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Endoscopy monitoring method and device

An endoscopy and endoscopy technology, which is applied in the field of deep learning to avoid misdiagnosis and missed diagnosis and improve the detection rate

Active Publication Date: 2019-01-04
青岛美迪康数字工程有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the above-mentioned deficiencies in the prior art, the purpose of this application is to provide a method and device for endoscopy monitoring to solve or improve the above-mentioned problems

Method used

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Embodiment Construction

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.

[0065] Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0066] It should ...

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Abstract

A method and apparatus for monitoring an endoscopic examination are provided in an embodiment of the present application, wherein each key frame of a medical image acquired by a gastrointestinal endoscope is recognized by depth learning technology, an image recognition result and a first examination score are obtained, then, according to the image recognition result, the key frames with the digestive system viscera anatomy part as the target part are taken as digestive endoscopic images, and each digestive endoscopic image is filled in the image filling frame of the corresponding target part in the pre-configured image filling area, and the number of unfilled image filling frames is counted to generate the second examination score; then, each filled digestive endoscopic image is analyzed and recognized by image analysis, and a third examination score is generated according to the result of image analysis and recognition, and finally, an endoscopic examination monitoring result is generated according to the first examination score, the second examination score and the third examination score. Thus, the intelligent quality control can help the operator to complete the endoscopic operation better and improve the detection rate of lesions.

Description

technical field [0001] The present application relates to the field of deep learning, in particular, to an endoscopy monitoring method and device. Background technique [0002] Digestive endoscopy has become one of the important means for screening, diagnosing, and treating early upper gastrointestinal cancer, and endoscopic lesion biopsy pathology is the "gold standard" for diagnosing early upper gastrointestinal cancer. Endoscopic diagnosis and treatment technology is that medical personnel use endoscopic instruments to observe local lesions, obtain tissue materials, stop bleeding, resect, drain, repair or reconstruct channels through digestive lumens or artificially established channels, under direct vision or with the support of auxiliary equipment. Etc. Diagnosis and treatment measures for the purpose of clear diagnosis, cure of disease, relief of symptoms, improvement of function, etc. [0003] However, at present, medical personnel mainly rely on manual observation r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06N3/04
CPCG06T7/0012G06T2207/20081G06T2207/30028G06T2207/30092G06N3/045
Inventor 李延青冯健左秀丽李真李广超邵学军赖永航
Owner 青岛美迪康数字工程有限公司
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