.

[0012] These comprehensive or specific aspects may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium, or may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. [Effects of the Invention]

[0013] According to the present disclosure, quantitative evaluation of local areas of the lungs (microscopically) using dynamic images can provide information for determining the progression of disease. [Brief explanation of the drawings]

[0014] [Figure 1] Diagram showing the configuration of a dynamic image analyzer [Figure 2] Processing circuit functional block diagram [Figure 3] A diagram of the lung structure modeled on a cube [Figure 4A] A still image of the dynamic lung image showing the lungs in their enlarged state. [Figure 4B] A still image of the lungs when they are small, taken from a dynamic lung image. [Figure 5A] A diagram showing the regions of the reference image divided into 50-pixel regions. [Figure 5B] FIG. 10 is a diagram showing a state in which an area is displaced in a still image different from the reference image. [Figure 5C] FIG. 10 is a diagram showing a state in which an area is displaced in a still image different from the reference image. [Figure 6] FIG. 1 is a flowchart of a processing circuit. [Figure 7] FIG. 1 is a detailed flowchart of a processing circuit. [Figure 8] Example of elastic modulus map showing WIRE, X-axis, Y-axis, Z-axis, and composite elastic modulus, by region and after smoothing. [Figure 9] Example distortion maps showing WIRE, X-axis, Y-axis, Z-axis, and composite distortion, both regional and smoothed. [Figure 10A] The diagram shows the state in which the flexibility of the lung structure is reduced, the elastic modulus is increased, and the strain ε relative to the stress σ is reduced. [Figure 10B] Diagram showing the case where the elastic modulus differs on the X, Y, and Z axes [Figure 10C] A diagram showing severity by tilt [Figure 11] A diagram showing a window with buttons that allow doctors to select diseases to display. [Figure 12] An example showing the elastic modulus E on the 3rd, 4th, and 5th days of hospitalization DETAILED DESCRIPTION OF THE INVENTION

[0015] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings as appropriate.

[0016] <Dynamic image analysis device> The configuration of a dynamic image analysis device 100 according to an embodiment of the present disclosure will be described.

[0017] [composition] FIG. 1 is a diagram showing the configuration of a dynamic image analyzer 100.

[0018] The dynamic image analysis device 100 includes a processing circuit 110, an input / output unit 120, a communication unit 130, and a memory 140. The input / output unit 120 includes an input unit 121 and an output unit 122. The input unit 121 and the output unit 122 may be integrated. If input and output are performed via the communication unit 130, the input / output unit 120 may be omitted.

[0019] The processing circuit 110 is composed of a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc., and may include a neural network. The processing circuit 110 extracts features based on input medical images and estimates the disease level of a specific disease. Details of the processing circuit 110 will be described later.

[0020] The input unit 121 includes at least one of a touch panel, a keyboard, a mouse, a microphone, etc., and receives input based on the operation of a user (doctor, radiologist, etc.).

[0021] The output unit 122 includes at least one of a display, a speaker, a printer, etc., and outputs the result determined by the processing circuit 110 to the outside.

[0022] The communication unit 130 communicates with external devices wirelessly or via wired buses, LANs (Local Area Networks), the Internet, VPNs (Virtual Private Networks), public lines, etc. The communication unit 130 communicates with a Hospital Information System (HIS), a Radiology Information System (RIS), a Picture Archiving and Communication System (PACS), a dynamic analysis device, etc.

[0023] The memory 140 is composed of a ROM (Read Only Memory), a RAM (Random Access Memory), an EPROM (Erasable Programmable ROM), an EEPROM (Electrically EPROM), an HDD (Hard Disk Drive), etc., and stores dynamic images, various programs, etc.

[0024] FIG. 2 is a functional block diagram of the processing circuit 110.

[0025] The processing circuit 110 includes an acquisition unit 111 and a calculation unit 112 .

