Ear-nose-throat endoscope wireless image transmission system based on NFC near field triggering

Abstract

The invention discloses an ear-nose-throat endoscope wireless image transmission system based on NFC near field triggering, relates to the field of medical apparatuses and instruments, and solves the problem that an existing wireless image transmission system is poor in image acquisition and transmission efficiency. The data acquisition module is used for performing cavity cross-sectional area analysis according to an image intercepted by an endoscope to obtain target endoscopic video analysis data, screening disease matching patients according to patient symptoms and obtaining corresponding endoscopic video analysis data to obtain endoscopic patient initial matching data; the data analysis module is used for analyzing the cross sectional area of the endoscopic video stream and the endoscopic depth of a lens to obtain endoscopic cavity similarity and performing type division on the endoscopic video stream of the matched patient according to the endoscopic cavity similarity to obtain video stream matching data; and the image transmission module is used for carrying out endoscope near-field triggering setting and endoscopic image wireless transmission on the target endoscopic patient according to the video stream matching data. According to the system and the method, the collection efficiency and the transmission efficiency of the endoscopic image can be improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of medical devices, and relates to an NFC near-field triggering technology, in particular to an ear-nose-throat endoscope wireless image transmission system based on NFC near-field triggering. BACKGROUND

[0002] The existing rhinology endoscope has the following defects when acquiring and transmitting wireless images: 1. The existing rhinology endoscope needs personnel to manually connect and manually set the initial brightness and initial focal length of the endoscope when acquiring and transmitting wireless images, cannot automatically connect the equipment and adjust the initial shooting parameters for different rhinology patients, and thus leads to low rhinology endoscope image acquisition efficiency. 2. The existing rhinology endoscope cannot screen historical nasal endoscopy video streams in combination with the nasal cavity similarity of target patients and patients with the same disease when acquiring and transmitting wireless images, does not set the initial endoscopy focal length and initial endoscopy brightness of the endoscope in combination with matching consistent video streams, and thus cannot use the nfc near-field triggering technology to complete the initial connection and invalid transmission setting of the endoscope, so as to improve the endoscopy image transmission efficiency and transmission quality.

[0003] Therefore, the ear-nose-throat endoscope wireless image transmission system based on NFC near-field triggering is proposed. SUMMARY

[0004] In view of the defects in the prior art, the ear-nose-throat endoscope wireless image transmission system based on NFC near-field triggering is provided, and the application aims to improve the acquisition efficiency and transmission efficiency of endoscopy images.

[0005] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme: the ear-nose-throat endoscope wireless image transmission system based on NFC near-field triggering, and the specific working processes of the modules are as follows: The data acquisition module: acquires the historical endoscopy work video stream corresponding to the target endoscopy patient and performs frame-by-frame image interception, analyzes the cross-sectional area of the cavity of the intercepted image in combination with the endoscopy depth to obtain target endoscopy video analysis data, acquires the endoscopy video analysis data corresponding to the disease-matched patient through the clinical symptoms of the target endoscopy patient, and obtains the initial matching data of the endoscopy patient. The data analysis module: analyzes the cross-sectional area and the endoscopy depth of the endoscopy video stream according to the initial matching data of the endoscopy patient, obtains the endoscopy cavity similarity corresponding to the endoscopy video stream of the matched patient according to the analysis result, classifies the endoscopy video stream of the matched patient according to the endoscopy cavity similarity, and obtains the video stream matching data. An image transmission module: according to the video stream matching data, the target endoscopic patient is set with an endoscopic near field trigger and the endoscopic image is wirelessly transmitted.

[0006] Further, the initial matching data of the endoscopic patient is obtained, specifically as follows: The patients who need to be examined by ear-nose-throat endoscopy are obtained, and a plurality of endoscopic examination patients are obtained, and a target endoscopic patient is randomly selected from the plurality of endoscopic examination patients; The video stream of the historical endoscopic examination corresponding to the target endoscopic patient is obtained, and the historical endoscopic video stream is obtained, and the historical endoscopic video stream is analyzed, and the target endoscopic video analysis data is obtained according to the analysis result; The nasal clinical symptoms of the target endoscopic patient are obtained, and a plurality of target nasal symptoms are obtained, and the target nasal symptoms are compared and analyzed with the historical patients, and a plurality of disease matching patients are obtained according to the analysis result; The endoscopic working video stream corresponding to each disease matching patient is obtained, and a plurality of matching patient endoscopic video streams are obtained; The process of image analysis of the historical endoscopic video stream is repeated, and the endoscopic video analysis data corresponding to each matching patient endoscopic video stream is obtained; The endoscopic video analysis data corresponding to each matching patient endoscopic video stream and the target endoscopic video analysis data are defined as the initial matching data of the endoscopic patient.

[0007] Further, the target endoscopic video analysis data is obtained, specifically as follows: The historical video stream coverage period is obtained in the time period range covered by the historical endoscopic video stream, a motion screenshot time point is set in the historical video stream coverage period, and a sample endoscopic screenshot image is obtained by image interception of the historical endoscopic video stream at the motion screenshot time point; The cavity region circle analysis of the sample endoscopic screenshot image is performed, and the cavity cross-sectional area value corresponding to the sample endoscopic screenshot image is obtained according to the analysis result; The historical video stream coverage period is traversed using the motion screenshot time point, the cavity cross-sectional area value of the endoscopic screenshot image corresponding to each time point is obtained, and the plurality of cavity cross-sectional area values obtained are set as M1 cavity cross-sectional area to Ma cavity cross-sectional area according to the order of the corresponding acquisition time points; The endoscope lens endoscopy depth in the cavity cross-sectional area value of M1 cavity cross-sectional area is obtained, and the M1 lens endoscopy depth is obtained. The endoscope lens endoscopy depth in the cavity cross-sectional area value of M2 cavity cross-sectional area is obtained, and the M2 lens endoscopy depth is obtained. Similarly, the endoscope lens endoscopy depth in the cavity cross-sectional area value of Ma cavity cross-sectional area is obtained, and the Ma lens endoscopy depth is obtained. M1 cavity cross-sectional area to Ma cavity cross-sectional area and M1 lens endoscopy depth to Ma lens endoscopy depth are set as target endoscopy video analysis data.

