Medical image processing system and method of operation

Abstract

To provide a medical image processing system which can efficiently perform detection of an abnormality in an instrument due to a failure without using a special sensor for detecting a failure and analysis of a failure cause by recording the detection result in an external device for each failure, and an operation method thereof.SOLUTION: A medical image processing system comprises: an external device having a processor; and an endoscope system, acquires a real-time medical treatment moving image during an endoscopic examination from the endoscope system, receives a trigger signal having information about the failure occurrence created on the basis of a failure scene of the medical treatment moving image from the endoscope system, temporarily stores the medical treatment moving image, extracts a failure moving image having the failure scene from the temporarily-stored medical treatment moving image on the basis of reception timing of the trigger signal, and stores the failure moving image in a main storage area.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a medical imaging system and method of operation. [Background technology]

[0002] In medical devices such as endoscopes, it is common for systems to automatically detect abnormalities such as equipment failures and save them as error logs. The error log records the type of abnormality, the date and time of occurrence, as well as the device settings, program processing status, and communication status between modules at the time the abnormality occurred. The error log makes it possible to understand the fact that an abnormality such as a failure occurred and the circumstances under which it occurred. However, when detecting failures using the error log, it is difficult to identify the specific nature of the failure or its cause. For this reason, it is necessary to understand the specific nature of the failure using data other than the error log.

[0003] Specifically, in Patent Document 1, inspections are performed on multiple status signals that indicate the operating status of the equipment. When a status signal is detected to be outside an allowable range, the time of detection, the time elapsed since startup, and the status thereafter are recorded. The type of abnormality is also displayed using a light, sound, etc. In Patent Document 2, an abnormality is detected from data indicating the operating status of the equipment, and the operating status is recorded along with the type of abnormality detected. It is determined whether the abnormality has been confirmed as a malfunction, and the recorded data is erased when an abnormality that has not been confirmed as a malfunction is detected. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 5-5633 [Patent Document 2] Japanese Patent Application Laid-Open No. 2003-57076 Summary of the Invention [Problem to be solved by the invention]

[0005] In Patent Document 1, abnormalities are detected using equipment status signals, while in Patent Document 2, the type of abnormality is determined as either one that occurs temporarily during extremely high loads, etc., and is likely to self-recover over time, or one that is not. In Patent Documents 1 and 2, signals from the equipment's operating status are acquired, and the type of abnormality is determined by detecting, recording, and judging the abnormality. Even if it can be determined that the abnormality is not due to a malfunction, such as a temporary high load caused by external noise, it is difficult to determine that it is a malfunction or to identify its cause.

[0006] Furthermore, in devices with size constraints such as endoscopes, it is not possible to install dedicated sensors for detecting faults, or these are costly. Furthermore, analyzing all of the data obtained from the inspection results requires time and effort from the user, which is inefficient. In addition, the data storage capacity of endoscope systems is not always sufficient, making constant storage inefficient. Therefore, there is a need to efficiently identify the nature of the fault and identify the cause when detecting faults from inspection results obtained from conventional inspection equipment and recording them in external devices.

[0007] The present invention aims to provide a medical image processing system and its operating method that can detect abnormalities in equipment due to failures without using dedicated sensors to detect failures, and can efficiently analyze the cause of the failure by recording the detection results for each failure in an external device. [Means for solving the problem]

[0008] The medical image processing system of the present invention comprises: Program memory and An external device having a processor, and an endoscope system of Preparation, By running the program in the program memory, The processor acquires real-time medical videos from the endoscopic system during an endoscopic examination, acquires a trigger signal from the endoscopic system containing information about a failure occurrence created based on a failure scene in the medical video, temporarily stores the medical videos in an external device, and extracts failure videos containing failure scenes from the temporarily stored medical videos based on the timing of receiving the trigger signal in the external device, and stores the failure videos in a main memory area of ​​the external device.

[0009] The processor Extraction start timing of It is preferable to determine the time based on the reception timing, and extract a failure video including scenes before and after the time based on the reception timing from the medical video.

[0010] The processor It is preferable to set a limit period for the trigger signal after receiving the trigger signal, and not start extraction if the trigger signal is received within the limit period.

[0011] It is preferable to set an upper limit to the number of times extraction is performed.

[0012] It is preferable to temporarily store the failure videos and select the failure videos to be stored.

[0013] It is preferable to select based on the type of failure and the order of reception timing.

[0014] It is preferable to calculate the importance of the failure video based on information on the occurrence of the failure, and to select the failure video based on the importance.

[0015] Preferably, the importance is calculated based on the visibility of the fault or the severity of the fault.

[0016] It is preferable to calculate the importance based on the type of endoscope.

[0017] It is preferable to select between the temporarily saved failure video and the newly extracted failure video in an alternative format.

[0018] At the time of extraction, it is preferable to process the personal information contained in the image information of the medical video so that it cannot be deleted or viewed.

[0019] It is preferable to temporarily store the medical video in non-volatile memory.

[0020] It is preferable to select the malfunction video temporarily stored in the nonvolatile memory regardless of the completion status of the endoscopic examination.

[0021] When extracting the failure video, it is preferable to set a different identifier for each failure video, check the identifier of the failure video stored in the main memory area, and delete the failure video having the same identifier as the checked identifier from the non-volatile memory.

[0022] The method for operating a medical image processing system of the present invention includes: 1. A method of operating a medical imaging system comprising: The method includes the steps of acquiring real-time medical videos from an endoscopic system during an endoscopic examination, receiving a trigger signal from the endoscopic system having information on the occurrence of a failure created based on a failure scene in the medical video, temporarily storing the medical video, extracting a failure video having a failure scene from the temporarily stored medical video based on the timing of receiving the trigger signal, and storing the failure video in a main memory area. [Effects of the Invention]

[0023] According to the present invention, it is possible to detect abnormalities in equipment due to failures without using a dedicated sensor for detecting failures, and to record the detection results for each failure in an external device, thereby efficiently analyzing the cause of the failure. [Brief explanation of the drawings]

