Patent Publication Number: US-2023153995-A1

Title: Radiographic image processing apparatus and computer-readable medium

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present invention claims priority under 35 U.S.C. § 119 to Japanese Application, 2021-184448, filed on Nov. 12, 2021, the entire contents of which being incorporated herein by reference. 
     BACKGROUND 
     Technological Field 
     The present invention relates to a radiographic image processing apparatus and a computer-readable medium. 
     Description of the Related Art 
     There is known a technique of determining an abnormality in each radiographic image acquired by imaging during the capturing of radiographic images. 
     For example, JP 2020-48864 A discloses that radiographic images generated during the capturing of moving images in which the emission of radiation and the generation of a radiographic image are repeated at high speed are acquired, it is determined whether or not there is an abnormality in each of the acquired radiographic images, and an operation at the time of abnormality, such as “stop control for emission of radiation”, “delete radiographic image”, “do not output to outputter”, and “do not perform analysis”, is performed when it is determined that there is an abnormality. 
     SUMMARY 
     In JP 2020-48864 A, the determination regarding whether or not there is an abnormality is repeated each time an image of several tens of frames per second is acquired during exposure. However, many dynamic images (moving images) have more than several hundred frames. If an image processing apparatus with low processing performance (low spec) or the like is used to determine whether or not there is an abnormality in a dynamic image, a long processing time is required. As a result, the user may not be able to check images smoothly. 
     It is an object of the present invention to shorten the processing time required for determining an abnormality in a captured dynamic image. 
     To achieve at least one of the abovementioned objects, according to an aspect of the present invention, a radiographic image processing apparatus reflecting one aspect of the present invention comprises: an acquirer that acquires a dynamic image including a plurality of frame images captured by a radiographic imaging apparatus; a hardware processor that determines whether or not there is an abnormality in the dynamic image by using some of the frame images of the acquired dynamic image; and a notifier that notifies of a result of the determination by the hardware processor. 
     To achieve at least one of the abovementioned objects, according to another aspect of the present invention, a non-transitory computer-readable medium reflecting one aspect of the present invention stores a program that causes a computer to perform: acquiring a dynamic image including a plurality of frame images captured by a radiographic imaging apparatus; determining whether or not there is an abnormality in the dynamic image by using some of the frame images of the acquired dynamic image; and notifying of a determination result in the abnormality determination. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The advantages and features provided by one or more embodiments of the invention will become more fully understood from the detailed description given hereinbelow and the appended drawings which are given by way of illustration only, and thus are not intended as a definition of the limits of the present invention, wherein: 
         FIG.  1    is a block diagram showing an example of a radiographic imaging system according to an embodiment of the present invention; 
         FIG.  2    is a block diagram showing the functional configuration of a radiographic image processing apparatus included in the radiographic imaging system shown in  FIG.  1   ; 
         FIG.  3    is a diagram showing an example of data storage in an abnormality determination database; 
         FIG.  4    is a diagram showing an example of an examination screen; 
         FIG.  5    is a flowchart showing the flow of an abnormality determination control process A performed by a controller shown in  FIG.  2   ; 
         FIG.  6    is a diagram for describing a method of selecting frame images used for abnormality determination; 
         FIG.  7    is a diagram for describing the extraction of the spine; 
         FIG.  8    is a diagram for describing calculation of the amount of change in lung apex position; 
         FIG.  9    is a diagram for describing the setting of a determination target region; 
         FIG.  10    is a diagram for describing trimming; 
         FIG.  11    is a diagram showing an example of an examination screen on which an alert is displayed; 
         FIG.  12    is a diagram showing an example of an examination screen on which a selection button for selecting an abnormality determination algorithm used for the next abnormality determination is displayed; and 
         FIG.  13    is a flowchart showing the flow of an abnormality determination control process B performed by the controller shown in  FIG.  2    in a second embodiment. 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
     Hereinafter, embodiments of the present invention will be described with reference to the diagrams. However, the technical scope of the present invention is not limited to the following embodiments and illustrated examples. 
     First Embodiment 
     (Configuration of Radiographic Imaging System  100 ) 
     First, a schematic configuration of a radiographic imaging system  100  according to a first embodiment will be described. 
       FIG.  1    is a diagram showing an example of the overall configuration of the radiographic imaging system  100 . 
     As shown in  FIG.  1   , the radiographic imaging system  100  includes a radiation generator  1 , a radiation detector  2 , and a radiographic image processing apparatus  3 . The radiographic image processing apparatus  3  is communicably connected to the radiation generator  1  and the radiation detector  2 . The radiographic image processing apparatus  3  can communicate with a hospital information system (HIS), a radiology information system (RIS), a picture archiving and communication system (PACS), a dynamic analysis device, and the like, all of which are not shown, through a communication network installed in the hospital. 
     Although not shown, the radiation generator  1  includes a generator that applies a voltage according to preset irradiation conditions based on the operation of an irradiation instruction switch, a radiation source that generates a dose of radiation (for example, X-rays) corresponding to the applied voltage when a voltage is applied from the generator, and the like. The radiation generator  1  generates radiation in a manner corresponding to a radiographic image to be captured. 
     The radiation generator  1  may be installed in the imaging room or may be configured as a medical vehicle that is movable together with the radiographic image processing apparatus  3  and the like. 
