Endoscope system and method for centralized processing of images

Abstract

The invention discloses an endoscope system and method for image centralized processing, and belongs to the technical field of medical instruments, the endoscope system comprises a plurality of sets of endoscope front-end equipment which are configured in different areas according to hospital department categories, and the endoscope front-end equipment comprises a light source integrated mirror body and image display equipment; endoscope rear-end equipment is configured in a centralized mode, and the endoscope rear-end equipment comprises an image processing cluster server, data exchange equipment and light source control equipment. After the light source integrated mirror body in a certain sub-region is connected, the image processing cluster server obtains parameter information of the light source integrated mirror body, and the following steps are executed based on the parameter information: regulating and controlling the used light source parameters of the light source integrated mirror body; calling a processing resource to carry out centralized processing on image data input by the light source integrated mirror body; and the processed image data is transmitted to the image display equipment in the corresponding group of the light source integrated mirror body to be displayed. According to the invention, the resource utilization rate of the endoscope system is improved, and endoscope data intercommunication and integration among departments are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical devices, in particular to an endoscope system and method for image centralized processing. BACKGROUND

[0002] An endoscope image processing system is generally composed of an image processing host, a cold light source, a display, and a scope. At present, many departments in hospitals use endoscope equipment, for example, the digestive department uses a digestive department endoscope, the respiratory department uses a bronchoscope, the surgical department uses a rigid endoscope, and the urology department uses a ureter, etc.

[0003] In the specific use process, the endoscope equipment in the hospital is currently used independently by department, the endoscope image system cannot be simply scheduled between departments, and the corresponding image detection results cannot be directly retrieved from each other, which is not conducive to resource integration and cost control. At the same time, each endoscope equipment independently uses a trolley or a boom, which occupies a large space in the department, the wiring is chaotic and the cost is high. In general, these endoscope systems are mostly in an idle or non-saturated state, and the resources are seriously wasted.

[0004] Therefore, in the hospital application process, how to design a low-cost and high-resource utilization endoscope image processing system is a technical problem we need to solve. SUMMARY

[0005] The present application is mainly an endoscope system and method for image centralized processing, which solves the problems of the prior art.

[0006] In a first aspect, the present application provides an image centralized processing method of an endoscope system, a plurality of groups of endoscope front-end devices are configured according to the categories of hospital departments, and the endoscope front-end devices at least include a light source integrated scope and an image display device; an endoscope back-end device is centrally configured, and the endoscope back-end device at least includes an image processing cluster server, a data exchange device, and a light source control device; When a light source integrated scope in a sub-region is connected, the image processing cluster server acquires parameter information of the light source integrated scope based on the data exchange device, and executes the following based on the parameter information: the image processing cluster server controls the light source control device to regulate the use of the light source parameter of the light source integrated scope; and, the processing resource is called to centrally process the image data input by the light source integrated scope; The processed image data is transmitted by the data exchange device to the image display device in the group corresponding to the light source integrated scope for display, and the image centralized processing is completed.

[0007] Based on the above technical scheme, the parameter information at least includes the type, model and area information of the light source integrated mirror.

[0008] Based on the above technical scheme, the image data input by the light source integrated mirror is processed by the called processing resource, specifically: Based on the type and model information of the light source integrated mirror, the image processing algorithm corresponding to the current light source integrated mirror is called; Based on the area information of the light source integrated mirror, the idle server information in the corresponding image processing cluster server corresponding to the department is obtained to select the idle server for image processing.

[0009] Based on the above technical scheme, it also includes: The image processing cluster server is configured with a network node; Before obtaining the idle server information in the corresponding image processing cluster server corresponding to the area, the image processing cluster server calls first data through the network node, and the first data at least includes the current registration information data, payment information data and diagnosis time period data of the corresponding department; Based on the first data and the area information, the image processing cluster server predicts the total amount of image processing resources occupied in the future time period based on the machine learning model; Based on the predicted total amount of image processing resources, the idle server with the smallest resource occupation rate is selected for image processing.

[0010] Based on the above technical scheme, it also includes: Based on the network node, the diagnosis single information of the corresponding patient is obtained; The image processing cluster server predicts the use time length of the current light source integrated mirror and the image processing resource occupation amount based on the diagnosis information of the diagnosis single; The idle server information in the corresponding department is obtained, and at least one idle server that can execute the image processing resource occupation amount task within the use time length is selected based on the use time length, and the idle server with the shortest execution time length and the smallest resource occupation rate is selected for image processing.

