Comprehensive Review on Application of Attention Mechanism in Retinal Vessel Segmentation

被引：0
|
作者：
Pei, Junpeng [1 ]
Wang, Yousong [1 ]
Li, Zenghui [1 ]
Wang, Wei [2 ]
机构：
[1] School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai,200093, China
[2] PLA Naval Medical Center, Naval Medical University, Shanghai,200433, China
来源：
Computer Engineering and Applications | 2024年 / 60卷 / 14期
关键词：
Automatic segmentation of retinal vessels plays an important role in computer-aided diagnosis of ophthalmology and cardiovascular diseases. Attention mechanism can improve the efficiency and accuracy of image feature extraction in classical neural network models; so attention mechanism is widely used in retinal vessel segmentation models. This paper firstly reviews the commonly used datasets and evaluation metrics for retinal vessel segmentation; subsequently; attention mechanisms are categorized into two types: selective attention mechanisms and self-attention mechanisms; based on their working principles. Meanwhile; according to the data domain of computer vision tasks; attention methods are divided into three categories: channel attention; spatial attention; and mixed attention. Combined with the task of retinal vessel segmentation; the paper highlights the specific applications of representative attention models of these three types and conducts performance comparisons and evaluations of relevant models. Finally; the problems of attention mechanism and the development trend in the future are discussed. © 2024 Journal of Computer Engineering and Applications Beijing Co; Ltd; Science Press. All rights reserved;
D O I：
10.3778/j.issn.1002-8331.2311-0049
中图分类号：
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页码：50 / 65
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