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Artificial intelligence-based endoscopy assistance system

An artificial intelligence and auxiliary system technology, applied in the field of neural network, can solve the problem of lack of unified operating standards, achieve comprehensive and safe inspection, improve inspection quality, and avoid false or missed inspections.

Active Publication Date: 2022-05-31
萱闱(北京)生物科技有限公司 +1
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the course of practice, it is found that during the use of endoscopes, the inspection quality is completely controlled by the operator, and there is no uniform operating standard, and the operator needs to operate the endoscope for a long time, and also needs to check the endoscope. The collected images are carefully observed

Method used

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Embodiment Construction

[0047] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that given this

[0048] Those skilled in the art know that the embodiments of the present invention can be implemented as a system, device, device, method

[0049] According to an embodiment of the present invention, an artificial intelligence-based endoscopy assistance system, medium and

[0050] In addition, any number of elements in the drawings is for illustration and not limitation, and any designation is for distinction only,

[0051] The principles and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0054] The inspection data acquisition module 110 is configured to obtain inspection data through the endoscopic device, wherein the inspection data is at least

[0055] The inspection quality monitoring module 120 is configured to ...

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Abstract

The invention provides an artificial intelligence-based endoscopic examination auxiliary system. The system includes: an inspection data collection module configured to acquire inspection data through an endoscope device, the inspection data at least including inspection time data and inspection image data; an inspection quality monitoring module configured to perform data processing on the inspection data , the data processing at least includes data statistics and data classification, and then respectively input specific types of inspection data into corresponding quality monitoring models based on neural networks to determine inspection quality; the inspection auxiliary module is configured to For the part or object corresponding to the image data, input the inspection image data into the corresponding recognition model based on the neural network to obtain the identification for auxiliary operation, and output the identification and the corresponding inspection image data according to the preset method .

Description

Artificial intelligence-based endoscopy assistance system technical field Embodiments of the present invention relate to the technical field of neural networks, more specifically, embodiments of the present invention relate to a An artificial intelligence-based endoscopy assistance system. Background technique [0002] This section is intended to provide a background or context for the embodiments of the invention that are recited in the claims. here The description is not admitted to be prior art by inclusion in this section. [0003] At present, in order to accurately diagnose diseases in the human body (such as the digestive tract, etc.), the The images in the gastrointestinal tract help doctors to identify the lesions in the digestive tract, and based on the identified lesions, the diseases of the digestive tract can be advanced. Diagnose. However, in practice, it is found that during the use of endoscopy, the inspection quality is completely controlled by the op...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06T7/0012G06N3/04G06N3/08G06T2207/10068G06T2207/20081
Inventor 乔元风曾凡
Owner 萱闱(北京)生物科技有限公司
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