[0008] Further, the sample endoscopy image is analyzed for cavity region circle line, specifically as follows: The nasal cavity cavity region in the sample endoscopy image is marked, and a pixel point is randomly selected in the marked nasal cavity cavity region to obtain a cavity feature pixel point. A parallel circle line perpendicular to the long axis direction of the nasal cavity is drawn through the cavity feature pixel point to obtain a cavity feature circle line. A straight line perpendicular to the long axis direction of the nasal cavity is drawn through the feature pixel point to obtain a cavity feature straight line. The center direction of the sample endoscopy image is set as the distal extension direction of the cavity feature straight line, and the edge direction of the sample endoscopy image is set as the proximal extension direction corresponding to the cavity feature straight line. The image pixel points covered by the cavity feature circle line are obtained to obtain a plurality of circle line covered pixel points.

[0009] Further, the sample endoscopy image is analyzed for cavity region circle line, specifically as follows: If the obtained circle line covered pixel points are all in the nasal cavity cavity region, a cavity update pixel point is randomly selected in the proximal extension direction of the cavity feature straight line to obtain a cavity update pixel point. The distance interval between the cavity update pixel point and the cavity feature pixel point is an update pixel distance. A parallel circle line perpendicular to the long axis direction of the nasal cavity is drawn through the cavity update pixel point to obtain a cavity update circle line. The image pixel points covered by the cavity feature circle line are obtained to obtain a plurality of circle line covered pixel points. If the obtained circle line covered pixel points exist pixel points not in the nasal cavity cavity region, the cavity feature circle line is set as the maximum cavity circle line corresponding to the sample endoscopy image. If the obtained circle line covered pixel points are all in the nasal cavity cavity region, the above process is repeated until the obtained circle line covered pixel points exist pixel points not in the nasal cavity cavity region. If the obtained circle line covering pixel points exist pixel points not in the nasal cavity cavity region, a cavity feature pixel point is reselected in the extension direction of the distal end of the cavity characteristic straight line, an updated cavity pixel point is obtained, the distance interval between the updated cavity pixel point and the cavity feature pixel point is an updated pixel distance, a parallel circle line perpendicular to the direction of the nasal cavity long axis is drawn through the updated cavity pixel point, an updated cavity circle line is obtained, the image pixel points covered by the cavity feature circle line are obtained, and a plurality of circle line covering pixel points are obtained. If the obtained circle line covering pixel points are all in the nasal cavity cavity region, the cavity feature circle line is set as the largest cavity circle line corresponding to the sample endoscopic image, and if the obtained circle line covering pixel points exist pixel points not in the nasal cavity cavity region, the above process is repeated until the obtained circle line covering pixel points are all in the nasal cavity cavity region. The image region marked by the largest cavity circle line in the sample endoscopic image is obtained, a sample cavity space cross-sectional region is obtained, and a cavity cross-sectional area value corresponding to the sample endoscopic image is obtained by obtaining the area value of the sample cavity space cross-sectional region.

[0010] Further, a disease matching patient is obtained, and the specific process is as follows: A plurality of historical endoscopic patients are obtained by obtaining historical patients who have completed rhinologic endoscopy, and a sample endoscopic patient is selected from the plurality of historical endoscopic patients. The rhinologic clinical symptoms of the sample endoscopic patient are obtained, the obtained plurality of rhinologic clinical symptoms are compared with the target rhinologic symptom for symptom consistency, the rhinologic clinical symptoms that are consistent after comparison are set as consistent symptoms, and the ratio of the number value of the consistent symptoms to the number value of the target rhinologic symptom is calculated to obtain a clinical symptom matching degree corresponding to the sample endoscopic examination. The process of obtaining the clinical symptom matching degree corresponding to the sample endoscopic examination is repeated, and the clinical symptom matching degree corresponding to each historical endoscopic patient is obtained. A symptom matching degree preset interval is set, if the clinical symptom matching degree is in the symptom matching degree preset interval, the corresponding historical endoscopic patient is divided into a disease matching patient, and if the clinical symptom matching degree is not in the symptom matching degree preset interval, the corresponding historical endoscopic patient is divided into a non-disease matching patient.

[0011] Further, video stream matching data is obtained, and the specific process is as follows: Endoscopic patient initial matching data is obtained, target endoscopic video analysis data and endoscopic video analysis data corresponding to each matching patient endoscopic video stream are obtained according to the endoscopic patient initial matching data. According to the target endoscopic video analysis data, M1 cavity cross-sectional area to Ma cavity cross-sectional area and M1 lens endoscopic depth to Ma lens endoscopic depth are obtained, in a plane rectangular coordinate system, the coordinate point with the horizontal coordinate being the M1 lens endoscopic depth and the vertical coordinate being the M1 cavity cross-sectional area is set as the H1 target coordinate point, the coordinate point with the horizontal coordinate being the M2 lens endoscopic depth and the vertical coordinate being the M2 cavity cross-sectional area is set as the H2 target coordinate point, and so on, the coordinate point with the horizontal coordinate being the Ma lens endoscopic depth and the vertical coordinate being the Ma cavity cross-sectional area is set as the Ha target coordinate point; The H1 target coordinate point to the Ha target coordinate point is sequentially connected to obtain a target endoscopic cross-section change polyline, and a plane rectangular coordinate system in which the target endoscopic cross-section change polyline is located is set as an endoscopic cross-section coordinate system; In the obtained multiple matching patient endoscopic video streams, a sample matching video stream is randomly selected, and an endoscopic cross-section change polyline corresponding to the sample matching video stream is obtained according to the endoscopic video analysis data corresponding to the sample matching video stream, and is marked in the endoscopic cross-section coordinate system to obtain a sample endoscopic cross-section change polyline; The sample endoscopic cross-section change polyline and the target endoscopic cross-section change polyline are subjected to geometric feature analysis, and the endoscopic cavity similarity corresponding to the sample matching video stream is obtained according to the analysis result; The process of obtaining the endoscopic cavity similarity corresponding to the sample matching video stream is repeated to obtain the endoscopic cavity similarity corresponding to each matching patient endoscopic video stream; An endoscopic cavity similarity matching interval is set, if the endoscopic cavity similarity is in the endoscopic cavity similarity matching interval, the corresponding matching patient endoscopic video stream is set as a matching consistent video stream, if the endoscopic cavity similarity is not in the endoscopic cavity similarity matching interval, the corresponding matching patient endoscopic video stream is set as a non-matching consistent video stream, and video stream matching data is obtained.

