Moving image analysis apparatus, moving image processing system, and diagnostic index providing computer program product

Abstract

This invention relates to a dynamic image analysis apparatus, a dynamic image processing system, and a computer program product for providing diagnostic indicators. The dynamic image analysis apparatus includes: an acquisition unit that acquires a dynamic image obtained by irradiating the chest of a subject during calm breathing with radiation and taking a photograph, and acquires respiratory information related to breathing and diaphragm information related to the diaphragm; and an output unit that calculates and outputs an indicator representing the respiratory state based on the respiratory information and the diaphragm information.

Description

Technical Field

[0001] This invention relates to a dynamic image analysis device, a dynamic image processing system, and a computer program product that provides diagnostic indicators. Background Technology

[0002] Many patients admitted to ICUs (Intensive Care Units) require mechanical ventilation with endotracheal intubation. For patients on mechanical ventilation, prolonged intubation carries a risk of respiratory complications, thus prompting the desire to wean them off the ventilator as early as possible (extubation). Currently, extubation criteria such as the SBT (Spontaneous Breathing Trial) are used to determine extubation appropriateness. However, the SBT includes many evaluation items, involving subjective judgment, which can sometimes be difficult for physicians to assess and place a significant psychological burden on them.

[0003] [Existing Technical Documents]

[0004] [Non-patent document 1] S. Spadaro et al., "Can diaphragmatic ultrasonography performed during the T-tube trial predict weaning failure? The role of diaphragmatic rapid shallow breathing index," Critical Care, 2016 Summary of the Invention

[0005] As an objective indicator for extubation, the RSBI (Rapid Shallow Breathing Index) has been proposed, which is a value obtained by dividing the number of breaths per minute by the ventilation volume per minute. However, it has been reported that the RSBI has low accuracy as an indicator for extubation (Non-Patent Literature 1). This is because, although the diaphragm muscles are the main muscles for respiratory movements, sometimes muscles other than the diaphragm compensate for respiratory movements, so the ventilation volume does not necessarily represent the patient's respiratory capacity.

[0006] In contrast to the RSBI described above, there is also an index such as D-RSBI, which is a value obtained by dividing the number of breaths per minute by the diaphragm displacement (Non-Patent Document 1). In D-RSBI, an ultrasound diagnostic device is used to measure the diaphragm displacement during breathing. However, the ultrasound diagnostic device uses a detector to measure the diaphragm displacement, so the measured value varies depending on the position or angle of the detector contact, resulting in poor reproducibility.

[0007] Thus, the current situation is unable to provide indicators that can objectively diagnose respiratory status with high accuracy and reproducibility. The expectation is to provide indicators that can objectively diagnose respiratory status with high accuracy and reproducibility.

[0008] The purpose of this invention is to provide a dynamic image analysis device, a dynamic image processing system, and a computer program product for providing diagnostic indicators, which can provide diagnostic indicators that can objectively diagnose the respiratory state during calm breathing with high accuracy and reproducibility.

[0009] The dynamic image analysis apparatus of the present invention comprises:

[0010] The acquisition unit obtains dynamic images of the chest of a subject during calm breathing by irradiating it with radiation and taking photographs, acquiring respiratory information related to breathing and diaphragmatic information related to the diaphragm; and

[0011] The output unit calculates and outputs an index representing the respiratory state based on the respiratory information and the diaphragm information.

[0012] The dynamic image processing system of the present invention comprises:

[0013] A mobile medical vehicle, comprising a dynamic imaging device and a trolley, wherein the dynamic imaging device irradiates the chest of a subject during calm breathing and captures a dynamic image, and the trolley carries the dynamic imaging device and is configured to be mobile; and

[0014] The aforementioned dynamic image analysis device.

[0015] The diagnostic indicators involved in this invention provide a computer program product that enables a computer to execute a dynamic image analysis device:

[0016] Processing of dynamic images obtained by irradiating and photographing the chest of a subject during calm breathing, acquiring respiratory information related to respiration, and diaphragmatic information related to the diaphragm; and

[0017] Based on the respiratory information and the diaphragm information, the processing outputs an index representing the respiratory state.

[0018] According to the present invention, diagnostic indicators can be provided that can objectively diagnose respiratory status during calm breathing with high accuracy and reproducibility. Attached Figure Description

[0019] Figure 1 This is a diagram illustrating an example of the overall structure of a dynamic image processing system.

[0020] Figure 2 This is a block diagram showing the functional structure of the main body of the moving image photography device.

[0021] Figure 3 This is a block diagram illustrating an example of the functional structure of a dynamic image analysis device.

[0022] Figure 4 This diagram illustrates the SBT start safety benchmark and SBT success benchmark in the ventilator weaning protocol.

[0023] Figure 5 This is a flowchart illustrating the method for providing diagnostic indicators implemented by a dynamic image analysis device.

[0024] Figure 6 This diagram illustrates a method for determining the number of breaths per minute and the displacement of the diaphragm from dynamic images captured by a motion picture camera.

[0025] Figure 7 It shows that including through Figure 6 The diagram summarizes the analysis of the respiratory rate, diaphragmatic displacement, and diagnostic indicators obtained by the method described in the text.

[0026] Figure 8 This is a flowchart illustrating the method for providing other diagnostic indicators implemented by the dynamic image analysis device.

[0027] Figure 9 This is a diagram illustrating other methods for determining the number of breaths per minute and the displacement of the diaphragm from moving images captured by a moving image camera.

[0028] Figure 10 It shows that including through Figure 9 The diagram summarizes the analysis of the respiratory rate, diaphragmatic displacement, and diagnostic indicators obtained by the method described in the text.

[0029] Figure 11 It is a diagram showing an analytical summary of respiratory and heart rate information derived from dynamic images captured by a motion picture camera. Detailed Implementation

[0030] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0031] [Dynamic Image Processing System]

[0032] Figure 1 This is a diagram illustrating an example of the overall structure of the dynamic image processing system 1.

[0033] The dynamic image processing system 1 includes at least a dynamic image capturing device 10 and a dynamic image parsing device 40. The dynamic image processing system 1 may also further include an image management device 50, a client terminal 60, etc.

[0034] The motion imaging device 10, as an example, is configured as a mobile medical vehicle, and is a preferred device for visiting patients P (the subject) who are difficult to move to other rooms, as described below. The motion imaging device 10 performs motion imaging of the patient P, for example, as... Figure 1 The image shown is a dynamic photograph of patient P who is admitted to the ICU and has difficulty moving to other rooms.

[0035] Here, motion photography refers to repeatedly irradiating (pulsed irradiation) a patient P with pulsed radiation (e.g., X-rays) at a predetermined frame rate, thereby obtaining multiple frame images. Furthermore, a motion image refers to a series of frame images obtained through motion photography. Additionally, the motion analysis described later refers to the analytical processing performed on the motion images, which includes not only analyzing the activity of the subject based on the motion images, but also emphasizing or reducing (removing) predetermined structures by analyzing the motion images.

