Patent Publication Number: US-2023142775-A1

Title: Information processing apparatus, information processing method, and storage medium

Description:
BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present invention relates to an information processing apparatus, an information processing method, and a storage medium. 
     Description of the Related Art 
     There is known CADe (Computer-Aided Detection) in which a computer analyzes a medical image and detects a candidate of a lesion that is an abnormality associated with a disease. In addition, along with the development of AI (Artificial Intelligence) technology, the types of lesions to be covered are increasing. 
     Japanese Patent Laid-Open No.7-37056 discloses a diagnostic supporting apparatus that divides a medical image into small regions, calculates a feature amount on a small region basis, and displays an image with a display density or display color changing depending on the feature amount superimposed on the medical image. Also, Japanese Patent Laid-Open No. 2005-65944 discloses a diagnostic supporting apparatus that detects an abnormal shadow candidate based on a detection condition, investigates abnormal shadow candidate detection performance for each abnormal shadow detection condition, and displays the investigated detection performance. 
     However, in a case where a detection result is not displayed by either of the methods of Japanese Patent Laid-Open Nos. 7-37056 and 2005-65944, it is difficult to discriminate whether a lesion cannot be detected even in a case where lesion detection processing is performed or whether no lesion is detected because lesion detection processing is not executed. 
     The present invention has been made in consideration of the above-described problem, and provides an information processing technique capable of presenting an operating state of lesion detection processing. 
     SUMMARY OF THE INVENTION 
     According to one aspect of the present invention, there is provided an information processing apparatus comprising: an operating state obtaining unit configured to obtain information representing an operating state of detection processing by a lesion detection unit configured to detect a lesion from medical image data; and an information presentation unit configured to, in a case where the information representing the operating state is information representing a state in which the detection processing cannot be executed, present information corresponding to a reason why the detection processing cannot be executed. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram showing the configuration of an information processing system according to the first to third embodiments; 
         FIG.  2    is a block diagram showing the hardware configuration of an information processing apparatus according to the first to third embodiments; 
         FIG.  3    is a block diagram showing the functional configuration of the information processing apparatus according to the first embodiment; 
         FIG.  4    is a view showing an example of the user interface screen of the information processing apparatus according to the first embodiment, 
         FIG.  5    is a flowchart showing processing of the information processing apparatus according to the first embodiment; 
         FIG.  6    is a block diagram showing the functional configuration of the information processing apparatus according to the second embodiment; 
         FIG.  7    is a view showing an example of the user interface screen of the information processing apparatus according to the second embodiment; 
         FIG.  8    is a flowchart showing processing of the information processing apparatus according to the second embodiment; 
         FIG.  9 A  is a view showing an example of the user interface screen of the information processing apparatus according to the third embodiment: 
         FIG.  9 B  is a view showing an example of the user interface screen of the information processing apparatus according to the third embodiment; 
         FIGS.  10 A and  10 B  are flowcharts showing processing of the information processing apparatus according to the third embodiment; and 
         FIG.  11    is a block diagram showing the functional configuration of the information processing apparatus according to the third embodiment. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Hereinafter, embodiments will be described in detail with reference to the attached drawings. Note, the following embodiments are not intended to limit the scope of the claimed invention. Multiple features are described in the embodiments, but limitation is not made to an invention that requires all such features, and multiple such features may be combined as appropriate. Furthermore, in the attached drawings, the same reference numerals are given to the same or similar configurations, and redundant description thereof is omitted. 
     First Embodiment 
     In the first embodiment, an information processing apparatus that displays a medical image such as an X-ray CT (Computed Tomography) image or an MRI (Magnetic Resonance Imaging) image will be described. 
     For example, when a plurality of CADe operate and detect lesion candidates (a “lesion candidate” will be referred to as a “lesion” hereinafter), the information processing apparatus according to this embodiment presents the detection result to a user. The information processing apparatus also decides the type of an associated lesion associated with at least one lesion from the detection result (from a plurality of lesions detected by the plurality of CADe), and presents the result of CADe corresponding to the type of the associated lesion. CADe can cope with a pulmonary nodule, chest wall mass, peritoneal mass, hepatic mass, pancreatic mass, renal mass, colon mass, reticular shadow, honeycomb lung, bronchiectasis, pleuritis, pleural effusion, tenosynovitis, bone erosion, osteitis, pancreatic hypertrophy, pancreatic necrosis, and the like. 
     Configuration of Information Processing System 
       FIG.  1    is a block diagram showing the configuration of an information processing system  10  including the information processing apparatus according to this embodiment. Referring to  FIG.  1   , the information processing system  10  includes a case database (to be referred to as a case DB hereinafter)  102 . an information processing apparatus  101 , and a LAN (Local Area Network)  103  (network). 
     The case DB  102  stores medical image data captured by an apparatus for capturing a medical image, such as a CT apparatus. The case DB  102  also has a database function of providing the medical image data to the information processing apparatus  101  via the LAN  103 . More specifically, the case DB  102  according to this embodiment is a known PACS (Picture Archiving and Communication Systems). 
     Hardware Configuration 
       FIG.  2    is a block diagram showing the hardware configuration of the information processing apparatus  101  according to this embodiment. Referring to  FIG.  2   , the information processing apparatus  101  includes a storage medium  201 , a ROM (Read Only Memory)  202 , a CPU (Central Processing Unit)  203 , and a RAM (Random Access Memory)  204 . The information processing apparatus  101  also includes a LAN interface  205 , an input interface  208 , a display interface  206 , and an internal bus  211 . 
     The storage medium  201  is a storage medium such as an HDD (Hard Disk Drive) that stores an OS (Operating System), processing programs configured to perform various kinds of processing according to this embodiment, and various kinds of information. The ROM  202  stores a program configured to initialize hardware and activate the OS, such as a BIOS (Basic Input Output System). The CPU  203  performs arithmetic processing when executing the BIOS, OS, and processing programs. The RAM  204  temporarily stores information when the CPU  203  executes a program. The LAN interface  205  is an interface supporting a standard such as IEEE (Institute of Electrical and Electronics Engineers) 802.3ab and configured to perform communication via the LAN  103 . A display  207  (display unit) displays a user interface screen, and the display interface  206  converts screen information to be displayed on the display  207  into a signal and outputs it to the display  207 . A keyboard  209  performs key input, a mouse  210  designates a coordinate position on a screen and inputs a button operation, and the input interface  208  receives signals from the keyboard  209  and the mouse  210 . The internal bus  211  transfers signals when performing communication between the blocks. 
     Functional Configuration 
       FIG.  3    is a block diagram showing the functional configuration of the information processing apparatus  101  according to this embodiment. Referring to  FIG.  3   , the information processing apparatus  101  includes an image obtaining unit  311 , a lesion detection unit  312 , a detection result obtaining unit  313 , a detected lesion designation unit  314 , an associated lesion decision unit  315 , an associated lesion detection obtaining unit  316 , an operating state obtaining unit  317 , and an information presentation unit  318 . These functional configurations are implemented by reading out a predetermined computer program stored in the storage medium  201  to the RAM  204  and executing arithmetic processing by the CPU  203 . 