     Although not shown, the radiation detector  2  includes a substrate in which pixels each including a radiation detection element for generating an electric charge according to a dose upon receiving radiation and a switch element for storing and emitting an electric charge are arranged in a two-dimensional manner (in a matrix), a scanning circuit that switches ON/OFF of each switch element, a read circuit that reads the amount of electric charges emitted from each pixel as a signal value, a controller that generates a radiographic image from a plurality of signal values read by the read circuit, an output unit that outputs data of the generated radiographic image to the outside, and the like. 
     The radiation detector  2  may have a built-in scintillator or the like, so that the emitted radiation is converted into light having another wavelength, such as visible light, by the scintillator and an electric charge corresponding to the converted light is generated (so-called indirect type) or may directly generate an electric charge from radiation without a scintillator or the like (so-called direct type). 
     The radiation detector  2  may be of a dedicated machine type integrated with an imaging table or may be of a portable type (cassette type). 
     The radiation detector  2  generates a radiographic image corresponding to the emitted radiation in synchronization with the timing at which the radiation is emitted from the radiation generator  1  and transmits the generated radiographic image to the radiographic image processing apparatus  3 . 
     That is, the radiation generator  1  and the radiation detector  2  form a radiographic imaging apparatus. The radiation source of the radiation generator  1  and the radiation detector  2  are arranged so as to face each other with a gap therebetween and the radiation from the radiation source is emitted to a subject S placed between the radiation source of the radiation generator  1  and the radiation detector  2 , so that it is possible to take a radiographic image of the subject S and acquire a radiographic image. The radiographic imaging may be still image capturing or may be dynamic imaging in which the movement of the subject S is imaged. 
     Here, the still image capturing refers to acquiring one radiographic image of the subject S in response to one imaging operation (pressing of an irradiation instruction switch). The dynamic imaging refers to acquiring a plurality of radiographic images of the subject S by repeatedly emitting radiation, such as X-rays, to the subject S in a pulsed manner at predetermined time intervals (pulse irradiation) in response to one imaging operation or by continuously emitting radiation, such as X-rays, to the subject S at a low dose rate without interruption in response to one imaging operation (continuous irradiation). A series of radiographic images obtained by dynamic imaging are called a dynamic image. Each of the plurality of radiographic images forming the dynamic image is called a frame image. 
     The dynamic imaging includes moving image capturing but does not include capturing a still image while displaying a moving image. The dynamic image includes a moving image but does not include an image obtained by capturing a still image while displaying a moving image. 
     The radiographic image processing apparatus  3  has a function as a console for controlling radiographic imaging. The radiographic image processing apparatus  3  has a function of performing abnormality determination processing for determining whether or not there is an abnormality in the radiographic image transmitted from the radiation detector  2  and providing notification when it is determined that there is an abnormality. 
     In the present application, an image with an abnormality refers to an image that is not captured in a normal state and has an abnormal state that cannot be used for analysis or diagnosis. 
       FIG.  2    is a block diagram showing the functional configuration of the radiographic image processing apparatus  3 . 
     As shown in  FIG.  2   , the radiographic image processing apparatus  3  includes a controller  31  (hardware processor), a communicator  32 , a storage  33 , a display  34 , an operation interface  35 , a sound outputter  36 , and a light outputter  37 , all of which are connected to each other by a bus  38 . 
     The radiographic image processing apparatus  3  may not include the display  34  or the operation interface  35 , and a display device (tablet terminal or the like) including a display, or an operation interface may be connected to the radiographic image processing apparatus  3 . 
     The controller  31  includes a central processing unit (CPU), a random access memory (RAM), and the like. 
     The CPU of the controller  31  centrally controls the operation of each unit of the radiographic image processing apparatus  3  by reading various programs stored in the storage  33 , loading the programs to the RAM, and performing various processes according to the loaded programs. The controller  31  functions as an abnormality determiner and a thinning-out means of the present invention by performing an abnormality determination control process (abnormality determination control process A described later). 
     The communicator  32  is a communication module or the like. 
     The communicator  32  transmits and receives various signals or various kinds of data to and from the radiation generator  1 , the radiation detector  2 , and other external devices or systems (HIS, RIS, PACS, dynamic analysis device, and the like) connected through a communication network (a local area network (LAN), a wide area network (WAN), the Internet, and the like). 
     The storage  33  is a nonvolatile semiconductor memory, a hard disk, or the like, and stores various programs executed by the controller  31 , parameters necessary for executing the programs, and the like. 
     The storage  33  also stores order information regarding examinations (each imaging included in the examinations) transmitted from the HIS, the RIS, and the like. The order information includes examination ID, examination date, patient information, clinical department (requesting clinical department), disease name, and information regarding each imaging included in the examination (imaging part and imaging direction (chest dynamic PA, abdomen dynamic PA, and the like), body position, type of analysis (ventilation, blood flow, and the like), and breathing protocol (breath-hold, quiet breathing, deep breathing, and the like)). 
     The storage  33  stores an imaging part and an imaging direction and imaging conditions (for example, irradiation conditions (tube current, tube voltage, irradiation time, mAs value, frame rate, and the like), reading conditions (pixel size, frame rate, and the like)) in association with each other. 