[0036] The moving images captured by the moving image capturing device 10 are sent to the moving image parsing device 40. The moving image parsing device 40 performs dynamic parsing on the moving images sent from the moving image capturing device 10. Details about the moving image parsing device 40 will be described later.

[0037] The moving image captured by the moving image imaging device 10 and the analysis result dynamically analyzed by the moving image analysis device 40 are sent to the image management device 50. The image management device 50 manages the moving image by associating it with the analysis result obtained from the dynamic analysis of the moving image. The image management device 50 is a medical image management system, such as a PACS (Picture Archiving and Communication System).

[0038] The client terminal 60 is a terminal used by doctors and other medical practitioners. Based on the operation of the medical practitioners, it reads dynamic images from the image management device 50, analyzes the results, and provides prompts in a way that the medical practitioners can view.

[0039] [Motion Image Photography Device]

[0040] The dynamic image imaging device 10 includes a main body 11, a radiation source 12, and an FPD (Flat Panel Detector) 13.

[0041] The main body 11 is a device for performing dynamic imaging using radiation, as detailed later. The main body 11 is mounted on a trolley configured to be movable using wheels or similar means, forming a mobile medical cart capable of being moved to the vicinity of the patient P. Alternatively, the dynamic imaging device 10 can also be a portable device with mobility, in which case it may not have wheels. Furthermore, the dynamic imaging device 10 can also be placed in a radiology room, in which case the mobile patient P becomes the subject of the imaging.

[0042] Furthermore, the main unit 11 is connected to a network N, such as a LAN (Local Area Network), via an access point (AP) 20 located within the facility, through communication, such as wireless communication. The main unit 11 can send and receive data with other devices via the network N. Other devices include the aforementioned dynamic image analysis device 40, image management device 50, and client terminal 60.

[0043] The radiation source 12, controlled by the device body 11, irradiates the radiographic target area of ​​the patient P with radiation (X-rays). In the case of dynamic radiography, the radiation source 12, for example, pulses the radiation and irradiates the patient P. The radiation source 12 is mounted, for example, on an arm of the device body 11, but is not shown in the figure. The arm is movably configured to allow the radiation source 12 to be positioned opposite the radiographic target area of ​​the patient P.

[0044] FPD 13 is a portable radiation detector corresponding to dynamic radiography, detecting radiation transmitted to the radiographic subject area of ​​patient P. Various known FPDs can be used with FPD 13. Furthermore, radiation irradiation from radiation source 12 and radiography based on FPD 13 are configured to be synchronized by known synchronization control, such as time correction based on time-synchronization communication.

[0045] FPD 13, for example, includes radiation detection elements arranged in a two-dimensional pattern on a glass substrate. The radiation detection elements are composed of semiconductor image sensors such as photodiodes. The radiation detection elements detect the intensity of radiation emitted from the radiation source 12 and transmitted through the patient P, and convert the detected radiation into an electrical signal for storage. Each radiation detection element is connected to a switch such as a TFT (Thin Film Transistor), which controls the storage and retrieval of the electrical signal, allowing it to be output as image data.

[0046] Patient P is a patient wearing a ventilator 30. Ventilator 30 is an example of a respiratory assist device.

[0047] Here is a brief explanation of the ventilator 30. The ventilator 30 is a device used to assist the breathing of patients P who are unable to breathe or whose breathing is insufficient, by allowing respiratory gases to enter and exit the lungs for mechanical ventilation and artificial respiration. There are several ways to wear the ventilator 30, but for patients P in the ICU, methods such as endotracheal intubation (inserting the tube 31 into the trachea through the mouth or nose) or tracheotomy (inserting the tube 31 into the trachea through the trachea) are commonly used.

[0048] Then, the dynamic image imaging device 10 irradiates radiation from the radiation source 12 with the FPD 13 positioned opposite the radiation source 12 across the patient P, and performs dynamic imaging of the patient P.

[0049] Figure 2 This is a block diagram showing the functional structure of the main body 11 of the device.

[0050] The main body 11 functions as a control console (camera control device) and also functions as a computer. The main body 11 is as follows: Figure 2 The device is configured to include a control unit 101, an operation unit 102, a display unit 103, a storage unit 104, a communication unit 105, a drive unit 106, a battery 107, a connector 108, and a charging unit 109. All parts of the main body 11 are connected via a bus 110.

[0051] The control unit 101 consists of a CPU (Central Processing Unit), RAM (Random Access Memory), etc. In response to the input of the operation unit 102, the CPU reads the system program and various processing programs stored in the storage unit 104 and expands them into the RAM, and executes various processes according to the expanded programs.

[0052] The control unit 101 controls the moving image imaging device 10, but it may also have a parsing unit 101a with the same functions as the moving image parsing device 40 described later.

[0053] The operation unit 102 includes a touch panel with transparent electrodes arranged in a grid pattern covering the surface of the display unit 103. The touch panel detects the position pressed by a finger, stylus, etc., and inputs the position information as operation information to the control unit 101. In addition, the operation unit 102 includes a radiation switch 102a. The radiation switch 102a is a switch for the user to indicate radiation irradiation and imaging of the radiation source 12.

[0054] The display unit 103 is composed of a monitor such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube). The display unit 103 displays information according to the instructions of the display signal input from the control unit 101.

[0055] The storage unit 104 is composed of non-volatile semiconductor memory, hard disk, etc. The storage unit 104 stores various programs executed by the control unit 101, parameters required for program execution, processing results, and other data.

[0056] The communication unit 105 and FPD 13 transmit and receive data via wired or wireless communication, and transmit and receive data with the dynamic image analysis device 40, image management device 50, client terminal 60, etc. connected to the network N via AP 20.

[0057] The drive unit 106 is a circuit that drives the radiation source 12. The drive unit 106 and the radiation source 12 are connected via a cable.

[0058] Battery 107 supplies power to various parts of the device body 11 and the radiation source 12. Battery 107 can be charged externally via AC cable 111.

[0059] Connector 108 is disposed inside the housing 120 and is electrically connected to FPD 13 housed in the housing 120.

[0060] Based on the control from the control unit 101, the charging unit 109 charges the connected FPD 13 via the connector 108 using the power supplied from the battery 107.

[0061] The dynamic image imaging device 10, having the above-described structure, irradiates the chest of a patient P who is breathing calmly and captures a dynamic image. Then, as described below, the dynamic image analysis device 40 performs dynamic analysis of the dynamic image and outputs diagnostic indicators representing the respiratory status of the patient P. The diagnostic indicators output by the dynamic image analysis device 40 can also be displayed on the display unit 103 of the dynamic image imaging device 10 as analysis summaries AS1 and AS2 described later.

[0062] [Dynamic Image Analysis Device]

[0063] The dynamic image resolution device 40 is, for example, a computer such as a PC or workstation. The dynamic image resolution device 40 can be a desktop computer or a portable computer, such as a laptop or tablet computer.