     In  FIG.  3   , the case DB  102  stores medical image data  321 - i  (i = 1, 2, 3,...), and provides the medical image data  321 - i  (i = 1, 2, 3....) to the information processing apparatus  101  via the LAN  103 . The medical image data  321 - i  (i = 1, 2, 3,...) are, for example. DICOM (Digital Imaging and Communications in Medicine) files. 
     Image Obtaining Unit  311   
     The image obtaining unit  311  obtains the medical image data  321 - i  (i = 1, 2, 3,...) as an inspection target from the case DB  102  via the LAN interface  205  and the LAN  103 . In this embodiment, obtaining of the medical image data  321 - i  (i = 1, 2, 3,...) complies with DICOM. 
     Lesion Detection Unit  312   
     The lesion detection unit  312  functions as a plurality of CADe and detects a lesion from the obtained medical image data  321 - i  (i = 1, 2, 3,...). To detect a lesion, a detector that has learned a CNN (Convolutional Neural Network) is used. For the learning of the detector, a set of medical image data and data representing a lesion region in the medical image data is used as supervisors data. The medical image data of the supervisory data is input to the CNN, and the parameters of the CNN are adjusted such that the error between the output value of the CNN and the data representing a lesion region becomes small. The lesion detection unit  312  may be configured to detect one lesion by one CNN or detect a plurality of lesions by one CNN 
     Detection Result Obtaining Unit  313   
     The detection result obtaining unit  313  obtains the detection results of a plurality of lesions by the lesion detection unit  312 . The detection results include information representing the type of each detected lesion and information capable of specifying the position of each lesion in the medical image data  321 - i  (i = 1, 2, 3....). The information representing the type of a lesion is, for example, an ID (identification information) uniquely assigned to each lesion type of the plurality of detected lesions. The information capable of specifying the position of a lesion in the medical image data takes a form of, for example, coordinate information representing the position of a lesion or a mask image capable of displaying the position of a lesion superimposed on the medical image data. The form of the information capable of specifying the position of a lesion may change for each lesion type. 
     Detected Lesion Designation Unit  314   
     The detected lesion designation unit  314  detects, based on a user operation, an operation of designating at least one lesion (the detection result of a lesion) from the plurality of lesions (the detection results of lesions) obtained by the detection result obtaining unit  313 . The user can designate at least one lesion from the detection results of the plurality of lesions by operating the mouse  210  or the keyboard  209 . The detection results of the plurality of lesions obtained by the detection result obtaining unit  313  are displayed in a list on a user interface screen  400  (for example,  402  in  FIG.  4   ). The user can change the highlight position of the detection result in a lesion detection result display region  402  using a left click of the mouse  210  or the direction keys or the tab key of the keyboard  209  and designate a lesion (the detection result of a lesion) by operating the enter key or the space key. Based on the operation of the user, the detected lesion designation unit  314  accepts the designation of at least one lesion from the detection results of the plurality of lesions. Note that without using the operation of the user, at least one lesion can be designated from the plurality of lesions (the detection results of lesions) obtained by the detection result obtaining unit  313 . For example, in a case where a plurality of lesions are obtained by the detection result obtaining unit  313 , the detected lesion designation unit  314  designates a lesion with the largest region or a lesion with the highest severity level. 
     Associated Lesion Decision Unit  315   
     The associated lesion decision unit  315  decides the type of a lesion (associated lesion) associated with the lesion designated by the detected lesion designation unit  314 . The associated lesion decision unit  315  decides the type of an associated lesion associated with a detected lesion. As associated lesion type decision processing, for example, the associated lesion decision unit  315  may hold the relationship between lesion types and associated lesion types as information in a table format and decide an associated lesion type based on the table. In a case where a plurality of lesions are designated, the associated lesion decision unit  315  may calculate a logical sum (OR) or a logical product (AND) for each associated lesion type obtained from the table for each designated lesion type and obtain the type of the associated lesion. Which one of OR and AND is to be used may be designated as setting information in advance, selected by the user as needed, or selected in accordance with the combination of designated lesions. Also, the associated lesion decision unit  315  may hold the combination of a plurality of lesion types and an associated lesion type corresponding to that as information in a table format and decide an associated lesion type using the information in the table format. Alternatively, the associated lesion decision unit  315  may decide an associated lesion type from the combination of a plurality of lesion types based on a rule, such as an if-then rule, for associating the combination of lesion types and an associated lesion type. 
     The table or the rule used to decide an associated lesion type is created based on, for example, medical knowledge. The medical knowledge includes, for example, the relationship between a primary lesion and a metastatic lesion, the relationship of complications, a relationship concerning evaluation of a risk of aggravation, and the like. As for the relationship between a primary lesion and a metastatic lesion, for example, associated lesions of a pulmonary nodule suspected of being a primary lung cancer are masses in a chest wall, peritoneum, liver, pancreas, and the like, which are considered as the metastasis destinations of the primary lung cancer. In addition, for a pulmonary nodule suspected of being a metastatic lung cancer, masses in a colon, kidney, mammary gland, and the like, which are considered as primary lesions, are associated lesions. Also, a reticular shadow in a lung may be a complication of rheumatoid arthritis, and to discriminate it, tenosynovitis, bone erosion, osteitis, and the like are defined as associated lesions. In a case of pancreatitis, to evaluate a risk of aggravation, pancreatic hypertrophy, pancreatic necrosis, and the like are defined as associated lesions. 
     Associated Lesion Detection Obtaining Unit  316   
     The associated lesion detection obtaining unit  316  obtains the detection result of the lesion detection unit  312  for the associated lesion type decided by the associated lesion decision unit  315 . That is, the associated lesion detection obtaining unit  316  obtains the detection result of the associated lesion decided by the associated lesion decision unit  315  from the detection results of the plurality of lesions by the lesion detection unit  312 . 
     Operating State Obtaining Unit  317   
     The operating state obtaining unit  317  obtains, from the lesion detection unit  312 , information (to be also referred to as operating information hereinafter) representing the operating state of detection processing by the lesion detection unit  312  that detects a lesion from medical image data. Also, the operating state obtaining unit  317  obtains information representing the operating state of detection processing by the lesion detection unit  312  that detects an associated lesion in accordance with an associated lesion type. Note that the operating state of detection processing can also be rephrased as the performing state or execution state of detection processing. 
     The information representing the operating state according to the first embodiment includes information representing, for each lesion type, whether lesion detection (lesion detection processing) by the lesion detection unit  312  is executed (presence/absence of execution). That is, the information representing the operating state includes information representing that lesion detection processing is executed (detected by executing detection processing or undetected even in a case where detection processing is executed) and information representing that lesion detection processing is unexecuted. Also, the information representing the operating state includes information representing that lesion detection processing is being executed, that is, information representing a state in which lesion detection processing is started but not yet completed. In a case where lesion detection processing is being executed, the operating state obtaining unit  317  may obtain, from the lesion detection unit  312 , information representing the degree of progress of detection processing and the time remaining until the end of detection processing, and the information presentation unit  318  may present (display) at least one of the degree of progress of detection processing and the time remaining until the end of detection processing, which are obtained by the operating state obtaining unit  317 , on the display  207  (display unit) together with the information representing the operating state. 
