CN113724230A - Novel endoscope diagnosis system for early digestive tract cancer lesion based on artificial intelligence - Google Patents
Novel endoscope diagnosis system for early digestive tract cancer lesion based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses a novel endoscope diagnosis system for early cancer lesions of the digestive tract based on artificial intelligence, which comprises a medical diagnosis information module, an endoscope switch, an endoscope diagnosis module and an external data comparison module, wherein the digestive tract endoscope module is used for performing endoscope visit on the digestive tract of a patient to obtain the internal image data of the digestive tract; the image preprocessing module is used for preprocessing an image obtained by a patient through endoscopic scouting of the digestive tract, forming annotation and standardization processing and simultaneously forming data information, using a data cloud platform and a database as data support, determining an expected diagnosis result by combining a medical diagnosis information module and an auxiliary diagnosis model, transmitting the diagnosis result to an AI intelligent server after determining the expected diagnosis result, performing secondary comparison by using AI video comparison information and the database as data support to determine the diagnosis result, determining the diagnosis result by using an early cancer prompting module, and assisting medical care personnel in judging the disease state of the patient.
Description
Technical Field
The invention relates to the technical field of auxiliary diagnosis, in particular to a novel endoscope diagnosis system for early digestive tract cancer lesion based on artificial intelligence.
Background
In the application of knowledge in the medical field, the research of ontologies and knowledge maps is endless. In recent years, the research on medical ontology in China has a cardiovascular disease knowledge base established based on ontology theory, on the basis, the domain knowledge ontology is modeled, the knowledge ontology is formally stored, and an auxiliary diagnosis system is developed. The resource is a data carrier comprising semantic information, and the ontology model construction method taking the resource as the core provides a basis for semantic information retrieval. The method has the advantages that a single disease is used as a carrier, the ontology is established to correspond to disease knowledge one by one, a disease ontology knowledge base with an intelligent reasoning function is established, a sharable and reusable diagnosis knowledge base is established for a medical expert system, and the application of artificial intelligence in the field of medical image diagnosis is paid more and more attention with the development of artificial intelligence technology based on deep learning. Through the artificial intelligence technology, the pathological changes which possibly appear can be automatically judged according to the medical images, the automatic screening of the medical images is completed, and the digestive tract diseases are frequently encountered diseases and common diseases and seriously threaten the life health of people. Digestive endoscopy and pigment endoscopy are the first choice for diagnosing digestive tract diseases, but the mucosal surface of the digestive tract often covers a large amount of foams and mucus, so that the visual field of the endoscope is blurred, the observation of an endoscopist is seriously influenced, and even various false images are caused, and the method is one of the main reasons for missed diagnosis and misdiagnosis.
Most of the existing diagnosis systems compare early cancer models, but most of the contents in the models are invariable, and the diagnosis system can only judge by the experience of medical staff when facing a new emergency situation.
Disclosure of Invention
The invention aims at the defects, provides a novel endoscope diagnosis system for early cancer lesions of the digestive tract based on artificial intelligence, updates the content in real time, uploads and downloads the latest early cancer diagnosis structure by using a cloud data platform, records videos and images by using an endoscope, assists medical staff in judging the early cancer by intelligently comparing the contents of the images and the images of the endoscope, performs secondary comparison by using a model and a database after comparison, judges and compares the past early cancer data with the existing data, and improves the judgment capability of the medical staff to solve the problems.
The technical scheme of the invention is realized as follows:
a novel endoscope diagnosis system for early cancer lesions of the digestive tract based on artificial intelligence comprises a medical diagnosis information module, an endoscope switch, an endoscope diagnosis module and an external data comparison module, wherein the endoscope diagnosis information module comprises a digestive tract endoscope module, an image preprocessing module, a big data image comparison module, an auxiliary diagnosis model module, a data cloud platform module and an expected diagnosis result module;
the digestive tract endoscope module is used for performing endoscopic visit on the digestive tract of a patient to obtain image data inside the digestive tract;
the image preprocessing module is used for preprocessing an image obtained by the endoscopic visit of the digestive tract of a patient, forming annotation and standardized processing and simultaneously forming data information;
the big data comparison module is used for comparing image data of the endoscope of the patient with early diagnosis data;
the medical diagnosis information module is used for comparing medical diagnosis information of patients into data;
the auxiliary diagnosis model module is internally provided with an endoscope early cancer chemical staining recognition model and an electronic staining early cancer recognition model;
the data cloud platform module is used for providing data support of past cases;
the expected diagnosis result module is used for storing an expected diagnosis structure in the big data comparison module and the auxiliary diagnosis model, and is interactively connected with the data cloud platform module.