[0011] Based on the above technical scheme, the machine learning model is obtained by the following way: Build a convolutional neural network model; The historical registration information data, payment information data, diagnosis time period data and image processing resource occupation amount data are taken as input, and the total amount of image processing resources occupied in the future time period is taken as output, and the convolutional neural network model is trained and verified until the requirements are met.

[0012] Based on the above technical scheme, the image data input by the light source integrated mirror is processed by the called processing resource, including: The image processing cluster server obtains diagnosis sheet information of the corresponding patient based on the network node, obtains cause information and area information that need to be detected based on the diagnosis sheet information; Real-time detection is performed on the obtained image data, and based on the detection result: Judge whether the current detection area is consistent with the required detection area, if not, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device, and the image display device displays the image in real time, and synchronously displays the prompt information; And, based on the obtained cause information, obtain the recommended detection area and / or the key detection area corresponding to the cause, when the recommended detection area and / or the key detection area appear in the real-time detection of the obtained image data, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device, and the image display device displays the image in real time, and synchronously displays the prompt information.

[0013] Based on the above technical solution, the prompt information includes one or any two of voice prompt, direction guide mark, graphic mark and color mark.

[0014] Based on the above technical solution, it also includes: Based on the real-time obtained image data, the detection object in the corresponding area of the image data is identified, and based on the identification result, it is judged whether the detection object in the current area has a lesion, and based on the identification result, the degree and grade of the lesion are judged, and preliminary diagnosis data is synchronously generated and sent to the image display device; When the preliminary diagnosis data exists, the image display device sends out diagnosis auxiliary information prompt, and the user can view the preliminary diagnosis data based on the diagnosis auxiliary information prompt.

[0015] In a second aspect, the present application provides an endoscope system for centralized image processing, comprising: The endoscope front-end device is configured in several groups according to the hospital department category, and the endoscope front-end device at least includes a light source integrated scope and an image display device; The endoscope rear-end device at least includes an image processing cluster server, a data exchange device and a light source control device, the light source integrated scope is respectively connected with the image processing cluster server through the data exchange device and the light source control device, and the image display device is connected with the image processing cluster server through the data exchange device; Wherein, the image processing cluster server is used for, when the light source integrated scope in a certain sub-area is connected, obtaining the parameter information of the light source integrated scope based on the data exchange device, and based on the parameter information: The light source control device controls the use of the light source parameter of the light source integrated mirror body. and, The processing resource processes the image data input by the light source integrated mirror body, and displays the processed image data on the image display device in the corresponding group of the light source integrated mirror body through the data exchange device, thereby completing the image centralized processing.

[0016] The endoscope system and method for image centralized processing provided by the present application can configure corresponding endoscope front-end devices according to the needs of hospital departments, reduce the supporting structure of the front-end device (such as reducing the setting of the trolley), greatly reduce the space occupancy rate of the device, and are convenient to use, only need to connect the back-end device through a line, are convenient to arrange, and have low cost. At the same time, the centralized back-end device is used to process, analyze, transmit, control and deploy data of all front-end devices, thereby reducing the cost of each single endoscope system, reducing resource waste, improving resource utilization, realizing data intercommunication and integration between departments, and being more convenient to manage and use. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the embodiments of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and do not limit the present application. In the drawings: Figure 1 The flowchart of the image centralized processing method of the endoscope system in the present embodiment. DETAILED DESCRIPTION

[0018] The exemplary embodiments will be described in detail herein with reference to the accompanying drawings. Unless otherwise defined, the same numbers in different drawings indicate the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0019] In the prior art, endoscope systems are basically arranged in hospitals in units of departments. Since endoscope systems are allocated by types, departments, etc., each endoscope system is a complete whole, which is basically composed of an image processing host, a cold light source, a display, and a mirror body when configured. Since each system is configured completely, the space and resources occupied are large. In the use process, the utilization rate of more endoscopes is low. At the same time, due to the large demand of some departments, the endoscope system cannot meet the needs, and increasing the endoscope system undoubtedly increases the cost.

[0020] Based on this, the technical concept of the present application is: based on the existing endoscope setting and use problems in the hospital, under the premise of facilitating the independent use and mutual cooperation of various departments in the hospital, a kind of endoscope system is designed, which can reduce the cost of equipment and arrangement, integrate the resources and data of endoscope system in various departments, improve the resource utilization rate of endoscope system and use convenience.