[0026] The acquisition unit 111 acquires a dynamic image. The dynamic image may be acquired from an external system such as a RIS via the communication unit 130 based on an external input via the input unit 121 or the communication unit 130, or may be acquired from the memory 140. The dynamic image is, for example, a dynamic image of the lungs.

[0027] The calculation unit 112 calculates the strain and elastic modulus of the captured lungs based on the dynamic image acquired by the acquisition unit 111. The calculation unit 112 also displays the calculated strain and elastic modulus on the output unit 122 or on an external device via the communication unit 130. Details will be described later.

[0028] [Lung modeling] Figure 3 is a diagram of a model of the lung structure, where the lung structure corresponds to a cube. In actual lungs, there are many more lung structures on the X, Y, and Z axes. Dynamic images are taken by a dynamic imaging device that repeatedly irradiates pulsed radiation along the Z axis and captures the transmitted radiation as still images on the XY plane (Z plane).

[0029] First, let us consider the change in size of the lung structure with breathing. Since the size of the lung structure changes with breathing, we can think of the size of the cube in Figure 3 as changing.

[0030] Figure 4 shows one still image among the dynamic lung images, which shows the state in which radiation is irradiated from the Z-axis direction in Figure 3 and the XY plane is photographed.

[0031] FIG. 4A is a diagram showing a still image of the dynamic lung image in which the lungs are large (e.g., at maximum inspiration). For example, the right lung is shown divided into sections at predetermined intervals. For example, the still image of the large lungs is set as the reference image. FIG. 4B is a diagram showing a still image of the dynamic lung image in which the lungs are small (e.g., at maximum expiration). The still image of the small lungs may be set as the reference image. In FIG. 4B, the same area as the reference image is divided into multiple sections, but the overall size of the sections is smaller because the lungs are small. In other words, the lungs change from a large state (FIG. 4A) to a small state (FIG. 4B) over time.

[0032] The difference in size of lung structures varies depending on the flexibility (elastic modulus) of the lungs. For example, if the lung structure is stiff (high elastic modulus), it does not contract much, so the difference in size between a large lung structure and a small lung structure is small. If the lung structure is soft (low elastic modulus), it contracts a lot, so the difference in size between a large lung structure and a small lung structure is large.

[0033] Therefore, by comparing the size of the lungs in a series of still images that make up a dynamic image, the flexibility of the lung structure can be grasped.

[0034] Thus, by comparing Figure 4A and Figure 4B, we can understand the softness of the lung structure on the X and Y axes, but we cannot understand the softness of the lung on the Z axis.

[0035] For example, in interstitial pneumonia, the lung structure becomes fibrotic, causing it to contract in some directions but not others. Therefore, it is necessary to understand the flexibility of the lung structure in all three dimensions.

[0036] Elasticity Modulus The stress that deforms an object is σ xx , σ yy , σ zz , σ xy , σ xz , σ yx , σyz , σ zx , σ zy The nine stress components are defined as σ xx , σ yy , σ zz are the normal stresses to the X plane (YZ plane), Y plane (XZ plane), and Z plane (XY plane), respectively, and σ xy , σ xz , σ yx , σ yz , σ zx , σ zy is the shear stress.

number

[0037] According to Hooke's law, the elastic modulus E is given by σ=Eε In other words, when we look at the stress components,

number

[0038] Since only vertical strain needs to be considered for changes in the size of the lung structure, only vertical stress is considered, and shear stress may be set to 0. Therefore, in the present disclosure,

number

number

[0039] Strain ε xx , ε yy , ε zz are the distortions of the X-axis, Y-axis, and Z-axis, respectively, so the change in size of the lung structure Δ x , Δ y , Δ z is.

[0040] Therefore, the stresses σ in the X, Y and Z axesxx , σ yy , σ zz and displacement Δ x , Δ y , Δ z If we know the elastic modulus E x , E y , E z can be obtained.

