Blood vessel and fundus image segmentation method, device and equipment and readable storage medium

Abstract

The embodiment of the invention discloses a blood vessel and eye fundus image segmentation method, device and equipment and a readable storage medium, and relates to the computer vision technology ofartificial intelligence. Specifically, the method comprises steps of acquiring a blood vessel image to be segmented, such as a fundus image; performing feature extraction on the blood vessel image such as the fundus image to obtain high-level feature information; performing dictionary learning on the high-level feature information based on a preset dictionary to obtain dictionary representation corresponding to the high-level feature information; selecting a plurality of channels of the high-level feature information according to the dictionary representation to obtain target feature information; fusing the target feature information with the high-level feature information to obtain channel attention feature information; and segmenting blood vessels in the blood vessel image, such as the fundus image, according to the channel attention feature information to obtain a blood vessel segmentation result. According to the scheme, global information loss of the characteristic blood vessel image such as the fundus image can be avoided, and the segmentation accuracy of the blood vessel image such as the fundus image is greatly improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a method, device, equipment and readable storage medium for segmenting blood vessels and fundus images. Background technique [0002] The structural state of fundus blood vessels has a very important connection with various systems of the whole body, which can help people to prevent and treat certain diseases early. For example, arteriosclerosis, hypertension, diabetes, cardiovascular disease, and age-related macular degeneration will all affect the shape of blood vessels in the fundus, changing the width and curvature of arteries and veins. However, in actual operation, due to the influence of illumination differences and individual variations, it is difficult for doctors to obtain blood vessel information manually, and the diagnosis results are more subjective and have errors. Therefore, it is of great clinical significance to realize the automatic segmentation...

AI Technical Summary

Problems solved by technology

[0004] During the research and practice of the prior art, the inventors of the present invention found that, because the features extracted by the deep learning network tend to lose the global information of the image, the segmentation accuracy is not high

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