[0024] [Figure 1] FIG. 1 is an explanatory diagram showing the configuration of a medical image processing system. [Figure 2] FIG. 2 is a functional block diagram of a processor device. [Figure 3] FIG. 2 is a block diagram showing the functions of the medical image processing apparatus. [Figure 4] 10A and 10B are explanatory diagrams of a medical video on which a fault detection process has been performed. [Figure 5] 10A, 10B, and 10C are explanatory diagrams of frame images detected in the fault detection process. [Figure 6]FIG. 2 is an explanatory diagram of data transmitted from a processor device to a medical image processing device. [Figure 7] FIG. 10 is an image diagram showing a playback screen of a medical video. [Figure 8] FIG. 10 is an explanatory diagram illustrating the extraction of a failure video in a first extraction range in response to a trigger signal. [Figure 9] FIG. 10 is an explanatory diagram illustrating extraction of a failure video in a second extraction range in response to a trigger signal. [Figure 10] FIG. 10 is an explanatory diagram illustrating extraction of a failure video in a third extraction range in response to a trigger signal. [Figure 11] FIG. 10 is an image diagram showing a video of a failure displayed on a screen. [Figure 12] FIG. 10 is an image diagram showing a fault video and a fault still image displayed on the screen. [Figure 13] FIG. 10 is an explanatory diagram illustrating a case where extracted failure videos are stored without being selected. [Figure 14] FIG. 10 is an explanatory diagram illustrating a case where extracted failure videos are selected and saved. [Figure 15] FIG. 10 is an image diagram showing a thumbnail display of a video of a failure. [Figure 16] 1 is a flowchart showing a series of processing steps according to the present invention. [Figure 17] FIG. 11 is an explanatory diagram illustrating temporary storage of a failure video in a nonvolatile memory in the second embodiment. [Figure 18] FIG. 11 is an explanatory diagram of data transmitted from the processor device to the medical image processing device in the third embodiment. [Figure 19] FIG. 10 is an explanatory diagram of data transmitted from the processor device to the medical image processing device in the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0025] [First embodiment] FIG. 1 is a diagram showing the configuration of a medical image processing system 10 having an endoscope system 11 according to an embodiment of the present invention. The medical image processing system 10 includes an endoscope system 11, a medical image processing device 17, a display 18, and a user interface (UI) 19. The endoscope system 11 includes an endoscope 12, a light source device 13, a processor device 14, a display 15, and a user interface (UI) 16. The processor device 14 is electrically connected to the light source device 13, the display 15, the user interface 16, and the medical image processing device 17. The medical image processing device 17 is electrically connected to the display 18 and the user interface 19. The processor device 14 and the medical image processing device 17 have programs related to processing such as image processing stored in a program memory (not shown). The medical image processing device 17 is an external device not included in the endoscope system 11 that captures medical videos by endoscopic examination.

[0026] The endoscope 12 has an elongated shape and includes an insertion section 12a that is inserted into the patient's body to acquire images, and an operation section 12b that accepts user operations such as bending the insertion section 12a and zooming when acquiring images, as well as a freeze operation to acquire still images. The freeze operation is realized by pressing a freeze button 12d provided on the operation section 12b. The tip of the insertion section 12a is also provided with a tip section 12c that has an imaging function and that irradiates illumination light and projects treatment tools.

[0027] The light source device 13 is optically connected to the endoscope 12 and supplies illumination light to the endoscope 12 during endoscopic examination. The display 15 displays images acquired by the processor device 14. The user interface 16 is an input device for inputting data to the processor device 14, and may use a keyboard, mouse, foot pedal, gesture recognizer, voice recognizer, etc. Input may be made using input means provided in the medical device, such as a switch on the endoscope 12, rather than the user interface 16. Note that images include moving images, still images, and frame images that make up moving images.

[0028] Unless otherwise specified, white light is used for illumination during endoscopic imaging, and a video signal of 60 frames per second (60 fps) is acquired and the imaging time is recorded. When the video signal is 60 fps, it is preferable to count the time in units of 1 / 100 of a second.

[0029] The medical image processing device 17 is a device capable of transmitting and receiving data to and from the processor device 14, and receives medical video and failure information data. The medical image processing device 17 temporarily stores the received medical video, and extracts and stores failure videos using the failure information. It is preferable to use a built-in SSD (Solid State Drive) for storage. Instead of an SSD, a recording medium such as a USB (Universal Serial Bus) memory or an HDD (Hard Disc Drive) may be used.

[0030] 2, in the processor device 14, a central control unit (not shown) constituted by an image control processor runs programs in a program memory, thereby realizing the functions of an image acquisition unit 21, an input reception unit 22, an output control unit 23, and a fault identification unit 25. In addition, with the realization of the function of the fault identification unit 25, the functions of a fault determination unit 26, a trigger signal creation unit 27, and a still image creation unit 28 are also realized.

[0031] The processor device 14 acquires medical videos and still images captured in real time by the endoscope 12, performs fault detection processing, and displays the images on the display 15. The processor device 14 also transmits a trigger signal containing fault information, such as the type of fault detected by the fault detection processing, to the medical image processing device 17.

[0032] The image acquisition unit 21 receives data such as medical videos captured by the endoscope 12. The acquired medical videos are transmitted to the output control unit 23 and the fault identification unit 25. The input receiving unit 22 is connected to the user interface 16. The output control unit 23 controls the display of the medical videos on the display 15 and the transmission of the medical videos to the medical image processing device 17.

[0033] 3, in the medical image processing device 17, a central control unit (not shown) constituted by an image control processor operates a program in a program memory, thereby realizing the functions of a data acquisition unit 31, an input receiving unit 32, an output control unit 33, a main memory area 34, and a failure video extraction unit 35. In addition, with the realization of the function of the failure video extraction unit 35, the functions of an extraction range setting unit 36, a mode control unit 37, a temporary storage unit 38, an extraction unit 39, and a selection unit 41 are also realized. Furthermore, the extraction unit 39 includes the function of an image information management unit 40, and the selection unit 41 includes the functions of a temporary storage unit for selection 42 and an importance calculation unit 43.

[0034] The fault detection process and generation of the trigger signal performed by the processor device 14 will now be described. The fault determination unit 26 performs fault detection process on the medical video captured by the endoscope 12 to detect whether or not there is a fault in the endoscope 12 and to determine the type of fault. The trigger signal generation unit 27 generates a trigger signal that has information on frame images with faults determined by the fault determination unit 26 and fault information, and has a trigger function that causes the medical image processing device 17 to start extraction processing.

[0035] The fault determination unit 26 performs fault detection processing in real time during the endoscopic examination. When the endoscopic examination starts, the image acquisition unit 21 receives one or a small number of frame images at a time and inputs them to the fault identification unit 25. The frame images input to the fault identification unit 25 are sequentially subjected to fault detection processing by the fault determination unit 26, and a fault scene is detected.

[0036] As shown in FIG. 4, a fault detection process for a medical video 50 captured in vivo and showing consecutive frames in time will be described. The fault determination unit 26 classifies the types of frames constituting the medical video 50 through fault detection process. FIG. 4(A) shows a portion of a group of consecutive frame images constituting the medical video 50, and the fault detection process classifies the frames into one of three types: a normal frame image 51 with no faults, a fault frame image 52 with an abnormality due to a fault, and a fault-free abnormal frame image 53 with an abnormality but not a fault. After classification, information on the fault frame image 52 is sent to the medical image processing device 17 as a trigger signal. Note that the medical video 50 acquired by the processor device 14 is not a video file, but a group of frame images being captured in real time.

