Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.
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ABSTRACT:
SUBMITTER: Yao Z
PROVIDER: S-EPMC9922312 | biostudies-literature | 2023 Feb
REPOSITORIES: biostudies-literature
Publications
Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.
Yao Zhao Z Luo Ting T Dong YiJie Y Jia XiaoHong X Deng YinHui Y Wu GuoQing G Zhu Ying Y Zhang JingWen J Liu Juan J Yang LiChun L Luo XiaoMao X Li ZhiYao Z Xu YanJun Y Hu Bin B Huang YunXia Y Chang Cai C Xu JinFeng J Luo Hui H Dong FaJin F Xia XiaoNa X Wu ChengRong C Hu WenJia W Wu Gang G Li QiaoYing Q Chen Qin Q Deng WanYue W Jiang QiongChao Q Mou YongLin Y Yan HuanNan H Xu XiaoJing X Yan HongJu H Zhou Ping P Shao Yang Y Cui LiGang L He Ping P Qian LinXue L Liu JinPing J Shi LiYing L Zhao YaNan Y Xu YongYuan Y Zhan WeiWei W Wang YuanYuan Y Yu JinHua J Zhou JianQiao J
Nature communications 20230211 1
Elastography ultrasound (EUS) imaging is a vital ultrasound imaging modality. The current use of EUS faces many challenges, such as vulnerability to subjective manipulation, echo signal attenuation, and unknown risks of elastic pressure in certain delicate tissues. The hardware requirement of EUS also hinders the trend of miniaturization of ultrasound equipment. Here we show a cost-efficient solution by designing a deep neural network to synthesize virtual EUS (V-EUS) from conventional B-mode im ...[more]
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