KR20240018193A - Method for processing images related to importance, server and recording medium - Google Patents

Abstract

In one embodiment, acquiring a subject video related to a medical practice; Obtaining image information about the target video; Obtaining non-image information, including at least one of vital signals for the medical practice, attribute information for the target video, and audio information for the target video; Obtaining characteristic information about the target video based on the video information and the non-video information; and performing image processing on the target video based on importance determined based on the characteristic information. A method, device, and recording medium including a step are disclosed.

Description

Image processing method, server and recording medium related to importance {Method for processing images related to importance, server and recording medium}

This disclosure relates to the field of technology for performing image processing based on the importance of images related to medical practice, and specifically, processing of images based on the importance derived using image information and non-image information about images. It is related to the technical field that performs.

Recently, endoscopic devices equipped with cameras have been used in various fields, and video devices that are inserted into the patient's body or film the procedure or surgery site have become miniaturized and popular, and the number of cases of video acquisition in internal and surgical surgeries is increasing. In addition, with the recent development of big data and artificial intelligence, the number of hospitals and doctors who want to process videos into medical information content and conduct various studies, such as standardization studies on technology and evaluation studies on the usability of tools based on this, has increased. There is a demand for video storage and quick retrieval of key scenes.

Meanwhile, the importance of videos acquired in various medical environments (e.g., surgery videos) may vary depending on the content and related matters, and the methods of managing and handling the videos, such as storage period and storage method, depending on the importance. In addition, although it may be different, in the past, acquired videos are simply stored, and technology for deriving the importance of the video and managing and handling the video according to the derived importance is not provided.

Accordingly, in the past, an inconvenient method was used, such as the user directly classifying the video and, if necessary, the user directly reviewing the content of the video and assigning importance to it. This is a technology that can effectively solve the problems of the prior art. The provision of is urgently needed.

Korean Patent No. 10-2237198 (2021.04.01), artificial intelligence-based medical image reading service system

The problem to be solved in this disclosure is to determine the importance of the video based on the analysis results of the video related to medical practice, and determine the storage period, storage location, file naming, etc. This is to make it easy to manage.

The problems to be solved by this disclosure are not limited to the technical problems described above, and other technical problems may exist.

As a technical means for achieving the above-described technical problem, an image processing method related to importance according to the first aspect of the present disclosure includes the steps of acquiring a target video related to medical practice; Obtaining image information about the target video; Obtaining non-image information, including at least one of vital signals for the medical practice, attribute information for the target video, and audio information for the target video; Obtaining characteristic information about the target video based on the video information and the non-video information; and performing image processing on the target video based on the importance determined based on the characteristic information.

Additionally, the step of performing the image processing may determine at least one of a storage location, storage period, index, and file name for the target video based on the characteristic information and the importance.

In addition, the step of performing the image processing includes performing image processing on the target video so that the higher the importance, the higher the security level of the storage location, and the longer the storage period, and storing the index and the file name in the characteristic information. It can be decided based on

Additionally, in the step of acquiring the characteristic information, the characteristic information may be acquired based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for the image information.

Additionally, in the step of determining the characteristic information, the characteristic information may be obtained based on an emotion analysis result based on the voice information.

Additionally, the importance may be determined based on the length of a section where the first risk section in the target video determined according to the image information and the second risk section in the target video determined according to the emotion analysis result overlap.

Additionally, performing the image processing may include determining a first risk level for the first risk section; determining a second risk level for the second risk interval; determining a third risk level corresponding to a product of the first risk level and the second risk level; and determining the importance to correspond to a value obtained by multiplying the length of the overlapping section by the third risk level.

An image processing device related to importance according to a second aspect of the present disclosure includes a receiving unit that acquires a target video related to medical practice; And acquiring image information for the target video, and acquiring non-image information, including at least one of vital signals for the medical action, attribute information for the target video, and audio information for the target video, It may include a processor that acquires characteristic information about the target video based on video information and the non-video information, and performs image processing on the target video based on the importance determined based on the characteristic information. .

Additionally, the processor may determine at least one of a storage location, storage period, index, and file name for the target video based on the characteristic information and the importance.

In addition, the processor may perform image processing on the target video so that the higher the importance, the higher the security level of the storage location, and the longer the storage period, and determine the index and the file name based on the characteristic information. there is.

Additionally, the characteristic information may be obtained based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information regarding the image information.

