An endoscope blind area coverage detection method, system, device and storage medium

Abstract

The application discloses an endoscope blind area coverage detection method, system, device and storage medium, and comprises the following steps: acquiring a three-dimensional structure of a monitoring target object; acquiring pose information and field of view information of the endoscope; acquiring a monitoring line group according to the pose information and the field of view information; acquiring contact information of the monitoring line group and the monitoring target object according to the monitoring line group and the three-dimensional structure; and determining a contact area detected under a current pose of the endoscope according to the contact information. The method has the beneficial effects that the contact information of the monitoring line and the monitoring target object is used to determine the contact area, the detection blind area can be effectively reduced, and the detected area can be truly reflected; and the contact detection speed of the monitoring line and the monitoring target object is fast, the time consumption is short, and the detected area can be quickly determined.

Description

TECHNICAL FIELD

[0001] The present application relates to the medical field, in particular to an endoscope blind area coverage detection method, system, device and storage medium. BACKGROUND

[0002] Endoscopy is a kind of optical instrument examination that checks the diseases in the body by sending the endoscope into the body through the natural cavity of the human body. The endoscope is an optical instrument that can check the diseases in the body by sending the endoscope into the body through the natural cavity of the human body. It can directly observe the lesions in the cavity of the organ, determine the position and range, and take photographs, biopsies or brushings, greatly improving the diagnostic accuracy of cancer and enabling certain treatments.

[0003] The existing endoscope blind area monitoring mostly uses a combination of pose sensors and deep learning technology. The deep learning technology is used to identify the key parts of the area to be checked, and whether all the key parts are identified is used to measure whether all the areas are checked. However, the key parts cannot represent the whole area, and there is still a risk of missed detection.

[0004] The current endoscopy is prone to miss some areas for doctors with less experience, resulting in incomplete coverage of endoscopy. Therefore, a method for blind area monitoring during endoscopy is needed to distinguish between checked and unchecked areas of the entire area to be checked, so as to help doctors achieve fast and complete coverage of endoscopy. SUMMARY

[0005] In order to overcome the shortcomings and deficiencies of the prior art, the present application discloses an endoscope blind area coverage detection method, which determines and detects the area by monitoring the contact information between the line of sight and the monitoring target object, effectively reduces the detection blind area, and truly reflects the detected area. The method comprises:

[0006] obtaining a three-dimensional structure of a monitoring target object;

[0007] obtaining pose information and field of view information of the endoscope;

[0008] obtaining a monitoring line of sight group according to the pose information and the field of view information, the monitoring line of sight group being composed of a plurality of monitoring lines of sight;

[0009] obtaining contact information between the monitoring line of sight group and the monitoring target object according to the monitoring line of sight group and the three-dimensional structure;

[0010] determining a contact area detected by the endoscope at the current pose according to the contact information.

[0011] Further, the method for obtaining the three-dimensional structure of the inspection area comprises the following steps:

[0012] acquiring a two-dimensional medical image of the monitoring target object;

[0013] acquiring a first feature parameter according to the two-dimensional medical image;

[0014] scanning the monitoring target object to obtain a basic three-dimensional structure;

[0015] acquiring a second feature parameter according to the basic three-dimensional structure;

[0016] inputting the first feature parameter and the second feature parameter into a deep learning model registration process to obtain a three-dimensional structure.

[0017] Further, the pose information at least includes a spatial position and a pose matrix.

[0018] Further, the field of view information at least includes range information and angle information;

[0019] The monitoring line group is acquired according to the pose information and the field of view information, and includes:

[0020] The monitoring plane and the monitoring starting point are determined according to the pose information and the field of view information;

[0021] The monitoring line group is acquired according to the monitoring starting point and the monitoring plane.

[0022] Further, the contact area detected by the endoscope in the current pose is determined according to the contact information, and includes:

[0023] When the number of contact points of the same monitoring line on the monitoring target object is less than 1, the specified area is an uncontacted area;

[0024] When the number of contact points of the same monitoring line on the monitoring target object is greater than or equal to 1, the area of the contact point closest to the monitoring target object is selected as the contact area.