The external data comparison module also comprises an AI intelligent server, and the AI intelligent server is provided with a communication system, a hospital registration system, a case system, a medical settlement system and a database;
the external data comparison module also comprises an AI video comparison information module, the AI video comparison information module is provided with a picture extraction characteristic module, a video characteristic extraction module and a joint proofreading module, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the AI intelligent server, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the joint proofreading module, the joint proofreading module can extract and compare the same characteristics in the picture characteristic extraction module and the video characteristic extraction module, the joint proofreading module is connected with the AI intelligent server, and when the joint proofreading module has an error, the joint proofreading module can retransmit the error information to the AI intelligent server;
the external data comparison module also comprises a precancer prompt module, the precancer prompt module comprises an identification result display module, an identification position display module and a dyeing prompt module, the identification result display module is used for displaying a final data identification result, the identification position display module is used for displaying the specific position of the precancer in the digestive tract, and the dyeing prompt module is used for displaying the probability of a human body focus corresponding to the human body;
the electronic staining image module and the chemical staining image module can respectively display a chemical staining image and an electronic staining image of a focus image of a human body;
the external data comparison module also comprises a future half-year pathological diagram module, the future half-year pathological diagram module can simulate and display the information of the electronic staining images and the chemical staining images of the early cancer at various stages and different times in the future half year after the electronic staining images and the chemical staining images appear in the early cancer prompting module, and the future half-year pathological diagram module is connected with the AI intelligent server;
the external data comparison module further comprises a client side APP, the client side APP is in interactive connection with the AI intelligent server, the client side APP can support data through the AI intelligent server, specific information of a patient is displayed, and meanwhile, after early cancer diagnosis of the patient, a future half-year pathological diagram is transmitted to the client side APP of the user through the AI intelligent server in real time.
Preferably, the medical diagnosis information module further comprises a blood detection information module, an X-ray barium meal detection module and an esophageal ct detection information module.
Preferably, the medical diagnosis information module is interactively connected with the big data image comparison module, and the medical diagnosis information module records specific detection data of patients in the blood detection information module, the X-ray barium meal detection module and the esophagus ct detection information module and transmits the information to the big data comparison module for data comparison.
Preferably, the image preprocessing module is divided into a picture preprocessing module and a video preprocessing module, the picture preprocessing module and the video preprocessing module are connected with the big data image comparison module, the key images in the pictures are intercepted through the image preprocessing, and meanwhile, the key videos in the video preprocessing module are formed into streaming media and are transmitted into the big data image comparison module.
Preferably, the external data comparison module further comprises an AI video display, the AI video display is interactively connected with the AI video comparison information module, both the AI video display and the AI video comparison information module are interactively connected with the early cancer prompting module, and the AI intelligent server is interactively connected with the AI video comparison information module.
Preferably, an endoscope switch is interactively connected with the endoscope diagnosis module and the external data comparison module.
Preferably, an AI intelligent voice broadcast and a red-blue double-color lamp are matched with an AI video display to carry out data display and accurate diagnosis prompt on early cancer in the early cancer prompt module.
Preferably, the AI intelligent server further comprises a database, wherein the database comprises a patient information database, a past patient information database, a comprehensive patient data information database, a picture preprocessing information database, a video preprocessing information database, and an auxiliary diagnosis model database.
Preferably, the patient information database is used for storing patient information data of current endoscopic diagnosis, the past patient information database is used for storing cases and specific information of previous similar early cancer patients, the comprehensive patient data information database is used for storing comprehensive medication information of all patient information, the video preprocessing information database is used for storing preprocessing video data in an endoscope, the picture preprocessing information database is used for storing preprocessing pictures in the endoscope, and the auxiliary diagnosis model database is used for storing diagnosis model data of early cancer.
Preferably, the AI video comparison information is interactively connected with an AI intelligent server, the AI video comparison information adopts Redis storage database intermediate information, and the Redis storage information is accessed by a search engine in an AI video display for display.