Additionally, the processor may obtain the characteristic information based on an emotion analysis result based on the voice information.

In addition, the importance may be determined based on the length of a section where the first risk section in the target video determined according to the image information and the second risk section in the target video determined according to the emotion analysis result overlap.

Additionally, the processor determines a first risk level for the first risk interval, determines a second risk level for the second risk interval, and calculates a value obtained by multiplying the first risk level and the second risk level. The corresponding third risk level can be determined, and the importance can be determined to correspond to a value obtained by multiplying the length of the overlapping section and the third risk level.

According to a third aspect of the present disclosure, the method may include a computer-readable recording medium recording a program for executing the method of the first aspect on a computer.

According to an embodiment of the present disclosure, the user is not required to manually determine the importance of each video.

In addition, video management becomes easier by processing videos with priority for videos judged to be relatively important.

The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned may be clearly understood by those skilled in the art from the description below.

FIG. 1 is a diagram illustrating a medical image processing system in which a device operates in conjunction with a network, according to an embodiment.
Figure 2 is a block diagram schematically showing the configuration of a device according to an embodiment.
Figure 3 is a flowchart illustrating each step in which a device performs image processing on a target video based on importance, according to an embodiment.
FIG. 4 is a flowchart illustrating each step in which a device determines at least one of a storage location, storage period, index, and file name for a target video, according to an embodiment.
Figure 5 is a flowchart illustrating each step in which a device acquires characteristic information according to an embodiment.
FIG. 6 is a diagram schematically illustrating an example in which a device acquires image information from a target video, according to an embodiment.
FIG. 7 is a diagram schematically illustrating an example in which a device acquires audio information from a target video according to an embodiment.

Advantages and features in the present disclosure, and methods for achieving them, will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the disclosure is complete and to those skilled in the art. It is provided to provide complete information.

The terms used herein are for describing embodiments and are not intended to limit the disclosure. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. As used in the specification, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other elements in addition to the mentioned elements. Like reference numerals refer to like elements throughout the specification, and “and/or” includes each and every combination of one or more of the referenced elements. Although “first”, “second”, etc. are used to describe various components, these components are of course not limited by these terms. These terms are merely used to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may also be the second component within the technical spirit of the present disclosure.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined.

Spatially relative terms such as “below”, “beneath”, “lower”, “above”, “upper”, etc. are used as a single term as shown in the drawing. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms that include different directions of components during use or operation in addition to the directions shown in the drawings. For example, if a component shown in a drawing is flipped over, a component described as “below” or “beneath” another component will be placed “above” the other component. You can. Accordingly, the illustrative term “down” may include both downward and upward directions. Components can also be oriented in other directions, so spatially relative terms can be interpreted according to orientation.

Hereinafter, embodiments will be described in detail with reference to the drawings.

FIG. 1 is a diagram illustrating a medical image processing system in which a device 100 operates in conjunction with a network, according to an embodiment.

As shown in FIG. 1, the medical image processing system includes an information acquisition device 110, a device 100, an external server 130, a storage medium 140, a communication device 150, a virtual server 160, and a user. It may include a terminal 170 and a network.

However, those skilled in the art will understand that other general-purpose components other than those shown in FIG. 1 may be included in the medical image processing system. For example, a medical image processing system may further include a blockchain server (not shown) that operates in conjunction with a network. Alternatively, according to another embodiment, those skilled in the art may understand that some of the components shown in FIG. 1 may be omitted.

The device 100 according to an embodiment may operate in conjunction with a medical image processing system, and operations performed through the medical image processing system may also be performed through the device 100. Additionally, the device 100 may obtain information related to medical procedures such as surgery from the information acquisition device 110. The information acquisition device 110 may include, but is not limited to, a photographing device, a recording device, a biological signal acquisition device, etc. Biological signals may include signals obtained from living organisms, such as body temperature signals, pulse signals, respiration signals, blood pressure signals, electromyography signals, and brain wave signals, without limitation. The imaging device, which is an example of the information acquisition device 110, may include a first imaging device (e.g., CCTV, etc.) for photographing the entire operating room situation and a second imaging device (e.g., endoscope, etc.) for intensively photographing the surgical site. may, but is not limited to this.