[0021] Therefore, the image centralized processing method and system of the endoscope system provided by the present application aim to solve the above technical problems of the prior art.

[0022] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific examples. The following specific examples can be combined with each other, and the same or similar concepts or processes may not be described again in some examples. The embodiments of the present application will be described below with reference to the drawings.

[0023] As shown in Figure 1 The first embodiment of the present application provides an image centralized processing method of an endoscope system, which specifically includes the following steps: S1, a plurality of groups of endoscope front-end devices are configured according to the categories of hospital departments, and the endoscope front-end devices at least include light source integrated mirror bodies and image display devices; S2, an endoscope rear-end device is centrally configured, and the endoscope rear-end device at least includes an image processing cluster server, a data exchange device and a light source control device; S3, when a light source integrated mirror body in a certain sub-region is connected, the image processing cluster server acquires parameter information of the light source integrated mirror body based on the data exchange device, and based on the parameter information, the image processing cluster server performs: The image processing cluster server controls the light source control device to adjust the use light source parameters of the light source integrated mirror body; and, calls processing resources to centrally process the image data input by the light source integrated mirror body; The processed image data is transmitted by the data exchange device to the image display device in the group corresponding to the light source integrated mirror body for display, and the image centralized processing is completed.

[0024] The embodiment configures the required number of front-end devices in each department according to the requirements of different departments. For example, the Department of Gastroenterology is configured with a gastroenteroscope, the Department of Respiratory Medicine is configured with a bronchoscope, and the Department of Surgery is configured with a rigid endoscope. In application, the endoscope front-end device in the embodiment only needs to be configured with a light source integrated mirror body and an image display device. The light source integrated mirror body is an endoscope mirror body structure integrated with a light source in the prior art, which only needs to be connected with a corresponding plug or through a data line. The image display device is configured according to the commonly used devices in the prior art, such as a computer display screen. Similarly, the image display device also only needs to be connected with a corresponding plug or through a data line. Since other structures are omitted, more additional devices such as a trolley can be omitted in the department, the overall space occupancy rate is reduced, and the line arrangement and maintenance are more convenient.

[0025] As one of the core ideas of the embodiment, the supporting devices of the endoscope in each department are integrally arranged in the corresponding area in a centralized manner. The data exchange device can be used for data intercommunication between the light source integrated mirror body, the image display device and the image processing cluster server. The light source control device is in data intercommunication with the image processing cluster server for light source control of the light source integrated mirror body. The image processing cluster server is a cluster server composed of multiple single servers through software or hardware connection, which can control and distribute image processing resources based on image processing data.

[0026] It should be noted that the data exchange device is mainly used for data transmission, including image data input by the light source integrated mirror body and image data output after processing by the image processing cluster server. In order to facilitate use and ensure data integrity, the data exchange device of the embodiment can include two, one for video input data exchange device and one for video output data exchange device, so that the data interaction can be classified.

[0027] Further, when the light source integrated mirror body in a sub-area is connected, the image processing cluster server obtains the parameter information of the light source integrated mirror body based on the data exchange device, and then adjusts the light source parameter of the light source integrated mirror body based on the parameter. The endoscope can automatically adjust the light source for use. During the use of the light source integrated mirror body, the image data detected by the light source integrated mirror body is transmitted to the image processing cluster server through the data exchange device. The image processing cluster server can pick up corresponding software resources and / or hardware resources to process the data in real time, and transmit the data to the image display device in the group corresponding to the light source integrated mirror body through the data exchange device for display, thereby forming a complete endoscope data processing system.

[0028] Based on this, the embodiment is based on the needs and actual use of the hospital, and the endoscope front-end device is configured according to the needs of the department, and the endoscope rear-end device is integrated into a whole, so that all endoscope front-end devices can be matched and served by one rear-end device, and the service resources of the rear-end device can be reasonably allocated based on the use of the endoscope, thereby improving the resource utilization rate, and further reducing the overall cost of the endoscope system, improving the use convenience, and under this design, the resources of each department can be shared and used, and the resource scheduling and intelligent management of the hospital system are facilitated.