Compared with the prior art, the invention has the advantages and positive effects that:
1. when a patient carries out endoscopic diagnosis, information shot by an endoscope is divided into a picture preprocessing module and a video preprocessing module through an image preprocessing module, important parts in pictures and videos are simultaneously transmitted to a big data image comparison module, a data cloud platform and a database are used as data support, an expected diagnosis result is determined by combining a medical diagnosis information module and an auxiliary diagnosis module, the expected diagnosis result is transmitted to an AI intelligent server after being determined, secondary comparison is carried out by taking AI video comparison information and the database as data support to determine the diagnosis result, and the early cancer prompting module is used for determining the diagnosis result to assist medical staff in judging the disease state of the patient.
2. According to the invention, after the patient obtains the electronic staining image and the chemical staining image through the early cancer prompt, the client side APP is connected with the AI intelligent server, and the AI intelligent server transmits the future half-year pathological diagram to the client side in real time, so that the patient can conveniently diagnose and treat according to the self condition.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic diagram of an architecture of a novel endoscopic diagnosis system for early stage digestive tract cancer based on artificial intelligence according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an architecture of a medical diagnosis information module in a novel endoscope diagnosis system for early stage cancer of digestive tract based on artificial intelligence according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an AI intelligent server in a novel endoscope diagnosis system for early stage cancer of digestive tract based on artificial intelligence according to an embodiment of the invention;
FIG. 4 is a schematic diagram of an architecture of AI video contrast information of a novel early digestive tract cancer lesion endoscopic diagnosis system based on artificial intelligence according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an architecture of an early cancer prompt module in a novel endoscope diagnosis system for early cancer lesions in the digestive tract based on artificial intelligence according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described with reference to the accompanying drawings and examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
The invention is further described with reference to the following figures and specific examples.
As shown in fig. 1-5, the novel endoscope diagnosis system for early cancer lesion of digestive tract based on artificial intelligence according to the embodiment of the present invention comprises a medical diagnosis information module, an endoscope switch, an endoscope diagnosis module and an external data comparison module, including a digestive tract endoscope module, an image preprocessing module, a big data image comparison module, an auxiliary diagnosis model module, a data cloud platform module and an expected diagnosis result module;
the digestive tract endoscope module is used for performing endoscopic visit on the digestive tract of a patient to obtain image data inside the digestive tract;
the image preprocessing module is used for preprocessing an image obtained by the endoscopic visit of the digestive tract of a patient to form annotation and standardized processing and simultaneously form data information;
the big data comparison module is used for comparing the image data of the endoscope of the patient with early diagnosis data;
the medical diagnosis information module is used for forming data by medical diagnosis information of patients and comparing the data;
the auxiliary diagnosis model module is internally provided with an endoscope early cancer chemical staining recognition model and an electronic staining early cancer recognition model;
the data cloud platform module is used for providing data support of past cases;
the expected diagnosis result module is used for storing expected diagnosis structures in the big data comparison module and the auxiliary diagnosis model, and the expected diagnosis result module is in interactive connection with the data cloud platform module.
The external data comparison module also comprises an AI intelligent server, and the AI intelligent server is provided with a communication system, a hospital registration system, a case system, a medical settlement system and a database;
the external data comparison module also comprises an AI video comparison information module, the AI video comparison information module is internally provided with a picture extraction characteristic module, a video characteristic extraction module and a joint proofreading module, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the AI intelligent server, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the joint proofreading module, the joint proofreading module can extract and compare the same characteristics in the picture characteristic extraction module and the video characteristic extraction module, the joint proofreading module is connected with the AI intelligent server, and when the joint proofreading module has an error, the joint proofreading module can retransmit the error information to the AI intelligent server;
the external data comparison module also comprises a precancer prompt module, the precancer prompt module comprises an identification result display module, an identification position display module and a dyeing prompt module, the identification result display module is used for displaying a final data identification result, the identification position display module is used for displaying the specific position of the precancer in the digestive tract, and the dyeing prompt module is used for displaying the probability of a human body focus corresponding to the human body;
the electronic staining image module and the chemical staining image module can respectively display a chemical staining image and an electronic staining image of a focus image of a human body;
the external data comparison module also comprises a future half-year pathological diagram module, the future half-year pathological diagram module can simulate and display the information of the electronic staining images and the chemical staining images of the early cancer at various stages and different times in the future half year after the electronic staining images and the chemical staining images appear in the early cancer prompt module, and the future half-year pathological diagram module is connected with the AI intelligent server;
wherein, still including the customer end APP among the external data contrast module, for interactive connection between customer end APP and the AI intelligent server, can support for the data through the AI intelligent server among the customer end APP, show patient's specific information, transmit the customer end APP of user in real time through the AI intelligent server with half a year pathological diagram in the future after the early cancer of patient is diagnosed simultaneously.
