计算机与数字工程2024，Vol.52Issue(3)：922-924,939,4.DOI:10.3969/j.issn.1672-9722.2024.03.048
基于生成对抗网络的医学图像扩充算法
Medical Image Expansion Algorithm Based on Generative Adversarial Networks
于志勇1
作者信息
- 1. 中国石油大学(华东)计算机科学与技术学院 青岛 266580
- 折叠
摘要
Abstract
Generative adversarial networks have achieved significant results in many fields by virtue of their powerful fitting ability.The paper proposes a generative adversarial network-based image generation method for lung CT images,which combines the feature extraction ability of the self-attentive mechanism and the fitting ability of the generative adversarial network to the data distribution,as well as the specificity processing for the input vector,and the experimental results show that the paper method gen-erates images with high quality as well as usability.关键词
生成对抗网络/CT图像/自编码/数据集扩充Key words
generative adversarial networks/CT images/self-coding/dataset expansion分类
信息技术与安全科学引用本文复制引用
于志勇..基于生成对抗网络的医学图像扩充算法[J].计算机与数字工程,2024,52(3):922-924,939,4.