[0025] Further, the pose information and the field of view information of the endoscope are acquired, and include:

[0026] The pose information and the field of view information of the endoscope in different poses are acquired by controlling the endoscope to change the pose;

[0027] The contact information of the monitoring line group and the monitoring target object is acquired according to the monitoring line group and the three-dimensional structure, and includes:

[0028] A plurality of contact information of the monitoring line group and the monitoring target object in different poses is acquired;

[0029] The contact area detected by the endoscope in the current pose is determined according to the contact information.

[0030] obtaining a plurality of contact regions corresponding to the plurality of contact information; and integrating the plurality of contact regions in the three-dimensional structure display.

[0031] Further, the integrating the plurality of contact regions in the three-dimensional structure display comprises:

[0032] real-time recording the plurality of contact regions;

[0033] real-time marking the contact regions and displaying the contact regions in the three-dimensional structure by animation.

[0034] In another aspect, the present application also provides an endoscope blind area coverage detection system, comprising:

[0035] a three-dimensional structure obtaining module configured to obtain a three-dimensional structure of a monitoring target object;

[0036] a monitoring information obtaining module configured to obtain pose information and field of view information of the endoscope;

[0037] a monitoring line of sight obtaining module configured to obtain a monitoring line of sight group according to the pose information and the field of view information;

[0038] a contact information obtaining module configured to obtain contact information of the monitoring line of sight group and the monitoring target object according to the monitoring line of sight group and the three-dimensional structure;

[0039] a region determining module configured to determine a contact region detected at a current pose of the endoscope according to the contact information.

[0040] In a third aspect, the present application also provides an electronic device, which comprises a processor and a memory, and the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement an endoscope blind area coverage detection method as described above.

[0041] In a fourth aspect, the present application also provides a computer readable storage medium, and the storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by a processor to implement an endoscope blind area coverage detection method as described above.

[0042] The implementation of the present embodiment has the following effects:

[0043] 1. The contact information of the monitoring line and the monitoring target is monitored to determine the detection area, which can effectively reduce the detection blind area and truly reflect the detected area; and the contact detection speed of the monitoring line and the monitoring target is fast, the time consumption is short, and the detected area can be quickly determined.

[0044] 2. The detected area is recorded in real time on the three-dimensional structure, and the detected area is marked, the contact detection speed of the monitoring line and the monitoring target is fast, and the time consumption of obtaining the contact information is short, and recording the detected area in real time on the three-dimensional structure will not cause delay. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0046] Figure 1 The endoscope blind area coverage detection method flowchart provided for the embodiment of the present application;

[0047] Figure 2 The three-dimensional structure acquisition method flowchart provided for the embodiment of the present application;

[0048] Figure 3 The cone field of view schematic diagram provided for the embodiment of the present application;

[0049] Figure 4 The cone field of view and monitoring target contact effect schematic diagram provided for the embodiment of the present application;

[0050] Figure 5 The monitoring line and monitoring target contact effect schematic diagram provided for the embodiment of the present application;

[0051] Figure 6 The endoscope blind area coverage detection system block diagram provided for the embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the person skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0053] EMBODIMENT

[0054] As an optical instrument, the endoscope can directly observe the lesions inside the internal organs by sending the endoscope into the patient's body. During the examination, the doctor needs to be very familiar with the internal organs. If the detection blind area is large, it will seriously affect the disease diagnosis, and for doctors with relatively insufficient experience, it is easy to miss part of the area detection. The existing endoscope cannot distinguish between detected and undetected areas, therefore, the embodiment provides an endoscope blind area detection method, which can intuitively distinguish between undetected areas and detected areas by monitoring whether the line of sight contacts the monitoring target object, as shown in Figure 1 The method comprises the following steps:

[0055] S1: obtaining the three-dimensional structure of the monitoring target object;

[0056] In order to facilitate the doctor to intuitively view the current detection situation, it is necessary to obtain the current three-dimensional structure of the monitoring target object for display on the display device. The doctor uses the endoscope for detection at the same time, and the entire three-dimensional structure is displayed on the display device. When the endoscope detects an area, the display device will display that the area has been detected. In order to improve the detection accuracy, the three-dimensional structure must also reflect the structure of the monitoring target object. The conventional three-dimensional structure acquisition method is to first obtain a plurality of two-dimensional medical images, input the two-dimensional medical images into a deep learning model, and generate a three-dimensional structure. However, the three-dimensional structure generated from the two-dimensional medical images of the monitoring target object belongs to two forms of representation. Due to the difference in their respective three-dimensional coordinate systems, they do not completely coincide in three-dimensional space, and cannot accurately reflect the true three-dimensional morphology of the monitoring target object. Therefore, the embodiment improves the method for obtaining the three-dimensional structure, as shown in Figure 2 The specific steps are as follows:

[0057] S11: obtaining the two-dimensional medical image of the monitoring target object;

[0058] S12: obtaining the first feature parameter according to the two-dimensional medical image;

[0059] S13: scanning the monitoring target object to obtain a basic three-dimensional structure;

[0060] S14: obtaining the second feature parameter according to the basic three-dimensional structure;

[0061] S15: inputting the first feature parameter and the second feature parameter into a deep learning model for registration processing to obtain a three-dimensional structure.

[0062] Firstly, a two-dimensional medical image of the patient's affected area is obtained, which can be obtained by a two-dimensional information acquisition device, such as X-ray scanning, and a first feature parameter is obtained according to the two-dimensional medical image. In this embodiment, the monitoring target is taken as an example of the stomach, and the first parameter of the stomach structure is obtained. The first feature parameter includes but is not limited to the two-dimensional coordinates of the following parts: the cardia, the lesser curvature of the stomach, the gastric fundus, the gastric tract, and the pyloric part. Then, the basic three-dimensional structure of the monitoring target is obtained by a three-dimensional information acquisition device, such as CT scanning of the stomach, and the basic three-dimensional structure of the patient's stomach is obtained. The second feature parameter of the basic three-dimensional structure is obtained, which includes but is not limited to the three-dimensional coordinates of the following parts: the cardia, the lesser curvature of the stomach, the gastric fundus, the gastric tract, and the pyloric part. Finally, the first feature parameter and the second feature parameter are input into a deep learning model for registration processing, and the three-dimensional structure is generated after the registration processing is completed. The registration processing includes synchronous deformation operation of the three-dimensional coordinates of each part in the basic three-dimensional structure, so that the second feature parameter is fitted with the second feature parameter, that is, the size, direction, and position of each part in the basic three-dimensional structure are adjusted, so that the two-dimensional medical image is the projection of the adjusted three-dimensional oral structure at a certain angle, and the three-dimensional structure truly reflects the actual stomach structure, improving the accuracy of detection.

[0063] The endoscope has different sizes, different orientations, and different endoscope specifications, and the monitored area size and angle are different, so before detecting the monitoring target, the pose information and field of view information of the endoscope need to be obtained; the specific steps are as follows:

[0064] S2: Obtain the pose information and field of view information of the endoscope;

[0065] The pose information of the endoscope is obtained by using the built-in pose sensor at the front end of the endoscope, wherein the pose information includes but is not limited to spatial position and pose matrix;

[0066] The field of view information includes but is not limited to distance information and angle information, and the current detection area of the endoscope is determined by obtaining the specific position, pose matrix, and field of view information of the endoscope.

[0067] During the examination of the monitoring target by the endoscope, the endoscope moves along the preset trajectory and rotates, and by constantly changing the pose information of the endoscope, more areas of the monitoring target are detected, and the endoscope changes the pose information to detect the monitoring target, while the detected areas are recorded and marked in the three-dimensional result, and the specific steps are as follows:

[0068] S21: Control the endoscope to change the pose, and obtain the pose information and field of view information of the endoscope;

[0069] The control endoscope changes the pose according to a preset track, and the preset track includes an examination track of the monitoring target object according to the experience of a doctor, or a set of examination tracks automatically generated by inputting the type of the monitoring target object into a deep learning model and combining the first feature parameter and the second feature parameter in the three-dimensional structure. Each person's internal organs are different, and a set of examination tracks is generated for the first feature parameter and the second feature parameter of different patients, so that the endoscope detection is more thorough and comprehensive.

