CN111419154A - AI artificial intelligence wireless endoscope camera system - Google Patents
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- A61B1/00002—Operational features of endoscopes
- A61B1/00004—Operational features of endoscopes characterised by electronic signal processing
- A61B1/00009—Operational features of endoscopes characterised by electronic signal processing of image signals during a use of endoscope
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- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
- A61B1/00002—Operational features of endoscopes
- A61B1/00011—Operational features of endoscopes characterised by signal transmission
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Abstract
The invention discloses an AI artificial intelligence wireless endoscope camera system, which comprises a wireless endoscope camera acquisition device, a Pad, a remote server, a disease sample plate picture acquisition module, a disease sample plate picture database, a disease sample plate picture classification and judgment module, an image recognition algorithm realization and verification module, an AI artificial intelligence remote analysis sample plate and a judgment result feedback module; the wireless endoscope camera shooting and collecting device is in signal connection with the Pad through wireless signals, and the Pad is in signal connection with the remote server through wireless signals. The AI artificial intelligent wireless endoscope camera system provided by the invention realizes accurate analysis of the acquired disease picture, can obtain accurate disease information, realizes automatic AI judgment results, can be used for conducting endoscopy in primary hospitals, and solves the problem that endoscopy is difficult to conduct in primary hospitals.
Description
Technical Field
The invention relates to the technical field of endoscopes, in particular to an AI artificial intelligence wireless endoscope camera system.
Background
An endoscope is a tube equipped with a light that can enter the stomach orally or through other natural orifices. Since a lesion which cannot be visualized by X-ray can be seen by an endoscope, it plays a very important role in the medical field. The endoscope has been improved for 200 years, from the original hard tube type endoscope, the half-curve type endoscope to the fiber endoscope and the present electronic endoscope, the image quality has a secondary leap. Originally, a hard tube endoscope developed by Bozzine uses candle light as a light source, and then is changed into a bulb as a light source, and a color photo or a color electric view is obtained from the endoscope at present, the image is no longer a common image of a tissue organ, twenty-like microcosmic idea observed under a microscope, tiny lesions are clear and distinguishable, and the image quality reaches a higher level.
In the prior art, the handle end of the electronic endoscope is connected with the imaging device through a video data line so as to transmit signals acquired by an image acquisition unit of the electronic endoscope to the imaging device through the video data line for display. Moreover, the handle end and the imaging equipment of the conventional electronic endoscope have huge volumes, high manufacturing cost and inconvenient carrying, and the acquired picture information has the same parts due to various disease symptoms, so that the acquired picture information needs to be processed and analyzed, but not all doctors can accurately analyze the disease symptoms according to naked eyes, and the AI artificial intelligent wireless endoscope camera system is provided for analyzing the picture acquired by the endoscope more accurately to obtain an accurate analysis result.
Disclosure of Invention
The invention aims to provide an AI artificial intelligence wireless endoscope camera system, which can realize accurate analysis of acquired disease pictures, accurate disease information can be obtained, automatic AI judgment results can be realized, primary hospitals can also carry out endoscopy, and the problem that primary hospitals are difficult to carry out endoscopy is solved, so that the problem that primary endoscopy is difficult to carry out in the background technology is solved.
In order to achieve the purpose, the invention provides the following technical scheme: an AI artificial intelligence wireless endoscope camera system comprises a wireless endoscope camera acquisition device, a Pad, a remote server, a disease sample plate picture acquisition module, a disease sample plate picture database, a disease sample plate picture classification and judgment module, an image recognition algorithm realization and verification module, an AI artificial intelligence remote analysis sample plate and a judgment result feedback module; the wireless endoscope camera shooting and collecting device is in signal connection with the Pad through a wireless signal, and the Pad is in signal connection with the remote server through a wireless signal; the output end of the disease sample plate image acquisition module is connected with the input end of a disease sample plate image database, and the output end of the disease sample plate image database is connected with the input end of a remote server; the disease sample plate image classification and judgment module, the image recognition algorithm realization and verification module, the AI artificial intelligence remote analysis sample plate and the judgment result feedback module are connected with a remote server.