[0041] Displacement In dynamic lung imaging, changes in the image are assumed to be due to changes in lung structure, and changes in lung structure can be measured by detecting changes in the image based on optical flow.

[0042] Dynamic radiography consists of multiple still images, so by comparing the lung position in each still image, the displacement of the lung in the X and Y axes (Δ x and Δ y ) can be calculated.

[0043] First, one still image from among the dynamic images is taken as a reference image. Fig. 5A shows regions ABCD obtained by dividing the reference image into, for example, 50-pixel regions. Fig. 5B shows a state in which regions ABCD have been displaced to regions EFGH in a still image other than the reference image. The size of the division may correspond to the size of a single lung structure, or may be another size, and may be set according to processing power and image quality.

[0044] In this disclosure, distortion is calculated as a change in the size and shape of the region. Since distortion is a change in the positional relationship between each point, it is sufficient to calculate how much points F, G, and H have displaced relative to point E relative to the positions of points B, C, and D relative to point A. Since region ABCD is an infinitesimal region, region EFGH is approximated as a parallelogram, and Δ x and Δ y may be required.

[0045] FIG. 5C shows an example of calculating the displacement for each of points F, G, and H. The average of the displacements of points F, G, and H relative to the X axis and the Y axis is Δ x and Δy If the sum of the displacements of points E, F, G, and H is divided by 2, the displacement shown in FIG. 5B can be calculated as follows: x and Δ y is the same value as

[0046] The reference image may be the first still image in a series of still images that make up the dynamic image.

[0047] As described above, when the area ABCD is displaced to the area EFGH, the displacement amount Δ x and Δ y can be obtained.

[0048] On the other hand, Δ z can be determined from the change in concentration.

[0049] There are capillaries on the surface of the lung structure, and blood flows through the capillaries. The density of the capillaries changes as the size of the lung structure changes. As the lung structure becomes smaller, the density of the capillaries increases, and as the lung structure becomes larger, the density of the capillaries decreases. A change in the density of the capillaries means a change in the density of the blood, and the change in the density of the blood is detected as a change in the density of a still image (the rate of change or the density difference). The density of region ABCD may be calculated as the average density of the entire region, or as the average density of points A, B, C, and D.

[0050] By detecting the change in density in the area ABCD, the displacement in the Z-axis direction Δ z can be calculated. Since the density of a still image is the received intensity of radiation, the amount of charge (signal value) detected by a radiation detection device having multiple detection elements may be used as the density. If the lung structure is considered spherical and the Z axis direction in the reference image is assumed to be the same size as the X axis and Y axis, the density of the reference image is the density when the Z axis direction is 50 pixels, so the displacement Δ z can be obtained.

[0051] Since the displacement Δ is the strain ε, according to Hooke's law (σ=Eε), if the stress σ can be found, the elastic modulus E can be found.

[0052] [stress] Respiratory movement is the movement of a fluid called air. Since changes in the size of lung structures are based on respiratory movement, changes in the size of lung structures are based on dynamic pressure. According to Berne's theorem, dynamic pressure q is expressed as follows for density ρ and fluid velocity v: q=pv 2 / 2 is.

[0053] In this disclosure, dynamic pressure q is stress σ, density ρ is gas density P, and fluid velocity v is movement velocity V, so σ=PV 2 / 2 have the following relationship.

[0054] Stress σ xx , σ yy , σ zz are the normal stresses on the X, Y, and Z planes, so they are the stresses on the X, Y, and Z axes, respectively. x , P y , P z , V, which is the movement speed V decomposed into X-axis, Y-axis, and Z-axis x , V y , V z Similarly, σ xx =P x V x 2 / 2 σ yy =P y V y 2 / 2 σ zz =P z V z 2 / 2 have the following relationship.

[0055] In this disclosure, the lung structure expands when air enters the lungs, and contracts when air leaves the lungs. In other words, the lung structure changes due to the stress of the air. Since the stress due to the air is equal on the X-axis, Y-axis, and Z-axis, σ xx =σ yy =σ zz is.

