DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction
-
- Guang Yang
- Imperial College London, National Heart & Lung Institute, London, U.K.
-
- Simiao Yu
- Imperial College London, Data Science Institute, London, U.K.
-
- Hao Dong
- Imperial College London, Data Science Institute, London, U.K.
-
- Greg Slabaugh
- Department of Computer Science, City University of London, London, U.K.
-
- Pier Luigi Dragotti
- EEE Department, Imperial College London, London, U.K.
-
- Xujiong Ye
- School of Computer Science, University of Lincoln, Lincoln, U.K.
-
- Fangde Liu
- Imperial College London, Data Science Institute, London, U.K.
-
- Simon Arridge
- CMIC, University College London, London, U.K.
-
- Jennifer Keegan
- Imperial College London, National Heart & Lung Institute, London, U.K.
-
- Yike Guo
- Imperial College London, Data Science Institute, London, U.K.
-
- David Firmin
- Imperial College London, National Heart & Lung Institute, London, U.K.
書誌事項
- 公開日
- 2018-06
- 権利情報
-
- https://creativecommons.org/licenses/by/3.0/legalcode
- DOI
-
- 10.1109/tmi.2017.2785879
- 公開者
- Institute of Electrical and Electronics Engineers (IEEE)
この論文をさがす
収録刊行物
-
- IEEE Transactions on Medical Imaging
-
IEEE Transactions on Medical Imaging 37 (6), 1310-1321, 2018-06
Institute of Electrical and Electronics Engineers (IEEE)