An attention mechanism U-shaped densely connected retinal blood vessel segmentation method

Abstract

The invention relates to an attention mechanism U-shaped densely connected retinal (a novel retinal blood vessel segmentation method fusing DenseNet and Attention U-net network) blood vessel segmentation method, comprising the steps of retinal blood vessel image preprocessing and constructing a retinal blood vessel segmentation model. The method of the invention can effectively solve the problemsthat adjacent blood vessels are easy to connect, the micro blood vessels are too wide, the small blood vessels are easy to break, the blood vessel intersection is insufficient in segmentation, the image noise is too sensitive, the gray value of the object and the background is crossed, the optic disc and the lesion focus are missegmented, and the like. The method of the invention integrates a plurality of network models under the condition of low complexity, the excellent segmentation results are obtained on DRIVE dataset, the accuracy and sensitivity are 96.95% and 85.94%, respectively, whichare about 0.59% and 7.92% higher than those published in the latest literature.

Description

technical field [0001] The invention relates to a U-shaped densely connected retina (a new type of retina fused with DenseNet and Attention U-net network) blood vessel segmentation method with an attention mechanism, which better solves the problems of insufficient microvessel segmentation, too wide microvessel segmentation, and crossed blood vessels in the existing algorithm. Segmentation breaks at the lesion, blood vessel breakage at the lesion, lesion and optic disc mis-segmented into blood vessels, etc. Background technique [0002] The human retina is a light-sensitive tissue covering the inner surface of the eye, and the retinal blood vessels are the only part of the systemic vascular system that can be directly observed without trauma. Information such as the number, branch, angle, and width of retinal blood vessels can be used as information related to retinal blood vessels. The basis for the diagnosis of the disease. The convolutional neural network method has powe...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to propose a U-shaped densely connected retinal vessel segmentation method with an attention mechanism in view of the complexity and variety of retinal vessel features and the shortcomings of existing segmentation algorithms.

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