[0012] Further, the endoscopic cross-section change polyline is subjected to geometric feature analysis, and the specific process is as follows: The horizontal coordinate value of the left end edge coordinate point corresponding to the sample endoscopic cross-section change polyline is obtained to obtain a first left end horizontal coordinate value, the horizontal coordinate value of the left end edge coordinate point corresponding to the target endoscopic cross-section change polyline is obtained to obtain a second left end horizontal coordinate value, if the first left end horizontal coordinate value is less than or equal to the second left end horizontal coordinate value, the left end edge coordinate point corresponding to the sample endoscopic cross-section change polyline is set as a first edge feature point, if the first left end horizontal coordinate value is greater than the second left end horizontal coordinate value, the left end edge coordinate point corresponding to the target endoscopic cross-section change polyline is set as the first edge feature point; The right end edge coordinate point corresponding to the sample endoscopic cross-section change polyline is acquired to obtain a first right end horizontal coordinate value, the right end edge coordinate point corresponding to the target endoscopic cross-section change polyline is acquired to obtain a second right end horizontal coordinate value, if the first right end horizontal coordinate value is less than or equal to the second right end horizontal coordinate value, the left end edge coordinate point corresponding to the target endoscopic cross-section change polyline is set as the second edge feature point, and if the first right end horizontal coordinate value is greater than the second right end horizontal coordinate value, the left end edge coordinate point corresponding to the sample endoscopic cross-section change polyline is set as the second edge feature point.

[0013] Further, the endoscopic cross-section change polyline is analyzed for geometric features, as follows: In the endoscopic cross-section coordinate system, a straight line perpendicular to the coordinate x-axis is drawn through the first edge feature point to obtain a first edge feature line, a straight line perpendicular to the coordinate x-axis is drawn through the second edge feature point to obtain a second edge feature line, and the closed area surrounded by the first edge feature line, the second edge feature line, the sample endoscopic cross-section change polyline and the target endoscopic cross-section change polyline is acquired to obtain a change polyline deviation area; The area of the change polyline deviation area is acquired to obtain a polyline deviation area value, the horizontal coordinate deviation of the second edge feature point and the first edge feature point is calculated to obtain a polyline deviation time period length value, and the vertical coordinate average value of the target endoscopic cross-section change polyline is calculated to obtain a target polyline vertical average value; The endoscopic cavity similarity corresponding to the sample endoscopic cross-section is obtained by calculating the polyline deviation area value, the polyline deviation time period length value and the target polyline vertical average value; The endoscopic cavity similarity corresponding to the sample matching video stream is calculated, and the specific formula is as follows: ; Wherein, Jmp is the endoscopic cavity similarity corresponding to the sample matching video stream, Szp is the polyline deviation area value, Tzp is the polyline deviation time period length value, and Zpz is the target polyline vertical average value.

[0014] Further, the endoscopic near-field trigger setting and image wireless transmission are as follows: The video stream matching data is acquired, the matching consistent video stream is acquired according to the video stream matching data, and the endoscope used for checking the target endoscopic patient is marked as a target endoscope; The initial adjustment focal length corresponding to each piece of matching consistent video stream is acquired, and the average of the obtained multiple initial adjustment focal lengths is calculated to obtain an initial endoscopic focal length, the endoscopic initial adjustment brightness corresponding to each piece of matching consistent video stream is acquired, and the average of the obtained multiple endoscopic initial adjustment brightness is calculated to obtain an initial endoscopic brightness; Synchronize the initial endoscopic focal length and the initial endoscopic brightness to the nfc near field trigger terminal, and complete the initial endoscopic focal length setting and the initial endoscopic brightness setting of the target endoscope through the nfc terminal built in the target endoscope and the nfc near field trigger terminal. After the setting is completed, the target endoscope performs real-time endoscopic image acquisition and wireless transmission of the real-time endoscopic image.

[0015] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present application are: 1. When performing wireless image acquisition and transmission, the present application can automatically connect the nasal endoscopic equipment and automatically adjust the initial shooting parameters according to the symptoms of different rhinology patients and the geometry of the nasal cavity, thereby effectively improving the image acquisition efficiency and quality of the rhinology endoscope. 2. The present application screens historical nasal endoscopic video streams by combining the nasal cavity similarity of the target patient and patients with the same disease, sets the initial endoscopic focal length and the initial endoscopic brightness of the endoscope by matching consistent video streams, and uses nfc near field trigger technology to complete the initial connection and invalid transmission setting of the endoscope, thereby effectively improving the endoscopic image transmission efficiency and quality. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to facilitate understanding by those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0017] Figure 1 The present application is a whole system block diagram; Figure 2 The present application is a cavity feature circle line schematic diagram; Figure 3 The present application is an extension direction schematic diagram. DETAILED DESCRIPTION

[0018] The technical solutions of the present application will be described below in conjunction with embodiments. Obviously, the described embodiments are only a part of the 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 are within the scope of protection of the present application.

[0019] Embodiment one Please refer to Figure 1 The present application provides a technical solution: an ear-nose-throat endoscope wireless image transmission system based on NFC near field trigger, comprising a data acquisition module, a data analysis module, an image transmission module and a server, the data acquisition module, the data analysis module and the image transmission module are connected with the server respectively, and the server controls the data acquisition module, the data analysis module and the image transmission module respectively. The data acquisition module obtains a historical endoscope working video stream corresponding to the target endoscopic patient, and performs frame-by-frame image interception. The target endoscopic video analysis data is obtained by combining the endoscopic depth to analyze the cross-sectional area of the intercepted image. The disease-matched patient is obtained by the clinical symptoms of the target endoscopic patient. The endoscopic video analysis data corresponding to the disease-matched patient is obtained, and the initial matching data of the endoscopic patient is obtained.

