Eye disease detection method, AR glasses and readable storage medium

Abstract

The invention discloses an eye disease detection method, AR glasses and a readable storage medium. The method comprises the steps of obtaining a to-be-detected human eye image; performing processing on the human eye image to obtain a diagnosis image, wherein the diagnosis image comprises at least one of an amplitude spectrogram corresponding to the human eye image and a phase spectrogram corresponding to the human eye image; and determining an eye diagnosis result according to the diagnosis image, and outputting the diagnosis result. Due to the fact that the diagnosis device can automaticallydetect whether a user suffers from the eye disease or not through the human eye image, manual diagnosis of whether the user suffers from the eye disease or not is not needed, and the detection efficiency of the eye disease of the user is relatively high.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an eye disease detection method, AR glasses and a readable storage medium. Background technique [0002] Cataracts are eye diseases that cause blindness in humans. These eye diseases threaten and damage the visual function of the optic nerve, not only make people lose their vision, see objects blurred, and even lead to blindness in severe cases. Among them, cataract patients suffer from lens metabolic disorder. The lens becomes cloudy due to protein denaturation, and the light is blocked by the cloudy lens and cannot be projected on the retina, resulting in blurred vision. Preventing further loss of vision through early diagnosis and selection of appropriate medical treatment and surgery is critical to reducing the incidence of blindness. [0003] In the prior art, the method of detecting eye diseases such as cataract is mainly through manual observation of the ...

AI Technical Summary

Problems solved by technology

Relying on doctors to perform manual detection of eye diseases leads to low detection efficiency of eye diseases

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