     Also, the operating state obtaining unit  317  obtains, from the lesion detection unit  312 , information representing the operating state of detection processing for the associated lesion decided by the associated lesion decision unit  315 . That is, the operating state obtaining unit  317  obtains information (to be also referred to as associated operating information hereinafter) representing the operating state of detection processing for the associated lesion by the lesion detection unit  312 . 
     The information representing the operating state of detection processing for the associated lesion includes information representing whether lesion detection (associated lesion detection processing) for the associated lesion by the lesion detection unit  312  is executed (presence/absence of execution). In a case of the associated lesion as well, the information representing the operating state of detection processing includes information representing that associated lesion detection processing is executed (detected by executing detection processing or undetected even in a case where detection processing is executed) and information representing that associated lesion detection processing is unexecuted. Also, the information representing the operating state of detection processing for the associated lesion includes information representing that associated lesion detection processing is being executed. 
     The operating state obtaining unit  317  may obtain information representing the operating state for all lesion types detected by the lesion detection unit  312 , or may obtain only information representing the operating state of detection processing for the associated lesion decided by the associated lesion decision unit  315 . 
     Information Presentation Unit  318   
     The information presentation unit  318  that presents the information representing the operating state controls display of the user interface screen  400   on the display  207 . The information presentation unit  318  displays, on the display  207 , an associated lesion detection result obtained by the associated lesion detection obtaining unit  316  and the information representing the operating state obtained by the operating state obtaining unit  317 . Also, the information presentation unit  318  displays, on the display  207 , the medical image data  321 - i  (i = 1, 2, 3,...) obtained by the image obtaining unit  311  and a lesion detection result obtained by the detection result obtaining unit  313 . When displaying detection results on the display  207 , the information presentation unit  318  displays the detection results of associated lesions and the detection results of other lesions (lesions obtained by the detection result obtaining unit  313 ) such that these can be discriminated. 
     In this embodiment, the information presentation unit  318  discriminatively displays (presents) the detection results of a plurality of lesions detected by the lesion detection unit  312  and the detection results of associated lesions. An example in which the information presentation unit  318  displays detection results in separate display regions such as a region (for example,  403 ) where the detection results of associated lesions are displayed and a region (for example,  402 ) where the detection results of other lesions are displayed, as indicated by the user interface screen  400  in  FIG.  4   , will be described. However, the present invention is not limited to this example, and the display of detection results by the information presentation unit  318  may be done such that the detection results can be discriminated by, for example, displaying characters or background in different colors or displaying different icon images. 
     In addition, the information presentation unit  318  displays such that whether it is information representing the operating state of detection processing for an associated lesion can be discriminated. In this embodiment, an example in which display is performed in separate display regions of the display  207 , like the detection results, will be described. However, the present invention is not limited to this example, and the information presentation unit  318  may display such that whether it is information representing the operating state of detection processing for an associated lesion can be discriminated by displaying characters or background in different colors or displaying different icon images. In a case where detection processing by the lesion detection unit  312  is executed, and a lesion is detected, the information presentation unit  318  presents the detected lesion. 
     User Interface Screen 
       FIG.  4    is a view showing an example of the user interface screen  400  of the information processing apparatus  101  according to this embodiment. The user interface screen  400  is displayed on the display  207 , and various kinds of operations by the user are input via the keyboard  209  or the mouse  210 . 
     In  FIG.  4   , the user interface screen  400  includes a medical image data display region  401 , the lesion detection result display region  402 , and the associated lesion detection result display region  403 . 
     The information presentation unit  318  displays, in the medical image data display region  401 , medical image data obtained by the image obtaining unit  311 . Also, the information presentation unit  318  can perform display control of changing the WL/WW (Window Level/Window Width), the slice position, the magnification ratio, and the like of the image displayed in the medical image data display region  401  in accordance with an operation by the keyboard  209  or the mouse  210 . 
     In addition, the information presentation unit  318  presents (displays) the position of a lesion designated by the detected lesion designation unit  314  on the display of the medical image data. Based on the detection result of the lesion obtained by the detection result obtaining unit  313 , the information presentation unit  318  displays an annotation  411  indicating the position of the lesion designated by the detected lesion designation unit  314  on the display of the medical image data in the medical image data display region  401 . As a display example of the position of the designated lesion, for example, an image (overlay image) that emphasizes the lesion region by highlight may be displayed on the medical image. 
     The information presentation unit  318  presents (displays) the detection results of a plurality of lesions and information representing the operating state of detection processing for each lesion together. In the lesion detection result display region  402 , the information presentation unit  318  displays detection results (lesion detection results)  421 - i  (i = 1, 2, 3, 4,...) of lesions obtained by the detection result obtaining unit  313 . The lesion detection results  421 - i  (i = 1, 2. 3, 4,...) correspond to the lesion detection results obtained by the detection result obtaining unit  313 . and only the lesion detection results obtained by the detection result obtaining unit  313  are displayed in the lesion detection result display region  402 . 
     In the lesion detection result display region  402 , the information presentation unit  318  presents (displays) the lesion detection results  421 - i  (i = 1, 2, 3, 4,...) and information representing the operating state of detection processing for the lesions obtained by the operating state obtaining unit  317  together. For example, a lesion detection result  421 - 1  indicates that a lesion of “lesion type 1-1” is detected. Display of “detected” is based on the information representing the operating state, and indicates that the lesion is detected by executing lesion detection (lesion detection processing) by the lesion detection unit  312  (this indicates that detection processing is executed, and the lesion is detected). 
     In the display of the lesion detection result display region  402 , display of “detected” in “lesion type 1-2”, “lesion type 2-1”, and “lesion type 2-2” is the same as described above, and indicates that the lesion types are detected by executing lesion detection processing by the lesion detection unit  312 . That is, it indicates that detection processing is executed, and the lesions are detected. 
     Also, in the lesion detection result display region  402 , the detection result of a lesion can be designated by an operation such as a left click of the mouse  210  on the detection result of the lesion. The detected lesion designation unit  314  detects an operation of designating at least one lesion, based on the user operation, from the detection results of the plurality of lesions obtained by the detection result obtaining unit  313 . 
     The information presentation unit  318  displays the designated detection result highlighted such that it can be discriminated from the detection results of other lesions. As an example of highlighting, for example, the frame lines and the background can be highlighted, as indicated by a lesion detection result  421 - 2 . As the highlighting, identification display (for example, characters or an icon image) for discrimination from the detection results of other lesions can be combined with the display of the detection result. 
     In accordance with the designation of the lesion detection result in the lesion detection result display region  402 , the information presentation unit  318  updates the display position of the annotation  411  based on the detection position of the lesion corresponding to the designated lesion detection result. 