[0064] The dynamic image analysis device 40 performs dynamic analysis of the dynamic images captured by the dynamic image photography device 10.

[0065] Figure 3 This is a block diagram illustrating an example of the functional structure of the dynamic image analysis device 40. The dynamic image analysis device 40 includes a control unit 41, an operation unit 42, a display unit 43, a storage unit 44, and a communication unit 45. The various components of the dynamic image analysis device 40 are connected via a bus 36.

[0066] The control unit 41 consists of a CPU and RAM, etc. In the control unit 41, the CPU responds to the operation of the operation unit 42, reads the system program and various processing programs stored in the storage unit 44 and expands them into RAM, and executes the action control and dynamic analysis of each part of the dynamic image analysis device 40 based on the expanded program.

[0067] The control unit 41 has an acquisition unit 411 and an output unit 412.

[0068] The acquisition unit 411 performs dynamic analysis on the moving image based on the setting information and obtains the analysis result. For example, the acquisition unit 411 performs dynamic analysis based on signal changes in multiple frame images.

[0069] In the acquisition section 411, the types of dynamic analysis include, for example, blood flow analysis mode, ventilation analysis mode, adhesion analysis mode, diaphragmatic movement analysis mode, and orthopedic correlation measurement mode. Each mode is briefly explained below.

[0070] Blood flow analysis mode is a mode that visualizes signal changes in the lung fields that are synchronized with the heartbeat.

[0071] The ventilation analysis mode is a mode that extracts the temporal signal changes in a specific time band and visualizes the lung tissue movement during respiration.

[0072] Adhesion analysis mode is a mode that visualizes the degree of adhesion of tissues.

[0073] The diaphragm movement analysis mode is a mode that automatically tracks the vertical movement of the diaphragm that accompanies breathing and quantifies the amount of vertical movement of the diaphragm.

[0074] Orthopedic-related measurement mode is a mode that measures the positional changes of specified bones in, for example, the limbs, and displays the movement trajectory.

[0075] Furthermore, in this embodiment, the control unit 41 executes the diagnostic indicator providing program and the respiratory status information providing program as a processing program, and the acquisition unit 411 and the output unit 412 perform the following processing.

[0076] Specifically, in the diagnostic indicator providing procedure, the acquisition unit 411 performs the following processing: From a dynamic image of a patient P's chest irradiated with radiation during quiet breathing, it acquires respiratory information related to breathing and diaphragm information related to the diaphragm. The acquisition unit 411 can acquire diaphragm information using the aforementioned diaphragm movement analysis mode, and can acquire both respiratory and diaphragm information simultaneously through dynamic analysis of the dynamic image. The output unit 412 performs the following processing: Based on the acquired respiratory and diaphragm information, it calculates and outputs diagnostic indicators representing the respiratory state.

[0077] Furthermore, in the respiratory status information providing program, the acquisition unit 411 performs the following processing: acquiring various respiratory-related information from a dynamic image of a patient P's chest irradiated with radiation during quiet breathing. These respiratory-related information include, for example, the aforementioned respiratory information and diaphragm information. The acquisition unit 411 can acquire the diaphragm information using the aforementioned diaphragm movement analysis mode, and can acquire multiple pieces of information simultaneously through dynamic analysis of the dynamic image. The output unit 412 performs processing to output the acquired multiple pieces of information in a summary manner. The output unit 412 may also include diagnostic indicators derived from the respiratory information and diaphragm information, outputting them in a summary manner.

[0078] More specifically, the respiratory information acquired by the acquisition unit 411 from the dynamic image is, as described below, the number of breaths per minute, and this respiratory information is acquired separately for the left and right lungs. In addition, the diaphragm information acquired by the acquisition unit 411 from the dynamic image is, as described below, the diaphragm displacement, and this diaphragm information is also acquired separately for the left and right lungs.

[0079] Furthermore, the diagnostic indicators output by output unit 412, as described later, are values ​​obtained by dividing the respiratory rate by the diaphragmatic displacement, and these diagnostic indicators are calculated separately for the left and right lungs. Then, output unit 412, as described later... Figure 7 , Figure 10 As shown, within one screen displayed on the display unit 43, diagnostic indicators are output together with dynamic images as analytical summaries AS1 and AS2.

[0080] The operation unit 42 is an operation device such as a keyboard, mouse, or trackball with cursor keys, numeric input keys, and various function keys, or a touch panel. The operation unit 42 generates indication signals based on the operator's input and outputs them to the control unit 41. Alternatively, the operation unit 42 may also have a touch panel on the display screen of the display unit 43. In this case, the indication signals input via the touch panel are output to the control unit 41.

[0081] The display unit 43 is composed of display devices such as CRT, liquid crystal display, and organic EL display. The display unit 43 displays input instructions from the operation unit 42 and data (moving images, analysis results, etc.) generated by the moving image imaging device 10 and the moving image analysis device 40, according to the display signal input from the control unit 41.

[0082] The storage unit 44 is composed of a non-volatile semiconductor memory, a hard disk, or the like. The storage unit 44 stores various programs executed by the control unit 41, parameters required for program execution, and data such as processing results (moving images, analysis results, etc.). Various programs are stored in the form of readable program code, and the control unit 41 executes actions according to that program code sequentially.

[0083] The communication unit 45 transmits and receives data with the dynamic image photography device 10, the image management device 50, the client terminal 60, etc.

[0084] [Ventilator weaning protocol]

[0085] The ventilator weaning protocol for removing the tube 31 of the ventilator 30 from the patient P includes protocols related to the SAT (Spontaneous Awakening Trial) and SBT (Spontaneous Breathing Trial). Protocols related to SAT include determining the SAT initiation safety criteria, implementing the SAT, and determining the SAT success criteria. Protocols related to SBT include determining the SBT initiation safety criteria, implementing the SBT, and determining the SBT success criteria.

[0086] In determining the safety criteria for starting SAT, it is determined whether the administration of sedatives to patient P can be discontinued or reduced. SAT is performed if the safety criteria for starting SAT are met.

[0087] During SAT, while sedation administration to patient P is discontinued or reduced, the likelihood of patient P becoming aroused is evaluated. Following SAT, protocols related to SBT are initiated if the SAT success criteria are met.

[0088] The dynamic image analysis device 40 with the above structure is used for SBT. Therefore, detailed descriptions of the SAT start security benchmark, SAT and SAT success benchmark are omitted, and well-known SAT start security benchmark, SAT and SAT success benchmark can be used.

[0089] In determining the safety baseline for starting SBT, it is determined whether the patient can be transferred to a state without assistance from the ventilator 30. If the criteria are met... Figure 4SBT is implemented under the premise of starting the safety baseline as shown in the diagram.

[0090] In SBT, spontaneous breathing of patient P is evaluated without ventilator support from ventilator 30. After performing SBT, spontaneous breathing of patient P is evaluated when it is determined to be satisfactory. Figure 4 Under the conditions shown in the SBT success criteria, the doctor determines the extubation of the tube 31 of the ventilator 30.

