现代信息科技2025，Vol.9Issue(4)：47-52,6.DOI:10.19850/j.cnki.2096-4706.2025.04.010
基于优化U-Net神经网络模型在医学图像分割的应用
Application of Medical Image Segmentation Based on Optimized U-Net Neural Network Model
张筱旭 1邵英龙 1严孟慧 1王健庆1
作者信息
- 1. 浙江中医药大学,浙江 杭州 310053
- 折叠
摘要
Abstract
Medical images are important references for clinical diagnosis.How to segment the lesion areas in medical images quickly and accurately has received extensive attention.At present,the use of Deep Learning for image processing has become the mainstream.Medical image segmentation has become a successful example of Deep Learning in the field of image processing due to its unique application scenarios.With its unique U-shaped structure,the U-Net network has achieved good performance in the field of medical image segmentation,but the network still has problems such as insufficient accuracy.This paper studies the automatic segmentation method of medical images based on the optimized U-Net model.The CBAM and SE modules are combined with the U-Net network structure to achieve highly accurate segmentation of human organs.The experimental results on the eyeball dataset show that the optimized U-Net network has higher accuracy(0.905)than the simple U-Net network.This study has important clinical application prospects,which can effectively segment human organs,lesion areas and other targets,and has a positive impact on medical practice.关键词
U-Net神经网络/图像分割/医学图像/注意力机制Key words
U-Net neural network/image segmentation/medical image/Attention Mechanism分类
计算机与自动化引用本文复制引用
张筱旭,邵英龙,严孟慧,王健庆..基于优化U-Net神经网络模型在医学图像分割的应用[J].现代信息科技,2025,9(4):47-52,6.
