Deep ADMM-Net for compressive sensing MRI

Advances in Neural Information Processing Systems

Volumn , Issue , 2016, Pages 10-18

  Yang, Yan ^a   Sun, Jian ^a   Li, Huibin ^a   Xu, Zongben ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPRESSED SENSING; DATA ACQUISITION; DATA FLOW ANALYSIS; DATA FLOW GRAPHS; FLOW GRAPHS; GRAPHIC METHODS; IMAGE PROCESSING; IMAGE RECONSTRUCTION; ITERATIVE METHODS; MAGNETIC LEVITATION VEHICLES; OPTIMIZATION; SIGNAL RECONSTRUCTION;

ALTERNATING DIRECTION METHOD OF MULTIPLIERS; COMPRESSIVE SENSING; COMPUTATIONAL OVERHEADS; COMPUTATIONAL SPEED; EFFECTIVE APPROACHES; OPTIMIZED PARAMETER; RECONSTRUCTION ACCURACY; SHRINKAGE FUNCTIONS;

MAGNETIC RESONANCE IMAGING;

EID: 85018917190     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Michael Lustig, David L Donoho, Juan M Santos, and John M Pauly. Compressed sensing mri. IEEE Journal of Signal Processing, 25(2):72-82, 2008.
2. Michael Lustig, David Donoho, and John M Pauly. Sparse mri: The application of compressed sensing for rapid mr imaging. Magnetic Resonance in Medicine, 58(6):1182-1195, 2007.
3. Kai Tobias Block, Martin Uecker, and Jens Frahm. Undersampled radial mri with multiple coils: Iterative image reconstruction using a total variation constraint. Magnetic Resonance in Medicine, 57(6):1086-1098, 2007.
4. Junfeng Yang, Yin Zhang, and Wotao Yin. A fast alternating direction method for tvl1-l2 signal reconstruction from partial fourier data. IEEE Journal of Selected Topics in Signal Processing, 4(2):288-297, 2010.
5. Chen Chen and Junzhou Huang. Compressive sensing mri with wavelet tree sparsity. In Advances in Neural Information Processing Systems, pages 1115-1123, 2012.
6. Xiaobo Qu, Di Guo, Bende Ning, and et al. Undersampled mri reconstruction with patch-based directional wavelets. Magnetic resonance imaging, 30(7):964-977, 2012.
7. Saiprasad Ravishankar and Yoram Bresler. Mr image reconstruction from highly undersampled k-space data by dictionary learning. IEEE Transactions on Medical Imaging, 30(5):1028-1041, 2011.
8. Zhifang Zhan, Jian-Feng Cai, Di Guo, Yunsong Liu, Zhong Chen, and Xiaobo Qu. Fast multi-class dictionaries learning with geometrical directions in mri reconstruction. IEEE Transactions on Biomedical Engineering, 2016.
9. Sheng Fang, Kui Ying, Li Zhao, and Jianping Cheng. Coherence regularization for sense reconstruction with a nonlocal operator (cornol). Magnetic Resonance in Medicine, 64(5):1413-1425, 2010.
10. Xiaobo Qu, Yingkun Hou, Fan Lam, Di Guo, Jianhui Zhong, and Zhong Chen. Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator. Medical Image Analysis, 18(6):843-856, 2014.
11. Ender M Eksioglu. Decoupled algorithm for mri reconstruction using nonlocal block matching model: Bm3d-mri. Journal of Mathematical Imaging and Vision, pages 1-11, 2016.
12. Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, and Jonathan Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundation and Trends in Machine Learning, 3(1):1-122, 2011.
13. Huahua Wang, Arindam Banerjee, and Zhi-Quan Luo. Parallel direction method of multipliers. In Advances in Neural Information Processing Systems, pages 181-189, 2014.
14. Krishna M Kavi, Bill P Buckles, and U Narayan Bhat. A formal definition of data flow graph models. IEEE Transactions on Computers, 100(11):940-948, 1986.
15. Yann Lécun, Leon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, 1998.
16. Karol Gregor and Yann LeCun. Learning fast approximations of sparse coding. In Proceedings of the 27th International Conference on Machine Learning, pages 399-406, 2010.
17. Uwe Schmidt and Stefan Roth. Shrinkage fields for effective image restoration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2774-2781, 2014.
18. Sun Jian and Xu Zongben. Color image denoising via discriminatively learned iterative shrinkage. IEEE Transactions on Image Processing, 24(11):4148-4159, 2015.
19. John R Hershey, Jonathan Le Roux, and Felix Weninger. Deep unfolding: Model-based inspiration of novel deep architectures. arXiv preprint arXiv:1409.2574, 2014.
20. Francis Bach, Rodolphe Jenatton, Julien Mairal, and Guillaume Obozinski. Optimization with sparsity-inducing penalties. Foundations and Trends in Machine Learning, 4(1):1-106, 2012.
21. David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams. Learning representations by back-propagating errors. Cognitive modeling, 5(3):1, 1988.
22. Matt A Bernstein, Sean B Fain, and Stephen J Riederer. Effect of windowing and zero-filled reconstruction of mri data on spatial resolution and acquisition strategy. Magnetic Resonance Imaging, 14(3):270-280, 2001.