Preferably, the wireless endoscope camera shooting and collecting device comprises an image collector, a first processor, a first 5.8G wireless audio/video transceiver module, a second processor, a video collector and a display, wherein a video output end of the image collector is connected with a video input end of the first 5.8G wireless audio/video transceiver module, each channel control end of the first 5.8G wireless audio/video transceiver module is respectively connected with an IO port of the first processor, and a signal transmitting channel of the first 5.8G wireless audio/video transceiver module is controlled by the first processor; the second processor is connected with the second 5.8G wireless audio/video transceiver module, and the video output end of the second 5.8G wireless audio/video transceiver module is connected with the display through the video collector; and each channel control end of the second 5.8G wireless audio/video transceiver module is respectively connected with an IO port of the second processor, and the second processor controls a signal receiving channel of the second 5.8G wireless audio/video transceiver module.
Preferably, a third 5.8G wireless audio/video receiving module and a first 5G signal transceiving module are arranged in the Pad, the third 5.8G wireless audio/video receiving module is in signal connection with the first 5.8G wireless audio/video transmitting module through a wireless signal, and the Pad controls a signal transmitting channel of the first 5G signal transceiving module.
Preferably, the remote server is internally provided with a second 5G signal transceiver module, the remote server is programmed with an AI artificial intelligence image core analysis algorithm, and the second 5G signal transceiver module is in signal connection with the first 5G signal transceiver module through a wireless signal.
Preferably, the disease template picture collection module is used for collecting various disease template pictures.
Preferably, the disease template picture database is used for storing various disease template pictures for calling out by a remote server.
Preferably, the disease sample plate image classification and determination module calls out all disease sample plate images in the disease sample plate image database, classifies all disease sample plate images according to different diseases, and determines symptoms corresponding to each disease sample plate image.
Preferably, the image recognition algorithm implementation and verification module calls out the result of the disease sample plate picture classification and judgment module for judging each disease sample plate picture, recognizes each disease sample plate picture, and performs algorithm verification.
Preferably, the AI artificial intelligence remote analysis template compares the picture information received by the remote server from the Pad end with each disease template picture to obtain a disease template picture matched with the picture information received from the Pad end, calls out disease information corresponding to the corresponding disease template picture, uploads the called out disease information to the remote server, and the remote server feeds back the result obtained by the judgment to the Pad through a built-in judgment result feedback module.
Compared with the prior art, the invention has the beneficial effects that: the AI artificial intelligence wireless endoscope camera system provided by the invention is characterized in that an image collector of a wireless endoscope camera collection device collects picture information in the stomach of a patient and outputs the collected information, a first processor controls a signal transmitting channel of a first 5.8G wireless audio/video transceiver module, a second 5.8G wireless audio/video transceiver module receives the picture information sent by the first 5.8G wireless audio/video transceiver module and transmits the information to a Pad, and the Pad transmits the received picture information to a remote server, wherein the Pad is used as an intermediate of the wireless endoscope camera collection device and the remote server for information transmission; 20000-plus-50000 picture libraries with different pathological changes are established in the disease template picture database, an expert group manually analyzes all pictures in the picture library, classifies various diseases and correspondingly places various diseases together, AI image recognition learning is carried out after pictures received by Pad are recognized, the pictures obtained by picture recognition learning are transmitted to a remote server, the remote server transmits information to a disease template picture classification and judgment module, and the information transmission is matched with various disease template pictures, so that the diseases corresponding to the pictures received by Pad can be obtained; then feeding back the obtained real information to the wireless endoscope camera shooting and collecting device, and finally displaying the disease information by a display, so that a doctor can obtain an accurate disease analysis result; the acquired disease pictures are integrally and accurately analyzed, the acquired disease information can be obtained, the AI automatic judgment result is realized, the primary hospital can also carry out endoscopy, and the problem that the primary hospital cannot carry out endoscopy easily is solved.
Drawings
FIG. 1 is a block diagram of the principle structure of the present invention;
FIG. 2 is a functional diagram of a first processor pin according to the present invention;
FIG. 3 is a functional diagram of a second processor pin according to the present invention;
fig. 4 is a schematic circuit diagram of a first 5.8G wireless audio/video transceiving module according to the present invention;
fig. 5 is a schematic circuit diagram of a second 5.8G wireless audio/video transceiver module according to the present invention.
