Cup-to-disk ratio determination method, device and equipment, and storage medium

Abstract

The invention relates to the field of artificial intelligence, and discloses a cup-to-disk ratio determination method, device and equipment, and a storage medium. The method comprises the following steps: obtaining and detecting an eye fundus image, and obtaining an optic disk region; inputting the optic disk region into a coding network of an image segmentation model, and extracting image features to obtain a first feature map; inputting the first feature map into a position correction network of the decoding network to obtain a position-corrected second feature map; performing convolution operation on the first feature map through a segmentation network in the decoding network to obtain a third feature map; splicing the second feature map and the third feature map through a connection layer to obtain an image segmentation result; according to an image segmentation result, calculating to obtain an optic cup diameter and an optic disc diameter; and calculating the cup-to-disc ratio of the fundus image according to the optic cup diameter and the optic disc diameter. According to the method, the accuracy of the optic cup and optic disc image obtained through segmentation is improved, multi-screening and screening missing conditions in the disease screening process are reduced, in addition, the invention further relates to a block chain technology, and the eye fundus image can be stored in a block chain.

Description

technical field [0001] The present invention relates to the field of artificial intelligence, in particular to a method, device, equipment and storage medium for determining the cup-to-disk ratio based on an image segmentation model. Background technique [0002] Glaucoma is one of the three major eye diseases that cause blindness in the world. Its irreversibility makes its early diagnosis and treatment play a vital role in improving the quality of life of patients. In the automatic screening of glaucoma, the cup-to-disk ratio is usually used as an evaluation index, and the cup and disc in the fundus image are segmented by a segmentation method, and then the cup-to-disk ratio is calculated. [0003] The prior art is generally divided into two methods to segment the optic disc and cup. 1. The traditional image processing method of feature extraction and clustering based on the color and texture features of the fundus image. 2. Based on deep neural network, such as U-Net, FCN...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to solve the technical problem that the accuracy of the cup-to-disk ratio cannot be guaranteed due to the low segmentation precision of the existing fundus image segmentation

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