     The storage  33  stores an abnormality determination DB (Data Base)  331 . As shown in  FIG.  3   , the abnormality determination DB  331  stores information (for example, respiratory medicine, chest, ventilation, . . . ) of at least one item (for example, clinical department, imaging part, analysis type, . . . ) included in the order information, the type of at least one abnormality determination algorithm used for abnormality determination of a dynamic image captured based on order information including the information, and information of frame images used at the time of abnormality determination (for example, thinning out to ½, thinning out to ¼, and frame numbers  100  to  200 ). The content of the abnormality determination DB  331  can be changed by the user according to the operation through the operation interface  35 , for example. 
     The storage  33  may be able to store a radiographic image. 
     The display  34  is a liquid crystal display (LCD), a cathode ray tube (CRT), or the like. 
     The display  34  displays an examination list screen, an examination screen  341  (see, for example,  FIGS.  4  and  11   ), notification information, and the like, based on control signals input from the controller  31 . The display  34  functions as a notifier of the present invention in cooperation with the controller  31 . 
     The operation interface  35  is an operation means configured to be operable by the user such as a keyboard including cursor keys, number input keys, and various function keys, a pointing device such as a mouse, a touch panel laminated on the surface of the display device, and the like. The operation interface  35  outputs a control signal corresponding to the operation performed by the user to the controller  31 . 
     The sound outputter  36  includes a speaker or the like, and outputs a sound and/or voice according to the control of the controller  31 . The sound outputter  36  functions as a notifier of the present invention in cooperation with the controller  31 . 
     The light outputter  37  is a light emitting diode (LED) or the like, and outputs light according to the control of the controller  31 . The light outputter  37  functions as a notifier of the present invention in cooperation with the controller  31 . 
     (Operation of Radiographic Image Processing Apparatus  3 ) 
     Next, the operation of the radiographic image processing apparatus  3  will be described. 
     For example, when order information is received from the HIS, the RIS, and the like (not shown) through the communicator  32 , the controller  31  stores the received order information in the storage  33  and displays the received order information on the examination list screen (not shown) of the display  34 . When order information regarding an examination to be performed is selected from the examination list screen, the controller  31  causes the display  34  to display the examination screen  341 . 
       FIG.  4    is a diagram showing an example of the examination screen  341 . As shown in  FIG.  4   , an imaging conditions button  341   a,  an image display region  341   b,  a patient information display region  341   c,  an examination stop button  341   d,  an examination end button  341   e,  and the like are provided on the examination screen  341 . 
     The imaging conditions button  341   a  is a button corresponding to each imaging included in the order information and is a button for setting imaging conditions (irradiation conditions or reading conditions) corresponding to each imaging in the radiation generator  1  or the radiation detector  2 . In order to identify each imaging included in the order information, for example, the imaging part and imaging direction of each imaging are displayed in the imaging conditions button  341   a.    
     The image display region  341   b  is a region where a radiographic image acquired by radiographic imaging is displayed. 
     The patient information display region  341   c  is a region where the patient information of a patient (subject S) to be examined is displayed. 
     The examination stop button  341   d  is a button for the user (imaging operator) to give an instruction to stop the examination. 
     The examination end button  341   e  is a button for the user to give an instruction to end the examination. 
     The user presses the imaging conditions button  341   a  corresponding to radiographic imaging to be performed next on the examination screen  341  to prepare for imaging. 
     When any of the imaging conditions buttons  341   a  on the examination screen  341  is pressed by the user&#39;s operation through the operation interface  35 , the controller  31  reads imaging conditions corresponding to the imaging part and imaging direction of the pressed imaging conditions button  341   a  from the storage  33  and transmits irradiation conditions, among the read imaging conditions, to the radiation generator  1  through the communicator  32 . The controller  31  transmits reading conditions, among the read imaging conditions, to the radiation detector  2  through the communicator  32 . 
     The radiation generator  1  sets the irradiation conditions received from the radiographic image processing apparatus  3  as irradiation conditions for the next radiographic imaging. The radiation detector  2  sets the reading conditions received from the radiographic image processing apparatus  3  as reading conditions for the next radiographic imaging. 
     The user positions the subject S between the radiation source of the radiation generator  1  and the radiation detector  2  and operates the irradiation instruction switch when preparations for imaging are completed. When the irradiation instruction switch is operated, the radiation generator  1  emits radiation to the subject S under the set irradiation conditions. The radiation detector  2  generates image data (frame images) of a radiographic image by accumulating and reading the emitted radiation in synchronization with the emission of radiation from the radiation generator  1  and transmits the image data to the radiographic image processing apparatus  3 . When the imaging conditions corresponding to the pressed imaging conditions button  341   a  are dynamic imaging, the radiation generator  1  and the radiation detector  2  repeat emission of radiation and generation and transmission of frame images for a predetermined time in synchronization with each other. The radiation detector  2  attaches a frame number indicating the order of imaging to each generated frame image and transmits the generated frame image, which has a frame number attached thereto, to the radiographic image processing apparatus  3 . 
     When a radiographic image from the radiation detector  2  is received through the communicator  32 , the radiographic image processing apparatus  3  performs abnormality determination processing for determining whether or not there is an abnormality in the received radiographic image. When it is determined that there is an abnormality, the radiographic image processing apparatus  3  notifies of the fact, for example, by displaying the fact on the examination screen  341  or by outputting the fact by sound. 
