Gastroscope-operation real-time auxiliary system and method based on deep learning

A deep learning and auxiliary system technology, applied in gastroscopy, computer-aided medical procedures, esophagoscopy, etc., can solve the problems of wasting time and money of patients, putting patients' lives in danger, wasting hospital testing resources, etc., to avoid secondary Less pain, improved accuracy and effectiveness

Active Publication Date: 2018-04-27
WUHAN ENDOANGEL MEDICAL TECH CO LTD
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AI Technical Summary

Problems solved by technology

The former requires the patient to go through a painful examination again, which not only wastes the time and money of t

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  • Gastroscope-operation real-time auxiliary system and method based on deep learning
  • Gastroscope-operation real-time auxiliary system and method based on deep learning

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Embodiment Construction

[0032] The present invention will be further described below in conjunction with specific examples and accompanying drawings.

[0033] The present invention provides a real-time assistant system for gastroscope operation based on deep learning, such as figure 1 As shown, it includes:

[0034] At least one client is used to monitor and upload the gastroscope image collected by the current gastroscope device through the network, and receive and display the feedback analysis result. Each client includes a communication module and an image demonstration module; among them, the communication module is used to send requests to the server and obtain analysis results from the server, which is specifically implemented as http communication; the image demonstration module is used to obtain analysis results based on , call the pictures representing each part and the markers of the part features for superimposed display. In this embodiment, the image demonstration module includes a back...

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Abstract

The invention provides a gastroscope-operation real-time auxiliary system based on deep learning. The system comprises at least one client and a service end, wherein the client is used for monitoringand uploading a gastroscope image collected by current gastroscope equipment through a network, and receiving and displaying a feedback analysis result; and the service end uses an REST configurationto instantly determine a position corresponding to the gastroscope image and a position characteristic according to the gastroscope image collected from the client and feeds back an analysis result tothe client. The service end includes a sample database, a convolution neural network model and a web service module. In the invention, image quality identification, position identification and position characteristic identification are performed on the collected image and identification results are displayed on the client; a reliable reference basis is provided for an operator; detection accuracyand validity are increased; the system is simple and is easy to use; and a condition that a patient suffers twice because of an unsuccessful check is avoided.

Description

technical field [0001] The invention belongs to the field of medical detection assistance, and in particular relates to a real-time assistance system and method for gastroscope operation based on deep learning. Background technique [0002] In order to improve the detection rate of early gastric cancer, a large-scale general survey is necessary, and the main method at present is gastroscopy. Therefore, there are often long queues in front of the gastroenterology department of the hospital, and the proficiency and judgment accuracy of the operating doctors are raised Very demanding. For patients, gastroscopy is not easy. In addition to fasting for at least 6 hours before the examination, the pain caused by intubation also daunts many patients. [0003] Usually, a complete gastroscopy report needs to include at least 31 pictures of 10 parts of oropharynx, esophagus, cardia, gastric fundus, gastric body, gastric angle, gastric antrum, pylorus, duodenal bulb and descending part...

Claims

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Application Information

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IPC IPC(8): G16H50/30G06T7/00G06N3/04A61B1/00A61B1/273
CPCA61B1/00009A61B1/2736G06T7/0012G06T2207/30092G06N3/045
Inventor 于红刚万新月胡珊
Owner WUHAN ENDOANGEL MEDICAL TECH CO LTD
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