[0056] Here, since the gas density P of the air is 1, if the air movement speed V is known, the stress σ xx , σ yy , σ zz , can be obtained.

[0057] For example, if a patient is wearing a ventilator, the air velocity V is the flow rate set on the ventilator. It is also possible to detect the amount of diaphragm movement based on a dynamic image and calculate the air velocity V based on the amount of diaphragm movement. In this way, the air velocity V for each of exhalation and inspiration can be calculated, and therefore the stress σ can be calculated.

[0058] [process] FIG. 6 is a diagram showing a flowchart of the processing circuit 110.

[0059] The acquisition unit 111 acquires a dynamic image (step S601).

[0060] The calculation unit 112 calculates the amount of displacement along the X and Y axes based on the dynamic image acquired by the acquisition unit 111. The calculation unit 112 also calculates the amount of displacement along the Z axis based on the density difference between the still images that make up the dynamic image (step S602).

[0061] The calculation unit 112 calculates the elastic moduli of the X-axis, Y-axis, and Z-axis from the displacement amounts of the X-axis, Y-axis, and Z-axis (step S603).

[0062] The calculation unit 112 causes the output unit 122 to display the displacement amounts and elastic moduli along the X-, Y-, and Z-axes calculated by the calculation unit 112 (step S604). A display control unit (not shown) in the processing circuit 110 may cause the display unit to display the amounts of displacement along the X-, Y-, and Z-axes instead of the calculation unit 112. The displacement amounts along the X-, Y-, and Z-axes may be displayed between steps S602 and S603.

[0063] FIG. 7 is a detailed flowchart of the processing circuit 110.

[0064] The acquisition unit 111 acquires a dynamic image (step S701).

[0065] The calculation unit 112 extracts a still image of maximum inspiration and a still image of maximum expiration from the dynamic images acquired by the acquisition unit 111 (step S702).

[0066] The calculation unit 112 determines either the still image at maximum inspiration or the still image at maximum expiration as the reference image, and sets regions of 50×50 pixels each in the reference image (step S703).

[0067] The calculation unit 112 calculates the distortion ε of the X-axis and Y-axis for each region based on the optical flow relative to the reference image. x and ε y is calculated (step S704).

[0068] The calculation unit 112 calculates the Z-axis distortion ε for each region based on the rate of change of the signal value (amount of charge). z (Step S705). If we consider the lung structure to be spherical and assume that the Z axis direction in the reference image is the same size as the X axis and Y axis, the density of the reference image is the density when the Z axis direction is 50 pixels. Therefore, the strain ε z can be calculated.

[0069] The calculation unit 112 calculates ε x and ε y and ε calculated in step S705 zThe distortion map is generated based on the distortion ε on the X axis (step S706). x , strain ε on the Y axis y , Z-axis strain ε z This is a map showing the above by region.

[0070] The calculation unit 112 calculates the amount of movement of the diaphragm based on the dynamic image. The calculation unit 112 calculates the movement speed v of the diaphragm based on the calculated amount of movement and the frame rate of the dynamic image (step S707). Instead of calculating the movement speed v of the diaphragm, the calculation unit 112 may acquire a flow rate set in the ventilator. The flow rate set in the ventilator may be acquired from the ventilator via the communication unit 130, from the patient's electronic medical record, from the memory 140, or by other means.

[0071] The calculation unit 112 calculates the stress σ from the moving speed v of the diaphragm or the flow rate set in the artificial respirator. x , σ y , σ z is calculated (step S708).

[0072] The calculation unit 112 calculates the strain ε x , ε y , and ε z and the stress σ calculated in step S708. x , σ y , σ z Based on the elastic modulus E x , E y , E z is calculated (step S709).

[0073] The calculation unit 112 calculates the elastic modulus E x , E y , E z The elastic modulus map is generated based on the elastic modulus E on the X axis (step S710). x , Y-axis elastic modulus E y , Z-axis elastic modulus E z This is a map showing the above by region.