By adopting the technical scheme, in the technical scheme, whether a patient needs to carry out the inspection of the digestive tract endoscope is judged through the medical diagnosis information, in the inspection process of the digestive tract endoscope, the digestive tract endoscope is divided into images and videos, the images shot by the endoscope are divided into the image preprocessing module and the video preprocessing module through the image preprocessing module, after the processing of the image preprocessing module and the video preprocessing module is completed, the data are led into the big data image comparison module in the big data image comparison module to be interactively connected with the medical diagnosis information module, the data cloud platform module and the auxiliary diagnosis module, so that the data sharing is realized, the data cloud platform module searches for similar data in the big data by taking the data in the medical diagnosis information module as a keyword, and simultaneously carries out the comparison with the auxiliary diagnosis module and the similar data, thereby yielding the desired diagnostic result.
Specifically, the medical diagnosis information module further comprises a blood detection information module, an X-ray barium meal detection module and an esophageal ct detection information module.
By adopting the technical scheme, whether the patient is detected by the blood detection, the primary judgment of medical staff, the X-ray barium meal detection and the esophageal ct detection are recorded in the medical diagnosis information module, after the patient is detected, the information can be used as a condition for judging whether the patient needs to carry out endoscope detection, the information is transmitted into the big data image comparison module and is compared through the matching auxiliary diagnosis model module, and meanwhile, the data is transmitted to the data cloud platform to be used as a data search keyword.
Specifically, the medical diagnosis information module is interactively connected with the big data image comparison module, and the medical diagnosis information module can record specific detection data of patients in the blood detection information module, the X-ray barium meal detection module and the esophagus ct detection information module and transmit the information to the big data comparison module for data comparison.
Specifically, the image preprocessing module is divided into a picture preprocessing module and a video preprocessing module, the picture preprocessing module and the video preprocessing module are connected with the big data image comparison module, key images in the pictures are intercepted through image preprocessing, and meanwhile, the key videos in the video preprocessing module are formed into streaming media and are transmitted into the big data image comparison module.
By adopting the technical scheme, the information shot by the alimentary canal endoscope can be transmitted into the picture preprocessing module and the video preprocessing module in the image preprocessing module, the picture preprocessing module can carry out the sharpening processing on the picture, and simultaneously, the video and the picture are subjected to the data informatization, so that the subsequent big data image comparison is conveniently carried out
Specifically, the external data comparison module further comprises an AI video display, an AI video display and an AI video comparison information module which are in interactive connection, the AI video display and the AI video comparison information module are in interactive connection with the early cancer prompting module, and the AI intelligent server is in interactive connection with the AI video comparison information module.
By adopting the technical scheme, video data are provided in the AI video display through the AI video comparison information module, and diagnosis confirmation prompt is carried out through the early cancer prompt module after patient data information is compared in the AI video display and the AI video comparison information module.
Specifically, the endoscope switch is interactively connected with the endoscope diagnosis module and the external data comparison module.
By adopting the technical scheme, the data of the endoscope diagnosis module is connected and interacted with the external data comparison module through the endoscope switch, so that data sharing is realized.
Specifically, the early cancer prompting module uses AI intelligent voice broadcast and a red and blue double-color lamp to cooperate with an AI video display to display data and prompt for accurate diagnosis of early cancer.
Specifically, the AI intelligent server further comprises a database, wherein the database comprises a patient information database, a past patient information database, a comprehensive patient data information database, a picture preprocessing information database, a video preprocessing information database and an auxiliary diagnosis model database.
Specifically, the patient information database is used for storing patient information data of current endoscope diagnosis, the past patient information database is used for storing cases and specific information of previous similar early cancer patients, the comprehensive patient data information database is used for storing comprehensive medication information of all patient information, the video preprocessing information database is used for storing preprocessing video data in an endoscope, the picture preprocessing information database is used for storing preprocessing pictures in the endoscope, and the auxiliary diagnosis model database is used for storing diagnosis model data of early cancer.
Specifically, AI video comparison information is interactively connected with an AI intelligent server, the AI video comparison information adopts Redis storage database intermediate information, and the Redis storage information is accessed by a search engine in an AI video display for display.
