A meibomian gland infrared image auxiliary recognition system and method based on deep learning

An infrared image and deep learning technology, applied in the field of image recognition, can solve problems such as lack of quantitative indicators, save time, improve prognosis, and improve the detection rate of dry eye

Pending Publication Date: 2019-04-09
武汉大学人民医院
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, limited by the technical level and human resources, for the specific problem of meibomian gland structural abnormality, at this stage, it can only be evaluated based on the rough estimation of the camera operator, and there is a lack of specific quantitative indicators.

Method used

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  • A meibomian gland infrared image auxiliary recognition system and method based on deep learning
  • A meibomian gland infrared image auxiliary recognition system and method based on deep learning

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Embodiment Construction

[0018] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0019] please see figure 1 , a deep learning-based meibomian gland infrared image aided recognition system provided by the present invention, including a client, a server, and a database;

[0020] The client is used to upload the meibomian gland images collected by the infrared camera equipment to the server, and receive and display the analysis results fed back by the server;

[0021] This embodiment includes at least one client, which is used to monitor and upload the meibomian gland image collected by the current ocular surface analysis device through the...

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Abstract

The invention discloses a meibomian gland infrared image auxiliary recognition system and method based on deep learning. The meibomian gland infrared image auxiliary recognition system comprises a client, a server and a database. The client is used for uploading the meibomian gland image acquired by the infrared camera equipment to the server, and receiving and displaying an analysis result fed back by the server; The server is used for immediately judging a part corresponding to the image and a part feature according to the image acquired from the client and feeding an analysis result back tothe client; And the database is used for storing the images acquired by the infrared camera equipment and the analysis result fed back by the server. The collected meibomian gland images are identified in real time through the convolutional neural network model, the portions and the portion features are identified, real-time prompting is carried out on the image display system, accurate and reliable reference is provided for doctors, the detection accuracy and effectiveness are improved, the method is simple and easy to use, and remarkable social and economic values are achieved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and relates to a meibomian gland infrared image auxiliary recognition system and method, in particular to a deep learning-based auxiliary recognition system and method for the abnormal range of meibomian glands. Background technique [0002] With the improvement of living standards, the types of video terminal equipment are increasing, the frequency of use per capita is increasing, the time is increasing, and many social problems such as environmental pollution and eye drops abuse are affecting the incidence of dry eye in the population. It affects hundreds of millions of people around the world. population. Ocular discomfort caused by dry eye includes disabling pain and visual fluctuations, severely limiting normal daily activities such as driving, reading, and entertainment. Literature has shown that the impact of moderate to severe dry eye on the quality of life of patients is equiv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H30/20G16H50/20G06N3/04
CPCG16H30/20G16H50/20G06N3/045
Inventor 杨燕宁周奕文于薏陈奕云胡珊吴练练
Owner 武汉大学人民医院
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