[0020] Specifically as follows: A plurality of endoscopic examination patients are obtained by obtaining a patient who needs to be examined by an ear-nose-throat endoscope. One target endoscopic patient is randomly selected from the plurality of endoscopic examination patients. It should be noted that: In the present application, the endoscopic examination performed by the target endoscopic patient is a nasal cavity endoscopic examination. In the present application, the patient who needs to be examined by an ear-nose-throat endoscope does not include a patient who performs an endoscopic examination for the first time, i.e., each patient who needs to be examined has a historical endoscopic working video stream.

[0021] The historical endoscopic examination corresponding to the target endoscopic patient is video-streamed to obtain a historical endoscopic video stream. The historical endoscopic video stream is analyzed, and the target endoscopic video analysis data is obtained according to the analysis result. It should be noted that: In the present application, the historical endoscopic video stream referred to herein is specifically a video stream corresponding to the last endoscopic examination at the current time.

[0022] The historical video stream coverage period is obtained by obtaining the period range covered by the historical endoscopic video stream. A motion screenshot time point is set in the historical video stream coverage period. The historical endoscopic video stream at the motion screenshot time point is image-intercepted to obtain a sample endoscopic interception image. The cavity region circle line analysis is performed on the sample endoscopic interception image, and the cavity cross-sectional area value corresponding to the sample endoscopic interception image is obtained according to the analysis result. It should be noted that: In the present application, in the historical video stream coverage, the endoscope lens is always parallel to the long axis of the nasal cavity, and the geometric center point of the endoscope lens is always coincided with the geometric center point of the nasal cavity cross section.

[0023] Please refer to Figure 2 The nasal cavity region in the sample endoscopic interception image is marked, and a pixel point is randomly selected in the marked nasal cavity region to obtain a cavity feature pixel point. A parallel circle line perpendicular to the direction of the long axis of the nasal cavity is drawn through the cavity feature pixel point to obtain a cavity feature circle line. Please refer to Figure 3 , a straight line perpendicular to the long axis direction of the nasal cavity is drawn through the characteristic pixel point, a cavity characteristic straight line is obtained, the center direction of the sample endoscope intercepted image is set as the distal end extension direction of the cavity characteristic straight line, and the edge direction of the sample endoscope intercepted image is set as the proximal end extension direction corresponding to the cavity characteristic straight line; The image pixel points covered by the cavity characteristic circle line are obtained, and a plurality of circle line covered pixel points are obtained. If the obtained circle line covered pixel points are all in the nasal cavity region, a cavity update pixel point is selected in the proximal end extension direction of the cavity characteristic straight line, the distance interval between the cavity update pixel point and the cavity characteristic pixel point is an update pixel distance, a parallel circle line perpendicular to the long axis direction of the nasal cavity is drawn through the cavity update pixel point, a cavity update circle line is obtained, the image pixel points covered by the cavity characteristic circle line are obtained, and a plurality of circle line covered pixel points are obtained. If the obtained circle line covered pixel points exist pixel points not in the nasal cavity region, the cavity characteristic circle line is set as the maximum cavity circle line corresponding to the sample endoscope intercepted image, and the above process is repeated until the obtained circle line covered pixel points exist pixel points not in the nasal cavity region. If the obtained circle line covered pixel points exist pixel points not in the nasal cavity region, a cavity update pixel point is selected in the distal end extension direction of the cavity characteristic straight line, the distance interval between the cavity update pixel point and the cavity characteristic pixel point is an update pixel distance, a parallel circle line perpendicular to the long axis direction of the nasal cavity is drawn through the cavity update pixel point, a cavity update circle line is obtained, the image pixel points covered by the cavity characteristic circle line are obtained, and a plurality of circle line covered pixel points are obtained. If the obtained circle line covered pixel points are all in the nasal cavity region, the cavity characteristic circle line is set as the maximum cavity circle line corresponding to the sample endoscope intercepted image, and the above process is repeated until the obtained circle line covered pixel points are all in the nasal cavity region. It should be noted here that: In the present application, the update pixel distance is specifically 10 pixel points in the coverage distance of the cavity characteristic straight line. In the present application, the nasal cavity region in the nasal endoscopic image is identified by setting a parallel circle line perpendicular to the long axis direction of the nasal cavity in the nasal endoscopic image, and the integrity coverage state of the circle line pixel point, the cavity cross-sectional area of different endoscopic depths is obtained according to the identification result, and the historical patients are screened for nasal cavity similarity analysis, which has the following advantages: In the nasal endoscopic image analysis process, a parallel circle line perpendicular to the long axis of the nasal cavity is first set to accurately identify the nasal cavity region by means of the complete pixel point coverage state. This method is not affected by the complex morphology of the nasal cavity, can clearly divide the nasal cavity and the surrounding tissue, effectively filter image noise, and ensure the accuracy of identification. Based on accurate nasal cavity region identification, the cross-sectional area of the cavity at different endoscopic depths is obtained, which can quantitatively present the structural characteristics of the nasal cavity, help doctors intuitively understand the size and shape changes of the nasal cavity, provide a strong basis for disease diagnosis, and also dynamically track the disease progression and treatment effect; Then, by screening historical patients, nasal similarity analysis is carried out to find cases with highly similar nasal conditions to the target patient. The initial focus and initial brightness data of the endoscope of these similar patients are used to initialize and adjust the brightness and focus of the endoscope of the target patient. In this way, the endoscope can quickly reach the parameter state suitable for the target patient's nasal examination, reducing the adjustment time and trial and error cost, improving the examination efficiency and accuracy, and laying a good foundation for subsequent accurate diagnosis and treatment.

