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1 Ergebnisse
1
Segmentation of Vestibular Schwannoma from Multi-parametric..:
, In:
Proceedings of the 2019 2nd International Conference on Digital Medicine and Image Processing
,
Lee, Wei-Kai
;
Wu, Chih-Chun
;
Huang, Tzu Hsuan
... - p. 8-11 , 2019
Link:
https://dl.acm.org/doi/10.1145/3379299.3379300
RT T1 <cTitle>Proceedings of the 2019 2nd International Conference on Digital Medicine and Image Processing</cTitle>: T1 <Title>Segmentation of Vestibular Schwannoma from Multi-parametric Magnetic Resonance Images using Convolutional Neural Network</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3379300&Exemplar=1&LAN=DE A1 Lee, Wei-Kai A1 Wu, Chih-Chun A1 Huang, Tzu Hsuan A1 Lin, Chun-Yi, A1 Lee, Cheng-Chia A1 Chung, Wen-Yuh A1 Wang, Po-Shan A1 Lu, Chia-Feng A1 Wu, Hsiu-Mei A1 Guo, Wan-Yuo A1 Wu, Yu-Te PB ACM YR 2019 K1 Convolutional neural network K1 Multi-parametric MR images K1 Segmentation K1 Vestibular schwannoma K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by regression K1 Machine learning approaches K1 Neural networks SP 8 OP 11 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3379299.3379300 DO https://dl.acm.org/doi/10.1145/3379299.3379300 SF ELIB - SuUB Bremen
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