[0070] S3: Obtain a monitoring line group according to the pose information and the field of view information, the monitoring line group being composed of a plurality of monitoring lines;

[0071] As shown in Figure 3 , the position of the endoscope is taken as a starting point, and when the endoscope emits a monitoring line to the surrounding, a conical monitoring field is formed, that is, a conical field of view, wherein a is the detection angle of the endoscope, and L is the monitoring distance of the endoscope. When the pose information of the endoscope and the three-dimensional structure of the monitoring target object are determined, the region on which the endoscope projects on the monitoring target object, that is, the monitoring plane β, can be calculated by the parameter equation through the known detection angle a and monitoring distance L. Whether the region has been detected can be determined by whether the conical line of sight collides with the monitoring target object. Collision means contact, that is, the conical body contacts the monitoring target object. However, collision testing of the monitoring target object by the entire conical field of view is prone to blind areas, as shown in Figure 4 , when the monitoring target object has a small protrusion, the conical body is shot at the protruding part of the monitoring target object, and only the plane γ close to the position of the endoscope can be actually seen, and the plane δ behind the plane is hidden. However, the field of view is detected by the range, and the small protrusion is collided by the conical body, but the system still considers that the plane δ behind has been detected. Therefore, the conical field of view is divided into a certain number of monitoring lines Y in this embodiment, and the detected region is determined by the collision between the monitoring lines and the monitoring target object. The monitoring line is faster than the conical field of view in colliding with the monitoring target object, and the monitoring line acquisition method is as follows:

[0072] S31: Determine the monitoring plane and the monitoring starting point according to the pose information and the field of view information;

[0073] First, the pose information of the current endoscope needs to be obtained. The monitoring starting point, that is, the specific position of the endoscope, can be obtained through the pose information. The monitoring plane is also determined according to the field of view information, that is, under the condition that the specific position, angle information and distance information of the endoscope are determined, the monitoring plane on which the conical field of view projects on the monitoring target object can be determined.

[0074] S32: Obtain a monitoring line group according to the monitoring starting point and the monitoring plane.

[0075] By the determined monitoring starting point and monitoring plane, a monitoring line of sight emitted by the monitoring starting point can be determined, the determined monitoring plane is evenly divided into multiple regions according to coordinates, and monitoring lines of sight are respectively emitted to each region of the monitoring plane from the monitoring starting point, so that the regions detected by the endoscope are determined by the collision of the monitoring lines of sight with the regions, after the monitoring line of sight group is obtained, the detected regions are determined by the contact information between the monitoring line of sight group and the monitoring target object, and the contact information obtaining step is as follows:

[0076] S4: obtaining contact information between the monitoring line of sight group and the monitoring target object according to the monitoring line of sight group and the three-dimensional structure;

[0077] S41: obtaining multiple contact information between the monitoring line of sight and the monitoring target object in different poses;

[0078] Whether the region has been detected is determined by whether the monitoring line of sight emitted from the endoscope contacts the monitoring target object, when the pose of the endoscope changes, the region projected by the endoscope on the monitoring target object is different, and the contact information of the endoscope in different poses is recorded in real time.

[0079] S5: determining a contact region detected by the endoscope in the current pose according to the contact information.

[0080] When the number of contact points of the same monitoring line of sight on the monitoring target object is less than 1, the specified region is an uncontacted region.

[0081] When the number of contact points of the same monitoring line of sight on the monitoring target object is greater than or equal to 1, the region of the contact point closest to the monitoring target object is selected as a contact region.

[0082] As Figure 5As shown, when the monitoring view line collides with the small protrusion of the monitoring target object, the first collision point, that is, the contact point, indicates that the area where the first collision point is located can be detected, which is the contact area. If you want to detect the back plane of the small protrusion, you must collide the monitoring view line with the back plane, and a monitoring view line can only determine whether the area where the first collision point of the small protrusion and the monitoring view line is located has been detected. Multiple monitoring view lines can form a complete conical monitoring field. When the endoscope is detecting, the endoscope moves, and the area detected by the endoscope on the three-dimensional structure is marked accordingly. If a small area in the large monitored area is not marked, it can be concluded that the area may be blocked and not detected. The doctor can detect the blind area again according to the mark until the blind area is marked on the three-dimensional structure; the projection plane of the endoscope on the monitoring target object is evenly divided into regions, each region has a monitoring view line colliding with the region, and the region where the collision point is located is judged as a detected region. When the monitoring view line has multiple collision points with the region, the region where the collision point close to the endoscope is located is judged as a monitored region. The monitoring view line collides with the monitoring target object faster than the entire cone collides with the monitoring target object, and more truly reflects the current detected area.