[0037] FIG. 4(B) shows the same group of frame images as FIG. 4(A), with each rectangle representing one frame image. The fault detection process identifies a fault scene consisting of multiple fault frame images 52 representing the same fault in the medical video 50. In other words, consecutive fault frame images 52 with the same type of fault and the same features shown in the images are identified as a fault scene representing one fault. In FIG. 4(B), three consecutive frames are considered to be a fault scene, but the number of frame images comprising an actual fault scene is dozens or more, making it a huge number. Furthermore, a fault frame image 52 consisting of only one frame, rather than consecutive frames, can also be identified as a fault scene. Note that fault frame images 52 of the same fault that are not completely consecutive but detected with a frequency of at least a certain level, for example, 80% or more, may also be determined to be one fault scene. The fault video extraction process, which will be described later, is performed for each fault scene, and the first fault frame image 52 in a fault scene is detected by a trigger signal. R This is the timing at which the trigger signal is received, and is the starting point for the extraction process.

[0038] The fault detection process involves detecting fault frame images 52 from frame images in the acquired medical video 50, and fault determination, which determines the type of fault, such as "disconnection," "dirty scope," or "damage to the lens," for the fault frame images 52. The determination result is sent to the trigger signal creation unit 27.

[0039] As shown in FIG. 5, the frame images classified by the fault detection process each have different characteristics. As shown in FIG. 5(A), a normal frame image 51 is a frame image in which no abnormality was detected. As shown in FIG. 5(B), a fault frame image 52 is a frame image in which a fault of the endoscope 12 was detected, such as a state in which a "disconnection" causes a broken line C to appear as a vertical or horizontal line in the image, or a state in which a portion of the image is filled in regardless of the observation target due to "scope contamination," resulting in the inclusion of a non-lesion abnormal region T. Furthermore, as shown in FIG. 5(C), a fault-free abnormal frame image 53 is a frame image that is abnormal but free of faults, such as a state in which the image is partially or entirely obscured due to "external noise," or a state in which a lesion region R is displayed in the image as a severe "lesion." The fault-free abnormal frame image 53 is treated in the same way as the normal frame image 51 in the extraction process.

[0040] The fault detection process is performed using, for example, the functions of a trained model required for the fault detection process. That is, the fault determination unit 26 has a computer algorithm consisting of a neural network that performs machine learning, and performs specific inference to detect the presence or absence of a fault for each frame image of the input medical video 50 according to the learning content, and to determine the type of fault if a fault is present. It is preferable that the inference results include not only the classification results of the frame images and the type of fault, but also information such as the degree of match with the learning content previously learned.

[0041] The trigger signal creation unit 27 creates failure information and a trigger signal having a trigger function for each detected failure frame image 52. The failure information includes information such as the type of failure in the failure frame image 52, the scale of the failure, and the failure scene formed by consecutive failure frame images 52, and the trigger function is a trigger that starts the process of extracting a failure video from the medical video 50 in the medical image processing device 17. Since the failure detection process and trigger signal creation are performed in real time, the trigger signal is created in conjunction with the detection of the failure frame image 52. The created trigger signal is sent to the medical image processing device 17 via the output control unit 23.

[0042] The still image creation unit 28 creates a failure still image, which is a still image of the failure frame image 52 detected by the failure detection process. The failure still image is preferably created simultaneously with the trigger signal. The created failure still image is transmitted to the medical image processing device 17 via the output control unit 23. Note that only the first failure still image is created from the failure frame images 52 of consecutive and same type of failure. Made by Growth do Good too.

[0043] As shown in FIG. 6 , a medical video 50 is transmitted to the display 15, and the medical video 50 and a trigger signal are transmitted to the medical image processing device 17 via the output control unit 23 of the processor device 14. Data transmission may be wired or wireless. In the wired case, the medical video 50 may be transmitted using a DVI (Digital Visual Interface) as a video transmission line, and the trigger signal may be transmitted using RS232c (Recommended Standard 232 version C) as a trigger transmission line, or the medical video 50 and the trigger signal may be transmitted to the medical image processing device 17 using a USB cable. The data transmitted to the medical image processing device 17 is received by the data acquisition unit 31. Note that the medical video 50 transmitted to the display 15 and the medical image processing device 17 is the same, so the data may be transmitted to the medical image processing device 17 via the display 15.

[0044] Since the medical video 50 is captured in real time, data is constantly transmitted, but the trigger signal is generated and transmitted only when a failure is detected. Since the medical video 50 transmitted to the medical image processing device 17 does not contain failure information, the medical image processing device 17 identifies the failure frame image 52 by comparing it with the trigger signal.

[0045] As shown in FIG. 7, the display 15 constituting the endoscope system 11 plays back a medical video 50 and displays an image display area 60 where the captured content can be confirmed, and an image information display field 61 where image information of the played back medical video 50 is displayed. The image display area 60 performs real-time playback during an endoscopic examination, and the image information displayed in the image information display field 61 includes, for example, a patient ID 62, a patient name 63, an endoscope type, and an operation history. In FIG. 7, the patient ID 62 is "□□□□," the patient name is "△△△△," and the endoscope type is "upper gastrointestinal endoscope." The operation history is preferably displayed in reverse chronological order, displaying the history of operations performed on the operation unit 12b of the endoscope 12 in reverse chronological order. For example, it is preferable to display the most recent operation as the "bend" operation, the second most recent operation as the "zoom" operation, and the third most recent operation as the "freeze" operation.

[0046] The medical image processing device 17, which is an external device to the endoscope system 11, extracts and stores the failure video based on the medical video 50 and trigger signal received in real time from the processor device 14. The medical image processing device 17 acquires the real-time medical video 50 from the endoscope system 11 during the endoscopic examination, one The acquired medical video 50 is temporarily stored in the temporary storage unit 38, and a trigger signal is acquired, which is created by the endoscope system, and has a trigger function for starting extraction and failure information created based on the failure scene. Upon receiving the trigger signal, the extraction unit 39 extracts a failure video having a failure scene from the temporarily stored medical video 50. The extracted failure video is stored in the main memory area 34 of the medical image processing device 17. The medical image processing device 17 also acquires the failure still image created by the still image creation unit 28.

[0047] Because the reception of the trigger signal is asynchronous with the reception of the medical video 50, an error occurs between the timing of the trigger signal and the timing at which the medical image processing device 17 acquires the failure frame image 52 corresponding to the trigger signal. Because the trigger signal is created based on information detected from the medical video 50, it is likely to be delayed from the corresponding frame of the medical video 50. Therefore, it is preferable to perform extraction including this error.

[0048] The extraction range setting unit 36 ​​sets the extraction range for extracting the failure video before the start of the endoscopic examination. In response to reception of a trigger signal, the extraction unit 39 executes extraction processing according to one of the set first to third extraction ranges. The start timing of extraction in the trigger function is determined by information on the reception timing of the trigger signal in the medical image processing device 17, and it is preferable to extract a failure video including scenes before and after the trigger signal in chronological order from the medical video 50 based on the reception timing of the trigger signal.