In the figure: 1. a wireless endoscope camera shooting and collecting device; 11. an image collector; 12. a first processor; 13. the first 5.8G wireless audio/video transceiving module; 14. the second 5.8G wireless audio/video transceiving module; 15. a second processor; 16. a video collector; 17. a display; 2. pad; 21. a third 5.8G wireless audio/video transceiving module; 22. a first 5G signal transceiving module; 3. a remote server; 31. a second 5G signal transceiving module; 4. a disease sample plate picture acquisition module; 5. a disease template picture database; 6. a disease sample plate picture classification and judgment module; 7. realizing and verifying an image recognition algorithm; 8. AI artificial intelligence remote analysis template; 9. and a judgment result feedback module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, an AI artificial intelligence wireless endoscopic camera system comprises a wireless endoscopic camera acquisition device 1, a Pad2, a remote server 3, a disease template picture acquisition module 4, a disease template picture database 5, a disease template picture classification and judgment module 6, an image recognition algorithm implementation and verification 7, an AI artificial intelligence remote analysis template 8 and a judgment result feedback module 9; the wireless endoscope camera shooting and collecting device 1 is in signal connection with the Pad2 through wireless signals, and the Pad2 is in signal connection with the remote server 3 through wireless signals; the output end of the disease sample plate picture acquisition module 4 is connected with the input end of a disease sample plate picture database 5, and the output end of the disease sample plate picture database 5 is connected with the input end of the remote server 3; the disease sample plate picture classification and judgment module 6, the image recognition algorithm realization and verification module 7, the AI artificial intelligence remote analysis sample plate 8 and the judgment result feedback module 9 are all connected with the remote server 3.
Wherein: the wireless endoscope camera shooting and collecting device 1 comprises an image collector 11, a first processor 12, a first 5.8G wireless audio/video receiving and transmitting module 13, a second 5.8G wireless audio/video receiving and transmitting module 14, a second processor 15, a video collector 16 and a display 17, wherein a video output end of the image collector 11 is connected with a video input end of the first 5.8G wireless audio/video receiving and transmitting module 13, control ends of channels of the first 5.8G wireless audio/video receiving and transmitting module 13 are respectively connected with an IO port of the first processor 12, and a signal transmitting channel of the first 5.8G wireless audio/video receiving and transmitting module 13 is controlled by the first processor 12; the second processor 15 is connected with the second 5.8G wireless audio/video transceiver module 14, and the video output end of the second 5.8G wireless audio/video transceiver module 14 is connected with the display 17 through the video collector 16; each channel control terminal of the second 5.8G wireless audio/video transceiver module 14 is connected to an IO port of the second processor 15, and the second processor 15 controls a signal receiving channel of the second 5.8G wireless audio/video transceiver module 14.
Wherein: the Pad2 is internally provided with a third 5.8G wireless audio/video transceiver module 21 and a first 5G signal transceiver module 22, the third 5.8G wireless audio/video transceiver module 21 is in signal connection with the first 5.8G wireless audio/video transceiver module 13 through wireless signals, and the Pad2 controls a signal transmission channel of the first 5G signal transceiver module 22.
Wherein: the remote server 3 is internally provided with a second 5G signal transceiver module 31, the remote server 3 is programmed with an AI artificial intelligence image core analysis algorithm, and the second 5G signal transceiver module 31 is in signal connection with the first 5G signal transceiver module 22 through wireless signals.
Wherein: the disease sample plate picture acquisition module 4 is used for acquiring various disease sample plate pictures.
Wherein: the disease template picture database 5 is used for storing various disease template pictures for calling out and using by the remote server 3.
Wherein: the disease sample plate image classification and judgment module 6 calls all disease sample plate images in the disease sample plate image database 5, classifies all disease sample plate images according to different diseases, and judges symptoms corresponding to all disease sample plate images.
Wherein: the image recognition algorithm implementation and verification module 7 calls the result of the disease sample plate image classification and judgment module 6 for judging each disease sample plate image, recognizes each disease sample plate image and performs algorithm verification.
Wherein: the AI artificial intelligence remote analysis template 8 compares the picture information received by the remote server 3 from the Pad2 end with each disease template picture to obtain a disease template picture matched with the picture information received from the Pad2 end, calls out disease information corresponding to the corresponding disease template picture, uploads the called out disease information to the remote server 3, and the remote server 3 feeds back the judgment result to the Pad2 through the built-in judgment result feedback module 9.