[0083] S51: Obtain a plurality of contact areas corresponding to a plurality of contact information; integrate the plurality of contact areas in a three-dimensional structure display.

[0084] Each contact area corresponding to each monitoring view line can be displayed in the three-dimensional structure. Integrating all contact areas corresponding to the monitoring view lines can enable a doctor to directly view all areas that have been detected in the three-dimensional structure.

[0085] S511: Real-time record a plurality of contact areas;

[0086] S512: Real-time mark the contact areas and display them through animation in the three-dimensional structure;

[0087] The contact information obtained by the endoscope through detection of the monitoring target object in different poses is recorded in real time through the three-dimensional structure and displayed through animation. The contact detection speed of the monitoring view line and the monitoring target object is fast, and the time consumption for obtaining the contact information is short. The real-time recording of the detected area on the three-dimensional structure does not produce delay, and the doctor can know the current detection containing a blind area in the first time and immediately adjust the endoscope to change the pose to detect the blind area, thereby effectively improving the diagnosis accuracy of the disease.

[0088] As shown in Figure 6 The embodiment also provides an endoscope blind area coverage detection system, which can realize all functions of the above method. The system comprises:

[0089] A three-dimensional structure acquisition module 601 is configured to acquire a three-dimensional structure of a monitoring target object.

[0090] The monitoring information acquisition module 602 is configured to acquire the pose information and the field of view information of the endoscope.

[0091] The monitoring line of sight acquisition module 603 is configured to acquire a monitoring line of sight group according to the pose information and the field of view information.

[0092] The contact information acquisition module 604 is configured to acquire contact information between the monitoring line of sight group and the monitoring target object according to the monitoring line of sight group and the three-dimensional structure.

[0093] The region determination module 605 is configured to determine a region detected by the endoscope at a current pose according to the contact information.

[0094] Embodiments of the present application also provide an electronic device, which comprises a processor and a memory, and the memory stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the endoscope blind area coverage detection method in the method embodiments.

[0095] Embodiments of the present application also provide a storage medium, which can be arranged in a server to save at least one instruction, at least one program, a code set or an instruction set for implementing the endoscope blind area coverage detection method in the method embodiments, which are loaded and executed by the processor to implement the endoscope blind area coverage detection method provided by the above method embodiments.

[0096] Optionally, in the present embodiment, the above storage medium can be located in at least one network server of a plurality of network servers of a computer network. Optionally, in the present embodiment, the above storage medium can include but is not limited to a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk and various media that can store program codes.

[0097] From the above embodiments of the endoscope blind area coverage detection method, system, electronic device and storage medium provided by the present application, it can be seen that in the embodiments of the present application, the region detected by the endoscope is determined according to the contact information between the monitoring line of sight emitted by the endoscope and the monitoring target object, the detected region is determined through the contact information between the monitoring line of sight emitted by the endoscope and the monitoring target object, the blind area coverage during detection can be reduced, and compared with the contact information between the all-seeing field of view cone and the monitoring target object, the monitoring line of sight collides with the monitoring target object faster, and the detection time is shorter.

[0098] It should be noted that the above-mentioned embodiments of the present application are only for the purpose of description, and do not represent the advantages and disadvantages of the embodiments. And the above describes a specific embodiment of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from the order in the embodiments and still achieve the desired result. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or advantageous.

[0099] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the difference from other embodiments. Especially, for system and server embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiment.

[0100] A person of ordinary skill in the art can understand that all or part of the steps of the above-mentioned embodiments can be completed by hardware, or by program instructing relevant hardware, and the program can be stored in a computer readable storage medium, such as read-only memory, magnetic disk or optical disk.

[0101] The embodiment is implemented, and has the following effects:

[0102] 1. By monitoring the contact information between the monitoring line of sight and the monitoring target object, the detection area can be determined, which can effectively reduce the detection blind area and truly reflect the detected area; and the contact detection speed between the monitoring line of sight and the monitoring target object is fast, the time consumption is short, and the detected area can be quickly determined.