[0024] The image region marked by the maximum cavity circle line in the sample endoscopic image is obtained, and the sample cavity space cross-sectional region is obtained. The area value of the sample cavity space cross-sectional region is obtained, and the cross-sectional area value of the cavity corresponding to the sample endoscopic image is obtained. The historical video stream coverage period is traversed using the motion screenshot time point, and the cross-sectional area value of the cavity corresponding to the endoscopic image at each time point is obtained. The obtained multiple cross-sectional area values of the cavity are set as M1 cross-sectional area to Ma cross-sectional area according to the order of the corresponding acquisition time points. It should be noted that: In this application, M1, M2, M3,..., Ma in M1 cross-sectional area to Ma cross-sectional area are respectively the marker symbols corresponding to the cross-sectional area values.

[0025] The endoscopic depth when the endoscope lens is at the cross-sectional area value of M1 cross-sectional area is obtained, and the M1 lens endoscopic depth is obtained. The endoscopic depth when the endoscope lens is at the cross-sectional area value of M2 cross-sectional area is obtained, and the M2 lens endoscopic depth is obtained. Similarly, the endoscopic depth when the endoscope lens is at the cross-sectional area value of Ma cross-sectional area is obtained, and the Ma lens endoscopic depth is obtained. M1 cross-sectional area to Ma cross-sectional area and M1 lens endoscopic depth to Ma lens endoscopic depth are set as target endoscopic video analysis data; The nasal clinical symptoms of the target endoscopic patient are obtained, and multiple target nasal symptoms are obtained. It should be noted that: In the present application, the rhinological clinical symptoms referred to herein include, but are not limited to, nasal congestion, increased nasal secretion, and nosebleed.

[0026] The historical patients who have completed rhinoscopy are obtained, and a plurality of historical endoscopy patients are obtained. The rhinological clinical symptoms of the sample endoscopy patient are obtained, and the obtained plurality of rhinological clinical symptoms are compared with the target rhinological symptoms for symptom consistency, the rhinological clinical symptoms that are consistent after comparison are set as consistent symptoms, the ratio of the number of consistent symptoms to the number of target rhinological symptoms is calculated, and the clinical symptom matching degree corresponding to the sample endoscopy is obtained. The process of obtaining the clinical symptom matching degree corresponding to the sample endoscopy is repeated, and the clinical symptom matching degree corresponding to each historical endoscopy patient is obtained, and a symptom matching degree preset interval is set, if the clinical symptom matching degree is in the symptom matching degree preset interval, the corresponding historical endoscopy patient is divided into a disease matching patient, and if the clinical symptom matching degree is not in the symptom matching degree preset interval, the corresponding historical endoscopy patient is divided into a non-disease matching patient. It should be noted that: The endoscopy historical matching record is obtained, and the plurality of historical disease matching patients obtained according to the endoscopy historical matching record are obtained, and the clinical symptom matching degree corresponding to each historical disease matching patient is obtained, the maximum value of the clinical symptom matching degree is set as the upper limit of the symptom matching degree preset interval, and the minimum value of the clinical symptom matching degree is set as the lower limit of the symptom matching degree preset interval, and the symptom matching degree preset interval is obtained.

[0027] Each endoscopy video stream corresponding to each disease matching patient is obtained, and a plurality of matching patient endoscopy video streams are obtained. It should be noted that: In the present application, the endoscopy video stream referred to herein has the same time length as the historical endoscopy video stream.

[0028] The process of image analysis of the historical endoscopy video stream is repeated, and the endoscopy video analysis data corresponding to each matching patient endoscopy video stream is obtained. The endoscopy video analysis data corresponding to each matching patient endoscopy video stream and the target endoscopy video analysis data are defined as endoscopy patient initial matching data. The data analysis module performs cross-sectional area analysis and lens endoscopy depth analysis on the endoscopy video stream according to the initial matching data of the endoscopy patient, obtains the endoscopy cavity similarity corresponding to the matching patient endoscopy video stream according to the analysis result, performs type division on the matching patient endoscopy video stream according to the endoscopy cavity similarity, and obtains video stream matching data; The specific implementation is as follows: Obtain initial matching data of the endoscopy patient, and obtain target endoscopy video analysis data and endoscopy video analysis data corresponding to each segment of the matching patient endoscopy video stream according to the initial matching data of the endoscopy patient. Obtain M1 cavity cross-sectional area to Ma cavity cross-sectional area and M1 lens endoscopy depth to Ma lens endoscopy depth according to the target endoscopy video analysis data, set a coordinate point with the horizontal coordinate being the M1 lens endoscopy depth and the vertical coordinate being the M1 cavity cross-sectional area as an H1 target coordinate point, set a coordinate point with the horizontal coordinate being the M2 lens endoscopy depth and the vertical coordinate being the M2 cavity cross-sectional area as an H2 target coordinate point, and set a coordinate point with the horizontal coordinate being the Ma lens endoscopy depth and the vertical coordinate being the Ma cavity cross-sectional area as an Ha target coordinate point. It should be noted that: In the present application, H1, H2, H3,..., Ha in the H1 target coordinate point to the Ha target coordinate point are respectively the mark symbols corresponding to the target coordinate points.