[0074] The calculation unit 112 calculates the strain ε x , ε y , ε z Based on the synthetic strain ε xyz The calculation unit 112 also calculates the elastic modulus E x , E y , E z Based on the composite elastic modulus E xyz (Step S711). xyz and the composite elastic modulus E xyz is calculated as a map.

[0075] [display] The elastic modulus E can be calculated by determining the strain ε (displacement Δ) and stress σ.

[0076] The strain ε and stress σ are determined for each of the regions ABCD obtained by dividing the reference image that constitutes the dynamic image, and therefore the elastic modulus E can be determined for each of the divided regions.

[0077] The calculated strains ε of the X-axis, Y-axis, and Z-axis are displayed for each region (strain map).

[0078] In addition, the elastic modulus E of the X-axis, Y-axis, and Z-axis x , E y , E z is displayed for each region (elastic modulus map).

[0079] The calculated strain or elastic modulus may be normalized by setting the strain or elastic modulus of a normal lung structure to 1. By normalizing the strain or elastic modulus of a normal lung structure to 1, the severity of the lung structure can be easily grasped.

[0080] The colors of the displayed strain or elastic modulus may be changed for each of the X-axis, Y-axis, and Z-axis. For example, the X-axis may be displayed in red, the Y-axis in green, and the Z-axis in blue. The color (density) may be changed depending on the value of the strain or elastic modulus of each region. For example, regions with high strain or elastic modulus on the X-axis may be displayed in dark red (e.g., scarlet), and regions with low strain or elastic modulus on the X-axis in light red (e.g., pink). For example, regions with high strain or elastic modulus on the Y-axis may be displayed in dark green (e.g., dark green), and regions with low strain or elastic modulus on the Y-axis in light green (e.g., light green). For example, regions with high strain or elastic modulus on the Z-axis may be displayed in dark blue (e.g., indigo), and regions with low strain or elastic modulus on the Z-axis in light blue (e.g., light blue).

[0081] The strain or elastic modulus (composite elastic modulus) obtained by combining the strains or elastic moduli of the X-axis, Y-axis, and Z-axis may be displayed. For example, the combined strain or elastic modulus may be displayed in purple, with areas of high combined strain or elastic modulus displayed in dark purple (e.g., dark color) and areas of low combined strain or elastic modulus displayed in light purple (e.g., mauve). The combination may be a vector combination, or the average (sum divided by 3) of the strains or elastic moduli of the X-axis, Y-axis, and Z-axis may be calculated.

[0082] The average elastic modulus of the area belonging to the upper lobe, the average elastic modulus of the area belonging to the middle lobe, and the average elastic modulus of the area belonging to the lower lobe may be calculated, and the elastic moduli may be displayed in overlapping fashion in the corresponding locations.

[0083] Along with the display of each region, the results of smoothing processing performed on the region may also be displayed.

[0084] By displaying the strain or elastic modulus for each region, the pathology of each part of the lung can be understood.

[0085] In addition, a WIRE may be displayed, which shows how a region obtained by dividing the reference image into 50 pixel regions on the XY plane is distorted. The still image for which the WIRE is displayed may be the still image with the greatest distortion.

[0086] FIG. 8 shows an example of an elastic modulus map displaying the WIRE, the X-axis, Y-axis, Z-axis, and composite elastic modulus for each region and the results of smoothing processing. The average elastic modulus need not be displayed if necessary. WIRE directly represents the distortion, and the distorted state is displayed as is, as in FIG. 5C. The upper row shows the display for each region, and the lower row shows the results of smoothing processing. FIG. 8 shows an example in which the average elastic modulus for the region belonging to the upper lobe, the average elastic modulus for the region belonging to the middle lobe, and the average elastic modulus for the region belonging to the lower lobe are displayed in an overlapping manner on the X-axis. The average elastic modulus for the upper, middle, and lower lobes may also be displayed in an overlapping manner on the Y-axis, Z-axis, and composite elastic modulus. The average elastic modulus displayed in an overlapping manner may be a normalized elastic modulus with the elastic modulus of a normal lung structure set to 1.