[0103] 2. The detected area is recorded in real time on the three-dimensional structure, and the detected area is marked, the contact detection speed between the monitoring line of sight and the monitoring target object is fast, and the time consumption of obtaining the contact information is short, and the real-time recording of the detected area on the three-dimensional structure will not cause delay.

[0104] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An endoscope blind spot coverage detection method, characterized by, The method comprises the steps of: acquiring a three-dimensional structure of a monitoring target object; acquiring pose information and field of view information of the endoscope; acquiring a monitoring line group from the pose information and the field of view information, the monitoring line group being composed of a plurality of monitoring lines; acquiring contact information of the monitoring line group and the monitoring target object from the monitoring line group and the three-dimensional structure; determining a contact area detected at a current pose of the endoscope from the contact information; the determination of the contact area detected at the current pose of the endoscope from the contact information comprises: when the number of contact points of a same monitoring line on the monitoring target object is less than 1, designating the monitoring target object as a non-contact area; when the number of contact points of a same monitoring line on the monitoring target object is greater than or equal to 1, selecting an area of a contact point closest to the monitoring target object as the contact area; each contact area corresponding to each monitoring line can be displayed in the three-dimensional structure.

2. The method of claim 1, wherein, The acquisition of the three-dimensional structure of the monitoring target object comprises the steps of: acquiring a two-dimensional medical image of the monitoring target object; acquiring a first feature parameter from the two-dimensional medical image; scanning the monitoring target object to obtain a basic three-dimensional structure; acquiring a second feature parameter from the basic three-dimensional structure; inputting the first feature parameter and the second feature parameter into a deep learning model for registration processing to obtain the three-dimensional structure.

3. The method of claim 1, wherein, The pose information at least includes a spatial position and a pose matrix.

4. The endoscope blind area coverage detection method according to claim 1, characterized in that, the field of view information at least includes range information and angle information; the acquisition of the monitoring line group from the pose information and the field of view information comprises: determining a monitoring plane and a monitoring starting point from the pose information and the field of view information; acquiring the monitoring line group from the monitoring starting point and the monitoring plane.

5. The method of claim 1, wherein, The acquisition of the pose information and the field of view information of the endoscope comprises: controlling the endoscope to change the pose to acquire the pose information and the field of view information of the endoscope at different poses; the acquisition of the contact information of the monitoring line group and the monitoring target object from the monitoring line group and the three-dimensional structure comprises: acquiring a plurality of contact information of the monitoring line group and the monitoring target object at different poses; the determination of the contact area detected at the current pose of the endoscope from the contact information comprises: acquiring a plurality of contact areas corresponding to a plurality of contact information; and integrating the plurality of contact areas in the three-dimensional structure display.

6. The method of claim 5, wherein the blind spot coverage detection method is performed by an endoscope. The integration of the plurality of contact areas in the three-dimensional structure display comprises: real-time recording of the plurality of contact areas; real-time marking of the contact areas and animation display in the three-dimensional structure.

7. An endoscope blind spot coverage detection system, comprising: comprise: a three-dimensional structure acquisition module for acquiring a three-dimensional structure of a monitoring target object; a monitoring information acquisition module for acquiring pose information and field of view information of the endoscope; a monitoring line acquisition module for acquiring a monitoring line group from the pose information and the field of view information; The contact information acquisition module is configured to acquire contact information of the monitoring line-of-sight group and the monitoring target object according to the monitoring line-of-sight group and the three-dimensional structure; The region determination module is configured to determine a contact region detected in the current pose of the endoscope according to the contact information; The determination of the contact region detected in the current pose of the endoscope according to the contact information comprises: When the number of contact points of the same monitoring line-of-sight on the monitoring target object is less than 1, the monitoring target object is designated as an uncontacted region; When the number of contact points of the same monitoring line-of-sight on the monitoring target object is greater than or equal to 1, a region of the contact point closest to the monitoring target object is selected as the contact region; and each contact region corresponding to each monitoring line-of-sight can be displayed in the three-dimensional structure.

8. An electronic device, comprising: The device comprises a processor and a memory, and the memory stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the endoscope blind area coverage detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the endoscope blind area coverage detection method according to any one of claims 1 to 6.

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