     In the case of a still image, only one image needs to be determined. Therefore, even if the processing performance of the radiographic image processing apparatus  3  is low (spec is low), the influence on the image checking by the user is low. In the case of a dynamic image, however, a plurality of frame images (for example, one dynamic image includes several hundred frames (for example, 300 frames)). For this reason, if the abnormality determination processing is performed on all the frame images, a long processing time is required. As a result, the user cannot easily perform the next work such as image checking. Not all frame images are necessarily required to determine abnormality. For example, when there is a lung field defect, several to several tens of frame images are acquired per second. For this reason, there is a high possibility that frame images with a lung field defect will be depicted in several surrounding frames. When determining an abnormality, in general, not all frame images are required. 
     Therefore, when dynamic imaging is started, the controller  31  of the radiographic image processing apparatus  3  according to the present embodiment starts performing the abnormality determination control process A shown in  FIG.  5   , so that the processing time for abnormality determination processing on the dynamic image can be shortened compared with that in the known methods. 
     Hereinafter, the abnormality determination control process A will be described with reference to  FIG.  5   . The abnormality determination control process A is performed by cooperation between the CPU of the controller  31  and programs stored in the ROM or the storage  33 . 
     In the abnormality determination control process A, the controller  31  first acquires order information regarding the dynamic imaging that has started (step S 1 ) and determines an abnormality determination algorithm corresponding to the acquired order information by referring to the abnormality determination DB  331  (step S 2 ). 
     Although the abnormality determination algorithm is determined based on the order information herein, the user may determine the abnormality determination algorithm according to the operation through the operation interface  35 . 
     Then, the controller  31  sequentially acquires frame images received through the communicator  32  (step S 3 ) and selects some frame images to be used for abnormality determination (step S 4 ). 
     For example, the controller  31  acquires, from the abnormality determination DB  331 , information (the number of thinning-out or a thinning-out range) of frame images to be used for abnormality determination in the abnormality determination algorithm corresponding to the order information determined in step S 2  and selects some frame images to be used for abnormality determination, among the plurality of frame images of the received dynamic image, based on the acquired information. For example, as shown in  FIG.  6   , by thinning out the number of received frame images by a predetermined number at predetermined intervals based on the acquired information or by acquiring some frame images in a predetermined range (that is, a predetermined range of frame numbers) that are continuous in the time direction, among the received frame images, based on the acquired information, frame images to be used for abnormality determination are selected. 
     For example, when the information of frame images to be used for abnormality determination, which is acquired from the abnormality determination DB  331 , is “thinning out to ½”, the controller  31  selects frame images to be used for abnormality determination by performing thinning-out processing in which frame images sequentially received from the radiation detector  2  are acquired every other frame number (frame images that are not acquired are thinned out) to reduce the number of frame images. 
     For example, when the information of frame images to be used for abnormality determination, which is acquired from the abnormality determination DB  331 , is “thinning out to ¼”, the controller  31  selects frame images to be used for abnormality determination by performing thinning-out processing in which frame images sequentially received from the radiation detector  2  are acquired every three frame numbers (frame images that are not acquired are thinned out) to reduce the number of frame images. The number of frame images acquired every N (N is a positive integer) is not limited to one and may be plural. For example, when the information of frame images to be used for abnormality determination acquire from the abnormality determination DB  331  is “frame numbers 100 to 200”, frame images in the range of frame numbers 100 to 200, among the frame images sequentially received from the radiation detector  2 , are selected as frame images to be used for abnormality determination. 
     Frame images to be used at the time of abnormality determination may also be selected by further thinning out frame images whose frame numbers are within a predetermined range. 
     Then, the controller  31  performs abnormality determination processing on the selected frame images by using the abnormality determination algorithm determined in step S 2  (step S 5 ). 
     For example, as an abnormality determination algorithm that can be used by the radiographic image processing apparatus  3  when the imaging part is the chest, at least one of the following abnormality determination algorithms (1) to (9) is included. 
     (1) Frame images of the maximum expiratory position and/or the maximum inspiratory position are acquired from the selected frame images, and it is determined based on the lung field area of each of the acquired frame images whether or not there is an abnormality in the dynamic image. 
     For example, the reference area of the maximum inspiratory position and/or the maximum expiratory position of the general lung field or the areas of the maximum inspiratory position and the maximum expiratory position calculated from the dynamic image captured in the past for each patient (in association with patient information) are stored in the storage  33 . When the difference between the lung field area of the maximum inspiratory position and/or the maximum expiratory position calculated from the selected frame images and the reference area or the previous lung field area of the same patient is equal to or greater than a predetermined threshold value, it is determined that there is an abnormality. When the above difference is less than the threshold value, it is determined that there is no abnormality. 
     For example, when the lung field area of the maximum inspiratory position is smaller than the reference area of the maximum inspiratory position or the lung field area of the previous maximum inspiratory position of the same patient by a predetermined threshold value or more, it is determined that there is an abnormality because adequate breathing is not possible (inhaling is not sufficient). For example, when the lung field area of the maximum expiratory position is larger than the reference area of the maximum expiratory position or the lung field area of the previous maximum expiratory position of the same patient by a predetermined threshold value or more, it is determined that there is an abnormality adequate breathing is not possible (exhaling is not sufficient). 
     The lung field area can be calculated, for example, based on the pixel size and the number of pixels of a lung field region recognized from the selected frame images. Although the method of recognizing the lung field region is not particularly limited, the recognition of the lung field region can be performed by using, for example, image processing such as edge detection, deep learning, and machine learning using teacher data. 