[0049] The extraction process is performed based on the extraction range set by the extraction range setting unit 36. First extraction range in extracts a group of consecutive frame images within a range of n seconds before and after the trigger signal reception timing as the scenes before and after the trigger signal. The second extraction range extracts a range in which trigger signals of the same type of fault occur consecutively. The third extraction range extracts consecutive frame images within a certain range of n seconds before and after the second extraction range. It is preferable to set the first extraction range when standardizing or shortening the recording time of fault videos, set the second extraction range when comparing a large number of fault videos, and set the third extraction range when comparing fault scenes with normal scenes.

[0050] The fixed periods of n seconds before and after the first extraction range and the third extraction range are preferably, for example, 3 seconds (n=3) or 5 seconds (n=5), which allow comparison with normal frame images 51 before and after the occurrence of a fault, and which do not place a strain on storage. It is also preferable to determine the extraction range of normal frame images 51 based on the type of fault, the duration of the fault, and the average area of ​​the abnormal part caused by the fault in the frame image, determined in the fault detection process. For example, for a fault scene that lasts a long time or a fault scene where the type of fault is "disconnection," the value of n seconds, i.e., the range of fault videos to be extracted, is lengthened.

[0051] For the second and third extraction ranges, the upper limit of the recording range for each failure video is set in advance. In cases where the failure is not temporary and will not recover on its own, or where self-recovery takes time, the recording range of the failure video is determined after a certain period of time has passed. For example, if a failure scene is detected for 5 seconds, that point in time is set as the end of the failure video to be extracted. It is not limited to 5 seconds, but can be 10 seconds or 30 seconds.

[0052] The mode control unit 37 controls the extraction and storage of failure videos. The mode control unit 37 is set to either a normal mode or a storage mode, and in the storage mode, the mode is further classified into one of first to fourth storage modes depending on the conditions and method for extracting and storing failure videos from the medical video 50. The storage mode is preferably set in advance before the endoscopic examination. In the normal mode, the acquired medical video 50 is displayed in real time on the display 15 or the display 18 and stored in the main memory area 34 of the medical image processing device 17.

[0053] In the first storage mode, the extracted failure videos are not selected and are all stored in the main storage area 34. In the second to fourth storage modes, the extracted failure videos are sent to the selection unit 41 and temporarily stored in the selection temporary storage unit 42. keep The fault video is temporarily stored in the memory area 32 and selected for storage in the main memory area 34. In the second storage mode, the video is selected based on the type of fault and the order of fault detection, in the third storage mode, the video is selected based on the type of fault and the severity of the fault, and in the fourth storage mode, the video is selected by the user. to Details of the extraction and selection will be described later.

[0054] The temporary storage unit 38 stores the real-time images of the medical video 50 transmitted from the processor device 14 in a temporary storage area. The temporary storage area is formed in a volatile memory or a non-volatile memory, and if it is a non-volatile memory, it may be physically the same as the main storage area 34. Note that the medical video 50 recording the entire medical examination may only be stored temporarily and does not need to be stored in the main storage area 34.

[0055] The extraction unit 39 receives the trigger signal from the data acquisition unit 31 and acquires a group of frame images to be extracted as a failure video based on the trigger signal from the temporary storage unit 38. 、 That is, the failure frame image 52 is identified in the temporarily saved medical video 50. In accordance with the settings of the trigger signal and extraction range, the failure video is extracted from the medical video 50. It is preferable that the failure video retains information about the trigger signal.

[0056] The trigger signal is transmitted every time a failure frame image 52 is detected, so a large number of trigger signals are received in each failure scene. 、 In other words, there is no need to acquire multiple failure videos of the same failure scene, and if they are acquired, the amount of extraction processing will be enormous, which will put a strain on the storage capacity. Therefore, when starting to extract failure videos, it is preferable to limit the start of extraction from the same failure scene.

[0057] In the extraction process, a certain period of time is set as a limit period for the trigger function that does not start a new extraction process after receiving a trigger signal, and if a trigger signal is received during the limit period, the trigger function is not realized, and the failure information of the failure frame image 52 is received and compared with the medical video 50. Lottery The extraction is realized again after the expiration of the limit period, which begins immediately after the trigger signal is received and ends either at the end of the extraction range or a certain number of seconds after the end.

[0058] As shown in Figure 8, in the extraction process for the first extraction range, a first limit period is set as the limit period for the trigger function. During the first limit period, only failure information is acquired from the received trigger signal. The first limit period ends either n seconds after the timing of receiving the trigger signal, which is the end of the first extraction range, or after the end of the extraction range.

[0059] As shown in Figures 9 and 10, in the extraction process for the second and third extraction ranges, a second limit period is set as the limit period for the trigger function. During the second limit period, new extraction is not initiated for the same type of fault, but fault information is obtained from the trigger signal, and the extraction range is extended when consecutive trigger signals of the same type are received. The second limit period ends simultaneously with or after the extraction range is determined. The longer the number of consecutive trigger signals of the same type is received, the longer the second limit period becomes.

[0060] The image information management unit 40 manages the image information contained in the medical video 50 and the fault information acquired from the trigger signal. The fault information is information relating to the state of the fault, such as the non-lesion abnormal region T in the fault frame image 52, and is linked to the extracted fault video 54. The fault information includes, for example, the timing of receiving the trigger signal, the type of fault, the area of ​​the non-lesion abnormal region T caused by the fault, and the duration of the fault scene.

[0061] In addition to extracting the failure video, the extraction process also edits image information other than the failure information. The failure video 54 is used to analyze the failure of the endoscope 12, but the person in charge of the analysis is not the user of the endoscope 12, but a serviceman from the medical device manufacturer. For this reason, it is necessary to ensure that the patient information contained in the image information of the medical video 50 cannot be obtained from the failure video 54. During the extraction process, the image information management unit 40 processes patient information such as the patient ID 62 and patient name 63 recorded in the medical video 50 so that it cannot be deleted or viewed. Processing includes masking, such as filling in text, and pixelating text.

[0062] Even if the user who performed the endoscopic examination views or analyzes the failure video 54, patient information is not retained when creating data to be handled outside the hospital network. Also, if the failure frame image 52 contains a lesion area R, disease information such as the name of the detected lesion is also treated as patient information. Therefore, the lesion information is also deleted during the extraction process or processed so that it cannot be viewed.

[0063] When a large number of failure scenes are detected from the medical video 50, the extraction and selection processes take time, and it takes time to acquire and check the failure video 54. For this reason, it is preferable to set an upper limit on the number of times that the extraction of the failure video 54 can be performed. When an upper limit is set, extraction stops when a set number of failures, such as 5 or 10, are detected. For example, if the upper limit is set to 5 times, extraction will not be performed even if a failure frame image 52 is detected after the failure video 54 has been extracted. After the upper limit is reached, specifically, there are methods to set the trigger function limit period to unlimited, so that the trigger signal itself will not be accepted, or to switch from save mode to normal mode in the mode control unit and end the failure detection process. Furthermore, an upper limit may be set for each type of failure. Note that the upper limit is number may be set to once to determine whether the endoscope 12 has a malfunction.