The device 100 according to one embodiment may acquire a target video (video, still image, etc.), which is an image related to a medical procedure such as surgery, from the information acquisition device 110. The device 100 may perform image processing on the acquired image. Image processing according to an embodiment may include naming, encoding, storage, transmission, editing, metadata creation, storage location, and storage period for each image, but is not limited thereto.

The device 100 according to one embodiment may transmit medical treatment-related information obtained from the information acquisition device 110 as is or as updated information to the network. Transmission information transmitted by the device 100 to the network may be transmitted to external devices 130, 140, 150, 160, and 170 through the network. For example, the network transmits the transmission information sent by the device 100 to the network as is, such as the external server 130, the storage medium 140, the communication device 150, the virtual server 160, and the user terminal 170. Alternatively, it can be updated and transmitted. Device 100 may also receive information (eg, feedback information, update request, etc.) received from external devices 130, 140, 150, 160, and 170. The communication device 150 may refer to a device used for communication without limitation (eg, a gateway), and the communication device 150 may communicate with a device that is not directly connected to the network, such as the user terminal 180.

The device 100 according to one embodiment may include an input unit, an output processor, a memory, etc., and may also include a display device (not shown), as will be described later. For example, through the display device, the user can view communication status, memory usage status, power status (e.g., battery state of charge, external power supply, etc.), thumbnails for stored videos, currently operating mode, etc. You can check, etc. Meanwhile, display devices include liquid crystal display, thin film transistor-liquid crystal display, organic light-emitting diode, flexible display, and 3D display. display), electrophoretic display, etc. Additionally, the display device may include two or more displays depending on the implementation type. Additionally, when the touchpad of the display has a layered structure and is configured as a touch screen, the display can be used as an input device in addition to an output device.

Additionally, networks may communicate with each other through wired or wireless communication. For example, a network may be implemented as a type of server and may include a Wi-Fi chip, Bluetooth chip, wireless communication chip, NFC chip, etc. Of course, the device 100 can communicate with various external devices using a Wi-Fi chip, Bluetooth chip, wireless communication chip, NFC chip, etc. Wi-Fi chips and Bluetooth chips can communicate using Wi-Fi and Bluetooth methods, respectively. When using a Wi-Fi chip or a Bluetooth chip, various connection information such as SSID and session key are first transmitted and received, and various information can be transmitted and received after establishing a communication connection using this. Wireless communication chips can perform communication according to various communication standards such as IEEE, ZigBee, 3G (3rd Generation), 3GPP (3rd Generation Partnership Project), and LTE (Long Term Evolution). The NFC chip can operate in the NFC (Near Field Communication) method using the 13.56MHz band among various RF-ID frequency bands such as 135kHz, 13.56MHz, 433MHz, 860~960MHz, 2.45GHz, etc.

The input unit according to one embodiment may refer to a means through which a user inputs data to control the device 100. For example, the input unit includes a key pad, dome switch, and touch pad (contact capacitive type, pressure resistance type, infrared detection type, surface ultrasonic conduction type, integral tension measurement type, There may be a piezo effect method, etc.), a jog wheel, a jog switch, etc., but it is not limited thereto.

The output unit according to one embodiment may output an audio signal, a video signal, or a vibration signal, and the output unit may include a display device, a sound output device, and a vibration motor.

The user terminal 170 according to an embodiment may include, but is not limited to, various wired and wireless communication devices such as a smartphone, SmartPad, and tablet PC.

The device 100 according to an embodiment may update medical practice-related information acquired from the information acquisition device 110. For example, the device 100 may perform naming, encoding, storage, transmission, editing, metadata generation, storage location, and storage period determination for the image acquired from the information acquisition device 110. As an example, the device 100 may name an image file using metadata (eg, creation time) of the acquired image. As another example, the device 100 may classify images related to medical procedures obtained from the information acquisition device 110. The device 100 can use learned AI to classify images related to medical procedures based on various criteria such as type of surgery, operator, and location of surgery.

FIG. 2 is a block diagram schematically showing the configuration of the device 100 according to an embodiment.

Referring to FIG. 2, device 100 may include a receiver 210 and a processor 220.

In one embodiment, the receiver 210 may obtain a target video related to medical treatment from the information acquisition device 110. For example, the target video contains general information related to the patient's surgery, such as surgery scenes, tools used in surgery, type of surgery, surgical method, patient's physical condition at the time of surgery, images of the patient's body, and audio about the surgical situation. It could be a video.