     (2) The amount of change (the amount of change in position) in the diaphragm or ribcage is calculated from the selected frame images, and it is determined based on the calculated amount of change whether or not there is an abnormality in the dynamic image. 
     For example, the diaphragm or ribcage is extracted from each of the selected frame images, and a predetermined position of the extracted diaphragm, such as the coordinate (y-coordinate) of the highest position, or a predetermined position of the extracted ribcage, such as the coordinate (x-coordinate) of the outermost position, is acquired. Then, for example, assuming that the difference between the frame image with the smallest coordinate value and the frame image with the largest coordinate value is the amount of change, it is determined that there is an abnormality in the dynamic image when the amount of change is equal to or less than a predetermined threshold value, and it is determined that there is no abnormality in the dynamic image when the amount of change is larger than the threshold value. 
     As for the diaphragm, for example, the lower edge portion of the recognized lung field region can be extracted as the diaphragm. As for the ribcage, for example, the edge portion of the outer contour of the recognized lung field region can be extracted as the ribcage. 
     The abnormality determination algorithms (1) and (2) described above are for determining that there is an abnormality when it is not possible to perform respiratory movements necessary for diagnosis. Therefore, it is preferable not to apply the abnormality determination algorithms (1) and (2) to patients who have or are suspected of having certain diseases that do not allow adequate breathing. For example, when the order information includes a predetermined disease name, it is preferable that the controller  31  performs control so as not to apply the abnormality determination algorithms (1) and (2). 
     (3) The tilt angle of the subject S is calculated by using the selected frame images, and it is determined based on the calculated tilt angle whether or not there is an abnormality in the dynamic image. 
     For example, as shown in  FIG.  7   , the spine (indicated by a rectangle in  FIG.  7   ) is extracted from one of the selected frame images. If the extraction of the spine is successful, the tilt angle of the extracted spine with respect to the vertical direction (y direction) is calculated. If the tilt angle exceeds a predetermined range (for example, ±10°), it is determined that there is an abnormality. If the tilt angle is within the range, it is determined that there is no abnormality. If the extraction of the spine fails, the extraction of the spine from the next selected frame image is performed. If the extraction of the spine is successful, the tilt angle of the extracted spine with respect to the vertical direction is calculated. If the tilt angle exceeds a predetermined range (for example, ±10°), it is determined that there is an abnormality. If the tilt angle is within the range, it is determined that there is no abnormality. The extraction of the spine can be performed by using, for example, image processing such as edge detection. 
     In the abnormality determination algorithm (3), if the subject S is tilted by a predetermined threshold value or more, an abnormality may occur when performing the dynamic analysis. Therefore, it is determined that there is an abnormality when the tilt angle of the subject S is equal to or greater than the predetermined threshold value. In this example, the presence or absence of abnormality is determined only from one frame image from which the spine has been successfully extracted, but the presence or absence of abnormality may be determined from a plurality of frame images. 
     Displacement of the subject&#39;s posture during imaging affects the dynamic analysis or diagnosis. For this reason, the extraction of the spine from a predetermined frame image, for example, a first frame image, among the selected frame images, may be performed to measure the tilt angle (if the spine cannot be extracted, for example, the tilt angles of frame images with successively smaller frame numbers are measured), and the tilt angle may be set as a reference tilt angle. The tilt angle of the spine in the other selected frame images may be compared with the reference tilt angle, and it may be determined that there is an abnormality when the tilt angle is equal to or greater than a predetermined threshold value. 
     (4) The amount of change in a predetermined structure (for example, diaphragm position or lung field area) or the amount of change in image signal value within a predetermined structure region (for example, within a lung field region) is calculated by using the selected frame images, the calculated amount of change is compared with a threshold value set in advance for the breathing protocol (breathing state (breath-hold, deep breathing, quiet breathing, and the like) to be imaged), and it is determined based on the comparison result whether or not there is an abnormality in the dynamic image (threshold value: breath-hold&lt;quiet breathing&lt;deep breathing). With this algorithm, it is possible to determine that there is an abnormality when breathing motion conforming to the breathing protocol is not performed. 
     (5) The position of the lung apex (indicated by a rectangle in  FIG.  8   ) is specified from the selected frame image. When the amount of change from the position of the lung apex of the frame image (previous image) with the closest frame number is equal to or greater than a predetermined threshold value, it is determined that there is an abnormality in the dynamic image. When the amount of change is less than the predetermined threshold value, it is determined that there is no abnormality. As for the position of the lung apex, for example, the highest position of the lung field region can be specified as the position of the lung apex. Since the lung apex is a location where movement is unlikely to occur, it can be determined that body movement has occurred when there is a positional change equal to or greater than a predetermined threshold value. 
     (6) Processing for detecting foreign matter (gauze or the like) and/or metal artifacts from the selected frame images is performed. When foreign matter and/or metal artifacts are detected, it is determined that there is an abnormality in the dynamic image. When foreign matter and/or metal artifacts are not detected, it is determined that there is no abnormality in the dynamic image. Any known technique may be used to detect foreign matter or metal artifacts. For example, foreign matter can be detected by using deep learning or machine learning using teacher data. Metal artifacts can be detected by, for example, binarization processing or graph cut processing that is advanced region extraction processing. Therefore, it is possible to detect abnormalities due to contamination by foreign matter or metal artifacts. 