[0029] Connect the H1 target coordinate point to the Ha target coordinate point in sequence to obtain a target endoscopy cross-sectional variation polyline, and set a plane rectangular coordinate system in which the target endoscopy cross-sectional variation polyline is located as an endoscopy cross-sectional coordinate system. Select a sample matching video stream from the obtained multiple segments of the matching patient endoscopy video stream, obtain an endoscopy cross-sectional variation polyline corresponding to the sample matching video stream according to the endoscopy video analysis data corresponding to the sample matching video stream, and mark the endoscopy cross-sectional variation polyline in the endoscopy cross-sectional coordinate system to obtain a sample endoscopy cross-sectional variation polyline. Perform geometric feature analysis on the sample endoscopy cross-sectional polyline and the target endoscopy cross-sectional variation polyline, and obtain the endoscopy cavity similarity corresponding to the sample matching video stream according to the analysis result. The specific implementation is as follows: Obtain a first left end horizontal coordinate value by obtaining a horizontal coordinate value of a left end edge coordinate point corresponding to the sample endoscopy cross-sectional polyline, obtain a second left end horizontal coordinate value by obtaining a horizontal coordinate value of a left end edge coordinate point corresponding to the target endoscopy cross-sectional polyline, set the left end edge coordinate point corresponding to the sample endoscopy cross-sectional polyline as a first edge feature point if the first left end horizontal coordinate value is less than or equal to the second left end horizontal coordinate value, or set the left end edge coordinate point corresponding to the target endoscopy cross-sectional polyline as the first edge feature point if the first left end horizontal coordinate value is greater than the second left end horizontal coordinate value. Obtaining the horizontal coordinate value of the right end edge coordinate point corresponding to the sample endoscopic cross-section polyline, obtaining a first right end horizontal coordinate value, obtaining the horizontal coordinate value of the right end edge coordinate point corresponding to the target endoscopic cross-section polyline, obtaining a second right end horizontal coordinate value, if the first right end horizontal coordinate value is less than or equal to the second right end horizontal coordinate value, setting the left end edge coordinate point corresponding to the target endoscopic cross-section polyline as a second edge feature point, if the first right end horizontal coordinate value is greater than the second right end horizontal coordinate value, setting the left end edge coordinate point corresponding to the sample endoscopic cross-section polyline as the second edge feature point; In the endoscopic cross-section coordinate system, a straight line perpendicular to the coordinate x-axis is drawn through the first edge feature point to obtain a first edge feature line, a straight line perpendicular to the coordinate x-axis is drawn through the second edge feature point to obtain a second edge feature line, and a closed area surrounded by the first edge feature line, the second edge feature line, the sample endoscopic cross-section change polyline and the target endoscopic cross-section change polyline is obtained to obtain a change polyline deviation area; Obtaining the area of the change polyline deviation area to obtain a polyline deviation area value, calculating the horizontal coordinate deviation of the second edge feature point and the first edge feature point to obtain a polyline deviation time period length value, and calculating the vertical average value of the target endoscopic cross-section change polyline to obtain a target polyline vertical average value; The endoscopic cavity similarity corresponding to the sample endoscopic cross-section is obtained by calculating the polyline deviation area value, the polyline deviation time period length value and the target polyline vertical average value; The endoscopic cavity similarity corresponding to the sample matching video stream is calculated, and the specific formula is as follows: ; Wherein, Jmp is the endoscopic cavity similarity corresponding to the sample matching video stream, Szp is the polyline deviation area value, Tzp is the polyline deviation time period length value, and Zpz is the target polyline vertical average value; The process of obtaining the endoscopic cavity similarity corresponding to the sample matching video stream is repeated to obtain the endoscopic cavity similarity corresponding to each matching patient endoscopic video stream; An endoscopic cavity similarity matching interval is set, if the endoscopic cavity similarity is in the endoscopic cavity similarity matching interval, the corresponding matching patient endoscopic video stream is set as a matching consistent video stream, if the endoscopic cavity similarity is not in the endoscopic cavity similarity matching interval, the corresponding matching patient endoscopic video stream is set as a non-matching consistent video stream, and video stream matching data is obtained; It should be noted that: The history matching consistent video stream in the endoscope history matching record is acquired, the endoscopic cavity similarity corresponding to each history matching consistent video stream is acquired respectively, and the obtained multiple endoscopic cavity similarities are compared in value size, the endoscopic cavity similarity with the maximum value is set as the upper limit of the endoscope similarity matching interval, the endoscopic cavity similarity with the minimum value is set as the lower limit of the endoscope similarity matching interval, and the endoscope similarity matching interval is obtained.

[0030] The image transmission module sets the endoscope near field trigger for the target endoscopic patient according to the video stream matching data and wirelessly transmits the endoscopic image. Specifically as follows: The video stream matching data is acquired, the matching consistent video stream is acquired according to the video stream matching data, and the endoscope used for examining the target endoscopic patient is marked as the target endoscope. The initial adjustment focal length corresponding to each piece of matching consistent video stream is acquired, the average of the obtained multiple initial adjustment focal lengths is calculated to obtain the initial endoscopic focal length, the initial adjustment brightness of the endoscope corresponding to each piece of matching consistent video stream is acquired, and the average of the obtained multiple initial adjustment brightness of the endoscope is calculated to obtain the initial endoscopic brightness. It needs to be explained here that: In the present application, the initial adjustment focal length referred to here is specifically the endoscope focal length after the initial endoscope focal length adjustment of the endoscope operator in the matching consistent video stream, and the initial adjustment brightness of the endoscope referred to here is specifically the endoscope brightness after the initial endoscope brightness adjustment of the endoscope operator in the matching consistent video stream.

[0031] The initial endoscopic focal length and the initial endoscopic brightness are synchronized to the nfc near field trigger terminal, and the initial endoscopic focal length setting and the initial endoscopic brightness setting of the target endoscope are completed through the nfc terminal built in the target endoscope and the nfc near field trigger terminal. The specific setting process is as follows: In the process of initial parameter configuration of the target endoscope, the initial endoscopic focal length value and the initial endoscopic brightness value are transmitted synchronously to the trigger terminal device with NFC near field communication function, so as to ensure that the terminal stores accurate and to-be-configured parameter information. Then, the endoscope equipment operator makes the part where the NFC communication module of the target endoscope is located contact the NFC near field trigger terminal which has stored the initial parameters, so as to establish a wireless direct communication link through the near field induction and data interaction mechanism specific to NFC technology. In the direct communication state, the NFC near field trigger terminal automatically transmits the stored initial endoscopic focal length setting instruction and the initial endoscopic brightness setting instruction to the internal control system of the target endoscope. After the target endoscope receives these setting instructions, the internal adjustment module thereof automatically operates the focal length adjustment unit and the brightness adjustment unit according to the instruction requirements, so as to complete the setting of the initial endoscopic focal length and the initial endoscopic brightness of the target endoscope, and enable the target endoscope to be put into subsequent use in the preset appropriate parameter state.

[0032] After the setting is completed, the target endoscope acquires real-time endoscopic images and transmits the real-time endoscopic images wirelessly.

[0033] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details and do not limit the present application to the specific embodiments. Obviously, according to the content of the present application, many modifications and changes can be made. The present application is selected and described in detail, so as to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited by the claims and their entire scope and equivalents.