[0064] When the storage mode is the first storage mode, selection is not performed, and therefore the failure videos 54 extracted by the extraction unit 39 are stored in the main memory area 34. When the storage mode is the second storage mode to the fourth storage mode, selection of the failure videos 54 to be stored is performed, and the failure videos 54 are transmitted from the extraction unit 39 to the selection unit 41, and temporarily stored in the temporary storage unit for selection 42.

[0065] The selection unit 41 selects the failure videos 54 according to the selection criteria defined for each of the second to fourth storage modes. By performing the selection, it is possible to narrow down the failure scenes that are likely to be useful for analyzing the cause of the failure. The selection is performed by at least one of comparing the failure scenes or failure information in the failure videos 54, or determining whether the failure scenes meet the criteria defined for each storage mode.

[0066] When the selection process is performed, the temporary storage unit for selection 42 temporarily stores each failure video 54 before the selection process is performed. The selection is preferably performed after the extraction process is completed and all the failure videos 54 are temporarily stored. The temporary storage is performed by storing the failure videos 54 in a temporary memory, which is a volatile memory or a nonvolatile memory, in the medical image processing device 17 via the temporary storage unit for selection 42. keepIf the temporary storage area is a non-volatile memory, the data may be temporarily stored in the same area as the main storage area 34.

[0067] The importance calculation unit 43 calculates the importance of each failure video 54. The importance can be expressed, for example, as a percentage (%) or a graded rating (high, medium, low). The more important a failure video 54 is, the more likely it is to be useful for failure analysis, etc. The failure information used to calculate the importance is acquired by the image information management unit 40, which stores failure information of trigger signals.

[0068] The importance is calculated using at least one of the order of trigger signal reception timing, the type of fault, the frequency of fault occurrence, the severity of the fault, the certainty of fault detection, the visibility of the fault, the impact, and the type of endoscope 12. The severity of the fault can be calculated using the area of ​​the non-lesion abnormal region T in the fault frame image 52, the color brightness, saturation, hue, and occurrence location. The visibility of the fault can be calculated from the difference in brightness between the non-lesion abnormal region T and the background subject. The types of endoscope 12 include treatment endoscopes, diagnostic endoscopes, upper gastrointestinal endoscopes, lower gastrointestinal endoscopes (colonoscopes), transnasal endoscopes, etc.

[0069] The output control unit 33 controls the display of the failure video 54 on the display 18. When displaying the failure video 54, the output control unit 33 accepts confirmation of the failure scene and reference to failure information via the user interface 16, as well as editing of image information including the failure information and the video configuration by the user. The temporarily saved medical video 50 may be output to the display 15 or the display 18 and displayed.

[0070] As shown in FIG. 11 , the display 18 displays an image display area 60 that displays the failure video 54 and corresponding failure still images, an image information display area 61 that displays image information including failure information, and a video playback toolbar 64 that displays the playback status of the failure video 54. In the image display area 60, for example, the failure video 54 can be played back in the order in which it was extracted, allowing the user to confirm the details of the failure. The failure information displayed in the image information display area 61 may include, for example, the type of failure, the duration of the failure scene, the average area of ​​the non-lesion abnormal region T, and the order of trigger signal reception timing. During the extraction process, personal information contained in the image information of the medical video 50 is processed to prevent viewing. For example, in FIG. 7, the patient ID 62 displayed as "□□□□" and the patient name 63 displayed as "△△△△" are irreversibly processed to make the text unreadable.

[0071] 12, in addition to the failure video 54, the display 18 may also display a failure still image 55 corresponding to the failure scene in the failure video 54 in the image display area 60. Since the failure still image 55 shows the failure scene in the failure video 54, it is possible to confirm the state of the failure, for example, the non-lesion abnormal area T.

[0072] Unless otherwise specified, the extraction process in each storage mode described below is performed within the first extraction range. For example, consecutive frame images are extracted for three seconds before and after the timing of the fault discovery, and the fault video 54 is obtained.

[0073] The storage mode is preferably set in advance by the user based on the content of the endoscopic examination, etc. The storage modes include a first storage mode in which no selection process is performed and all of the failure videos 54 extracted for each failure scene are stored in the main memory area 34, and a second to fourth storage mode in which the extracted failure videos 54 are sent to the temporary storage unit for selection 42 to be temporarily stored, and the failure videos 54 to be stored in the main memory area 34 are selected. keep There is a mode.

[0074] In the first storage mode, the medical video 50 temporarily stored in the temporary storage unit 38 fromThe first failure frame image 52 in the failure scene, that is, the failure video 54 is extracted based on the timing of receiving the trigger signal, and all of the extracted failure videos 54 are stored in the main memory area 34.

[0075] 13, in the first storage mode in which no sorting is performed, a case will be described as an example in which failure frame images 52a, 52b, and 52c, which are different failure scenes, are detected from a medical video 50. Based on the trigger signal, a failure video 54a having the failure scene of failure frame image 52a, a failure video 54b having the failure scene of failure frame image 52b, and a failure video 54c having the failure scene of failure frame image 52c are extracted based on the extraction range setting and stored in the main memory area 34. In the case of the first extraction range, failure videos 54 that are not affected by the length of the failure scene are each extracted.

[0076] The extraction and selection of the failure videos 54 in the second to fourth storage modes will be described below. All extracted failure videos 54 are temporarily stored in the temporary storage unit for selection 42. The failure videos 54 are selected based on the failure information, and the selected failure videos 54 are stored in the main memory area 34.

[0077] As shown in FIG. 14, a case will be described in which failure frame images 52a, 52b, and 52c, which are different failure scenes but have the same type of failure, are detected from a medical video 50 by the failure detection process in the second to fourth storage modes for sorting. Based on the trigger signal and the settings of the extraction range, a failure video 54a containing the failure scene of failure frame image 52a, a failure video 54b containing the failure scene of failure frame image 52b, and a failure video 54c containing the failure scene of failure frame image 52c are extracted and temporarily stored in the temporary storage unit for sorting 42. After all failure videos 54 to be sorted are temporarily stored, the sorting unit 41 compares each failure scene and sorts them according to the set sorting criteria. If the failure video 54c is selected, the failure videos 54a and 54b are deleted, and the failure video 54c is stored in the main memory area 34.

[0078] In the second and third storage modes, the failure videos 54 are sorted by failure type. When multiple failures are detected in the failure detection process, at least one failure video 54 for each type is saved in the main memory area 34. Even if multiple failures, including a type of failure that occurs frequently and has a large area of ​​non-lesion abnormal region T and a type of failure that occurs infrequently and has a small area of ​​non-lesion abnormal region T, are detected in the medical video 50, the scenes of each type of failure can be confirmed without missing any of the saved failure videos 54.