     In addition, based on the associated lesion detection results obtained by the associated lesion detection obtaining unit  316 , the information presentation unit  318  updates the display contents in the associated lesion detection result display region  403 . For example, in a case where the designation of the lesion detection result in the lesion detection result display region  402  is changed, the information presentation unit  318  updates the display contents in the associated lesion detection result display region  403  based on the detection result of the associated lesion associated with the lesion of the changed designation. 
     The information presentation unit  318  presents (displays) the detection results of associated lesions and information representing the operating state of detection processing for each associated lesion together. In the associated lesion detection result display region  403 , the information presentation unit  318  displays detection results (associated lesion detection results)  431 - i  (i = 1, 2, 3, 4,....) of associated lesions obtained by the associated lesion detection obtaining unit  316 . As The associated lesion detection results  431 - i  (i = 1, 2, 3, 4,...), the information presentation unit  318  displays the lesion types of the associated lesions. 
     In the associated lesion detection result display region  403 , the information presentation unit  318  displays the associated lesion detection results  431 - i  (i = 1, 2. 3, 4,...) and information representing the operating state of detection processing for the associated lesions obtained by the operating state obtaining unit  317  together. In the associated lesion detection result display region  403 , for example, as indicated by an associated lesion detection result  431 - 1 , even in a case where “lesion type 3” of the associated lesion is undetected, information representing that the associated lesion is undetected is displayed as the presentation of the operating state of detection processing for the associated lesion. Display of “undetected” is based on the information representing the operating state of detection processing for the associated lesion, and indicates that the associated lesion is not detected even in a case where lesion detection (associated lesion detection processing) by the lesion detection unit  312  is executed. That is, this indicates that detection processing is executed, and the lesion (associated lesion) is undetected. 
     In a case where detection processing for the associated lesion is unexecuted, information representing that the detection processing is unexecuted is displayed as the information representing the operating state. For example, in display of an associated lesion detection result  431 - 3 , concerning the operating state of detection processing for “lesion type 5” of the associated lesion, an indication (“unexecuted”) representing that detection processing is unexecuted is displayed. Display of “unexecuted” is based on the information representing the operating state of detection processing for the associated lesion, and indicates that associated lesion detection processing by the lesion detection unit  312  is unexecuted. 
     Processing Procedure 
       FIG.  5    is a flowchart showing processing of the information processing apparatus  101  according to this embodiment. This processing is started based on an instruction from another system or the user after activation of the information processing apparatus  101  . When starting the processing, a case as the target of the processing is designated. 
     In step S 501 , the image obtaining unit  311  obtains the medical image data  321 - i  (i = 1, 2, 3,...) of the case designated at the time of activation from the case DB  102  via the LAN  103 . 
     In step S 502 , the lesion detection unit  312  detects lesions from the medical image data  321 - i  (i = 1, 2, 3,...) obtained in step S 501 . 
     In step S 503 , the information presentation unit  318  displays the medical image data  321 - i  (i = 1, 2. 3,...) obtained in step S 501  in the medical image data display region  401  of the user interface screen  400 . The information presentation unit  318  also changes the WL/WW, the slice position, the magnification ratio, and the like of the displayed image based on the operation of the keyboard  209  or the mouse  210 . 
     In step S 504 , the detection result obtaining unit  313  obtains the detection results of the lesions from the lesion detection unit  312 . Each lesion detection result includes information representing the type of detected lesion and information capable of specifying the position of the lesion in the medical image data  321 - i  (i = 1, 2, 3,...). 
     In step S 505 , the information presentation unit  318  displays the lesion detection results  421 - i  (i = 1, 2, 3, 4,...) in the lesion detection result display region  402  of the user interface screen  400  based on the lesion detection results obtained in step S 504 . 
     In step S 506 , the detected lesion designation unit  314  determines the presence/absence of an operation of designating a lesion from the plurality of lesion detection results displayed in the lesion detection result display region  402 . That is, the detected lesion designation unit  314  detects the presence/absence of the operation of designating a detected lesion based on an input from the keyboard  209  or the mouse  210 . In a case where the detected lesion designation unit  314  detects a designation of a lesion in step S 506  (YES in step S 506 ), the process advances to step S 511 . On the other hand, in a case where a designation of a lesion is not detected in the determination of step S 506  (NO in step S 506 ), the process advances to step S 507 . 
     In step S 507 , the OS (Operating System) (not shown) determines whether to end the processing of the information processing apparatus  101 . The end of the processing is determined based on the presence/absence of an ending operation such as an OS shutdown operation, a power-off operation, an operation of closing a window, or a process stop. In a case where the OS detects the ending operation (YES in step S 507 ), the processing is ended. In a case where the ending operation is not detected (NO in step S 507 ), the process returns to step S 503 , and the same processing as described above is repeated from step S 503 . 
     On the other hand, in a case where the detected lesion designation unit  314  detects a designation of a lesion (YES in step S 506 ), in step S 511 , the associated lesion decision unit  315  decides an associated lesion associated with the designated lesion based on the lesion detection result designation detected in step S 506 . 
     In step S 512 , the associated lesion detection obtaining unit  316  obtains a detection result for the associated lesion decided in step S 511 . 
     In step S 513 , the information presentation unit  318  displays the associated lesion detection results  431 - i  (i = 1, 2, 3,...) in the associated lesion detection result display region  403  of the user interface screen  400  based on the associated lesion detection result obtained in step S 512 . 
     In step S 514 , the operating state obtaining unit  317  obtains information (associated operating information) representing the operating state of detection processing for the associated lesion decided in step S 511 . As the information representing the operating state, the operating state obtaining unit  317  obtains information representing whether lesion detection (associated lesion detection processing) for the associated lesion by the lesion detection unit  312  is executed (presence/absence of execution). The information representing the operating state of detection processing for the associated lesion includes information representing that associated lesion detection processing is executed (detected by executing detection processing or undetected even in a case where detection processing is executed), information representing that associated lesion detection processing is unexecuted, and information representing that associated lesion detection processing is being executed. 
     In step S 515 , the information presentation unit  318  displays (presents) the information representing the operating state of detection processing for the associated lesion, which is obtained in step S 514 . as the associated lesion detection result  431 - i  (i = 1, 2, 3,...) in the associated lesion detection result display region  403 . In a case where the processing of step S 515  is ended, the process advances to step S 507 . 
     In step S 507 , in a case where the OS detects the ending operation (YES in step S 507 ), the processing is ended. In a case where the ending operation is not detected (NO in step S 507 ), the process returns to step S 503 , and the same processing as described above is repeated from step S 503 . 
     According to this embodiment, it is possible to present the operating state of detection processing for detecting a lesion. Also, according to this embodiment, in a case where the user designates a detected lesion in the display on the user interface screen, the type of an associated lesion associated with the designated lesion is automatically decided, and the detection result of the associated lesion is displayed. Hence, even in a case where the number of lesions as the detection target increases, the presence/absence of the detection result of another associated lesion can easily be found. 
