2D and 3D bladder segmentation using U-Net-based deep-learning

被引：0
|
作者：
Ma, Xiangyuan [3 ]
Hadjiiski, Lubomir [1 ]
Wei, Jun [1 ]
Chan, Heang-Ping [1 ]
Cha, Kenny [2 ]
Cohan, Richard H. [1 ]
Caoili, Elaine M. [1 ]
Samala, Ravi [1 ]
Zhou, Chuan [1 ]
Lu, Yao [3 ]
机构：
[1] Department of Radiology, University of Michigan, Ann Arbor,MI, United States
[2] Center for Devices and Radiological Health, U.S. FDA, Silver Spring,MD, United States
[3] School of Data and Computer Science, Sun Yat-Sen University, Guangzhou,510275, China
来源：
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | 2019年 / 10950卷
关键词：
461.1 Biomedical Engineering - 461.4 Ergonomics and Human Factors Engineering - 723.5 Computer Applications - 746 Imaging Techniques - 901.2 Education - 921.6 Numerical Methods - 922.2 Mathematical Statistics;
D O I：
109500Y
中图分类号：
学科分类号：
摘要：
Computer aided diagnosis
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