QQ客服 官方微博 反馈留言

	3D conditional generative adversarial networks for high-quality PET image estimation at low dose
	Wang, Y.; Yu, B.; Wang, L.; Zu, C.; Lalush, D.S.; Lin, W.; Wu, X.; Zhou, J.; Shen, D.; Zhou, L.
刊名	NeuroImage
	2018
卷号	Vol.174页码:550-562
关键词	3D conditional GANs (3D c-GANs) Generative adversarial networks (GANs) Image estimation Low-dose PET Positron emission tomography (PET)
ISSN号	1053-8119
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/1820802
专题	四川大学
作者单位	1.g School of Computer Science, Chengdu University of Information Technology, China 2.f Department of Radiology and BRIC, University of North Carolina at Chapel Hill, United States 3.Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, NC, United States 4.School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China 5.h Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea 6.a School of Computer Science, Sichuan University, China 7.School of Computing and Information Technology, University of Wollongong, Australia 8.School of Electrical and Information Engineering, University of Sydney, Australia
推荐引用方式 GB/T 7714	Wang, Y.,Yu, B.,Wang, L.,et al. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose[J]. NeuroImage,2018,Vol.174:550-562.
APA	Wang, Y..,Yu, B..,Wang, L..,Zu, C..,Lalush, D.S..,...&Zhou, L..(2018).3D conditional generative adversarial networks for high-quality PET image estimation at low dose.NeuroImage,Vol.174,550-562.
MLA	Wang, Y.,et al."3D conditional generative adversarial networks for high-quality PET image estimation at low dose".NeuroImage Vol.174(2018):550-562.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。