     Also, since the operating state of lesion detection processing is displayed, even in a case where no lesion is detected, it is possible to easily discriminate whether no lesion is detected even in a case where lesion detection processing is executed, or no lesion is detected because lesion detection processing is not executed. 
     Modification of First Embodiment 
     The information processing apparatus  101  may be, for example, an image processing workstation, an electronic medical chart, an integration viewer configured to integrally display information from a plurality of types of apparatuses, or an apparatus for capturing a medical image, such as an ultrasonic diagnostic apparatus. 
     The lesion detection unit  312  may be located on another apparatus such as an image processing server connected to the information processing apparatus  101  via a network. Also, the lesion detection unit  312  may detect a lesion at the timing of capturing of the medical image data  321 - i  (i = 1, 2, 3,...), or may detect a lesion at the timing of storing the medical image data  321 - i  (i = 1, 2, 3,...) in the case DB  102 . In addition, when capturing medical image data or storing medical image data in the case DB  102 , the lesion detection unit  312  may detect a lesion by background processing and store the detection result in a storage device such as the case DB  102 . In this case, the detection result obtaining unit  313  obtains the detection result from the storage device. 
     The lesion detection unit  312  may detect a plurality of types of lesions from the obtained medical image data  321 - i  (i = 1, 2, 3,...) using a method other than the CNN, such as SVM (Support Vector Machine). Also, the associated lesion decision unit  315  may extract medical knowledge by language processing of a past interpretation report, a paper, or a diagnostic guideline and create a table or a rule used to decide an associated lesion. 
     Second Embodiment 
     In a case where associated lesion detection processing is unexecuted in information representing the operating state of detection processing for an associated lesion, an information processing apparatus  601  according to the second embodiment presents information representing whether the unexecuted detection processing can be executed or not, in addition to the information processing apparatus  101  of the first embodiment. In a case where associated lesion detection processing is unexecuted, and the unexecuted detection processing can be executed, an instruction unit  319  ( FIG.  6   ) of the information processing apparatus  601  instructs a lesion detection unit  312  to execute the unexecuted detection processing. Note that the system configuration of the information processing apparatus  601  according to the second embodiment is the same as in  FIG.  1   , and the hardware configuration is the same as in the first embodiment described with reference to  FIG.  2   . Hence, a description of these will be omitted. 
     In the processing of the information processing apparatus  601  to be described in the second embodiment, information representing the operating state includes information representing whether lesion detection (lesion detection processing) by the lesion detection unit  312  is executed (presence/absence of execution), and information representing whether lesion detection processing can be executed or not. That is, the information representing the operating state includes information representing that associated lesion detection processing is executed (detected by executing detection processing or undetected even in a case where detection processing is executed), information representing that lesion detection processing is unexecuted, and information representing that lesion detection processing is being executed. Note that in this embodiment, the unexecuted detection processing will be described using an associated lesion displayed in an associated lesion detection result display region  403  as an example. This also applies to a case where detection processing for a lesion displayed in a lesion detection result display region  402  is unexecuted. 
     Functional Blocks 
       FIG.  6    is a block diagram showing the functional configuration of the information processing apparatus  601  according to this embodiment. The same reference numerals as the functional blocks of the information processing apparatus  101  according to the first embodiment described with reference to  FIG.  3    denote the same functional blocks, and a description thereof will be omitted. In  FIG.  6   , the functional configuration of the information processing apparatus  601  is different in that the instruction unit  319  is provided, in addition to the information processing apparatus  101  according to the first embodiment. The functional configuration of the instruction unit  319  is implemented by reading out a predetermined computer program stored in a storage medium  201  to a RAM  204  and executing arithmetic processing by a CPU  203 . 
     Instruction Unit  319   
     In a case where detection processing is unexecuted, and the unexecuted detection processing can be executed, in the information representing the operating state of detection processing, the instruction unit  319  instructs the lesion detection unit  312  to execute the detection processing. In this embodiment, a configuration in which the instruction of unexecuted associated lesion detection processing by the instruction unit  319  is executed upon receiving a user confirmation via an instruction confirmation window  404  will be described. 
     User Interface Screen 
       FIG.  7    is a view showing an example of a user interface screen  700  of the information processing apparatus  601  according to this embodiment. Note that the same reference numerals as in the user interface screen  400  according to the first embodiment described with reference to  FIG.  4    denote the same parts, and a description thereof will be omitted. 
     An information presentation unit  318  controls display of the user interface screen  700  on a display  207 . The user interface screen  700  according to this embodiment has the same screen configuration as the user interface screen  400  described in the first embodiment. In this embodiment, additionally, in a case where detection processing of a lesion (associated lesion) is unexecuted, the information presentation unit  318  presents, on the user interface screen  700 , information representing whether unexecuted detection processing can be executed or not in associated lesion detection results  431 - i  (i = 1, 2, 3....). 
     As shown in  FIG.  7   , the information presentation unit  318  displays an indication (“unexecuted”) representing that detection processing of “lesion type 5” of an associated lesion is unexecuted and an indication (“executable”) representing that the detection processing can be executed together with the display of an associated lesion detection result  431 - 4 . 
     In a case where the user designates the display of the associated lesion detection result  431 - 4 , the information presentation unit  318  displays the frame lines and the background highlighted such that the designated display of the associated lesion detection result  431 - 4  can easily discriminated from the detection results (for example,  431 - 1  and  431 - 2 ) of other associated lesions. Note that as the highlighting, identification display (for example, characters or an icon image) can be combined with the display of the detection result to make discrimination from the detection results of other associated lesions. 
     In a case where the user designates the display of the associated lesion detection result  431 - 4 , the information presentation unit  318  displays, on the display  207 , the instruction confirmation window  404  for requesting confirmation of the user concerning whether to execute the unexecuted detection processing. That is, in a case where the associated lesion detection result (for example,  431 - 4 ) for which detection processing is unexecuted, and the unexecuted detection processing can be executed is designated by the designation operation of the user, the information presentation unit  318  displays the instruction confirmation window  404  on the display  207 . 
     In the instruction confirmation window  404 , the user can instruct, by operating a keyboard  209  or a mouse  210 , whether to execute the unexecuted detection processing. In a case where the user instructs “YES” in the instruction confirmation window  404 , the instruction unit  319  instructs the lesion detection unit  312  to execute detection processing of the associated lesion. On the other hand, in a case where the user instructs “NO” in the instruction confirmation window  404 , the instruction unit  319  does not instruct the lesion detection unit  312  to execute detection processing of the associated lesion. 
     Processing Procedure 
       FIG.  8    is a flowchart showing processing of the information processing apparatus  601  according to this embodiment. Note that the same step numbers as the steps of the processing procedure of the first embodiment described with reference to  FIG.  5    denote the same steps, and a description thereof will be omitted. 