     (7) The lung field region and the scapula are recognized from the selected frame images, and it is determined whether or not there is an abnormality in the dynamic image based on the positional relationship between the recognized scapula and lung field region (whether or not the recognized scapula and lung field region overlap each other). This is because, in the dynamic analysis, accurate analysis cannot be performed if the scapula covers the lung field region. Any known method may be used to detect the scapula. For example, the scapula can be detected by using deep learning or machine learning using teacher data. 
     (8) It is determined from the selected frame images whether or not a lung field defect has occurred. When it is determined that a lung field defect has occurred, it is determined that there is an abnormality in the dynamic image. When it is determined that a lung field defect has not occurred, it is determined that there is no abnormality. For example, if the lung field region does not fall within the irradiation field region, it is determined that a lung field defect has occurred. 
     (9) It is determined from the selected frame images whether there is an excess or deficiency of radiation dose. When it is determined that there is an excess or deficiency of radiation dose, it is determined that there is an abnormality in the dynamic image. When it is determined that there is no excess or deficiency of radiation dose, it is determined that there is no abnormality in the dynamic image. Although not particularly limited, whether or not there is an excess or deficiency of radiation dose can be determined, for example, by comparing the average value or median value of the image signal values within a region of interest (for example, the lung field in the case of the chest), which is set in advance for each imaging part, with a predetermined threshold value. 
     (10) It is determined from the selected frame images whether or not there is body movement of the subject. When it is determined that there is body movement of the subject, it is determined that there is an abnormality in the dynamic image. When it is determined that there is no body movement of the subject, it is determined that there is no abnormality in the dynamic image. The method for determining whether or not there is body movement of the subject is not particularly limited, but, for example, a method of performing determination based on the above-described amount of change in the position of the lung apex can be used. 
     When performing abnormality determination processing, as shown in  FIG.  9   , the controller  31  may set a region of a part of the selected frame image as a determination target region and perform the abnormality determination processing by using the image of the determination target region. The determination target region may be determined in advance according to the type of abnormality determination algorithm or may be designated by the user&#39;s operation through the operation interface  35 . Therefore, it is possible to further shorten the time required for the abnormality determination processing. The determination target region may be a plurality of regions. 
     Alternatively, as shown in  FIG.  10   , the controller  31  may reduce each of the selected frame images by trimming before performing abnormality determination and perform the abnormality determination processing by using the reduced image. For example, trimming is performed so that only the determination target region described above is left. Therefore, it is possible to further shorten the time required for the abnormality determination processing. 
     The controller  31  may perform pre-processing, such as gradation processing or frequency processing, on the selected frame images before performing the abnormality determination processing. 
     Then, the controller  31  determines whether or not it has been determined by the abnormality determination processing that there is an abnormality in the dynamic image (step S 6 ). 
     When it is determined that there is no abnormality in the dynamic image (step S 6 ; NO), the controller  31  normally displays the dynamic image on the display  34  (step S 7 ), and ends the abnormality determination control process A. For example, the dynamic image is displayed in the image display region  341   b  of the examination screen  341 . 
     When it is determined that there is an abnormality in the dynamic image (step S 6 ; YES), the controller  31  displays (informs) an alert indicating that there is an abnormality in the dynamic image on the display  34  (step S 8 ), and ends the abnormality determination control process A. For the alert, a sound may be output from the sound outputter  36 , or light may be output from the light outputter  37 . 
       FIG.  11    is a diagram showing an example of the examination screen  341  on which an alert is displayed. 
     For example, when it is determined that there is an abnormality, the controller  31  displays a message  342   a  indicating that an abnormality has been detected, as an alert to notify of the fact, on the examination screen  341 . The alert may be output from the sound outputter  36  or the light outputter  37 . Alternatively, an icon indicating that an abnormality has been detected may be displayed. Therefore, the user can easily recognize that there is an abnormality in the dynamic image obtained by dynamic imaging. A frame image determined to have an abnormality may be displayed in the image display region  341   b  of the examination screen  341 . Alternatively, the frame number  342   b  of a frame image determined to have an abnormality may be displayed on the examination screen  341 . Alternatively, the vicinity of the position of the image determined to have an abnormality in a seek bar (playback bar)  342   c  displayed at the bottom of the image display region  341   b  may be highlighted by adding color. 
     When it is determined that there is an abnormality in the dynamic image, the controller  31  may display a partial rejection button  342   d  and a total rejection button  342   e  on the examination screen  341 . 
     When the partial rejection button  342   d  is pressed, the controller  31  automatically rejects only the frame image in which an abnormality is detected (for example, deletes only the frame image in which an abnormality is detected from the storage  33 ). Alternatively, when the partial rejection button  342   d  is pressed, a pop-up screen for the user to specify the range to be rejected may be displayed, and the range specified by the user may be rejected. A dynamic image including other frame images may be stored in the storage  33  or output to a predetermined output destination, such as a PACS or a dynamic analysis device, through the communicator  32  in a state in which the dynamic image is attached to patient information or examination information (information of predetermined items in order information). 
     When the total rejection button  342   e  is pressed, the controller  31  dynamically rejects all frame images of the dynamic image (for example, deletes all frame images of the dynamic image from the storage  33 ). In this case, re-imaging is possible. For example, when the imaging conditions button  341   a  corresponding to the performed imaging is pressed, the imaging conditions are set again in the radiation generator  1  and the radiation detector  2 , and imaging becomes possible in response to the pressing of the irradiation instruction button. 