The AI artificial intelligence wireless endoscope camera system is characterized in that an image collector 11 of a wireless endoscope camera collection device 1 collects picture information in the stomach of a patient and outputs the collected information, a first processor 12 controls a signal transmitting channel of a first 5.8G wireless audio/video transceiver module 13, a second 5.8G wireless audio/video transceiver module 14 receives the picture information sent by the first 5.8G wireless audio/video transceiver module 13 and transmits the information to a Pad2, and the Pad2 transmits the received picture information to a remote server 3, wherein the Pad2 is used as an intermediate of the wireless endoscope camera collection device 1 and the remote server 3 for information transmission.
Wherein: the disease template picture acquisition module 4 is used for acquiring pictures of various disease templates and transmitting all the acquired pictures to the disease template picture database 5, the disease template picture database 5 establishes 20000 plus 50000 picture libraries with different lesions, the disease template picture database 5 transmits the acquired pictures with different lesions to the remote server 3, the disease template picture classification and judgment module 6 calls out pictures with different lesions from the remote server 3, the called pictures are manually analyzed by an expert group and classified by various disorders, and the various disorders are correspondingly placed together, so that the symptoms corresponding to the picture information received by the remote server 3 from Pad2 can be quickly and accurately judged, during actual operation, the remote server 3 transmits the picture information received by Pad2 to an image recognition algorithm to realize and verify 7 and AI artificial intelligence remote analysis template 8, the image information of the pictures received from the Pad2 is identified by an image identification algorithm and verified 7, the identified picture information is fed back to the remote server 3, the identified picture information is transmitted to an AI artificial intelligence remote analysis template 8 by the remote server 3, AI image identification learning is realized by the AI artificial intelligence remote analysis template 8, the information obtained by the picture identification learning is fed back to the remote server 3, the information is transmitted to a disease template picture classification and judgment module 6 by the remote server 3, the information transmission is matched with various disease template pictures, the disease corresponding to the picture received by the Pad2 is obtained, and then the disease information is fed back to the wireless endoscope camera shooting and collecting device 1 by a judgment result feedback module 9, the specific process is as follows: the judgment result feedback module 9 transmits the disease information out of the second 5G signal transceiver module 31, the third 5.8G wireless audio/video transceiver module 21 of the Pad2 receives the disease information transmitted by the second 5G signal transceiver module 31, the disease information is transmitted by the third 5.8G wireless audio/video transceiver module 21, the transmitted disease information is received by the first 5.8G wireless audio/video transceiver module 13 of the wireless endoscope camera shooting and collecting device 1, and transmits the information to the second 5.8G wireless audio/video transceiver module 14, the second processor 15 controls the signal transmitting channel of the second 5.8G wireless audio/video transceiver module 14, transmits the picture information to the video collector 16, the video collector 16 feeds the disease information back to the display 17 for display, therefore, a doctor operating the wireless endoscope camera shooting and collecting device 1 can obtain an accurate disease analysis result.
In summary, in the AI artificial intelligence wireless endoscopic camera system provided by the present invention, the image collector 11 of the wireless endoscopic camera collecting device 1 collects image information in the stomach of the patient, and outputs the collected information, the first processor 12 controls the signal transmission channel of the first 5.8G wireless audio/video transceiver module 13, the second 5.8G wireless audio/video transceiver module 14 receives the image information sent by the first 5.8G wireless audio/video transceiver module 13, and transmits the information to the Pad2, and the Pad2 transmits the received image information to the remote server 3, wherein the Pad2 is used as an intermediate between the wireless endoscopic camera collecting device 1 and the remote server 3 to perform information transmission; 20000-50000 picture libraries with different pathological changes are established in the disease template picture database 5, an expert group manually analyzes all pictures in the picture library, classifies various diseases and places the various diseases correspondingly, the pictures received by Pad2 are identified and then subject to AI image identification learning, the pictures obtained by the picture identification learning are transmitted to the remote server 3, the remote server 3 transmits information to the disease template picture classification and judgment module 6, and the information transmission is matched with the various disease template pictures, so that the diseases corresponding to the pictures received by Pad2 can be obtained; then feeding back the obtained real information to the wireless endoscope camera shooting and collecting device 1, and finally displaying the disease information by the display 17, so that a doctor can obtain an accurate disease analysis result; the acquired disease pictures are integrally and accurately analyzed, the acquired disease information can be obtained, the AI automatic judgment result is realized, the primary hospital can also carry out endoscopy, and the problem that the primary hospital cannot carry out endoscopy easily is solved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. An AI artificial intelligence wireless endoscope camera system is characterized by comprising a wireless endoscope camera acquisition device (1), a Pad (2), a remote server (3), a disease sample plate picture acquisition module (4), a disease sample plate picture database (5), a disease sample plate picture classification and judgment module (6), an image recognition algorithm realization and verification module (7), an AI artificial intelligence remote analysis sample plate (8) and a judgment result feedback module (9); the wireless endoscope camera shooting and collecting device (1) is in signal connection with the Pad (2) through wireless signals, and the Pad (2) is in signal connection with the remote server (3) through wireless signals; the output end of the disease sample plate picture acquisition module (4) is connected with the input end of a disease sample plate picture database (5), and the output end of the disease sample plate picture database (5) is connected with the input end of a remote server (3); the disease sample plate image classification and judgment module (6), the image recognition algorithm realization and verification module (7), the AI artificial intelligence remote analysis sample plate (8) and the judgment result feedback module (9) are connected with the remote server (3).
2. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the wireless endoscope camera shooting and collecting device (1) comprises an image collector (11), a first processor (12), a first 5.8G wireless audio/video receiving and sending module (13), a second 5.8G wireless audio/video receiving and sending module (14), a second processor (15), a video collector (16) and a display (17), wherein a video output end of the image collector (11) is connected with a video input end of the first 5.8G wireless audio/video receiving and sending module (13), each channel control end of the first 5.8G wireless audio/video receiving and sending module (13) is respectively connected with an IO port of the first processor (12), and a signal transmitting channel of the first 5.8G wireless audio/video receiving and sending module (13) is controlled by the first processor (12); the second processor (15) is connected with the second 5.8G wireless audio/video transceiving module (14), and the video output end of the second 5.8G wireless audio/video transceiving module (14) is connected with the display (17) through the video collector (16); and each channel control end of the second 5.8G wireless audio/video transceiving module (14) is respectively connected with an IO port of the second processor (15), and a signal receiving channel of the second 5.8G wireless audio/video transceiving module (14) is controlled by the second processor (15).
3. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the Pad (2) is internally provided with a third 5.8G wireless audio/video transceiving module (21) and a first 5G signal transceiving module (22), the third 5.8G wireless audio/video transceiving module (21) is in signal connection with the first 5.8G wireless audio/video transceiving module (13) through wireless signals, and the Pad (2) controls a signal transmission channel of the first 5G signal transceiving module (22).
4. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the remote server (3) is internally provided with a second 5G signal transceiver module (31), the remote server (3) is programmed with an AI artificial intelligence image core analysis algorithm, and the second 5G signal transceiver module (31) is in signal connection with the first 5G signal transceiver module (22) through wireless signals.
5. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the disease sample plate picture acquisition module (4) is used for acquiring various disease sample plate pictures.
6. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the disease sample plate picture database (5) is used for storing various disease sample plate pictures for calling out by the remote server (3).
7. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the disease sample plate picture classifying and judging module (6) calls all disease sample plate pictures in the disease sample plate picture database (5), classifies all disease sample plate pictures according to different diseases, and judges symptoms corresponding to all disease sample plate pictures.
8. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the image recognition algorithm implementation and verification module (7) calls the disease sample plate picture classification and judgment module (6) to judge the result of each disease sample plate picture, recognizes each disease sample plate picture and carries out algorithm verification.
9. The AI artificial intelligence wireless endoscopic camera system of claim 1, wherein: the AI artificial intelligence remote analysis template (8) compares the picture information received by the remote server (3) from the Pad (2) end with each disease template picture to obtain a disease template picture matched with the picture information received from the Pad (2) end, calls out disease information corresponding to the corresponding disease template picture, uploads the called out disease information to the remote server (3), and the remote server (3) feeds back the judgment result to the Pad (2) through a built-in judgment result feedback module (9).
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| CN112674703A (en) * | 2020-12-01 | 2021-04-20 | 泰州国安医疗用品有限公司 | Electronic site inflammation recognition system |
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