[0079] In the second storage mode, the failure videos 54 to be stored in the main memory area 34 are selected based on the type of failure and the chronological order of the timing of receiving the trigger signal in the medical video 50. For example, for each type of failure, the first or last N failure scenes from among the failure scenes contained in each failure video 54, or failure videos 54 corresponding to one failure scene at regular intervals are stored. First failure scene in In the latter case, the time since the start of the endoscopy has been short, making it easier to detect failures other than those caused by the endoscopy, such as scope contamination. In the latter case, if multiple failures occur, it is easier to detect multiple types of failures in a single failure scene. In addition, screening at regular intervals makes it possible to check whether there are any failures that occur throughout the entire endoscopy.

[0080] In the third storage mode, the importance of each failure video 54 is calculated for each type of failure, and the failure videos 54 to be stored in the main memory area 34 are selected based on the importance. The importance calculation unit 43 calculates the importance of each failure scene and associates it with the failure information. The importance indicates the possibility of a serious failure or its usefulness in analyzing the cause of the failure. For example, a calculation result with an importance of 70% or more, or "high," is saved as a failure video 54, and a calculation result with an importance of less than 70% or "low" is deleted. The method of calculating the importance will be described later. Furthermore, instead of evaluating the importance to be equal to or greater than a certain value, a certain number or percentage of failure videos 54 may be selected in descending order of importance from the failure videos 54 temporarily stored in the temporary storage unit for selection 42.

[0081] In the fourth storage mode, the user selects whether or not to individually save the failure video 54 in the main memory area 34. Specifically, the temporarily saved failure video 54 and image information including at least the failure information are displayed on the display 18, and the user checks the played failure video 54 and image information and selects the failure video 54 to individually save in the main memory area 34. User operations in the selection process are performed via the user interface 19, and include methods such as executing play commands and save commands provided in the command area 65 using a keyboard, mouse, or foot pedal. User operations may also be used to edit the image information.

[0082] As shown in FIG. 15, instead of playing the failure videos 54 one by one in order, the failure videos 54 may be displayed in a list in the image display area 60. It is preferable that the image display area 60 displays a list of each failure video 54, and the image information display field 61 displays image information for the selected failure video 54. Whether to save or delete the failure video 54 may be determined based on the image information. When playing back the selected failure video 54, it may be played back at the size displayed in the list, or it may be temporarily enlarged and played back as shown in FIG. 11. It is also preferable that for failure videos 54 that are not currently being played back in the image display area 60, the corresponding failure still images 55 are displayed as thumbnails. It is also possible to play back multiple failure videos 54 simultaneously.

[0083] The selection process is not limited to the contents of the second to fourth storage modes, and may combine the selection conditions of each storage mode. Furthermore, after the failure video 54 is saved in the main memory area 34, it may be displayed on the display 18 for confirmation.

[0084] The sorting process may be performed whenever a failure video 54 is extracted, rather than after the extraction process has been completed when all failure videos 54 have been collected. The most recently temporarily saved failure video 54 is compared in an either / or format with the newly extracted failure video 54, and the unnecessary one is deleted for selection. For example, in the third storage mode, the importance of the temporarily saved mth extracted failure video 54 and the newly extracted m+1th failure video 54 are compared, and the one with the lower importance is deleted. This allows the sorting process to be performed even when time or temporary storage space is limited.

[0085] The function of the selection unit 41 may be located inside the processor device 14. In that case, a trigger signal is sent for the selected fault, so the medical image processing device 17 may always operate in the first storage mode. Furthermore, the selection by the processor device 14 may be performed in conjunction with the selection unit 41 of the medical image processing device 17 to perform further selection. When using multiple selections, it is preferable to perform the selection under different conditions.

[0086] A series of operations for controlling the extraction and storage of a failure video 54 in this embodiment will be described with reference to the flowchart shown in Fig. 16. The endoscope system 11 acquires a real-time medical video 50 captured inside a living body by the endoscope 12 (step ST110). The processor device 14 in the endoscope system 11 performs a failure detection process for detecting a failure frame image 52 from the medical video 50 and determining whether a failure has occurred. A failure still image 55 may be created from the failure frame image 52 (step ST120). Simultaneously with the failure detection process, the medical video 50 is transmitted to the medical image processing device 17 (step ST130). If no failure scene is detected from the medical video 50 by the failure detection process (N in step ST140), it is determined that there is no failure in the endoscope 12 used in the endoscopic examination.

[0087] If a failure is detected in the medical video 50 by the failure detection process (Y in step ST140), a trigger signal containing information on the timing of the failure is created (step ST150). The trigger signal is immediately sent to the medical image processing device after it is created (step ST160). The medical image processing device 17 compares the trigger signal reception timing of the received trigger signal with the medical video 50 saved in real time, and identifies the trigger signal reception timing (step ST170). A failure video 54 containing at least a failure scene is extracted from the medical video 50 according to the set extraction range (step ST180). If a failure still image 55 is not acquired from the failure frame image 52 during failure detection, a failure still image 55 showing the failure scene contained in the failure video is also acquired (step ST190).

[0088] The extracted failure videos 54 may be stored in their entirety, or the failure videos 54 to be stored may be selected. Whether or not selection is performed is determined by the storage mode. When the storage mode is the first storage mode, that is, when the failure videos 54 are not selected (N in step ST200), all the extracted failure videos 54 are stored in the main memory area 34. Protection The process then ends (step ST230).

[0089] Since the selection process involves comparing the failure videos 54 with each other, it is preferable to perform the selection process after the extraction process is completed, i.e., after the endoscopic examination is completed. When selecting failure scenes in the second to fourth storage modes (Y in step ST200), the failure videos 54 are temporarily stored in the temporary storage unit for selection 42 (step ST210). The temporarily stored failure videos 54 are then judged for each storage mode to see if they meet certain criteria, and the failure videos 54 are compared with each other, and the failure videos 54 to be stored are selected (step ST220). The selected failure videos 54 are stored in the main memory area 34, and the process ends (step ST230).

[0090] [Second embodiment] In the first embodiment, the temporary storage area for temporarily storing the medical video 50 captured in real time during an endoscopic examination and the failure video 54 is the same whether it is a volatile memory or a non-volatile memory. No A mode of temporarily storing data in a volatile memory will be described below. Note that a description of the content common to the above embodiment will be omitted.

[0091] The functions of the temporary storage unit 38 and the temporary storage unit for selection 42 may be realized by a non-volatile memory that maintains stored data even when the medical image processing device 17 is not powered on. There may be a case where the power of the endoscope system 11 or the medical image processing device 17 is turned off during an endoscopic examination, or a case where the power of the medical image processing device 17 is turned off after an endoscopic examination is completed before the fault video 54 has been completely saved in the main memory area 34. Even in such cases, the data temporarily saved in the non-volatile memory can be prevented from being lost when the power is turned off.