     A rejected image may be output to a predetermined output destination (for example, a management device for managing rejected images) together with a flag indicating a rejected image. 
     When it is determined that some of the selected frame images have abnormalities, the controller  31  may immediately (in real time) perform the alert display of step S 8  or may perform the alert display of step S 8  after the end of the abnormality determination processing on all of the selected frame images. For example, based on the difference between the value used for determining whether or not there is an abnormality and the threshold value, it may be determined whether to display an alert in real time or to collectively issue an alert after the end of the abnormality determination processing. When it is determined that some of the selected frame images have abnormalities, the alert display of step S 8  is immediately performed, so that the user can immediately (in real time) recognize that there is an abnormality in the captured image. 
     After the end of the abnormality determination processing, as shown in  FIG.  12   , the controller  31  may cause the display  34  to display a selection button  341   j  for giving an instruction to perform abnormality determination processing based on an abnormality determination algorithm other than the abnormality determination algorithm used in step S 5 . Then, the controller  31  may additionally perform abnormality determination processing based on another abnormality determination algorithm, which is selected in response to the pressing of the selection button  341   j  by the operation interface  35 , on the dynamic image. Alternatively, abnormality determination processing based on another abnormality determination algorithm, which is set in advance, other than the abnormality determination algorithm used in step S 5  may be automatically performed. As a result, real-time performance can be emphasized, and the time-consuming abnormality determination processing can be postponed. 
     In this manner, since the controller  31  of the radiographic image processing apparatus  3  performs abnormality determination of a dynamic image captured by using some of the plurality of frame images forming the dynamic image, the abnormality determination can be performed with a low load. Therefore, it is possible to shorten the processing time required for determining an abnormality in the dynamic image. As a result, even if the radiographic image processing apparatus  3  is a low-spec apparatus with low processing performance, the processing time required for the abnormality determination processing can be reduced and accordingly, the user can quickly check the image or perform re-imaging. 
     Second Embodiment 
     Next, a second embodiment of the present invention will be described. 
     In the second embodiment, when the reception of frame images of a dynamic image from the radiation detector  2  through the communicator  32  starts, the controller  31  of the radiographic image processing apparatus  3  thins out the frame images for image checking (for example, thins out to 2 fps) in parallel with imaging, and performs simpler image processing than for the main images used for diagnosis, and sequentially displays the frame images obtained by thinning-out on the display  34  (for example, an image display region  241   b  of an examination screen  241 ). This frame image subjected to simple image processing for image checking is referred to as a live view image. In the second embodiment, a case will be described in which abnormality determination processing is performed by using the live view image. 
     Since the configurations of the radiographic imaging system  100  and each device in the second embodiment are the same as those described in the first embodiment, the description is cited, and the operation of the radiographic image processing apparatus  3  according to the second embodiment will be described. 
       FIG.  13    is a flowchart showing the flow of an abnormality determination control process (referred to as an abnormality determination control process B) in the second embodiment. The abnormality determination control process B is performed by cooperation between the CPU of the controller  31  and programs stored in the ROM or the storage  33 . 
     In the abnormality determination control process B, the controller  31  first acquires order information regarding the dynamic imaging that has started (step S 21 ) and determines an abnormality determination algorithm corresponding to the acquired order information by referring to the abnormality determination DB  331  (step S 22 ). 
     Since the processes of steps S 21  and S 22  are the same as those of steps S 1  and S 2  in  FIG.  5   , the description is cited. 
     Then, the controller  31  acquires live view images (step S 23 ). 
     As described above, the controller  31  generates live view images in parallel with imaging. The controller  31  acquires the generated live view images for abnormality determination. As described above, in the live view images, the number of frame images has already been reduced. It is also possible to further thin out the live view images. 
     Then, the controller  31  starts abnormality determination processing on the live view images by using the abnormality determination algorithm determined in step S 22  (step S 24 ). 
     Since the process of step S 24  is the same as that described in step S 5  of  FIG.  5    except that the frame image used in the process is a live view image, the description is cited. 
     Then, the controller  31  determines whether or not a specified time set in advance has passed from the start of the abnormality determination processing (step S 25 ). 
     When it is determined that the specified time has not passed (step S 25 ; NO), the controller  31  determines whether or not the abnormality determination processing on the last live view image has ended (step S 26 ). 
     When it is determined that the abnormality determination processing on the last live view image has not ended (step S 26 ; NO), the controller  31  returns to step S 25 . 
     When it is determined that the abnormality determination processing on the last live view image has ended (step S 26 ; YES), the controller  31  determines whether or not it has been determined by the abnormality determination processing that there is an abnormality in the dynamic image (step S 27 ). 
     When it is determined that there is no abnormality in the dynamic image (step S 27 ; NO), the controller  31  continues the normal display of the live view image on the display  34  (step S 28 ), and ends the abnormality determination control process B. For example, the display of the live view image in the image display region  341   b  of the examination screen  341 , which has already been performed, is continued. 
     When it is determined that there is an abnormality in the live view image (step S 27 ; YES), the controller  31  displays an alert indicating that there is an abnormality in the dynamic image on the display  34  together with the live view image (step S 29 ), and ends the abnormality determination control process B. Since the alert display is the same as that described in the first embodiment, the description is cited. 