Claims

1. A wireless image transmission system for ENT endoscopes based on NFC near-field triggering, characterized in that, include: Data acquisition module: acquires the historical endoscopic video stream corresponding to the target endoscopic patient and performs frame-by-frame image capture. Combines the endoscopic depth with cavity cross-sectional area analysis of the captured images to obtain target endoscopic video analysis data. Based on the clinical symptoms of the target endoscopic patient, it performs symptom matching patient screening, obtains endoscopic video analysis data corresponding to the symptom matching patients, and obtains initial matching data for endoscopic patients. Data Analysis Module: Based on the initial matching data of endoscopic patients, the module performs cross-sectional area analysis and lens endoscopic depth analysis on the endoscopic video stream. Based on the analysis results, it obtains the endoscopic cavity similarity corresponding to the endoscopic video stream of the matched patients. Based on the endoscopic cavity similarity, the module classifies the endoscopic video stream of the matched patients into different types to obtain video stream matching data. Image transmission module: Sets up near-field triggering for the endoscope and wirelessly transmits endoscopic images to the target endoscopic patient based on video stream matching data.

2. The NFC-based near-field triggered wireless image transmission system for ENT endoscopes according to claim 1, characterized in that, The initial matching data for endoscopic patients was obtained as follows: Acquire patients for endoscopic examinations, and randomly select a target endoscopic patient from among them; Video streams of historical endoscopic examinations corresponding to the target endoscopic patient are acquired to obtain historical endoscopic video streams. Image analysis is performed on the historical endoscopic video streams, and target endoscopic video analysis data is obtained based on the analysis results. The clinical symptoms of nasal diseases in the target endoscopic patients were obtained, resulting in multiple target nasal symptoms. The target nasal symptoms were compared and analyzed with those of historical patients, and multiple patients matching the symptoms were obtained based on the analysis results. For each patient matched with a disease, the corresponding endoscopic video stream is acquired, resulting in multiple endoscopic video streams for matched patients. The endoscopic video analysis data corresponding to each segment of the endoscopic video stream for matched patients is then obtained. Endoscopic video analysis data and target endoscopic video analysis data are defined as initial matching data for endoscopic patients.

3. The NFC-based near-field triggered wireless image transmission system for ENT endoscopes according to claim 2, characterized in that, The data obtained from the target endoscopic video analysis is as follows: The historical endoscopic video stream is captured within a time period covered by the historical video stream. A motion screenshot time point is set within the historical video stream coverage period to capture images from the historical endoscopic video stream, resulting in a sample endoscopic image. Perform cavity region circumferential analysis on the endoscopic images of the sample, and obtain the cross-sectional area value of the cavity corresponding to the endoscopic images of the sample based on the analysis results; By using motion capture time points to traverse the historical video stream coverage period, the cross-sectional area value of the cavity in the endoscope image captured at each time point is obtained. The cross-sectional area value of the cavity is then obtained according to the endoscopic depth at the corresponding acquisition time point. Multiple lens endoscopic depths are used to obtain target endoscopic video analysis data.

4. The NFC-based near-field triggered wireless image transmission system for ENT endoscopes according to claim 3, characterized in that, The cavity region was analyzed by circumferential analysis of the endoscopic images of the sample, as follows: The nasal cavity region in the endoscopic image is marked, and a pixel is randomly selected in the marked nasal cavity region to obtain the cavity feature pixel. A parallel circle line perpendicular to the long axis of the nasal cavity is drawn through the cavity feature pixel to obtain the cavity feature circle line. Draw a straight line perpendicular to the long axis of the nasal cavity through the feature pixel to obtain the cavity feature line, and obtain the distal extension direction and proximal extension direction for the cavity feature line respectively. The image pixels covered by the cavity feature circles are obtained, resulting in multiple circle-covered pixels.

5. The NFC-based near-field triggered wireless image transmission system for ENT endoscopes according to claim 4, characterized in that, The cavity region was analyzed by circumferential analysis of the endoscopic images of the sample, as follows: If all the pixels covered by the obtained circle are in the nasal cavity area, proceed to step 1; if there are pixels covered by the obtained circle that are not in the nasal cavity area, proceed to step 3. Step 1: Select a new cavity feature pixel in the proximal extension direction of the cavity feature line to obtain the cavity update pixel. Draw a parallel circle line perpendicular to the long axis of the nasal cavity through the cavity update pixel to obtain the cavity update circle line. Obtain the image pixels covered by the cavity feature circle line to obtain multiple circle line covered pixels. If there are pixels in the circle line covered pixels that are not in the nasal cavity area, set the cavity feature circle line as the largest cavity circle line corresponding to the sample endoscopic cropped image. Step 2: If all the pixels covered by the obtained circle are in the nasal cavity area, repeat Step 1 until there are pixels covered by the obtained circle that are not in the nasal cavity area, then proceed to Step 5. Step 3: Select a new cavity feature pixel in the direction of the far end of the cavity feature line to obtain the cavity update pixel. Draw a parallel circle line perpendicular to the long axis of the nasal cavity through the cavity update pixel to obtain the cavity update circle line. Obtain the image pixels covered by the cavity feature circle line to obtain multiple circle line covered pixels. If all the obtained circle line covered pixels are in the nasal cavity area, then set the cavity feature circle line as the largest cavity circle line corresponding to the sample endoscopic image. Step 4: If there are pixels covered by the obtained circle line that are not in the nasal cavity area, repeat step 3 until all pixels covered by the obtained circle line are in the nasal cavity area, then proceed to step 5. Step 5: Obtain the image region marked by the maximum cavity circle line in the sample endoscope image to obtain the sample cavity spatial cross-sectional region. Obtain the area value of the sample cavity spatial cross-sectional region to obtain the cavity cross-sectional area value corresponding to the sample endoscope image.

