Glaucoma auxiliary screening system based on decoupling training and reasoning

Abstract

The invention provides a glaucoma auxiliary screening system based on decoupling training and reasoning. The glaucoma auxiliary screening system comprises a control module, a fundus image acquisition module, a fundus image preprocessing module, a neural network reasoning module and an output module. The fundus image acquisition module is used for acquiring a fundus image of a user; the eye fundus image preprocessing module is used for preprocessing the collected eye fundus image; the neural network reasoning module is used for classifying and screening the eye fundus images; the output module is used for judging whether the user has a glaucoma symptom or not according to the classification screening result and giving a treatment suggestion; and the control module is used for controlling the eye fundus image acquisition, preprocessing, classification screening and result output work of all the modules. The mobility of the glaucoma screening system is improved, the requirement for large-scale glaucoma screening is met, glaucoma screening can be achieved anytime and anywhere at low cost and low threshold, and the system has important significance on early prevention of glaucoma.

Description

technical field [0001] The invention relates to the fields of artificial intelligence and medical imaging, in particular to a glaucoma auxiliary screening system based on decoupling training and reasoning. Background technique [0002] Glaucoma is an optic neuropathy characterized by progressive degeneration of retinal ganglion cells, visual field loss and decreased visual acuity. It is one of the main causes of irreversible blindness in my country. According to statistics, the number of glaucoma patients in China is as high as 15.82 million. Some scholars predict that in 2040, the number of glaucoma patients in the world will reach 111.82 million. [0003] If glaucoma is detected in an early stage and reasonable treatment measures are taken, most patients can stop the progression of the disease and preserve a certain degree of vision. However, the disease often has no obvious symptoms in the early stage, and many patients cannot be diagnosed until the advanced stage, resul...

AI Technical Summary

Problems solved by technology

Fundus images have the advantages of low cost, simple operation, and strong mobility. However, fundus images are collected clinically through fundus cameras. Traditional fundus cameras are bulky and not suitable for large-scale screening.

Moreover, fundus images require professional doctors to diagnose, and the changes in the optic disc and retinal nerve fiber layer in the early fundus images of glaucoma patients are difficult to distinguish with the naked eye. If the quality of the collected fundus images is not high enough, it is easy to cause misdiagnosis

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