     Also in the second embodiment, as shown in  FIG.  11   , a partial rejection button  342   d  and a total rejection button  342   e  may be displayed on the examination screen  341 , and a part or entirety of the dynamic image may be rejected in response to the pressing of the partial rejection button  342   d  or the total rejection button  342   e  as in the first embodiment. As shown in  FIG.  12   , the selection button  341   j  may be displayed on the examination screen  341 , and an abnormality determination based on an abnormality determination algorithm different from the executed abnormality determination processing, which is selected in response to the pressing of the selection button  341   j,  may be performed. A resume button or the like may be displayed so that the stopped abnormality determination processing can be resumed according to the user&#39;s operation when the abnormality determination processing is stopped on the way. 
     On the other hand, when it is determined that a specified time set in advance has passed from the start of the abnormality determination processing in step S 25  (step S 25 ; YES), the controller  31  stops the abnormality determination processing (step S 30 ), and ends the abnormality determination control process B. 
     As described above, in the second embodiment, the abnormality determination processing is performed by using the live view images generated for image checking, which are obtained by thinning out the frame images of the dynamic image and performing simple processing. This can contribute to real-time abnormality determination. When the processing time for the abnormality determination processing exceeds the specified time, the abnormality determination processing is stopped. Therefore, if the abnormality determination processing takes too much time, the determination can be stopped on the way to allow the user&#39;s operation. 
     As described above, according to the radiographic image processing apparatus  3 , the controller  31  acquires a dynamic image including a plurality of frame images captured by the radiographic imaging apparatus and determines whether or not there is an abnormality in the dynamic image by using some of the frame images of the acquired dynamic image. For example, thinning-out processing for reducing the number of frame images of the dynamic image is performed, and it is determined whether or not there is an abnormality in the dynamic image by using the frame images after the thinning-out processing. Alternatively, it is determined whether or not there is an abnormality in the dynamic image by using some frame images in a predetermined range that are continuous in the time direction of the dynamic image. 
     Therefore, since the abnormality determination can be performed with a low load, it is possible to shorten the processing time required for determining an abnormality in the dynamic image. As a result, even if the radiographic image processing apparatus  3  is a low-spec apparatus with low processing performance, the processing time required for the abnormality determination processing can be reduced and accordingly, the user can quickly check the image or perform re-imaging. 
     For example, the controller  31  determines the number of frame images to be thinned out based on the order information regarding the capturing of the dynamic image. Therefore, it is possible to determine the optimal number of frame images according to, for example, an imaging part, a clinical department, and the type of analysis included in the order information. 
     For example, the controller  31  determines whether or not there is an abnormality in the dynamic image by using a live view image generated for checking the dynamic image captured by the radiographic imaging apparatus. Therefore, it is possible to contribute to real-time abnormality determination. 
     For example, the controller  31  stops the determination processing when the processing time for the process of determining whether or not there is an abnormality in the dynamic image exceeds a specified time. Therefore, if the abnormality determination processing takes too much time, the determination can be stopped on the way to allow the user&#39;s operation. 
     For example, after determining whether or not there is an abnormality in the dynamic image by using one of a plurality of types of abnormality determination algorithms, additional abnormality determination can be performed by using another abnormality determination algorithm. Therefore, real-time performance can be emphasized, and the time-consuming abnormality determination processing can be postponed. 
     Since the controller  31  determines whether or not there is an abnormality in the dynamic image by using a partial determination target region of each of some of the frame images of the dynamic image, it is possible to further shorten the time required for the abnormality determination processing. 
     The controller  31  reduces each of some of the frame images of the dynamic image by trimming and determines whether or not there is an abnormality in the dynamic image by using the reduced images. Therefore, it is possible to further shorten the time required for the abnormality determination processing. 
     The radiographic image processing apparatus  3  includes the abnormality determination DB  331  that stores information of at least one item included in the order information regarding imaging and at least one of a plurality of types of abnormality determination algorithms so as to be associated with each other. The controller  31  determines an abnormality determination algorithm to be applied to the dynamic image based on the order information regarding the capturing of the dynamic image and the abnormality determination DB  331  and determines whether or not there is an abnormality in the dynamic image by using the determined abnormality determination algorithm. Therefore, it is possible to execute the abnormality determination algorithm according to, for example, an imaging part, a clinical department, and the type of analysis. 
     When it is determined that there is an abnormality in the dynamic image, the controller  31  outputs a message or an icon for notifying of the fact. Therefore, it is possible to make the user recognize that there is an abnormality in the dynamic image. 
     There is provided an operation means for the user to give an instruction to reject some or all of the frame images of the dynamic image when the controller  31  determines that there is an abnormality in the dynamic image. Therefore, the user can give an instruction to reject some or all of the frame images of the dynamic image. 
     The description in each of the above embodiments is a preferable example of the radiographic image processing apparatus according to the present invention, and the present invention is not limited thereto. 
     In the above description, an example is disclosed in which a hard disk, a semiconductor non-volatile memory, or the like is used as a computer-readable medium according to the present invention, but the present invention is not limited to this example. As other computer-readable media, a portable recording medium, such as a CD-ROM, can be applied. A carrier wave is also applied as a medium for providing data of a radiographic image display program according to the present invention through a communication line. 
     The detailed configuration and detailed operation of each device included in the radiographic image processing apparatus can also be appropriately changed without departing from the spirit of the invention. 
     Although embodiments of the present invention have been described and illustrated in detail, the disclosed embodiments are made for purposes of illustration and example only and not limitation. The scope of the present invention should be interpreted by terms of the appended claims.