[0091] Here, as the main project for starting the SBT safety benchmark, such as Figure 4 As shown, the following (A1)~(A5) exist.

[0092] (A1) Adequate oxygenation.

[0093] (A2) Hemodynamically stable.

[0094] (A3) There is sufficient inspiratory effort.

[0095] (A4) No abnormal breathing patterns were observed.

[0096] (A5) The patient's overall condition is stable.

[0097] The main items (A1) through (A5) above include various sub-items, but their detailed descriptions are omitted here. Among the main items (A1) through (A5), RSBI (Rapid Shallow Breathing Index) is a sub-item under "(A3) Sufficient inspiratory effort exists." However, as mentioned above, there are reports that RSBI has low accuracy as an indicator for judging extubation. Instead of RSBI, there is an indicator such as D-RSBI, but as mentioned above, its measurement reproducibility is also poor.

[0098] Therefore, in this embodiment, instead of RSBI and D-RSBI, the dynamic image analysis device 40 provides the diagnostic indicators described below as indicators that can objectively diagnose the respiratory state during calm breathing with high accuracy and reproducibility.

[0099] [Provide Diagnostic Indicators]

[0100] refer to Figures 5 to 7 The diagnostic indicators provided by the dynamic image analysis device 40 are described below.

[0101] Figure 5 This is a flowchart illustrating the method for providing diagnostic indicators implemented by the dynamic image analysis device 40. Figure 6 This is a diagram illustrating a method for determining the number of breaths and the amount of diaphragmatic displacement per minute from dynamic images captured by the dynamic image capturing device 10.

[0102] As described above, when the SAT success criteria are met, the SBT-related protocol is initiated, starting with the determination of the SBT initiation safety criteria. In this embodiment, during the determination of the SBT initiation safety criteria, in order to objectively assess respiratory effort, the dynamic image imaging device 10 performs dynamic imaging of the patient P during quiet breathing. Then, the dynamic image analysis device 40 outputs diagnostic indicators representing the respiratory state of the patient P during quiet breathing using the method described below.

[0103] (Step S11)

[0104] The control unit 41 of the dynamic image analysis device 40 acquires a dynamic image of the patient P's chest obtained through dynamic photography. The control unit 41 acquires, for example, the dynamic image captured by the dynamic image photography device 10 and stored in the storage unit 104 via a network N.

[0105] (Step S12A)

[0106] The acquisition unit 411 of the control unit 41 identifies lung field regions in each of the multiple frame images constituting the dynamic image to determine the position of the diaphragm. Regarding the identification of lung field regions, known image processing methods such as edge detection or machine learning methods can be used for identification. Furthermore, regarding the diaphragm, for example, the lower edge portion of the identified lung field region can be identified as the diaphragm.

[0107] For example, like part 411 Figure 6 As shown in frame image F, the lung field regions LL and RL of the left and right lungs are identified, and the lower edges of the lung field regions LL and RL are defined as the left and right diaphragms LD and RD. Furthermore, the location of the left diaphragm LD is determined by considering the position of the heart.

[0108] The position information of the diaphragm LD and RD is stored in the storage unit 44 for each frame image. Figure 7 The analysis summary AS1, when displaying frame image F, also shows the positions of the diaphragm LD and RD. Similarly, the lung field regions LL and RL can have their position information stored in storage unit 44 for each frame image, just like the diaphragm LD and RD. Figure 7 The analysis summary AS1 shows the positions of lung field regions LL and RL when frame image F is displayed.

[0109] (Step S13A)

[0110] The acquisition unit 411 calculates the number of breaths per minute and the displacement of the diaphragm per minute based on the displacement and period of the diaphragm position in the dynamic image. The number of breaths per minute is an example of respiratory information related to breathing, and the displacement of the diaphragm is an example of diaphragm information related to the diaphragm.

[0111] For example, like part 411 Figure 6 As shown in graph G, a graph depicting the displacement of the diaphragm over time (frame number of the frame image) is created. Based on the created graph, the number of breaths per minute and the displacement of the diaphragm are calculated. Furthermore, Figure 6 The graph G in the figure illustrates the right diaphragm, but the same graph can be made for the left diaphragm, and the number of breaths per minute and the displacement of the diaphragm can be calculated from the graph.

[0112] The acquisition unit 411 detects the period of displacement in the curve G, for example, calculates the number of breaths per minute based on the detected displacement period, and calculates the displacement of the diaphragm based on the minimum and maximum displacement values ​​in one period. When multiple periods are detected, the acquisition unit 411 can also calculate the number of breaths per minute based on the multiple periods, and can also calculate the average displacement based on the displacement of the diaphragm in each period.

[0113] The acquisition unit 411 may, for example, calculate the similarity of the waveforms in the curve G and set the resolution interval in a way that includes continuous waveforms with high similarity, or the operation unit 42 may be used to allow the user to set the resolution interval. In this case, the number of breaths per minute and the displacement of the diaphragm are calculated within the set interval.

[0114] (Steps S14 and S15)

[0115] The output unit 412 of the control unit 41 calculates diagnostic indicators by dividing (the number of breaths per minute) by (the displacement of the diaphragm) based on the respiratory rate and diaphragm displacement obtained by the acquisition unit 411, and outputs the calculated diagnostic indicators. The output diagnostic indicators, along with the obtained respiratory rate and diaphragm displacement, are stored in the storage unit 44. Figure 7 The parsing summary shown in AS1 is the parsing result.

[0116] The respiratory rate per minute and diaphragmatic displacement are obtained from dynamic images captured by radiographic imaging of the entire chest. Therefore, unlike ultrasound diagnostic devices, the measurements do not vary due to the position or angle of the detector contact, resulting in highly reproducible values. Furthermore, regarding the respiratory rate per minute and diaphragmatic displacement, because the dynamic images are dynamically analyzed to identify the left and right lung fields and determine the left and right diaphragms, highly accurate values ​​can also be obtained. As a result, the diagnostic indicators obtained through the above calculations become highly accurate and reproducible diagnostic indicators, allowing physicians to objectively diagnose the respiratory status of patient P during quiet breathing.

[0117] Figure 7It shows that including through Figure 6 The method described herein is used to calculate the respiratory rate per minute, diaphragmatic displacement, and diagnostic indicator DI. The summary of the analysis is shown in the AS1 graph.

[0118] Output unit 412, for example, will Figure 7 The analysis summary AS1 shown is displayed on the display unit 103. The analysis summary AS1 includes the frame image F of each of the left and right diaphragms, the curve G, the analysis result AR, and the summary SM.

[0119] The output unit 412 serves as a frame image F, displaying, for example, a frame image when the displacement is at its minimum and a frame image when the displacement is at its maximum. In this case, the output unit 412 also displays the diaphragm LD and RD, determined using the displayed frame images. Thus, the user can visually grasp the positions of the diaphragm LD and RD in the frame images. Alternatively, the output unit 412 can also display a dynamic image instead of the frame image F; in this case, simply displaying the diaphragm LD and RD is sufficient.