By adopting the technical scheme, Redis, namely remote dictionary service, a Key-Value database for source opening, and API of multiple languages are provided, Redis supports master-slave synchronization, patient record data can be synchronized from an AI intelligent server to any number of slave servers, so that the query of medical staff on past data is facilitated, the slave servers in a data cloud platform can be associated with master servers of other slave servers so as to provide more case data, and a search engine is a retrieval technology for retrieving formulated information from the Internet and feeding the information back to a user by using a specific strategy according to user requirements and a certain algorithm.
For the convenience of understanding the technical solutions of the present invention, the following detailed description will be made on the working principle or the operation mode of the present invention in the practical process.
In practical application, medical staff judges whether a patient needs to carry out gastrointestinal endoscopy examination or not through medical diagnosis information, and in the process of carrying out the gastrointestinal endoscopy examination, divides the gastrointestinal endoscope into images and videos, divides pictures shot by the endoscope into an image preprocessing module and a video preprocessing module through the image preprocessing module, guides data into a big data comparison module and a medical diagnosis information module in a big data image comparison module after the image preprocessing module and the video preprocessing module are processed, and carries out interactive connection between the data cloud platform module and an auxiliary diagnosis module to realize data sharing, the data cloud platform module carries out similar data search in big data by taking the data in the medical diagnosis information module as a keyword, and simultaneously carries out the same comparison with the auxiliary diagnosis module and the similar data to obtain an expected diagnosis result, after an expected diagnosis result is obtained, the data cloud platform module transmits expected diagnosis result data, image expected processing module data and video expected processing module data to the AI intelligent server together, the AI intelligent server transmits the expected diagnosis result data, the image expected processing module data and the video expected processing module data to the database, transmits the expected diagnosis result data, the image expected processing module data and the video expected processing module data to the AI video comparison information module, performs secondary comparison by using data and images in the AI video display, performs diagnosis confirmation prompt through the early cancer prompt module, and transmits a future half-year pathological diagram to a client APP of a user through the AI intelligent server after the early cancer of the patient is confirmed, so that the patient is prompted to perform diagnosis and treatment in time.
The present invention can be easily implemented by those skilled in the art from the above detailed description. It should be understood, however, that the intention is not to limit the invention to the particular embodiments described. On the basis of the disclosed embodiments, a person skilled in the art can combine different technical features at will, thereby implementing different technical solutions.
Claims (10)
1. The novel endoscope diagnosis system for early digestive tract cancer lesion based on artificial intelligence comprises a medical diagnosis information module, an endoscope switch, an endoscope diagnosis module and an external data comparison module, and is characterized by comprising a digestive tract endoscope module, an image preprocessing module, a big data image comparison module, an auxiliary diagnosis model module, a data cloud platform module and an expected diagnosis result module.
2. The novel endoscopic diagnosis system for early digestive tract cancer based on artificial intelligence as claimed in claim 1,
the digestive tract endoscope module is used for performing endoscopic visit on the digestive tract of a patient to obtain image data inside the digestive tract;
the image preprocessing module is used for preprocessing an image obtained by the endoscopic visit of the digestive tract of a patient, forming annotation and standardized processing and simultaneously forming data information;
the big data comparison module is used for comparing image data of the endoscope of the patient with early diagnosis data;
the medical diagnosis information module is used for comparing medical diagnosis information of patients into data;
the auxiliary diagnosis model module is internally provided with an endoscope early cancer chemical staining recognition model and an electronic staining early cancer recognition model;
the data cloud platform module is used for providing data support of past cases;
the expected diagnosis result module is used for storing an expected diagnosis structure in the big data comparison module and the auxiliary diagnosis model, and is interactively connected with the data cloud platform module;
the external data comparison module also comprises an AI intelligent server, and the AI intelligent server is provided with a communication system, a hospital registration system, a case system, a medical settlement system and a database;
the external data comparison module also comprises an AI video comparison information module, the AI video comparison information module is provided with a picture extraction characteristic module, a video characteristic extraction module and a joint proofreading module, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the AI intelligent server, the picture characteristic extraction module and the video characteristic extraction module are interactively connected with the joint proofreading module, the joint proofreading module can extract and compare the same characteristics in the picture characteristic extraction module and the video characteristic extraction module, the joint proofreading module is connected with the AI intelligent server, and when the joint proofreading module has an error, the joint proofreading module can retransmit the error information to the AI intelligent server;
