Method for performing eye ground focus recognition through eye ground color pictures

Abstract

The invention discloses a method for performing eye ground focus recognition through eye ground color pictures. All parts in the eye ground color pictures are automatically positioned and measured, the disease pre-screening effect is achieved, pictures with lesion suspicion are automatically screened out, and bleeding, effusion and microaneurysm can be positioned and recognized rapidly and efficiently, so that diabetic retinopathy and other diseases can be subjected to auxiliary diagnosis, and workloads of doctors are relieved; the result does not depend on doctor's experience, the result is more objective, the doctor can be effectively assisted in disease diagnosis, and the purpose of remote consultation is achieved.

Description

technical field [0001] The invention relates to a method for identifying fundus lesions in fundus color photographs. Background technique [0002] In order to quickly identify and draw the boundaries of common fundus lesions in fundus color photos in large quantities, it can quickly and effectively locate and identify hemorrhage, exudation and microvascular tumors, so as to assist in the diagnosis of diabetic retinopathy and other diseases. In clinical practice, due to the limited manpower of ophthalmologists in remote mountainous areas, grass-roots hospitals, and fundus-related film readers, such as mechanically reviewing a large number of fundus color photos one by one, the work content is heavy, single and repetitive, and the efficiency is not high. , wasting a lot of valuable human resources. The existing fundus color photo automatic recognition system also involves the automatic recognition and partition method of the fundus image, but it does not perform precise posit...

AI Technical Summary

Problems solved by technology

In clinical practice, due to the limited manpower of ophthalmologists in remote mountainous areas, grass-roots hospitals, and fundus-related film readers, such as mechanically reviewing a large number of fundus color photos one by one, the work content is heavy, single and repetitive, and the efficiency is not high. , wasting a lot of valuable human resources

The existing fundus color photo automatic recognition system also involves the automatic recognition and partition method of the fundus image, but it does not carry out the precise positioning of the fundus structure position, lesion identification

In addition, most of the existing methods use standard pictures on the Internet for reference comparison and identification. However, the color fundus pictures in clinical practice are not standard pictures, and even include many pictures with problems with focus and brightness. At present, many systems directly use the pictures Recognition, regardless of the quality of the picture, because the standard library on the Internet is a good quality picture, and the number is very small

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