[0120] Furthermore, the output unit 412 displays the curve G, and for example, displays dashed lines representing the time of maximum and minimum points. Thus, the user can visually grasp the period and displacement in the curve G.

[0121] Furthermore, the output unit 412 displays the analytical result AR numerically, including the average displacement of the diaphragm, the period of displacement, the number of breaths per minute, and the diagnostic index DI calculated above. Thus, the user can objectively understand the analytical result through numerical values.

[0122] Furthermore, the output unit 412 displays the values ​​of the diagnostic indicators DI at the left and right diaphragms and a bar graph BG as a summary SM. The bar graph BG is a graphical representation of the diagnostic indicators DI in a visual manner. Here, the diagnostic indicators DI of the right diaphragm are displayed at the top of the bar graph BG, and the diagnostic indicators DI of the left diaphragm are displayed at the bottom of the bar graph BG. In the bar graph BG, the left side of the threshold TV represents the acceptable numerical range, and the right side of the threshold TV represents the unacceptable numerical range.

[0123] In this way, the output unit 412 displays the analytical summary AS1 on one screen of the display unit 43, so that the doctor can confirm various information, including the diagnostic indicators DI at the left and right diaphragms, and objectively diagnose the respiratory status of the patient P during calm breathing.

[0124] In addition, while the motion imaging device 10 and the motion image analysis device 40 are used to determine the SBT start safety baseline, they can also be used before and after SBT-related protocols to diagnose the patient P's respiratory status. In this case, the settings of the ventilator 30 can be changed based on the patient P's respiratory status, such as diagnostic indicator DI.

[0125] Furthermore, while the dynamic image analysis device 40 obtains the diagnostic index DI from the dynamic image acquired by the dynamic image imaging device 10, if the dynamic image imaging device 10 has the aforementioned analysis unit 101a, the diagnostic index DI can also be obtained at the dynamic image imaging device 10 side. For example, the analysis unit 101a can also acquire the frame images constituting the dynamic image in real time during the capture of the dynamic image and calculate the diagnostic index DI for each respiratory cycle. In this case, the dynamic image imaging device 10 may, for example, display an analysis summary AS1 including the diagnostic index DI on the display unit 103.

[0126] [Summarize]

[0127] As described above, the dynamic image analysis apparatus 40 according to this embodiment has the aforementioned acquisition unit 411 and output unit 412 in the control unit 41.

[0128] According to the dynamic image analysis device 40 of this embodiment, the diagnostic index DI based on respiratory information (breathing count per minute) and diaphragm information (diaphragm displacement) has high accuracy and reproducibility as described above, thus providing a highly accurate and reproducible diagnostic index. Based on such a diagnostic index DI, the doctor can objectively diagnose the respiratory status of the patient P during quiet breathing, supporting the decision to remove the tube 31 of the ventilator 30 when the doctor deems it appropriate. Furthermore, compared to other methods, it is easier to determine whether extubation is feasible, and the psychological burden on the doctor can be reduced.

[0129] Furthermore, according to the dynamic image analysis device 40 of this embodiment, various respiratory-related information, such as respiratory information (breathing count per minute), diaphragm information (diaphragm displacement), and diagnostic index DI, are output in a summary manner. Thus, useful information for diagnosing the respiratory status of patient P during quiet breathing can be provided in a summary manner, allowing doctors to objectively diagnose patient P's respiratory status and supporting the decision to remove the tube 31 of the ventilator 30. Moreover, compared to the past, it is easier to determine whether extubation is appropriate, and the psychological burden on doctors can be reduced.

[0130] Furthermore, patients P wearing ventilators 30 (e.g., patients P in the ICU) are difficult to move. Such patients P are difficult to move to X-ray rooms, such as CT (Computed Tomography) rooms, where CT scans cannot be performed, and high-resolution images cannot be obtained. Therefore, when making extubation decisions, currently methods such as ultrasound diagnostic devices and visual inspection by doctors are necessary; there is no means to visualize the respiratory status with images including the entire lung. In this embodiment, by using a mobile medical vehicle equipped with the dynamic imaging device 10, the dynamic imaging device 10 can be brought to the patient P's side. Therefore, according to the dynamic image processing system 1 of this embodiment, dynamic images including the entire lung can be obtained without moving the patient P, and diagnostic indicators representing the respiratory status can be obtained.

[0131] <Variation Example 1>

[0132] Figure 8 This is a flowchart illustrating the method for providing other diagnostic indicators implemented by the dynamic image analysis device 40. Figure 9 This is a diagram illustrating another method for determining the number of breaths and the amount of diaphragmatic displacement per minute from dynamic images captured by the dynamic image imaging device 10.

[0133] In this variation, the moving image capturing device 10 and the moving image analyzing device 40 described in the above embodiments are also used; however, the method for providing diagnostic indicators implemented by the moving image analyzing device 40 differs from that in the above embodiments. Specifically, the dynamic analysis method of the captured moving image is different, as will be referred to below. Figure 8 and Figure 9 Please provide an explanation.

[0134] As described above in this variation, when determining the SBT start safety baseline, dynamic imaging of patient P during quiet breathing is performed by the dynamic image imaging device 10 in order to objectively determine respiratory effort. Then, the dynamic image analysis device 40 outputs diagnostic indicators representing the respiratory status of patient P during quiet breathing using the method described below.

[0135] (Step S11)

[0136] This step S11 and Figure 5 The steps S11 described herein are the same, therefore the same symbols are added and repeated descriptions are omitted.

[0137] (Step S12B)

[0138] The acquisition unit 411 of the control unit 41 identifies the left and right lung field regions LL and RL in each of the multiple frame images constituting the dynamic image, determines the positions of the left and right diaphragms, and sets the left and right pixel regions LP and RP that extend across the diaphragm in the vertical direction of the human body. This can be achieved by... Figure 5 The method described in step S12A is used to identify lung field regions LL and RL and determine the position of the diaphragm. Pixel regions LP and RP are, for example, 1 pixel in the left-right direction and 100 to 200 pixels in the vertical direction of the human body. The vertical direction of pixel regions LP and RP is set to always include the size of the diaphragm even if the diaphragm is displaced.

[0139] For example, like part 411 Figure 9 As shown in frame image F, lung field regions LL and RL are identified, and the lower edge of lung field regions LL and RL is determined as the left and right diaphragms (symbols omitted). Pixel regions LP and RP are defined that extend across the diaphragm in the vertical direction of the human body.

[0140] The position information of pixel regions LP and RP is stored in the storage unit 44. Figure 10 The analysis summary AS2, when displaying frame image F, also shows the positions of pixel regions LP and RP. Alternatively, the position information of lung field regions LL and RL can be stored in storage unit 44 for each frame image. Figure 10 The analysis summary AS2 shows the positions of lung field regions LL and RL when frame image F is displayed.