6. The NFC-based near-field triggered wireless image transmission system for otolaryngology endoscopes according to claim 1, characterized in that, The process of acquiring patients based on disease matching is as follows: The history of patients who have completed nasal endoscopy is obtained, resulting in multiple historical endoscopic examination patients. One sample endoscopic examination patient is randomly selected from the multiple historical endoscopic examination patients. Acquire the nasal clinical symptoms of patients undergoing endoscopic examination, compare the acquired nasal clinical symptoms with the target nasal symptoms for symptom consistency, set the nasal clinical symptoms with consistent symptom consistency as consistent symptoms, and calculate the ratio of the number of consistent symptoms to the number of target nasal symptoms to obtain the clinical symptom matching degree corresponding to the endoscopic examination of the sample. For each patient undergoing a historical endoscopic examination, the clinical symptom matching degree is obtained. A preset range for symptom matching degree is set. If the clinical symptom matching degree is within the preset range, the corresponding patient undergoing a historical endoscopic examination is classified as a patient with a matching symptom. If the clinical symptom matching degree is not within the preset range, the corresponding patient undergoing a historical endoscopic examination is classified as a patient without a matching symptom.

7. The NFC-based near-field triggered wireless image transmission system for otolaryngology endoscopes according to claim 6, characterized in that, The video stream matching data is obtained as follows: Acquire initial matching data for endoscopic patients, and based on the initial matching data for endoscopic patients, acquire target endoscopic video analysis data and endoscopic video analysis data corresponding to each segment of matched patient endoscopic video stream; Based on the target endoscopic video analysis data, the cavity cross-sectional area and lens endoscopic depth are obtained. The coordinates of the points with the lens endoscopic depth on the horizontal axis and the cavity cross-sectional area on the vertical axis are connected sequentially to obtain the target endoscopic cross-section change polygon. The plane rectangular coordinate system where the target endoscopic cross-section change polygon is located is set as the endoscopic cross-section coordinate system. In the acquired multi-segment matched patient endoscopic video streams, arbitrarily select a sample matched video stream, obtain the endoscopic cross-sectional change polyline corresponding to the sample matched video stream based on the endoscopic video analysis data, and mark it in the endoscopic cross-sectional coordinate system to obtain the sample endoscopic cross-sectional change polyline; Geometric feature analysis was performed on the sample endoscope cross-section polygon and the target endoscope cross-section change polygon. Based on the analysis results, the sample matching video stream and the endoscope cavity similarity corresponding to each segment of the matching patient endoscope video stream were obtained. Set an endoscope cavity similarity matching interval. If the endoscope cavity similarity is within the endoscope cavity similarity matching interval, then set the corresponding matched patient endoscope video stream as a matched video stream. If the endoscope cavity similarity is not within the endoscope cavity similarity matching interval, then set the corresponding matched patient endoscope video stream as a non-matched video stream, thus obtaining video stream matching data.

8. The NFC-based near-field triggered wireless image transmission system for ENT endoscopes according to claim 7, characterized in that, Geometric feature analysis was performed on the polygonal line representing the change in the endoscopic cross section, as detailed below: The abscissa values ​​of the left edge coordinate points corresponding to the broken line of the sample endoscopic cross section are obtained to obtain the first left edge abscissa value. The abscissa values ​​of the left edge coordinate points corresponding to the broken line of the target endoscopic cross section are obtained to obtain the second left edge abscissa value. If the first left edge abscissa value is less than or equal to the second left edge abscissa value, the left edge coordinate points corresponding to the broken line of the sample endoscopic cross section are set as the first edge feature points. If the first left edge abscissa value is greater than the second left edge abscissa value, the left edge coordinate points corresponding to the broken line of the target endoscopic cross section are set as the first edge feature points. The abscissa values ​​of the right edge coordinate points corresponding to the broken line of the sample endoscopic cross section are obtained to obtain the first right edge abscissa value. The abscissa values ​​of the right edge coordinate points corresponding to the broken line of the target endoscopic cross section are obtained to obtain the second right edge abscissa value. If the first right edge abscissa value is less than or equal to the second right edge abscissa value, the left edge coordinate point corresponding to the broken line of the target endoscopic cross section is set as the second edge feature point. If the first right edge abscissa value is greater than the second right edge abscissa value, the left edge coordinate point corresponding to the broken line of the sample endoscopic cross section is set as the second edge feature point.

9. The NFC-based near-field triggered wireless image transmission system for otolaryngology endoscopes according to claim 8, characterized in that, Geometric feature analysis was performed on the polygonal line representing the change in the endoscopic cross section, as detailed below: In the endoscopic cross-section coordinate system, a straight line perpendicular to the x-axis is drawn through the first edge feature point to obtain the first edge feature line. A straight line perpendicular to the x-axis is drawn through the second edge feature point to obtain the second edge feature line. The closed area enclosed by the first edge feature line, the second edge feature line, the sample endoscopic cross-section change line, and the target endoscopic cross-section change line is obtained to obtain the change line deviation area. The area of ​​the variable polyline deviation region is obtained, and the area value of the polyline deviation region is obtained. The abscissa deviation between the second edge feature point and the first edge feature point is calculated to obtain the length value of the polyline deviation time period. The average ordinate of the variable polyline of the target endoscopic section is calculated to obtain the average longitudinal ordinate of the target polyline. The similarity of the endoscopic cavity corresponding to the sample endoscopic cross section is obtained by calculating the area value of the broken line deviation region, the length value of the broken line deviation time period, and the longitudinal average value of the target broken line.

10. The NFC-based near-field triggered wireless image transmission system for otolaryngology endoscopes according to claim 1, characterized in that, The specific settings for endoscope near-field triggering and wireless image transmission are as follows: Acquire video stream matching data, acquire matching video streams based on the video stream matching data, and mark the endoscope used to examine the target endoscopic patient as the target endoscope; Obtain the initial adjustment focal length corresponding to each matching video stream, calculate the average of the multiple initial adjustment focal lengths to obtain the initial endoscopic focal length, obtain the initial endoscopic adjustment brightness corresponding to each matching video stream, and calculate the average of the multiple initial endoscopic adjustment brightnesses to obtain the initial endoscopic brightness. The initial endoscopic focus and initial endoscopic brightness are synchronized to the NFC near-field trigger terminal. The initial endoscopic focus and initial endoscopic brightness of the target endoscope are set by directly connecting the NFC terminal built into the target endoscope to the NFC near-field trigger terminal. Once the setup is complete, the target endoscope acquires real-time endoscopic images and transmits them wirelessly.

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