     In step S 516 , in a case where the designation operation of the user is performed on the display (step S 515 ) of the associated lesion detection results  431 - i  (i = 1, 2, 3,...), the instruction unit  319  determines, based on the information representing the operating state of detection processing, whether detection processing is unexecuted, and the unexecuted detection processing can be executed or not. In a case where detection processing is unexecuted, and the unexecuted detection processing cannot be executed in the determination processing of step S 516  (NO in step S 516 ), the instruction unit  319  returns the process to step S 507 . On the other hand, in a case where detection processing is unexecuted, and the unexecuted detection processing can be executed (YES in step S 516 ), the instruction unit  319  advances the process to step S 521 . 
     In step S 521 , the instruction unit  319  instructs the lesion detection unit  312  to execute detection processing of the associated lesion for which it has been determined in step S 516  that the information representing the operating state is “unexecuted”, and the detection processing can be executed. Then, the process returns to step S 507  to determine whether to end the processing. 
     In this embodiment, the information presentation unit  318  displays, on the display  207 . the instruction confirmation window  404  as shown in  FIG.  7    to request confirmation of the user concerning whether to execute the detection processing that is unexecuted and can be executed. In a case where the user instructs “YES” in the instruction confirmation window  404 , the instruction unit  319  instructs the lesion detection unit  312  to execute detection processing of the associated lesion. In a case where the user instructs “NO” in the instruction confirmation window  404 , the instruction unit  319  does not instruct the lesion detection unit  312  to execute detection processing of the associated lesion but ends the processing of this step and returns the process to step S 507 . 
     According to this embodiment, it is possible to present the operating state of detection processing for detecting a lesion. Also, according to this embodiment, in a case where the user designates a detected lesion in the display on the user interface screen, the type of an associated lesion associated with the designated lesion is automatically decided, and the detection result of the associated lesion is displayed. Hence, even in a case where the number of lesions as the detection target increases, the presence/absence of the detection result of another associated lesion can easily be found. 
     Also, since the operating state of lesion detection processing is displayed, even in a case where no lesion is detected, it is possible to easily discriminate whether no lesion is detected even in a case where lesion detection processing is executed, or no lesion is detected because lesion detection processing is not executed. 
     Furthermore, in a case where lesion detection processing is unexecuted and can be executed, lesion detection processing is instructed, thereby easily executing the instructed unexecuted lesion (associated lesion) detection processing. 
     Modification of Second Embodiment 
     In the second embodiment, the instruction of unexecuted associated lesion detection processing by the instruction unit  319  is executed upon receiving a user confirmation via the instruction confirmation window  404 . However, the instruction unit  319  may instruct execution of detection processing by the lesion detection unit  312  based on the information representing the operating state. That is, without receiving the user confirmation, in a case where detection processing is unexecuted, and the unexecuted detection processing can be executed based on the information representing the operating state, the instruction unit  319  may instruct the lesion detection unit  312  to execute the unexecuted lesion detection processing. 
     Third Embodiment 
     The configuration of an information processing system  10  including an information processing apparatus  1101  according to this embodiment is the same as in  FIG.  1   , and the hardware configuration of the information processing apparatus  1101  is the same as the hardware configuration of the information processing apparatus  101  according to the first embodiment described with reference to  FIG.  2   . 
       FIG.  11    is a block diagram showing the functional configuration of the information processing apparatus  1101  according to this embodiment. The same reference numerals as the functional blocks of the information processing apparatus  101  according to the first embodiment and the functional blocks of the information processing apparatus  601  according to the second embodiment denote the same functional blocks, and a description thereof will be omitted. In  FIG.  11   , the functional configuration of the information processing apparatus  1101  is different in that a lesion detection introduction unit  320  is provided, in addition to the information processing apparatus  101  according to the first embodiment and the information processing apparatus  601  according to the second embodiment. The functional configuration of the lesion detection introduction unit  320  is implemented by reading out a predetermined computer program stored in a storage medium  201  to a RAM  204  and executing arithmetic processing by a CPU  203 . 
     In the processing of the information processing apparatus  1101  to be described in the third embodiment, information representing the operating state includes information representing whether lesion detection (lesion detection processing) by a lesion detection unit  312  is executed (presence/absence of execution), information representing whether lesion detection processing can be executed or not, and information corresponding to the reason why the detection processing cannot be executed (the reason for “inexecutable”) in a case where the unexecuted detection processing cannot be executed (in a case of “inexecutable”). In a case where the information representing the operating state is information representing a state in which the detection processing cannot be executed, an information presentation unit  318  presents the information corresponding to the reason why the detection processing cannot be executed. 
     In a case where unexecuted detection processing cannot be executed (in a case of “inexecutable”) in the information representing the operating state, the information presentation unit  318  of the information processing apparatus  1101  according to this embodiment presents information corresponding to the reason why the detection processing cannot be executed (the reason for “inexecutable”), in addition to the configuration of the information processing apparatus  601  of the second embodiment. Note that in this embodiment, the “inexecutable” detection processing will be described using an associated lesion displayed in an associated lesion detection result display region  403  as an example. This also applies to a case where detection processing for a lesion displayed in a lesion detection result display region  402  is inexecutable. 
     User Interface Screen 
       FIGS.  9 A and  9 B  are views showing an example of a user interface screen  900  of the information processing apparatus  1101  according to this embodiment. Note that the same reference numerals as in the user interface screens according to the first embodiment described with reference to  FIG.  4    and the second embodiment described with reference to  FIG.  7    denote the same parts, and a description thereof will be omitted. 
     The information presentation unit  318  controls display of the user interface screen  900  on a display  207 . The user interface screen  900  ( FIGS.  9 A and  9 B ) according to this embodiment has the same screen configuration as the user interface screen  700  described in the second embodiment. 
     In this embodiment, in a case where unexecuted detection processing is inexecutable in the information representing the operating state, the information presentation unit  318  presents, on the user interface screen  900 , information corresponding to the reason for “inexecutable”. 
     In this embodiment, the information corresponding to the reason why the detection processing cannot be executed includes, concerning the designated lesion (associated lesion), information representing “unintroduced” in which a lesion detection function is not introduced to the lesion detection unit  312 , and information representing that the medical image data is data outside an execution condition of detection processing by the lesion detection unit  312  based on comparison between attributes the image data and the lesion detection unit  312 . 
     In the display examples shown in  FIGS.  9 A and  9 B , the information presentation unit  318  displays an indication (“inexecutable”) representing that detection processing of “lesion type 6” of the associated lesion cannot be executed, and an indication (“unintroduced”) representing that the detection function for the designated lesion (associated lesion) is not introduced to the lesion detection unit  312  together with the display of an associated lesion detection result  431 - 5 . 
     Also, the information presentation unit  318  displays an indication (“inexecutable”) representing that detection processing of “lesion type 7” of the associated lesion cannot be executed, and an indication (“outside execution condition”) representing that the medical image data is data that is not suitable for detection processing and is outside the execution condition together with the display of an associated lesion detection result  431 - 6 . 