[0087] FIG. 9 shows an example of a distortion map displaying the WIRE and the distortions on the X, Y, and Z axes for each region and the results of smoothing. The upper row shows the display for each region, and the lower row shows the results of smoothing. The average distortions for the upper, middle, and lower lobes on the X, Y, and Z axes may be displayed in an overlapping manner.

[0088] FIG. 10 shows the relationship between strain ε and stress σ. In FIG. 10, the elastic modulus for a normal lung (lung structure) is normalized to 1. Normalization may be performed using the average elastic modulus for a normal lung structure or the upper limit of the elastic modulus. FIG. 10A shows a state in which the flexibility of the lung structure decreases, increasing the elastic modulus and reducing strain ε relative to stress σ. FIG. 10B shows a case in which the elastic modulus differs on the X-axis, Y-axis, and Z-axis. The slope of the graph (the magnitude of the elastic modulus) can be used to determine the severity of a disease. FIG. 10C shows a diagram displaying the severity of a disease based on the slope. For example, region 1001 indicates the normal range, region 1002 indicates the mild range, and region 1003 indicates the severe range. For example, region 1001 may be displayed in blue, region 1002 in yellow, and region 1003 in red. The number of regions is not limited to three. The severe / mild / normal ranges may be set according to the disease. In Figure 10, the elastic modulus may be displayed for each of the upper, middle, and lower lobes. Figure 10C shows that the upper lobe is severely affected, the middle lobe is mildly affected, and the lower lobe is normal. Figure 10 may be displayed below the WIRE in Figures 8 and 9.

[0089] [disease] The type of disease the patient has, for example, COPD, interstitial pneumonia, or pneumothorax, has been diagnosed by other means. By inputting the patient's disease through the input unit 121, the doctor can cause the output unit 122 to display a display corresponding to the disease.

[0090] 11 is a diagram showing a window 1100 in which buttons are displayed for a doctor to select diseases to be displayed. Some diseases may not be displayed in the window 1100, or other diseases may be displayed, and the number of buttons displayed does not have to be four. For example, when a medical examination is input, the dynamic image analyzer 100 may display information for multiple diseases.

[0091] [COPD] In COPD patients, air-trapping can be observed, a condition in which multiple lung structures become emphysema, meaning that air cannot be expelled from the lung structures. Because air-trapping prevents the lung structures from contracting, their flexibility decreases, meaning their elasticity increases. In other words, the higher the elasticity (the lower the flexibility), the more serious the COPD condition can be determined to be.

[0092] Therefore, a doctor can diagnose the COPD condition in a COPD patient by viewing the displays of FIGS.

[0093] [Interstitial pneumonia] In patients with interstitial pneumonia, fibrosis of the lung structure can be observed. Fibrosis of the lung structure makes it difficult for the lung structure to contract in a certain direction. In other words, in dynamic images of patients with interstitial pneumonia, differences in softness (elastic modulus) occur along the X, Y, and Z axes, as shown in Figure 10B.

[0094] Therefore, for a patient with interstitial pneumonia, a doctor can understand the condition of the patient's interstitial pneumonia by viewing the displays in Figures 8, 9, and 10B.

[0095] [pneumothorax] In patients with pneumothorax (collapsed lung), air leaks into the thoracic cavity, compressing the lungs and causing them to shrink. Therefore, the strain ε of the lung structure in the compressed area decreases, and the elastic modulus increases.

[0096] Therefore, in a patient with pneumothorax, a doctor can diagnose the condition of pneumothorax by using the displays of FIGS.

