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	A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images
	Guo Le-Hang[1]; Wang Dan[2]; Qian Yi-Yi[3]; Zheng Xiao[4]; Zhao Chong-Ke[5]; Li Xiao-Long[6]; Bo Xiao-Wan[7]; Yue Wen-Wen[8]; Zhang Qi[9]; Shi Jun[10]
刊名	Clinical hemorheology and microcirculation
	2018
卷号	69页码:343-354
关键词	Contrast-enhanced ultrasound artificial intelligence deep canonical correlation analysis liver tumor multiple kernel learning
ISSN号	1875-8622
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/2180960
专题	上海大学
作者单位	1.[1]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 2.[2]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 3.[3]Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China. 4.[4]Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China. 5.[5]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 6.[6]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 7.[7]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 8.[8]Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University School of Medicine, Shanghai, China. 9.[9]Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China. 10.[10]Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China.
推荐引用方式 GB/T 7714	Guo Le-Hang[1],Wang Dan[2],Qian Yi-Yi[3],et al. A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images[J]. Clinical hemorheology and microcirculation,2018,69:343-354.
APA	Guo Le-Hang[1].,Wang Dan[2].,Qian Yi-Yi[3].,Zheng Xiao[4].,Zhao Chong-Ke[5].,...&Xu Hui-Xiong[11].(2018).A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images.Clinical hemorheology and microcirculation,69,343-354.
MLA	Guo Le-Hang[1],et al."A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images".Clinical hemorheology and microcirculation 69(2018):343-354.

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