In one embodiment, the processor 220 acquires image information about the target video, and non-image information including at least one of vital signals for medical operations, attribute information about the target video, and audio information about the target video. , obtain characteristic information about the target video based on image information and non-image information, and perform image processing on the target video based on the importance determined based on the characteristic information.

Additionally, the processor 220 may determine at least one of the storage location, storage period, index, and file name for the target video based on characteristic information and importance.

Additionally, the processor 220 may perform image processing on the target video so that the higher the importance, the higher the security level of the storage location and the longer the storage period, and determine the index and file name based on the characteristic information.

Additionally, the processor 220 may obtain characteristic information based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for image information.

Additionally, the processor 220 may obtain characteristic information based on an emotion analysis result based on voice information.

Additionally, the processor 220 determines a first risk level for the first risk interval, determines a second risk level for the second risk interval, and determines a value corresponding to the product of the first risk level and the second risk level. The third risk level can be determined, and the importance can be determined to correspond to the value multiplied by the length of the overlapping section and the third risk level.

In one embodiment, the importance of the target video is determined based on overall information related to the surgery (e.g., type of surgery, difficulty of the surgery, patient's physical condition, degree of damage when the target video is leaked, surgical tools used, etc.) can indicate the degree of importance.

In addition, those skilled in the art can understand that other general-purpose components in addition to the components shown in FIG. 2 may be further included in the device 100. For example, the device 100 may further include a display (not shown) that outputs the target video. Alternatively, according to another embodiment, those skilled in the art may understand that some of the components shown in FIG. 2 may be omitted.

The device 100 according to an embodiment can be used by a user or worker, and can be any device equipped with a touch screen panel, such as a mobile phone, smartphone, PDA (Personal Digital Assistant), PMP (Portable Multimedia Player), tablet PC, etc. It can be linked to various types of handheld wireless communication devices, and can also be connected to devices that have a basis for installing and running applications, such as desktop PCs, tablet PCs, laptop PCs, and IPTVs including set-top boxes. Can be included or linked.

The device 100 may be implemented as a terminal such as a computer that operates through a computer program to realize the functions described in this specification.

The device 100 according to an embodiment may include a server (not shown) corresponding to a medical image processing system, but is not limited thereto. A server corresponding to a medical image processing system according to an embodiment may directly perform image processing or provide an application that supports this.

Hereinafter, the description will focus on an embodiment in which the device 100 independently performs image processing, but as described above, it may be performed through interworking with a server corresponding to a medical image processing system. That is, the device 100 and the server corresponding to the medical image processing system according to one embodiment may be integrated in terms of their functions, and the server corresponding to the medical image processing system may be omitted, and either implementation It can be seen that the example is not limited.

The above-mentioned embodiments will be described in detail below with reference to FIGS. 3 to 5.

FIG. 3 is a flowchart illustrating each step in which the device 100 performs image processing on a target video based on importance, according to an embodiment.

In step S310, the device 100 may acquire a target video related to medical treatment.

In step S320, the device 100 may obtain image information about the target video.

For example, the image information may include various information related to the surgery in the video, such as the surgical situation, type of surgery, operator performing or assisting the surgery, bleeding monitoring information, vital signal monitoring information, and surgical tool monitoring information.

In step S330, the device 100 may acquire non-image information including at least one of vital signals for medical treatment, attribute information for the target video, and audio information for the target video.

For example, vital signals for medical practice may represent the entire data of signals (e.g., heart rate, etc.) indicating the physical condition and changes of a patient undergoing surgery within a target video, and attribute information about the target video is a type of metadata. It can include video length, video capacity, video shooting time, video saving time, video title, extension, storage location, etc. Additionally, the voice information for the target video may include information about the operator's voice acquired during the surgery in the target video. Non-image information may include at least one of vital signals, attribute information, and voice information.

In step S340, the device 100 may obtain characteristic information about the target video based on image information and non-image information.

For example, the characteristic information may include a first risk interval for the target video, a second risk interval, a first risk level for the first risk interval, a second risk level for the second risk interval, and an emotion analysis result based on voice information. It can include information about video and non-video characteristics related to the surgery within the video, such as the section where urgency appears, the degree of urgency, surgical tools used, vital signs, and bleeding status.

In one embodiment, the device 100 may acquire characteristic information based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for image information.