[0097] [Treatment status] Dynamic radiography allows for multiple dynamic radiography sessions for patients (those being imaged) because the patient is exposed to less radiation. Therefore, by comparing the modulus of elasticity E according to the treatment status, it is possible to know the progress of disease improvement due to the effects of treatment. Figure 12 shows an example of displaying modulus of elasticity E on the third, fourth, and fifth days of hospitalization. The modulus of elasticity E of the object to be displayed is Ex , E y , E z , E xyz When displaying multiple elastic moduli, the dynamic image analyzer 100 may display them in different colors for the third, fourth, and fifth days of hospitalization, or may display them in different colors for the fifth, third, and fifth days of hospitalization, or may display them in different colors for the sixth, fourth, and fifth days of hospitalization, or may display them in different colors for the sixth, fifth ... x , E y , E z , E xyz The display may be in a different color depending on the condition. A doctor can determine whether the patient's condition is improving or not by looking at the display in Figure 12. By understanding the improvement in the condition of the disease, a doctor can decide on a future treatment plan.

[0098] Although the embodiments have been described above with reference to the drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art can conceive of various modifications or alterations within the scope of the claims. It is understood that such modifications or alterations also fall within the technical scope of the present disclosure. Furthermore, the components in the embodiments may be combined in any manner without departing from the spirit of the present disclosure.

[0099] (1) A dynamic image analysis device according to one embodiment of the present disclosure includes an acquisition unit that acquires a dynamic image of a subject by dynamic photography, and a calculation unit that calculates, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images that constitute the dynamic image, and change amount data relating to the density of the regions.

[0100] (2) In an embodiment of the present disclosure, in the image assessment device of (1), the concentration is a signal value of the dynamic image.

[0101] (3) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (2), the two displacement data regarding the region are the distortion of the region in the X-axis direction and the Y-axis direction over time, and the change data regarding the density of the dynamic image is the rate of change of charge detected by the radiation detection device over time.

[0102] (4) In an embodiment of the image assessment device of the present disclosure, in the image assessment device of (3), the calculation unit calculates the distortion in the Z-axis direction based on the rate of change of the electric charge.

[0103] (5) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (4), the calculation unit calculates the elastic modulus in the X-axis direction based on the distortion in the X-axis direction, calculates the elastic modulus in the Y-axis direction based on the distortion in the Y-axis direction, and calculates the elastic modulus in the Z-axis direction based on the distortion in the Z-axis direction.

[0104] (6) In one embodiment of the present disclosure, the image assessment device according to (5) is the image assessment device, wherein the imaging target is an organ.

[0105] (7) In one embodiment of the present disclosure, in the image assessment device of (6), the organ is a lung.

[0106] (8) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (4), the calculation unit displays the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction in different colors on the display unit.

[0107] (9) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (8), the calculation unit displays the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction at a density corresponding to the distortion.

[0108] (10) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (4), the calculation unit calculates a distortion that is a combination of the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction.

[0109] (11) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (5), the calculation unit displays the elastic modulus in the X-axis direction, the elastic modulus in the Y-axis direction, and the elastic modulus in the Z-axis direction in different colors on the display unit.

[0110] (12) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (11), the calculation unit displays the elastic modulus in the X-axis direction, the elastic modulus in the Y-axis direction, and the elastic modulus in the Z-axis direction at a density corresponding to the elastic modulus.

[0111] (13) In one embodiment of the image assessment device of the present disclosure, in the image assessment device of (5), the calculation unit calculates a modulus of elasticity that is a composite of the modulus of elasticity in the X-axis direction, the modulus of elasticity in the Y-axis direction, and the modulus of elasticity in the Z-axis direction.

[0112] (14) In one embodiment of the present disclosure, the image assessment device of (5) is the image assessment device, wherein the calculation unit displays the normal elastic modulus and the calculated elastic modulus.

[0113] (15) In an embodiment of the present disclosure, in the image assessment device of (5), the calculation unit displays elastic moduli of a plurality of dynamic images.