[0029] It should be noted that the parameter information at least includes the type, model and area information of the light source integrated mirror body. In specific implementation, the types and models of the light source integrated mirror bodies in each department or in the endoscope front-end devices in the same department can be different. Therefore, when the endoscope needs to be controlled and image processed, the light source integrated mirror body can be controlled and the data can be processed based on the obtained parameter information. For example, the light source can be adjusted based on the type and model of the light source integrated mirror body, and the image processing algorithm (to be described below) can be obtained based on the type and model, which is used for subsequent data processing. The area information is used to obtain the setting area or position, number, etc. of the corresponding light source integrated mirror body, so as to facilitate data correspondence and subsequent sending of processed data to the image display device in the same group.

[0030] As a specific implementation, the processing resource retrieves the image data input by the light source integrated mirror body for centralized processing. Specifically, the image processing algorithm corresponding to the current light source integrated mirror body is retrieved based on the type and model information of the light source integrated mirror body, and the idle server information in the image processing cluster server corresponding to the department is obtained based on the area information of the light source integrated mirror body, so as to select the idle server for image processing.

[0031] In application, in order to avoid the problem that the resources of each department are occupied by each other, so that the corresponding department cannot use when needed, in the embodiment, the data algorithm of the corresponding endoscope system is obtained based on the corresponding light source integrated mirror body, and the corresponding area information is obtained based on the required resources of the algorithm, that is, the resource utilization of the corresponding department. The server allocated to the current department is preferentially processed, and when selected, the idle server suitable for the algorithm and having the smallest utilization rate is selected to execute image processing. In this way, the chaotic utilization of resources can be minimized, and the priority use of the resources allocated by each department can be ensured.

[0032] As a specific embodiment, the embodiment also includes that the image processing cluster server is configured with a network node; before acquiring the idle server information in the corresponding image processing cluster server corresponding to the region, the image processing cluster server calls first data through the network node, and the first data at least includes current registration information data, payment information data and diagnosis period data of the corresponding department; based on the first data and the region information, the image processing cluster server predicts the total amount of image processing resource occupation in a future period based on a machine learning model; based on the predicted total amount of image processing resource occupation, the idle server with the smallest resource occupation rate is selected for image processing.

[0033] In application, due to the differences in endoscope use in each department at different time periods every day in the hospital, especially some endoscopes have fasting and water requirements, the prohibited time also varies due to the detection site and cause, and some have no specific restrictions. Therefore, in order to make the endoscope system better utilize resources and cope with continuous irregular diagnosis requirements, the network node can interact with external hospital systems such as registration systems and payment systems in this embodiment. Thus, when the image processing cluster server selects a server, it can acquire first data based on the network node and predict the endoscope resource use in the region, i.e. the department, in a future period based on the first data and region information. Based on the use, the subsequent total amount of image processing resource occupation is judged. At this time, the idle server with the smallest resource occupation rate can be selected to process the current image based on the predicted total amount of image processing resource occupation. The idle server with the smallest resource occupation rate can be a cross-department server. Thus, the use of each department can be ensured, and each department can also reasonably utilize resources.

[0034] As one of the specific embodiments, the embodiment also includes that the image processing cluster server is configured with a network node; before acquiring the idle server information in the corresponding image processing cluster server corresponding to the region, the image processing cluster server calls first data through the network node, and the first data at least includes current registration information data, payment information data and diagnosis period data of the corresponding department; based on the first data and the region information, the image processing cluster server predicts the total amount of image processing resource occupation in a future period based on a machine learning model; based on the predicted total amount of image processing resource occupation, the idle server with the smallest resource occupation rate is selected for image processing.

[0035] In the application process, some endoscopes have a long use process, which will occupy image processing resources throughout the process, thereby affecting subsequent resource allocation and image processing. Based on this, the embodiment considers the use time of each light source integrated scope and the image processing resource occupation amount based on the above scheme, thereby selecting a server for cooperation processing based on the two, further improving the resource allocation effect.

[0036] As a feasible implementation, the machine learning model is obtained by: building a convolutional neural network model; taking historical registration information data, payment information data, diagnosis time period data, and image processing resource occupation data as input, taking the total amount of image processing resources occupied in the future time period as output, training and verifying the convolutional neural network model until the requirements are met.