[0092] When sorting is performed, the extracted failure videos 54 are temporarily stored in the temporary sorting storage unit 42, which is a non-volatile memory of the medical image processing device 17. If the power of the endoscope system 11 or the medical image processing device 17 is turned off during an endoscopic examination, the endoscopic examination is terminated at that point, and when the power is turned on again, sorting of the failure videos 54 begins. After the endoscopic examination is completed, a sorting process is performed, and the selected failure videos 54 are stored in the main memory area 34.

[0093] As shown in FIG. 17, when data is temporarily stored in a temporary storage area which is a nonvolatile memory, the case where the power is turned off during an examination will be described. In Examination A, the endoscopic examination is completed without the power being turned off, and in Examination B, the real-time examination is completed. InspectionThis is an endoscopic examination in which the endoscopic system 11 or the medical image processing device 17 is powered off during the examination. In examination A in which the user operates to terminate the endoscopic examination, the failure video 54 is saved as in the first embodiment. In examination B in which the end of the endoscopic examination is forcibly terminated by powering off rather than by user operation, when the power is turned on again, the failure video 54 is extracted from the medical videos 50 that were temporarily saved in the non-volatile memory at the time the power was turned off. In the second to fourth save modes, selection is also performed, and the failure video 54 is saved in the main memory area 34. By temporarily saving the failure video 54 in the non-volatile memory, it is possible to extract and select the failure video 54 from the medical videos 50 that were captured and temporarily saved regardless of the end status of the endoscopic examination, such as when the power is turned off during the examination.

[0094] In the saving process, after the selection is completed, the selected failure videos 54 are sent from the non-volatile memory to the main memory area 34. However, the power of the medical image processing device 17 may be turned off before the selection is completed or during the saving process, or the connection may be lost if the main memory area 34 is detachable from the medical image processing device 17. If the saving process is interrupted, it may be impossible to distinguish between failure videos 54 that have been saved in the main memory area 34 and failure videos 54 that have not been saved. For this reason, an identifier such as a flag is set when the failure videos 54 are extracted in order to automatically distinguish them.

[0095] When the failure videos 54 are temporarily saved, a different identifier is set for each failure video 54 after the failure videos 54 are extracted. The identifier is preferably a flag or the like, and is set as image information, but is not particularly limited as long as it allows the failure videos 54 to be distinguished from each other. When the interrupted saving process is resumed, the identifier of the failure video 54 saved in the main memory area 34 is checked, and the temporary failure video 54, which is a non-volatile memory, is set as the identifier. keep It is determined whether or not there is a failure video 54 with the same identifier in the area. If there is a failure video 54 with the same identifier as the confirmed identifier, it is not saved and is deleted from the nonvolatile memory.

[0096] If the failure video 54 for which the same identifier has not been confirmed is in the temporary storage area, it is determined that the failure video 54 is not stored in the main memory area 34, and a storage process is performed. Note that the identifier may be used not only when the storage process is interrupted, but also during normal storage process to confirm whether the storage has been performed reliably.

[0097] [Third embodiment] In the third embodiment, a form will be described in which, during the fault detection process, information contained in the trigger signal is embedded in the medical video 50, and a fault video 54 and a fault still image 55 are extracted. Note that a description of the content common to the above embodiments will be omitted. The fault identification unit 25 of the processor device 14 includes a data file in which the medical video 50 is edited in response to the creation of the trigger signal. In case, The function of a trigger signal providing unit (not shown) is realized.

[0098] 18, the processor device 14 edits the medical video 50 captured by the endoscope 12 in real time, assigns a trigger signal to a frame image in which a fault is detected, and transmits the trigger signal to the medical image processing device 17. It is preferable to perform fault detection processing and embed the trigger function and fault information of the trigger signal for the detected fault frame image 52 in the medical video 50 as an identifier such as a fault flag.

[0099] The medical image processing device 17 extracts the failure video 54 and the failure still image 55 based on the trigger function and failure information embedded in the temporarily stored medical video 50 acquired from the processor device of the endoscope system 11. By extracting from the medical video 50 with a failure flag attached, it is possible to eliminate errors between the timing of failure detection and the extracted frame image. The medical video 50 output from the output control unit 23 is preferably one that has undergone failure detection processing. In this case, the frame images captured during the endoscopic examination are displayed on the display 15 with a delay corresponding to the time required for the failure detection processing. If display delays are a problem, the medical video 50 before the failure detection processing may be transmitted from the output control unit 23 to the display 15.

[0100] [Fourth embodiment] In the fourth embodiment, a second medical video is created in the fault detection process by freezing a frame in which a fault is detected from the medical video 50 for a certain period of time, and is transmitted to the medical image processing device 17. Note that a description of the contents common to the above embodiments will be omitted. The fault identification unit 25 of the processor device 14 has the function of a second medical video creation unit (not shown) that creates a second medical video in which the medical video 50 is edited in response to fault detection. And do.

[0101] As shown in Figure 19, when the endoscopic examination begins, the processor device 14 copies the medical video 50 captured by the endoscope 12 in real time, edits the medical video 50, and transmits the edited second medical video to the medical image processing device 17 together with the medical video 50. The second medical video is a video that records the same content as the medical video 50 when no failure is detected, and freezes the video for a certain period of time after a failure is detected when a failure is detected. A trigger signal is also transmitted from the processor device 14 to the medical image processing device 17, separately from the medical video 50 and the second medical video. The second medical video transmitted from the endoscopic system 11 to the medical image processing device 17 together with the medical video 50 is temporarily stored in the temporary storage unit 38.

[0102] The extraction unit 39 extracts the failure video 54 from the medical video 50 and the failure still image 55 from the second medical video at the timing when the trigger signal is received from the endoscope system 11. The timing of the temporary storage of the medical video 50 and the second medical video in the temporary storage unit 38 and the timing of receiving the trigger signal are asynchronous, which causes an error. Since the same failure frame image 52 continues in the failure scene of the second medical video upon reception of the trigger signal, it is possible to obtain the failure still image 55 taken at the time the failure was detected, even though the timing is asynchronous.

[0103] The failure video 54 and failure still image 55 extracted by the same trigger signal are preferably associated with a failure flag or the like and stored in the main memory area 34. The second medical video is preferably not stored after the failure still image 55 is extracted, but is instead deleted.

[0104] As a modified example of the fourth embodiment, a form in which a failure video 54 and a failure still image 55 are extracted by a user operation will be described. During an endoscopic examination, a second trigger signal that serves as a trigger for extraction is generated by a freeze operation in which the user presses the freeze button 12d provided on the operation unit 12b of the endoscope 12. Upon receiving the second trigger signal manually generated from the endoscope system 11, the medical image processing device 17 extracts the failure video 54 from the medical video 50 and extracts the failure still image 55 from the second medical video.