[0141] (Step S13B)

[0142] The acquisition unit 411 calculates the displacement of the diaphragm and the number of breaths per minute based on the mapped image M obtained by mapping pixel regions LP and RP along the time axis.

[0143] For example, like part 411 Figure 9 As shown in the mapped image M, the pixel values ​​within the pixel region RP of each frame image are arranged in two dimensions along the time axis (the frame number of the frame image) to form the mapped image M. Then, the acquisition unit 411 performs image analysis on the mapped image M, for example, detecting the displacement of the intensity boundary (edge) of the pixel values ​​relative to the time axis, that is, the displacement of the diaphragm position along the time axis, and calculates the number of breaths per minute and the displacement of the diaphragm based on the displacement of the intensity boundary relative to the time axis. Furthermore, Figure 9 The mapping image M in the diagram is an example shown with respect to the right diaphragm, but the mapping can be done in the same way with respect to the left diaphragm, and the number of breaths per minute and the displacement of the diaphragm can be determined from the mapping image.

[0144] The acquisition unit 411 detects the period of displacement in the mapped image M, calculates the number of breaths per minute based on the detected period of displacement, and calculates the displacement of the diaphragm based on the minimum and maximum displacement values ​​in one period. If multiple periods are detected, the acquisition unit 411 can also calculate the number of breaths per minute based on the multiple periods, and further calculate the average displacement based on the displacement of the diaphragm in each period.

[0145] The acquisition unit 411 may, for example, calculate the similarity of the waveforms of the detected edges and set the resolution interval in a manner that includes continuous waveforms with high similarity, or the operation unit 42 may be used to allow the user to set the resolution interval. In this case, the number of breaths per minute and the displacement of the diaphragm will be calculated within the set interval.

[0146] Furthermore, in dynamic images, for example, when the outline of the diaphragm is unclear due to reasons such as low image contrast, it is impossible to determine the density boundary of the aforementioned pixel values, i.e., the position of the diaphragm, and sometimes it is difficult to automatically track the position of the diaphragm between frames. In this case, in step S12B above, the acquisition unit 411 sets the pixel regions LP and RP in the left-right direction of the human body to multiple pixels instead of one pixel, and averages the pixel values ​​of the multiple pixels in the left-right direction of the human body. Furthermore, in step S13B above, the acquisition unit 411 maps the pixel regions LP and RP, for which the pixel values ​​of the multiple pixels in the left-right direction of the human body have been averaged, along the time axis to create a mapped image M. As a result, even when the outline of the diaphragm is unclear in dynamic images, the contrast resolution in the vertical direction of the human body can be improved, the position of the diaphragm can be determined, and the position of the diaphragm can be automatically tracked between frames.

[0147] (Steps S14 and S15)

[0148] Steps S14 and S15 are Figure 5 Steps S14 and S15 described herein are the same, therefore the same symbols are added and repeated descriptions are omitted.

[0149] In this modified example, the respiratory rate per minute and the diaphragmatic displacement are obtained from dynamic images obtained by radiographic imaging of the entire chest. Therefore, the measurements do not vary depending on the position and angle of the detector contact, unlike those obtained with ultrasound diagnostic devices, resulting in highly reproducible values. Furthermore, regarding the respiratory rate per minute and diaphragmatic displacement, dynamic analysis of the dynamic images is performed to identify the left and right lung fields and determine the left and right diaphragms, thus obtaining highly accurate values. As a result, the diagnostic indicators obtained through the above calculations become highly accurate and reproducible diagnostic indicators, allowing physicians to objectively diagnose the respiratory status of patient P during quiet breathing.

[0150] Figure 10 It shows that including through Figure 9 The method described in the figure is used to calculate the respiratory rate per minute, diaphragmatic displacement, and diagnostic indicator DI. The summary of the analysis is shown in the AS2 graph.

[0151] The output unit 412 displays, for example, on the display unit 43. Figure 10 The parsing summary AS2 is shown. Parsing summary AS2 includes the frame image F of each of the left and right diaphragms, the mapped image M, the parsing result AR, and the summary SM.

[0152] The output unit 412 serves as a frame image F, displaying, for example, a frame image with the displacement at its minimum and a frame image with the displacement at its maximum. In this case, the output unit 412 also displays pixel regions LP and RP defined in the displayed frame image. Thus, the user can visually perceive the position of the diaphragm and the pixel regions LP and RP in the frame image. Furthermore, the output unit 412 can also display a moving image instead of the frame image F; in this case, the pixel regions LP and RP can also be displayed.

[0153] Furthermore, the output unit 412 displays the mapped image M, and for example, displays dashed lines representing the time of minimum points and single-dot dashed lines representing the maximum and minimum displacements. Thus, the user can visually grasp the period and displacement in the mapped image M.

[0154] In the parsing summary AS2, the parsing result AR and the summary SM are... Figure 7 The parsing summary AS1 shown is the same, so repeated explanations are omitted.

[0155] Therefore, the output unit 412 displays the analytical summary AS2 on one screen of the display unit 43, so that the doctor can confirm various information including the diagnostic indicators DI at the left and right diaphragms and objectively diagnose the respiratory status of the patient P during calm breathing.

[0156] Therefore, in this modified example, the dynamic image analysis device 40 can provide a diagnostic indicator DI with high accuracy and reproducibility, as described above. Based on this diagnostic indicator DI, the doctor can objectively diagnose the respiratory status of the patient P during quiet breathing, supporting the decision to remove the tube 31 of the ventilator 30. Furthermore, compared to the past, it is easier to determine whether extubation is feasible, and the psychological burden on the doctor can be reduced.

[0157] <Variation Example 2>

[0158] Figure 11 This is a diagram AS3 showing the analytical summary of respiratory and heart rate information derived from dynamic images captured by the dynamic image capturing device 10.

[0159] In this variation, the dynamic image capturing device 10 and dynamic image analyzing device 40 described in the above embodiments are also used. However, the object of dynamic analysis performed by the dynamic image analyzing device 40 is not only the diaphragm, but also the heart. The dynamic image analyzing device 40 obtains respiratory and heartbeat information through dynamic analysis of the diaphragm and heart in the dynamic image.

[0160] Therefore, in this modified example, the control unit 41 executes the tube removal judgment information providing program as a processing program, and the acquisition unit 411 and the output unit 412 perform the following processing.

[0161] Specifically, the extubation judgment information providing procedure performs the following processing: From a dynamic image obtained by irradiating the chest of a patient P wearing a ventilator 30 in a calm breathing state, information is acquired to assess whether extubation of the ventilator 30 is possible. This information includes respiratory information related to breathing and heart rate information related to heart rate. As described later, the acquisition unit 411 can acquire both respiratory and heart rate information simultaneously through dynamic analysis of the dynamic image. The output unit 412 performs processing to output the respiratory and heart rate information in a summary manner.