     As the screen configuration, the user interface screen  900  includes an introduction confirmation window  405  (for example,  FIG.  9 A ) configured to confirm whether to introduce the detection function, and an image obtaining confirmation window  406  (for example,  FIG.  9 B ) configured to confirm whether to obtain image data (medical image data) suitable for the execution condition. In accordance with the reason why detection processing is inexecutable (“unintroduced” or “outside application condition”), the information presentation unit  318  presents one of the introduction confirmation window  405  and the image obtaining confirmation window  406  on the user interface screen  900 . 
     Introduction Confirmation Window  405 : Fig.  9 A 
       FIG.  9 A  is a view showing the user interface screen  900  on which the introduction confirmation window  405  is displayed. As shown in  FIG.  9 A , in a case where the user designates display of the associated lesion detection result  431 - 5  (“inexecutable”. “unintroduced”), the information presentation unit  318  displays the associated lesion detection result  431 - 5  while highlighting the frame lines and the background such that it can easily be discriminated from the display of the detection results (for example,  431 - 2 ,  431 - 4 , and  431 - 6 ) of other associated lesions. Note that as the highlighting, identification display (for example, characters or an icon image) can be combined with the display of the detection result to make discrimination from the detection results of other associated lesions. 
     In a case where the user designates the display of the associated lesion detection result  431 - 5 , the information presentation unit  318  displays, on the display  207 , the introduction confirmation window  405  for requesting confirmation of the user concerning whether to introduce the unintroduced detection function to the lesion detection unit  312 . That is, in a case where display of the associated lesion detection result (for example,  431 - 5 ) for which detection processing is inexecutable, and the detection function corresponding to the unexecuted detection processing is unintroduced to the lesion detection unit  312  is designated by the designation operation of the user, the information presentation unit  318  displays the introduction confirmation window  405  on the display  207 . 
     In the introduction confirmation window  405 , the user can instruct, by operating a keyboard  209  or a mouse  210 , whether to introduce the unintroduced detection function to the lesion detection unit  312 . Here, introduction of the lesion detection function can include installing lesion detection software to be executed by the lesion detection unit  312  to detect a lesion and inputting information (for example, authentication information such as an activation key) for activating the unintroduced lesion detection function in the lesion detection software configured to detect a lesion. 
     In a case where the user instructs “NO” in the introduction confirmation window  405 , an instruction unit  319  does not perform processing associated with introduction of the unintroduced lesion detection function. On the other hand, in a case where the user instructs “YES” in the introduction confirmation window  405 , the instruction unit  319  executes the following processing. 
     Installation of Lesion Detection Software 
     In this embodiment, in a case where the information corresponding to the reason why detection processing cannot be executed is information representing “unintroduced”, the instruction unit  319  instructs the lesion detection introduction unit  320  to introduce the unintroduced lesion detection function. In a case where the user instructs “YES” in the introduction confirmation window  405 , the instruction unit  319  instructs the lesion detection introduction unit  320  to introduce the unintroduced lesion detection function. The lesion detection introduction unit  320  downloads the lesion detection software configured to implement the unintroduced lesion detection function from an external server (not shown) to a storage medium  201  via a LAN interface  205  and a LAN  103  and stores the lesion detection software. The lesion detection introduction unit  320  registers the lesion detection software in the lesion detection unit  312 . The lesion detection unit  312  reads out the registered lesion detection software and executes it, thereby executing the inexecutable lesion detection processing. 
     Input of Activation Key 
     In a case where the lesion detection software configured to implement the unintroduced lesion detection function is stored in the storage medium  201  in advance, in a case where the user instructs “YES” in the introduction confirmation window  405 , the instruction unit  319  instructs the lesion detection introduction unit  320  to introduce the unintroduced lesion detection function. 
     The lesion detection introduction unit  320  downloads an activation key (for example, a predetermined character string) used to activate the unintroduced lesion detection function in the lesion detection software from an external server (not shown) via the LAN interface  205  and the LAN  103  and temporarily stores the activation key in the RAM  204  or the like. The lesion detection introduction unit  320  registers the activation key in the lesion detection unit  312 . The lesion detection unit  312  reads out the lesion detection software from the storage medium  201  and sets the registered key, thereby executing the inexecutable lesion detection processing. 
     Image Obtaining Confirmation Window  406 : Fig.  9 B 
       FIG.  9 B  is a view showing the user interface screen  900  on which the image obtaining confirmation window  406  is displayed. As shown in  FIG.  9 B , in a case where the user designates display of the associated lesion detection result  431 - 6  (“inexecutable”, “outside application condition”), the information presentation unit  318  displays the associated lesion detection result  431 - 6  while highlighting the frame lines and the background such that it can easily be discriminated from the display of the detection results (for example.  431 - 2 ,  431 - 3 , and  431 - 5 ) of other associated lesions. Note that as the highlighting, identification display (for example, characters or an icon image) can be combined with the display of the detection result to make discrimination from the detection results of other associated lesions. 
     In a case where the user designates the display of the associated lesion detection result  431 - 6 , the information presentation unit  318  displays, on the display  207 , the image obtaining confirmation window  406  for requesting confirmation of the user concerning whether to obtain image data (medical image data) suitable for the execution condition. That is, in a case where display of the associated lesion detection result (for example,  431 - 6 ) for which detection processing is inexecutable, and the medical image data is data outside the execution condition (outside application condition) is designated by the designation operation of the user, the information presentation unit  318  displays the image obtaining confirmation window  406  on the display  207 . 
     The information presentation unit  318  presents the image obtaining confirmation window  406  including a condition designation portion  407  (checkbox) capable of adding or changing a condition to obtain medical image data that satisfies the execution condition of detection processing. The user can add or change the image obtaining condition by designating the condition designation portion  407  by operating the keyboard  209  or the mouse  210 . In the image obtaining confirmation window  406  shown in  FIG.  9 B , a state in which condition 1 and condition 2 are designated (with check marks), and condition 3 is excluded from the image obtaining condition (without a check mark) is displayed by the designation of the condition designation portion  407 . Here, the condition for image obtaining includes various conditions, and can include, for example, a modality for capturing a medical image, a reconstruction function, a contrast condition, a time phase, an image capturing range, and the like. 
     In the image obtaining confirmation window  406 , the user can instruct an image obtaining unit  311 , by operating the keyboard  209  or the mouse  210 , whether to obtain image data (medical image data) suitable for the execution condition. In a case where the user instructs “stop” in the image obtaining confirmation window  406 , the instruction unit  319  does not instruct the image obtaining unit  311  to obtain image data (medical image data) suitable for the execution condition. On the other hand, in a case where the user instructs “execute” in the image obtaining confirmation window  406 . the instruction unit  319  instructs the image obtaining unit  311  to obtain image data (medical image data) suitable for the designated execution condition. That is, in this embodiment, in a case where the information corresponding to the reason why detection processing cannot be executed is information representing that the data is outside the execution condition, the instruction unit  319  instructs the image obtaining unit  311  to obtain medical image data that satisfies the execution condition of detection processing. 
