福建电脑2024，Vol.40Issue(1)：48-51,4.DOI:10.16707/j.cnki.fjpc.2024.01.009
视网膜图像的血管分割方法
Blood Vessel Segmentation Method for Retinal Images
摘要
Abstract
Color retinal image segmentation is a computer-assisted medical method.This paper proposes an improved Unet image segmentation method to address the issue of low segmentation accuracy in retinal vascular images.Replace the output layer of the network from the full convolutional layer to the PSP pyramid structure layer,replace the activation function with ELU,and add a dropout mechanism.Before the image is transmitted to the network,data enhancement processing is randomly performed on the image with a certain probability.The test results show that compared with Unet,the improved algorithm has a 1.56%improvement in mAcc performance indicators and a 2.33%improvement in mdice performance indicators.关键词
视网膜血管/图像分割/深度学习神经网络/Unet网络Key words
Retinal Blood Vessels/Image Segmentation/Deep Learning Neural Networks/Unet Network分类
信息技术与安全科学引用本文复制引用
吴连雨,张秀娟..视网膜图像的血管分割方法[J].福建电脑,2024,40(1):48-51,4.基金项目
本文得到2023年国家级大学生创新创业项目(No.202310408016)资助. （No.202310408016）