For example, characteristic information obtained according to image information includes the type of surgical tool used, the time point and section at which each surgical tool was used, the time point and section when vital signals changed rapidly, and the time point and section when bleeding occurred above the standard value. It can be included.

Additionally, the device 100 may obtain characteristic information based on an emotion analysis result based on voice information.

For example, emotion analysis results are obtained through analysis of voice information extracted from the target video (e.g., voice graph analysis, etc.), and include the surgical situation of the target video, urgency, calmness, stability, and difficulty for the operator, etc. It may include whether emotions appear and the results of quantitative analysis of the emotions.

In step S350, the device 100 may perform image processing on the target video based on the importance determined based on the characteristic information.

For example, image processing may be an operation that determines one of the storage location, storage period, index, and file name for the target video based on characteristic information and importance.

A detailed description of an embodiment of determining the storage location, storage period, index, and file name for the target video will be described below with reference to FIG. 4.

In one embodiment, the device 100 may determine the importance based on the length of the section overlapping the first risk section in the target video determined according to the image information and the second risk section in the target video determined according to the emotion analysis result. .

For example, the device 100 may determine the first risk section in the target video based on the image information, such as a section where the amount of bleeding is greater than a preset level or a section where a sudden change in the vital signal occurs.

In addition, the device 100 selects a second risk section in the target video based on a section in which the urgency value of the operator's voice according to the target video is more than a preset value and a section in which the value for the emotional state indicating a dangerous situation is more than a preset value. can be decided.

In addition, when the first and second risk sections overlap, it can be viewed as more accurately indicating a dangerous situation, so the target video or the first risk section is selected based on the length of the section where the first and second risk sections overlap. and the importance of the second risk interval can be determined.

In more detail, the device 100 may determine the first risk level for the first risk section based on image information, and determine the second risk level for the second risk section based on the emotion analysis result. For example, the device 100 determines the risk level for the first risk section as the first risk level according to the case where the amount of bleeding according to the first risk section is greater than a preset level or when a sudden change in vital signals occurs, etc. The risk level for the second risk section can be set according to the case where the urgency value of the operator's voice according to the second risk section is more than the preset value, the value of the emotional state indicating a dangerous situation is more than the preset value, etc. 2 It can be determined by risk level.

Thereafter, the device 100 determines a third risk level corresponding to the value multiplied by the first risk level and the second risk level, and determines the length of the section where the first risk section and the second risk section overlap and the third risk level. The importance can be determined to correspond to the value multiplied by . By doing this, the importance of the target video can be determined according to the length of the section where the first and second risk sections overlap.

In one embodiment, the device 100 assigns high weight to vital signal monitoring information, bleeding monitoring information, attribute information, voice information, and surgical tool monitoring information in that order, and determines the importance of the target video based on the assigned weight. You can decide.

For example, the more rapid the change in the physical condition of a patient undergoing surgery is shown in the video, the easier it is to understand how to respond to an emergency situation. If the video is leaked, damages such as lawsuits are expected, so it is desirable to manage it with the utmost importance. In this regard, the highest weight may be given to vital signal monitoring information.

In addition, it can be determined whether the surgery is a risky surgery depending on whether the amount of bleeding is large or small, and the more dangerous the surgery, the more desirable it is to manage it based on a high level of security, so it is the second highest priority for bleeding monitoring information. Weights may be assigned.

In addition, because the target video can be easily found and identified according to the attribute information, and the target video can be easily managed accordingly, the attribute information may be given a high 3rd place weight.

In addition, based on the result of emotional analysis of the voice information, it is possible to determine whether the operator's voice is urgent or stable, and based on this, it is easy to determine the importance, so voice information can be given a high weight of 4th priority.

In addition, depending on the type of surgical tool, the degree of difficulty or importance of the surgery can be determined, but given that the degree to which surgical tools affect importance is relatively low compared to other factors, it ranks 5th in surgical tool monitoring information. Weights may be assigned.

The device 100 can more easily perform image processing on the target video by determining the importance based on the differently assigned weights.

FIG. 4 is a flowchart illustrating each step in which the device 100 determines at least one of a storage location, storage period, index, and file name for a target video, according to an embodiment.

In step S410, the device 100 may determine at least one of a storage location, storage period, index, and file name for the target video based on characteristic information and importance.

Additionally, in step S420, the device 100 may perform image processing on the target video so that the higher the importance, the higher the security level of the storage location and the longer the storage period.