     The image obtaining unit  311  may generate the medical image data satisfying the execution condition from already obtained medical image data, or may transmit an order for obtaining to an ordering system or the like to obtain the medical image data satisfying the execution condition from the outside. 
     Upon receiving the image obtaining instruction from the instruction unit  319 , the image obtaining unit  311  performs obtaining processing of image data (medical image data) suitable for the designated condition. When obtaining the medical image data from the outside, the image obtaining unit  311  outputs, via the LAN  103 , an image capturing instruction including a condition of image reconstruction and the like to an ordering system including an HIS (Hospital Information Systems) or an RIS (Radiology Information Systems). The image obtaining unit  311  may obtain image data captured by the modality of the HIS or RIS based on the designated condition, or may obtain image data suitable for the condition from the case DB  102  or a PACS (Picture Archiving and Communication Systems) (not shown). The image obtaining unit  311  stores the obtained image data in the storage medium  201 . The image data obtained by the image obtaining unit  311  is suitable for the execution condition (application condition) of lesion detection, and the lesion detection unit  312  can execute inexecutable lesion detection processing by using the image data obtained by the image obtaining unit  311 . 
     Processing Procedure 
       FIGS.  10 A and  10 B  are flowcharts showing processing of the information processing apparatus  1101  according to this embodiment. Note that the same step numbers as the steps of the processing procedure of the first embodiment described with reference to  FIG.  5    and the steps of the processing procedure of the second embodiment described with reference to  FIG.  8    denote the same steps, and a description thereof will be omitted. 
     In step S 517 , in a case where the designation operation of the user in the display (step S 515 ) of the associated lesion detection results  431 - i  (i = 1, 2, 3,...) is performed, the instruction unit  319  determines, based on the information representing the operating state of detection processing, whether detection processing is inexecutable, and the reason for “inexecutable” is “unintroduced”. In a case where detection processing is inexecutable, and the reason for “inexecutable” is “unintroduced” in the determination processing of step S 517  (YES in step S 517 ), the instruction unit  319  advances the process to step S 531 . 
     In step S 531 , the instruction unit  319  instructs the lesion detection introduction unit  320  to introduce the unintroduced lesion detection function. Upon receiving the instruction from the instruction unit  319 , the lesion detection introduction unit  320  performs introduction processing for introducing the lesion detection function. Detailed processing for introducing the lesion detection function has been described above with reference to the introduction confirmation window  405 . 
     In this embodiment, when executing the instruction, the user can instruct, in the introduction confirmation window  405 , whether to introduce the unintroduced detection function to the lesion detection unit  312  by operating the keyboard  209  or the mouse  210 . In a case where the user instructs “YES” in the introduction confirmation window  405 , the instruction unit  319  instructs the lesion detection introduction unit  320  to introduce the unintroduced lesion detection function. In a case where the user instructs “NO” in the introduction confirmation window  405 , the instruction unit  319  does not perform processing concerning introduction of the unintroduced lesion detection function but ends the processing of this step and advances the process to step S 518 . 
     On the other hand, in a case where detection processing is inexecutable, and the reason for “inexecutable” is not “unintroduced” in the determination processing of step S 517  (NO in step S 517 ), the instruction unit  319  advances the process to step S 518 . 
     In step S 518 , in a case where the designation operation of the user in the display (step S 515 ) of the associated lesion detection results  431 - i  (i = 1, 2, 3,...) is performed, the instruction unit  319  determines, based on the information representing the operating state of detection processing, whether detection processing is inexecutable, and the reason for “inexecutable” is “outside execution condition”. In a case where detection processing is inexecutable, and the reason for “inexecutable” is “outside execution condition” in the determination processing of step S 518  (YES in step S 518 ), the instruction unit  319  advances the process to step S 541 . 
     In step S 541 , the instruction unit  319  instructs the image obtaining unit  311  to obtain image data (medical image data) suitable for the designated condition. Upon receiving the image data (medical image data) obtaining instruction from the instruction unit  319 , the image obtaining unit  311  performs obtaining processing for obtaining image data (medical image data) suitable for the designated condition. Detailed processing has been described above with reference to the image obtaining confirmation window  406 . 
     In this embodiment, when executing the instruction, the user can instruct the image obtaining unit  311 , in the image obtaining confirmation window  406 . whether to obtain image data (medical image data) suitable for the execution condition by operating the keyboard  209  or the mouse  210 . In a case where the user instructs “execute” in the image obtaining confirmation window  406 , the instruction unit  319  instructs the image obtaining unit  311  to obtain image data (medical image data) suitable for the designated condition. In a case where the user instructs “stop” in the image obtaining confirmation window  406 . the instruction unit  319  does not instruct the image obtaining unit  311  to obtain image data (medical image data) suitable for the execution condition but ends the processing of this step. 
     On the other hand, in a case where detection processing is inexecutable, and the reason for “inexecutable” is not “outside execution condition” in the determination processing of step S 518  (NO in step S 518 ), the instruction unit  319  returns the process to step S 507 . 
     According to this embodiment, it is possible to present the operating state of detection processing for detecting a lesion. Also, according to this embodiment, in a case where the user designates a detected lesion in the display on the user interface screen, the type of an associated lesion associated with the designated lesion is automatically decided, and the detection result of the associated lesion is displayed. Hence, even in a case where the number of lesions as the detection target increases, the presence/absence of the detection result of another associated lesion can easily be found. 
     Since the operating state of lesion detection processing is displayed, even in a case where no lesion is detected, it is possible to easily discriminate whether no lesion is detected even in a case where lesion detection processing is executed, or no lesion is detected because lesion detection processing is not executed. 
     In a case where lesion detection processing is unexecuted and can be executed, lesion detection processing is instructed, thereby easily executing the instructed unexecuted lesion (associated lesion) detection processing. 
     Even in a case where detection processing is inexecutable, and the detection function corresponding to unexecuted detection processing is unintroduced, introduction of the lesion detection function is instructed, thereby easily introducing the necessary lesion detection function to the lesion detection unit  312 . 
     Even in a case where detection processing is inexecutable, and the medical image data is data outside the execution condition, obtaining of medical image data satisfying the execution condition is instructed, thereby easily obtaining medical image data necessary for executing lesion detection processing. 
     According to the present invention, it is possible to present the operating state of lesion detection processing. 
     Other Embodiments 
     Embodiment(s) of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be referred to more fully as a ‘non-transitory computer-readable storage medium’) to perform the functions of one or more of the above-described embodiment(s) and/or that includes one or more circuits (e.g., application specific integrated circuit (ASIC)) for performing the functions of one or more of the above-described embodiment(s), and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s) and/or controlling the one or more circuits to perform the functions of one or more of the above-described embodiment(s). The computer may comprise one or more processors (e.g., central processing unit (CPU), micro processing unit (MPU)) and may include a network of separate computers or separate processors to read out and execute the computer executable instructions. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions. 
     This application claims the benefit of Japanese Patent Application No. 2021-184222, filed Nov. 11, 2021. which is hereby incorporated by reference herein in its entirety.