[0162] Furthermore, in this modified example, the respiratory information acquired by the acquisition unit 411 from the dynamic image, as described below, includes respiratory rate, diaphragmatic displacement, and respiratory pattern, and this information is acquired separately for the left and right lungs. Additionally, the heartbeat information acquired by the acquisition unit 411 from the dynamic image, as described below, includes heart rate.

[0163] Furthermore, in this modified example, the respiratory information output by output unit 412, as described later, includes respiratory rate, diaphragmatic displacement, respiratory pattern, and diagnostic indicators, calculated separately for the left and right lungs. The diagnostic indicators represent the respiratory status of patient P and are indicators that can evaluate respiratory effort. Additionally, the heart rate information output by output unit 412 includes heart rate. Furthermore, output unit 412 as described below... Figure 11 As shown, on one screen displayed on display unit 43, AS3 outputs information representing respiratory rate, diaphragmatic displacement, respiratory pattern, diagnostic indicators, and heart rate along with dynamic images in a summary view.

[0164] Here, about Figure 4 The SBT success benchmark shown below includes the main evaluation items for specific evaluation.

[0165] (B1) Respiratory rate

[0166] (B2) Oxygen saturation (SpO2)

[0167] (B3) Partial pressure of carbon dioxide (PaCO2)

[0168] (B4) Heart rate

[0169] (B5) Blood pressure

[0170] (B6) Breathing effort

[0171] (B7) Breathing pattern

[0172] As explained below, by performing dynamic analysis of dynamic images by the dynamic image analysis device 40, four evaluation items (B1) respiratory rate, (B4) heart rate, (B6) respiratory effort, and (B7) respiratory pattern among the above evaluation items (B1) to (B7) can be obtained.

[0173] Regarding (B1) respiratory rate, as described above, the dynamic image analysis device 40 can obtain a curve G and a mapping image M representing the displacement of the diaphragm, and calculate the number of breaths per minute based on the obtained curve G and mapping image M.

[0174] Furthermore, as described above, the dynamic image analysis device 40 identifies lung field regions LL and RL in the frame image F, thus enabling it to calculate changes in lung field area and obtain representations. Figure 11 The curve LG showing the change in lung field area is shown. The dynamic image analysis device 40 can also calculate the number of breaths per minute based on the obtained curve LG. Thus, the dynamic image analysis device 40 calculates the respiratory rate based on the displacement of the diaphragm and the change in lung field area, thereby providing the respiratory rate as more reliable and useful information to the doctor.

[0175] Regarding (B6) respiratory effort, as described above, the dynamic image analysis device 40 calculates the diagnostic index DI representing the respiratory state based on the curve G representing the displacement of the diaphragm and the mapped image M. The diagnostic index DI is an indicator of the respiratory effort of patient P as a respiratory state.

[0176] Furthermore, as described above, the dynamic image analysis device 40 can also obtain the curve LG, and therefore, based on the obtained curve LG, it can perform the same calculation as the diagnostic index DI to obtain the diagnostic index LI representing the respiratory state. For example, the diagnostic index LI is obtained by dividing (the number of breaths per minute) by (the change in lung field area). The diagnostic index LI is also an indicator of the respiratory effort of patient P as a respiratory state.

[0177] In the dynamic image analysis device 40, the output unit 412 of the control unit 41 displays the change in lung field area, cycle, respiratory rate per minute, and diagnostic indicator LI as the analysis result L-AR using numerical values. Thus, the user can objectively understand the analysis results using numerical values.

[0178] Furthermore, the output unit 412 can also display bar graphs L-BG of the diagnostic indicator LI in the left and right lung fields, similar to the diagnostic indicator DI. The bar graph L-BG is a graphical representation of the diagnostic indicator LI in a visual manner; here, the diagnostic indicator LI of the right lung field is displayed at the top of the bar graph L-BG, and the diagnostic indicator LI of the left lung field is displayed at the bottom of the bar graph L-BG. In the bar graph L-BG, the left side of the threshold L-TV represents the acceptable numerical range, and the right side of the threshold L-TV represents the unacceptable numerical range.

[0179] In this way, the dynamic image analysis device 40 calculates the diagnostic indicators DI and LI based on the displacement of the diaphragm and the change in lung field area, thus providing doctors with more reliable and useful information about respiratory effort.

[0180] Regarding (B7) the breathing pattern, as described above, the dynamic image analysis device 40 can obtain a curve G representing the displacement of the diaphragm and a mapped image M, and therefore can obtain the breathing pattern from the curve G and the mapped image M. In this modified example, the dynamic image analysis device 40 pre-stores multiple breathing patterns representing breathing abnormalities in the storage unit 44. Then, the dynamic image analysis device 40 determines whether a breathing pattern is present and the corresponding breathing abnormality is present by matching the breathing pattern with the multiple breathing patterns stored in the storage unit 44 from the curve G and the mapped image M. Furthermore, the dynamic image analysis device 40 may, for example, use a recognizer that has performed machine learning on the multiple breathing patterns representing breathing abnormalities to determine whether a breathing abnormality is present and the corresponding breathing abnormality is present.

[0181] Furthermore, as described above, the dynamic image analysis device 40 can also obtain a curve graph LG, and thus a respiratory pattern can be obtained from the curve graph LG. Regarding the respiratory pattern obtained from the curve graph LG, as described above, the dynamic image analysis device 40 uses a pattern matching and recognition device to determine its validity and any respiratory abnormalities. In this way, the dynamic image analysis device 40 determines the respiratory pattern based on the displacement of the diaphragm and changes in the lung field area, and therefore can provide the physician with more reliable and useful information regarding the validity of the respiratory pattern and respiratory abnormalities.

[0182] Regarding (B4) heart rate, the dynamic image analysis device 40 applies the aforementioned diaphragm movement analysis mode to the myocardial wall. For example, it determines the position of the myocardial wall for each frame image F and generates a curve showing the displacement of the myocardial wall position relative to time (frame number of the frame image). Furthermore, the dynamic image analysis device 40 can also, similarly to the modified example 1 described above, set a pixel region CP spanning the myocardial wall and generate a mapped image CM obtained by mapping the pixel region CP along the time axis. Figure 11 This example illustrates the case where a mapped image CM has been created.

[0183] The dynamic image analysis device 40 can use edge detection, machine learning, etc. to identify lung field regions and heart regions, and determine the position of the myocardial wall and set the pixel region CP based on the identified lung field regions and heart regions.

[0184] Furthermore, the dynamic image analysis device 40 can determine the amount of myocardial wall displacement, the period of displacement, and the number of displacements per minute from the displacement curve of the myocardial wall and the mapped image CM, using the same method as described using the curve G and the mapped image M. Thus, the dynamic image analysis device 40 determines the heart rate and the amount of myocardial wall displacement based on the displacement curve of the myocardial wall and the mapped image CM, thereby providing the heart rate as more reliable and useful information to the doctor.