For example, if the importance of the target video is a first value, the target video is stored in a storage location corresponding to the first level (e.g., password input, etc.), which is the security level corresponding to the first value, and the target video is stored in a storage location corresponding to the first level (e.g., password input, etc.), and the importance is set to the second value. If it is a value, the target video can be stored in a storage location corresponding to the second level, which is the security level corresponding to the second value (e.g., password input and encryption key method, etc.).

In addition, when the importance of the target video is a first value, the target video may be stored in a storage location corresponding to the importance for a first period (e.g., 1 week), which is a storage period corresponding to the first value, and the target video may be stored in a storage location corresponding to the importance. In the case of a value, the target video may be stored in a storage location corresponding to the importance for a second period (eg, 2 weeks), which is a storage period corresponding to the second value.

In step S430, the device 100 may determine the index and file name for the target video based on characteristic information.

For example, the index for the target video is a kind of bookmark concept to easily find the target video determined by the surgical situation based on image information, type of surgery, video length, image capacity, and video shooting time according to non-image information. It may be information from Additionally, the device 100 may determine the file name based on characteristic information, such as “surgery type_surgery name_surgery date_....”.

FIG. 5 is a flowchart illustrating each step in which the device 100 acquires characteristic information according to an embodiment.

In step S510, the device 100 may obtain at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for image information.

For example, characteristic information obtained according to image information includes the type of surgical tool used, the time point and section at which each surgical tool was used, the time point and section when vital signals changed rapidly, and the time point and section when bleeding occurred above the standard value. It can be included.

In step S520, the device 100 may obtain an emotion analysis result based on voice information.

For example, emotion analysis results are obtained through analysis of voice information extracted from the target video (e.g., voice graph analysis, etc.), and include the surgical situation of the target video, urgency, calmness, stability, and difficulty for the operator, etc. It may include whether emotions appear and the results of quantitative analysis of the emotions.

The device 100 can determine the importance of the target video through the video and audio by acquiring characteristic information based on the video information and audio information.

FIG. 6 is a diagram schematically illustrating an example in which the device 100 acquires image information from a target video according to an embodiment.

For example, the device 100 may obtain surgical tool monitoring information, bleeding monitoring information, and vital signal monitoring information from the target video.

Specifically, the device 100 can determine the surgical tool used for each section or frame, bleeding state and amount, and vital signals through analysis of the target video, and provides the corresponding monitoring information as shown in the diagram of FIG. 6. It can be acquired and output as shown.

Referring to FIG. 6, the device 100 indicates the surgical tools according to the surgical tool monitoring information as “debakey forcep and Potts forcep” in the corresponding scene of the target video, and the bleeding monitoring information as “normal bleeding state, low bleeding amount.” It can be confirmed that the vital signal monitoring information is displayed as “normal”.

In this way, the importance of the target video can be more easily determined by obtaining monitoring information about surgical tools, bleeding, and vital signals from the target video.

FIG. 7 is a diagram schematically illustrating an example in which the device 100 acquires audio information from a target video according to an embodiment.

For example, the device 100 may acquire characteristic information based on an emotion analysis result based on voice information extracted from the target video.

Specifically, the emotion analysis results are obtained through analysis of audio information extracted from the target video (e.g., voice graph analysis, etc.), and emotions such as urgency, calmness, stability, and difficulty for the surgery situation in the target video and the operator, etc. It may include whether or not this appears and the results of quantitative analysis of emotions.

Referring to FIG. 7, the device 100 may obtain and output an emotion analysis result from voice information as shown in the diagram. Referring to the diagram in FIG. 7, the device 100 indicates urgency as “60/100” according to the emotion analysis results, calmness as “”, stability as “5/100”, etc., and accordingly, the target video It is easy to see that my surgical environment is a relatively urgent situation, and based on this, the importance of the target video can be easily determined.

Various embodiments of the present disclosure include one or more instructions stored in a storage medium (e.g., memory) that can be read by a machine (e.g., a display device or computer). It can be implemented as software. For example, the processor 220 of the device (eg, processor 220) may call at least one instruction among one or more instructions stored in the storage medium 140 and execute it. This allows the device to be operated to perform at least one function according to the at least one instruction called. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' only means that the storage medium is a tangible device and does not contain signals (e.g. electromagnetic waves). This term refers to cases where data is stored semi-permanently in the storage medium. There is no distinction between temporary storage cases.

