학술논문
Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis
Document Type
article
Author
Zhao Yao; Ting Luo; YiJie Dong; XiaoHong Jia; YinHui Deng; GuoQing Wu; Ying Zhu; JingWen Zhang; Juan Liu; LiChun Yang; XiaoMao Luo; ZhiYao Li; YanJun Xu; Bin Hu; YunXia Huang; Cai Chang; JinFeng Xu; Hui Luo; FaJin Dong; XiaoNa Xia; ChengRong Wu; WenJia Hu; Gang Wu; QiaoYing Li; Qin Chen; WanYue Deng; QiongChao Jiang; YongLin Mou; HuanNan Yan; XiaoJing Xu; HongJu Yan; Ping Zhou; Yang Shao; LiGang Cui; Ping He; LinXue Qian; JinPing Liu; LiYing Shi; YaNan Zhao; YongYuan Xu; WeiWei Zhan; YuanYuan Wang; JinHua Yu; JianQiao Zhou
Source
Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)
Subject
Language
English
ISSN
2041-1723
Abstract
The current use of elastography ultrasound faces challenges, including vulnerability to subjective manipulation, echo signal attenuation, unknown risks of elastic pressure and high imaging hardware cost. Here, the author shows a virtual elastography to empower low-end ultrasound devices with state-of-art elastography function.