[0105] A second medical moving image in which the image is frozen for a certain period of time by a freeze operation by the user is transmitted to the medical image processing device 17. In addition, a second trigger signal is generated by the trigger signal generating unit 27 by the freeze operation and transmitted to the medical image processing device 17. The medical image processing device 17 No. 2 When the trigger signal is received, the extracting unit 39 extracts the failure video 54 from the medical video 50 and the failure still image 55 from the second medical video, and stores them in the main storage area 34.

[0106] It is preferable that the failure video 54 or failure still image 55 extracted in response to the trigger signal and the failure video 54 and failure still image 55 extracted in response to the second trigger signal are processed and saved so that they can be visually distinguished by the user. For example, when extracted in response to the second trigger signal, it is preferable to process the images of the failure video 54 and failure still image 55 so that they are surrounded by a red frame or to add a symbol such as "△" to the upper right corner of the image. The word "manual" may also be added to the file name.

[0107] In the above embodiment, the hardware structure of the processing units that perform various processes, such as the central control unit, image acquisition unit 21, input receiving unit 22, output control unit 23 realized by the processor device 14, and the fault determination unit 26, trigger signal creation unit 27, still image creation unit 28, and second medical video creation unit included in the fault identification unit 25, and the central control unit, data acquisition unit 31, input receiving unit 32, output control unit 33 realized by the medical image processing device 17, and the extraction range setting unit 36, mode control unit 37, temporary storage unit 38, extraction unit 39, image information management unit 40, selection unit 41, temporary storage unit for selection 42, and importance calculation unit 43 included in the fault video extraction unit 35, are various processors as shown below. Various types of processors include a CPU (Central Processing Unit), which is a general-purpose processor that executes software (programs) and functions as various processing units, a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacturing such as an FPGA (Field Programmable Gate Array), and a dedicated electrical circuit, which is a processor with a circuit configuration designed specifically for executing various processes.

[0108] A single processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, multiple FPGAs, or a combination of a CPU and an FPGA). Also, multiple processing units may be configured with a single processor. Examples of multiple processing units configured with a single processor include, first, a configuration in which one processor is configured with a combination of one or more CPUs and software, as typified by client or server computers, and this processor functions as multiple processing units. Second, a configuration in which a processor is used to realize the functions of an entire system including multiple processing units on a single IC (Integrated Circuit) chip, as typified by a System on Chip (SoC). In this way, the various processing units are configured with one or more of the above-mentioned various processors as a hardware structure.

[0109] Furthermore, the hardware structure of these various processors is, more specifically, an electric circuit formed by combining circuit elements such as semiconductor elements, and the hardware structure of the memory unit is a storage device such as a hard disk drive (HDD) or a solid state drive (SSD). [Explanation of symbols]

[0110] 10 Medical image processing system 11 Endoscopy System 12 Endoscopy 12a Insertion part 12b Operation section 12c Tip 12d Freeze button 13 Light source device 14 Processor unit 15 Display 16 User Interface 17 Medical image processing equipment 18 Display 19 User Interface 21 Image acquisition unit 22 Input receiver 23 Output control section 25 Fault identification section 26 Failure determination section 27 Trigger signal generator 28 Still image creation section 31 Data Acquisition Section 32 Input receiver 33 Output control section 34 Main storage area 35 Fault video extraction section 36 Extraction range setting section 37 Mode control section 38 Temporary storage section 39 Extraction part 40 Image Information Management Department 41 Sorting Department 42 Temporary storage section for selection 43 Importance calculation part 50 Medical Videos 51 Normal frame image 52 Faulty frame images 52a Failure frame image 52b Failure frame image 52c Failure frame image 53 No fault abnormal frame image 54 Malfunction Video 54a Breakdown video 54b breakdown video 54c malfunction video 55 Failure still image 60 Image display area 61 Image information display field 62 Patient ID 63 Patient Name 64 Video Playback Toolbar 65 Command Area C. Disconnection R Lesion area T Non-lesional abnormal area

Claims

1. An endoscope system comprising: an external device having a program memory and a processor; By running the program in the program memory, the processor acquiring real-time medical video from the endoscopy system during an endoscopy examination; receiving a trigger signal having information about a failure occurrence generated based on a failure scene in the medical video from the endoscope system; Temporarily store the medical video; extracting a failure video including the failure scene from the temporarily stored medical video based on a timing of receiving the trigger signal; The medical image processing system stores the failure video in a main memory area.

2. The processor: determining a start timing of the extraction based on the reception timing; 2. The medical image processing system according to claim 1, wherein the failure video including scenes before and after the failure video in chronological order is extracted from the medical video based on the reception timing.

3. The processor: After receiving the trigger signal, set a limit period for the trigger signal; 3. The medical image processing system according to claim 1, wherein the extraction does not start if the trigger signal is received within the limited period.

4. The processor:

4. The medical image processing system according to claim 1, wherein an upper limit is set for the number of times the extraction is performed.

5. The processor: Temporarily save the failure video, 5. The medical image processing system according to claim 1, wherein the failure videos to be stored are selected.

6. The processor:

6. The medical image processing system according to claim 5, wherein the sorting is performed based on the type of failure and the order of the reception timings.

7. The processor: Calculating the importance of the failure video based on the information on the occurrence of the failure; 7. A medical image processing system according to claim 5, wherein the selection is performed based on the importance.

8. The processor:

8. The medical image processing system according to claim 7, wherein the importance is calculated based on the visibility of the failure or the severity of the failure.

9. The processor:

9. The medical image processing system according to claim 7, wherein the importance is calculated based on the type of endoscope.

10. The processor:

10. The medical image processing system according to claim 5, wherein the selection is performed in an either / or format between the temporarily stored failure video and the newly created failure video by the extraction.

11. The processor:

11. The medical image processing system according to claim 1, wherein, at the time of said extraction, personal information contained in the image information of said medical video is deleted or processed so as not to be viewable.

12. The processor:

12. The medical image processing system according to claim 1, wherein the medical video is temporarily stored in a non-volatile memory.

13. The processor:

13. The medical image processing system according to claim 12, wherein the malfunction video temporarily stored in the nonvolatile memory is selected regardless of the completion status of the endoscopic examination.

14. The processor: When extracting the failure video, a different identifier is set for each of the failure videos; Check the identifier of the failure video stored in the main storage area; 14. The medical image processing system according to claim 12, wherein the failure video having the same identifier as the confirmed identifier is deleted from the nonvolatile memory.

15. 1. A method of operating a medical imaging system comprising an external device having a processor and an endoscopy system, the method comprising: acquiring real-time medical video from the endoscopy system during an endoscopy examination; receiving a trigger signal from the endoscope system, the trigger signal having information about a failure that has been generated based on a failure scene in the medical video; Temporarily storing the medical video; extracting a failure video including the failure scene from the temporarily stored medical video based on a timing of receiving the trigger signal; and storing the failure video in a main memory area.

Images