According to one embodiment, methods according to various embodiments disclosed in the present disclosure may be included and provided in a computer program product. Computer program products are commodities and can be traded between sellers and buyers. The computer program product may be distributed in the form of a machine-readable storage medium 140 (e.g., compact disc read only memory (CD-ROM)), or through an application store (e.g., Play Store™) or between two users. It can be distributed (e.g. downloaded or uploaded) directly between devices (e.g. smartphones) or online. In the case of online distribution, at least a portion of the computer program product may be at least temporarily stored or temporarily created in a machine-readable storage medium 140, such as the memory of a manufacturer's server, an application store server, or a relay server. there is.

Although the present invention has been described with reference to the illustrative drawings, it is not limited to the disclosed embodiments and drawings, and those skilled in the art in the technical field related to the present embodiments may make modifications without departing from the essential characteristics of the above-mentioned description. You will be able to understand that it can be implemented in a certain form. Therefore, the disclosed methods should be considered from an explanatory rather than a restrictive perspective. Even if the operational effects according to the configuration of the present invention are not explicitly described and explained in the description of the embodiment, the effects that can be predicted by the configuration may also be recognized. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the equivalent scope should be construed as being included in the present invention.

100: device 110: information acquisition device
130: external server 140: storage medium
150: communication device 160: virtual server
170: User terminal
210: receiving unit 220: processor

Claims (15)

In an image processing method related to importance,
Obtaining a target video related to medical practice;
Obtaining image information about the target video;
Obtaining non-image information, including at least one of vital signals for the medical practice, attribute information for the target video, and audio information for the target video;
Obtaining characteristic information about the target video based on the video information and the non-video information; and
A method comprising: performing image processing on the target video based on importance determined based on the characteristic information. According to claim 1,
The step of performing the image processing is
A method of determining at least one of a storage location, storage period, index, and file name for the target video based on the characteristic information and the importance. According to claim 2,
The step of performing the image processing is
Perform image processing on the target video so that the higher the importance, the higher the security level of the storage location and the longer the storage period,
Determining the index and the file name based on the characteristic information. According to claim 1,
The step of acquiring the characteristic information is
A method of acquiring the characteristic information based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for the image information. According to claim 4,
The step of determining the characteristic information is
A method of acquiring the characteristic information based on an emotion analysis result based on the voice information. According to claim 5,
A method of determining the importance based on the length of a section where a first risk section in the target video determined according to the image information and a second risk section in the target video determined according to the emotion analysis result overlap. According to claim 6,
The step of performing the image processing is
determining a first risk level for the first risk interval;
determining a second risk level for the second risk interval;
determining a third risk level corresponding to a product of the first risk level and the second risk level; and
Determining the importance to correspond to a value obtained by multiplying the length of the overlapping section and the third risk level. In an image processing device related to importance,
A receiving unit that acquires a target video related to medical practice; and
Obtaining image information for the target video, acquiring non-image information including at least one of vital signals for the medical action, attribute information for the target video, and audio information for the target video, and A device comprising; a processor acquiring characteristic information about the target video based on information and the non-image information, and performing image processing on the target video based on importance determined based on the characteristic information. According to claim 8,
The processor is
A device that determines at least one of a storage location, storage period, index, and file name for the target video based on the characteristic information and the importance. According to clause 9,
The processor is
Perform image processing on the target video so that the higher the importance, the higher the security level of the storage location and the longer the storage period,
A device that determines the index and the file name based on the characteristic information. According to claim 8,
The processor is
A device that acquires the characteristic information based on at least one of surgical tool monitoring information, vital signal monitoring information, and bleeding monitoring information for the image information. According to claim 11,
The processor is
A device that acquires the characteristic information based on an emotion analysis result based on the voice information. According to claim 12,
The importance of the above is
A device that is determined based on the length of a section where a first risk section in the target video determined according to the image information and a second risk section in the target video determined according to the emotion analysis result overlap. According to claim 13,
The processor is
Determine a first risk level for the first risk interval,
determine a second risk level for the second risk interval;
Determine a third risk level corresponding to the product of the first risk level and the second risk level,
A device that determines the importance to correspond to a value obtained by multiplying the length of the overlapping section and the third risk level. A computer-readable recording medium recording a program for executing the method of any one of claims 1 to 7 on a computer.