[0037] As a feasible implementation, the processing resource called by the light source integrated endoscope inputs image data for centralized processing, including: The image processing cluster server obtains the diagnosis single information of the corresponding patient based on the network node, and obtains the cause information and region information that need to be detected based on the diagnosis single information; Real-time detection of acquired image data, and execution based on detection results: Determine whether the current detection region is consistent with the required detection region, if not, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device, and the image display device displays the image in real time., synchronously display the prompt information; And, based on the acquired cause information, obtain the recommended detection region and / or key detection region of the corresponding cause, when the recommended detection region and / or key detection region appears in the real-time detection of the acquired image data, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device, and the image display device displays the image in real time., synchronously display the prompt information.

[0038] During the use of the endoscope, in order to make the image processing more accurate and reduce the length of time of incorrect use of the endoscope, when performing image processing, the image processing cluster server can also detect real-time images and give corresponding prompts, thereby assisting in judging or guiding the use of the endoscope, improving the use effect of the endoscope and improving the detection accuracy.

[0039] As a specific implementation, the prompt information includes one or any two of voice prompts, direction guide marks, graphic marks, and color marks.

[0040] As a feasible implementation, the present embodiment further includes: Based on the real-time acquired image data, the detection objects in the corresponding region of the image data are identified, and based on the identification result, it is judged whether the detection objects in the current region exist lesions, and based on the identification result, the degree and grade of the lesions are judged, and preliminary diagnosis data are generated and sent to the image display device; When the preliminary diagnosis data exists, the image display device issues a diagnosis assistance information prompt, and the user can view the preliminary diagnosis data based on the diagnosis assistance information prompt.

[0041] After the endoscope is used, the diagnosing doctor needs to judge the diagnosis result and give a preliminary diagnosis conclusion, and in the spitting process, the image data can be analyzed and recognized to judge the lesion condition and give a preliminary diagnosis result, based on which the diagnosing doctor can view and verify the result with the own conclusion, thereby further improving the diagnosis effect based on the image processing.

[0042] Based on the image centralized processing method of the endoscope system, the second embodiment of the present application provides an image centralized processing endoscope system, which comprises: An endoscope front-end device is configured in several groups according to the hospital department category, and the endoscope front-end device at least comprises a light source integrated scope and an image display device; An endoscope back-end device at least comprises an image processing cluster server, a data exchange device and a light source control device, the light source integrated scope is connected with the image processing cluster server through the data exchange device and the light source control device, and the image display device is connected with the image processing cluster server through the data exchange device; The image processing cluster server is used to acquire the parameter information of the light source integrated scope based on the data exchange device when the light source integrated scope in a certain sub-region is connected, and execute the following based on the parameter information: Control the light source control device to control the light source parameter of the light source integrated scope; and, Call the processing resource to centrally process the image data input by the light source integrated scope, and transmit the processed image data to the image display device in the corresponding group of the light source integrated scope through the data exchange device to display, thereby completing the image centralized processing.

[0043] It should be understood that the present application is not limited to the precise construction which has been described above and illustrated in the accompanying drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

[0044] Those skilled in the art will appreciate that embodiments of the present application can be realized in the form of methods or systems. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.

[0045] It is also to be noticed that the term "comprising", "including", and "having" or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, includes or has a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "a" or "an", as used herein, mean "one or more" unless otherwise explicitly stated.

[0046] The foregoing is merely illustrative of the principles of this application and various modifications can be made by persons skilled in the art without departing from the scope of the application as defined by the appended claims.

[0047] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0048] It is to be understood that the application is not limited to the precise details of design or construction shown above and illustrated in the drawings, but that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is to be measured only by the appended claims.

Claims

1. An image centralized processing method of an endoscope system, characterized in that, a plurality of groups of endoscope front-end devices are configured in areas according to hospital department categories, the endoscope front-end devices at least including light source integrated scope bodies and image display devices; an endoscope back-end device is centrally configured, the endoscope back-end device at least including an image processing cluster server, a data exchange device, and a light source control device; after a light source integrated scope body in a sub-area is connected, the image processing cluster server acquires parameter information of the light source integrated scope body based on the data exchange device, and based on the parameter information, performs: the image processing cluster server controls the light source control device to regulate the use of light source parameters of the light source integrated scope body; and, processing resources are called to centrally process image data input by the light source integrated scope body; the processed image data is transmitted by the data exchange device to the image display device in the group corresponding to the light source integrated scope body for display, completing image centralized processing.