[0185] Furthermore, the dynamic image analysis device 40 can also calculate the diagnostic index CI, which represents the state of the heart, based on the amount of motion displacement of the myocardial wall, the period of motion displacement, and the number of motion displacements per minute. For example, the diagnostic index CI can be calculated by dividing (the number of motions per minute) by (the amount of motion displacement of the myocardial wall).

[0186] The output unit 412 uses numerical values ​​to display the amount of myocardial wall motion displacement, the period of motion displacement, the number of motion displacements per minute, and the diagnostic index CI as the analysis result C-AR. Thus, users can objectively understand the analysis results using numerical values.

[0187] Furthermore, the output unit 412 can also display a bar graph C-BG of the diagnostic indicator CI at the heart, similar to the diagnostic indicator DI. The bar graph C-BG is a graphical representation of the diagnostic indicator CI in a visual manner; here, the diagnostic indicator CI at the heart is displayed at the top of the bar graph C-BG. In the bar graph C-BG, the left side of the threshold C-TV represents the acceptable numerical range, and the right side of the threshold C-TV represents the unacceptable numerical range.

[0188] As explained above, the dynamic image analysis device 40 can simultaneously acquire and provide a summary of four evaluation items (B1) to (B7): (B1) respiratory rate, (B4) heart rate, (B6) respiratory effort, and (B7) respiratory pattern. As mentioned above, (B1) respiratory rate, (B4) heart rate, (B6) respiratory effort, and (B7) respiratory pattern are highly reliable and useful information. Therefore, information useful for determining whether to extubate the ventilator can be provided to the doctor simultaneously and in a summary manner. This allows the doctor to objectively diagnose the patient P's respiratory status, supporting the decision to remove the tube 31 of the ventilator 30. Furthermore, compared to the past, it is easier to determine whether extubation is appropriate, and the psychological burden on the doctor can be reduced.

[0189] The above embodiments are merely examples illustrating specific implementations of the invention and should not be used to limit the scope of the invention. That is, the invention can be implemented in various ways without departing from its spirit or main features.

[0190] [Explanation of Symbols]

[0191] 1: Dynamic image processing system; 10: Dynamic image photography device; 11: Device body; 12: Radiation source; 13: FPD; 20: AP; 30: Artificial respirator; 40: Dynamic image analysis device; 41: Control unit; 42: Operation unit; 43: Display unit; 44: Storage unit; 45: Communication unit; 50: Image management device; 60: Client terminal; 411: Acquisition unit; 412: Output unit.

Claims

1. A dynamic image analysis device, comprising: The acquisition unit obtains dynamic images of the chest of a subject during calm breathing by irradiating it with radiation and taking photographs, acquiring respiratory information related to breathing and diaphragmatic information related to the diaphragm; and The output unit calculates and outputs an index representing the respiratory state based on the respiratory information and the diaphragm information.

2. The dynamic image analysis device according to claim 1, wherein, The respiratory information is the number of breaths, the diaphragm information is the diaphragm displacement, and the index is the value obtained by dividing the number of breaths by the diaphragm displacement.

3. The dynamic image analysis device according to claim 2, wherein, The breathing rate is the number of breaths per minute.

4. The dynamic image parsing device according to claim 3, wherein, The acquisition unit identifies lung field regions in each of the multiple frame images constituting the dynamic image to determine the position of the diaphragm, and calculates the number of breaths per minute and the amount of diaphragm displacement based on the displacement of the diaphragm position relative to time.

5. The dynamic image parsing device according to claim 3, wherein, The acquisition unit identifies lung field regions in each of the multiple frame images constituting the dynamic image to determine the position of the diaphragm, sets a pixel region that extends across the diaphragm in the vertical direction of the human body, forms an image by arranging the pixel values ​​in the pixel region in two dimensions along the time axis, and calculates the number of breaths per minute and the amount of diaphragm displacement based on the displacement of the density boundary of the pixel values ​​in the formed image relative to the time axis.

6. The dynamic image parsing device according to claim 2, wherein, The output unit calculates the indices for the left and right lungs respectively.

7. The dynamic image parsing apparatus according to claim 2, wherein, The dynamic image analysis device also includes a display unit. The output unit outputs the indicator along with the dynamic image within one screen displayed on the display unit.

8. The dynamic image parsing device according to claim 2, wherein, The dynamic image is a dynamic image of a subject wearing a ventilator breathing calmly.

9. The dynamic image parsing device according to claim 2, wherein, The dynamic image is a dynamic image of the subject breathing calmly while wearing a ventilator but not using the ventilator to assist breathing.

10. A dynamic image processing system, comprising: A mobile medical vehicle, comprising a dynamic imaging device and a trolley, wherein the dynamic imaging device irradiates the chest of a subject during calm breathing and captures a dynamic image, and the trolley carries the dynamic imaging device and is configured to be mobile; and The dynamic image analysis device according to claim 1.

11. A diagnostic indicator provides a computer program product that enables a computer of a dynamic image resolution device to execute: Processing was performed by irradiating the chest of a subject during quiet breathing with radiation and then photographing dynamic images to obtain respiratory information related to respiration and diaphragmatic information related to the diaphragm; and The output processing, based on the respiratory information and the diaphragm information, outputs an index representing the respiratory state.

12. A computer program product providing diagnostic indicators according to claim 11, wherein, The respiratory information is the number of breaths, the diaphragm information is the diaphragm displacement, and the index is the value obtained by dividing the number of breaths by the diaphragm displacement.

13. A computer program product providing diagnostic indicators according to claim 12, wherein, The breathing rate is the number of breaths per minute.

14. A computer program product providing the diagnostic indicators according to claim 13, wherein, In the acquisition process, lung field regions are identified in each of the multiple frame images constituting the dynamic image to determine the position of the diaphragm, and the number of breaths per minute and the amount of diaphragm displacement are calculated based on the displacement of the diaphragm position relative to time.

15. A computer program product providing the diagnostic indicators according to claim 13, wherein, In the acquisition process, the position of the diaphragm is determined by identifying lung field regions in each of the multiple frame images constituting the dynamic image, a pixel region extending across the diaphragm in the vertical direction of the human body is set, and an image is formed by arranging the pixel values ​​in the pixel region in two dimensions along the time axis. The number of breaths per minute and the amount of diaphragm displacement are calculated based on the displacement of the density boundary of the pixel values ​​in the formed image relative to the time axis.

16. A computer program product providing diagnostic indicators according to claim 12, wherein, In the output processing, the indices are calculated for the left and right lungs respectively.

17. A computer program product providing diagnostic indicators according to claim 12, wherein, In the output processing, the indicator and the dynamic image are output together within one screen displayed on the display unit.

18. A computer program product providing diagnostic indicators according to claim 12, wherein, The dynamic image is a dynamic image of a subject wearing a ventilator breathing calmly.

19. A computer program product providing diagnostic indicators according to claim 12, wherein, The dynamic image is a dynamic image of the subject breathing calmly while wearing a ventilator but not using the ventilator to assist breathing.

Images