the external data comparison module also comprises a precancer prompt module, the precancer prompt module comprises an identification result display module, an identification position display module and a dyeing prompt module, the identification result display module is used for displaying a final data identification result, the identification position display module is used for displaying the specific position of the precancer in the digestive tract, and the dyeing prompt module is used for displaying the probability of a human body focus corresponding to the human body;
the electronic staining image module and the chemical staining image module can respectively display a chemical staining image and an electronic staining image of a focus image of a human body;
the external data comparison module also comprises a future half-year pathological diagram module, the future half-year pathological diagram module can simulate and display the information of the electronic staining images and the chemical staining images of the early cancer at various stages and different times in the future half year after the electronic staining images and the chemical staining images appear in the early cancer prompting module, and the future half-year pathological diagram module is connected with the AI intelligent server;
the external data comparison module further comprises a client side APP, the client side APP is in interactive connection with the AI intelligent server, the client side APP supports data through the AI intelligent server, specific information of a patient is displayed, and meanwhile, after early cancer diagnosis of the patient is confirmed, a future half-year pathological diagram is transmitted to the client side APP of the user through the AI intelligent server in real time;
the medical diagnosis information module also comprises a blood detection information module, an X-ray barium meal detection module and an esophagus ct detection information module.
3. The artificial intelligence-based novel endoscopic diagnosis system for early digestive tract cancer lesions according to claim 2, wherein the medical diagnosis information module is interactively connected with the big data image comparison module, and records the specific detection data of the patient in the blood detection information module, the X-ray barium meal detection module and the esophageal ct detection information module and outputs the information to the big data comparison module for data comparison.
4. The artificial intelligence-based novel endoscope diagnosis system for early digestive tract cancer lesions according to claim 2, wherein the image preprocessing module is divided into a picture preprocessing module and a video preprocessing module, the picture preprocessing module and the video preprocessing module are connected with the big data image contrast module, the image preprocessing module intercepts key images in the picture, and simultaneously forms streaming media with the key videos in the video preprocessing module and outputs the streaming media into the big data image contrast module.
5. The novel endoscope diagnosis system for early digestive tract cancer based on artificial intelligence, according to claim 2, wherein the external data comparison module further comprises an AI video display, the AI video display is interactively connected with the AI video comparison information module, both the AI video display and the AI video comparison information module are interactively connected with the early cancer prompting module, and the AI intelligent server is interactively connected with the AI video comparison information module.
6. The novel endoscopic diagnosis system for early digestive tract cancer based on artificial intelligence as claimed in claim 2, wherein the endoscopic switch is connected to the endoscopic diagnosis module and the external data contrast module.
7. The novel endoscope diagnosis system for early digestive tract cancer lesion based on artificial intelligence as claimed in claim 2, wherein the early cancer prompting module uses AI intelligent voice broadcast and red and blue double color lamps to cooperate with an AI video display to display data and prompt for accurate diagnosis of early cancer.
8. The artificial intelligence based endoscope diagnosis system for early stage of digestive tract cancer according to claim 2, wherein said database comprises patient information database, past patient information database, comprehensive patient information database, image preprocessing information database, video preprocessing information database, and auxiliary diagnosis model database.
9. The system according to claim 8, wherein the patient information database is used for storing patient information data of current endoscopic diagnosis, the past patient information database is used for storing cases and specific information of previous similar early cancer patients, the comprehensive patient information database is used for storing comprehensive medication information of all patient information, the video preprocessing information database is used for storing preprocessed video data in the endoscope, the picture preprocessing information database is used for storing preprocessed pictures in the endoscope, and the auxiliary diagnosis model database is used for storing diagnosis model data of early cancer.
10. The artificial intelligence based endoscope diagnosis system for early stage of digestive tract cancer according to claim 2, wherein said AI video contrast information is interactively connected to an AI intelligence server, said AI video contrast information uses Redis storage database intermediate information, and said display is performed by using a search engine to access the Redis storage information in an AI video display.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2023143014A1 (en) * | 2022-01-29 | 2023-08-03 | 王国华 | Endoscope-assisted inspection method and device based on artificial intelligence |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023143014A1 (en) * | 2022-01-29 | 2023-08-03 | 王国华 | Endoscope-assisted inspection method and device based on artificial intelligence |
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