2. The image concentrating processing method according to claim 1, characterized in that, The parameter information at least includes the type, model, and area information of the light source integrated scope body.

3. The image concentrating processing method according to claim 2, characterized in that, The processing resources called to centrally process the image data input by the light source integrated scope body are: based on the type and model information of the light source integrated scope body, the image processing algorithm corresponding to the current light source integrated scope body is called; based on the area information of the light source integrated scope body, idle server information in the corresponding department in the image processing cluster server is acquired to select an idle server for image processing.

4. The image concentrating processing method according to claim 3, characterized in that, Further comprising: the image processing cluster server is configured with a network node; before acquiring the idle server information in the corresponding area in the image processing cluster server, the image processing cluster server calls first data through the network node, the first data at least including current registration information data, payment information data, and diagnosis time period data of the corresponding department; based on the first data and the area information, the image processing cluster server predicts the total amount of image processing resources occupied in a future time period based on a machine learning model; based on the predicted total amount of image processing resources occupied, an idle server with the smallest resource occupation rate is selected for image processing.

5. The image concentrating processing method according to claim 4, characterized in that, Further comprising: diagnosis single information of the corresponding patient is acquired based on the network node; the image processing cluster server predicts the use duration of the current light source integrated scope body and the amount of image processing resources occupied based on the diagnosis information of the diagnosis single; idle server information in the corresponding department is acquired, and based on the use duration, at least one idle server that can execute the amount of image processing resource occupation tasks within the use duration is selected, and an idle server with the shortest execution duration and the smallest resource occupation rate is selected for image processing.

6. The image concentrating processing method according to claim 4, characterized by, The machine learning model is obtained by: building a convolutional neural network model; using historical registration information data, payment information data, diagnosis time period data, and image processing resource occupation data as input, and using the total amount of image processing resources occupied in a future time period as output, the convolutional neural network model is trained and verified until the requirements are met.

7. The image concentrating processing method according to claim 4, characterized by, The processing resources called to centrally process the image data input by the light source integrated scope body include: The image processing cluster server obtains the diagnosis sheet information of the corresponding patient based on the network node, obtains the cause information and the area information that need to be detected based on the diagnosis sheet information; Real-time detection is performed on the obtained image data, and based on the detection result, the following is performed: Determine whether the current detection area is consistent with the required detection area. If not, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device. When the image display device displays images in real time, the prompt information is synchronously displayed. Based on the obtained cause information, the recommended detection area and / or the key detection area corresponding to the cause are obtained. When the recommended detection area and / or the key detection area appear in the real-time detection of the obtained image data, the image processing cluster server synchronously generates prompt information and sends it to the image display device through the data exchange device. When the image display device displays images in real time, the prompt information is synchronously displayed.

8. The image concentrating processing method according to claim 7, characterized in that, The prompt information includes one or any two of voice prompts, directional guide marks, graphical marks, and color marks.

9. The image concentrating processing method according to claim 7, characterized in that, Also includes: Based on the real-time obtained image data, the detection objects in the corresponding area of the image data are identified, and based on the identification result, it is determined whether the detection objects in the current area have lesions, and based on the identification result, the degree and level of the lesions are determined. Synchronously generate preliminary diagnosis data and send it to the image display device; When the image display device displays images in real time, if the preliminary diagnosis data exists, the image display device issues a diagnosis assistance information prompt, and the user can view the preliminary diagnosis data based on the diagnosis assistance information prompt.

10. An endoscope system for image centralized processing, for implementing the image centralized processing method according to any one of claims 1 to 9, characterized by It includes: The endoscope front-end device is divided into several groups according to the hospital department category, and the endoscope front-end device at least includes a light source integrated scope and an image display device; The endoscope rear-end device at least includes an image processing cluster server, a data exchange device, and a light source control device. The light source integrated scope is respectively connected with the image processing cluster server through the data exchange device and the light source control device. The image display device is connected with the image processing cluster server through the data exchange device; The image processing cluster server is used to obtain the parameter information of the light source integrated scope based on the data exchange device when the light source integrated scope in a certain sub-area is connected, and based on the parameter information, the following is performed: Control the light source control device to control the use of the light source parameter of the light source integrated scope; And, Call the processing resources to centrally process the image data input by the light source integrated scope; The processed image data is transmitted from the data exchange device to the image display device in the corresponding group of the light source integrated scope for display, completing the image centralized processing.

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