[0114] (16) A dynamic image analysis method according to one embodiment of the present disclosure includes an acquisition step of acquiring a dynamic image of a subject by dynamic photography, and a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images constituting the dynamic image, and change amount data relating to the density of the regions.

[0115] (17) A dynamic image analysis program in one embodiment of the present disclosure causes a computer to execute an acquisition step of acquiring a dynamic image of a subject by dynamic photography, and a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing still images constituting the dynamic image, and change amount data relating to the density of the regions. [Industrial Applicability]

[0116] The present disclosure is useful for dynamic image analysis devices, methods, and programs. [Explanation of symbols]

[0117] 100 Dynamic image analysis device 110 Processing circuit 111 Acquisition Department 112 Calculation Unit 120 Input / output section 121 Input section 122 Output section 130 Communications Department 140 memory 1100 Window

Claims

1. an acquisition unit for acquiring a dynamic image of a subject by dynamic photography; a calculation unit that calculates, from the dynamic image, two pieces of displacement amount data relating to regions obtained by dividing a still image that constitutes the dynamic image, and change amount data relating to the density of the regions; A dynamic image analysis device comprising:

2. The concentration is a signal value of the dynamic image. The dynamic image analyzer according to claim 1 .

3. The two displacement amount data regarding the region are distortion in the X-axis direction and distortion in the Y-axis direction, which are distortions of the region over time, The change amount data regarding the density of the dynamic image is a change rate of the charge detected by the radiation detection device over time. The dynamic image analyzer according to claim 2 .

4. The calculation unit calculates the strain in the Z-axis direction based on the rate of change of the charge. The dynamic image analyzer according to claim 3 .

5. the calculation unit calculates an elastic modulus in the X-axis direction based on the strain in the X-axis direction, calculates an elastic modulus in the Y-axis direction based on the strain in the Y-axis direction, and calculates an elastic modulus in the Z-axis direction based on the strain in the Z-axis direction; The dynamic image analyzer according to claim 4.

6. The imaging target is an organ. The dynamic image analyzer according to claim 5 .

7. The organ is the lung. The dynamic image analyzer according to claim 6.

8. the calculation unit causes the display unit to display the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction in different colors; The dynamic image analyzer according to claim 4.

9. the calculation unit displays the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction at densities according to the distortions; The dynamic image analyzer according to claim 8.

10. the calculation unit calculates a combined distortion of the distortion in the X-axis direction, the distortion in the Y-axis direction, and the distortion in the Z-axis direction; The dynamic image analyzer according to claim 4.

11. the calculation unit causes the display unit to display the elastic modulus in the X-axis direction, the elastic modulus in the Y-axis direction, and the elastic modulus in the Z-axis direction in different colors; The dynamic image analyzer according to claim 5 .

12. the calculation unit displays the elastic modulus in the X-axis direction, the elastic modulus in the Y-axis direction, and the elastic modulus in the Z-axis direction at densities according to the elastic modulus; The dynamic image analyzer according to claim 11.

13. the calculation unit calculates a combined elastic modulus of the X-axis direction, the Y-axis direction, and the Z-axis direction; The dynamic image analyzer according to claim 5 .

14. The calculation unit displays the normal elastic modulus and the calculated elastic modulus. The dynamic image analyzer according to claim 5 .

15. The calculation unit displays the elastic moduli of a plurality of dynamic images. The dynamic image analyzer according to claim 5 .

16. an acquisition step of acquiring a dynamic image of the subject by dynamic photography; a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing the still image constituting the dynamic image, and change amount data relating to the density of the regions; A dynamic image analysis method for an information processing device comprising:

17. On the computer, an acquisition step of acquiring a dynamic image of the subject by dynamic photography; a calculation step of calculating, from the dynamic image, two displacement amount data relating to regions obtained by dividing the still image constituting the dynamic image, and change amount data relating to the density of the regions; A dynamic image analysis program that executes the following:

Images