Fetching the paper…
Reading the bibliography…
This paper presents a deep learning method for faster magnetic resonance imaging (MRI) by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for why the proposed approach works well.
[] H. Nyquist 1928 Certain topics in telegraph transmission theory Trans. AIEE
1928
Earlier work this paper cites.
[] P.C. Lauterbur 1973 Image Formation by Induced Local Interactions: Examples of Employing Nuclear Magnetic Resonance Nature
1973
Earlier work this paper cites.
[] D.K. Sodickson and W.J. Manning 1997 Simultaneous acquisition of spatial harmonics (SMASH): fast imaging with radiofrequency coil arrays Magn. Reson. Med
1997
Earlier work this paper cites.
[] E. Haacke, R. Brown, M. Thompson and R. Venkatesan 1999 Magnetic resonance imaging Physical Principles and Sequence Design (New York: Wiley)
1999
Earlier work this paper cites.
[] K.P. Pruessmann, M. Weiger, M.B. Scheidegger and P. Boesiger 1999 SENSE: sensitivity encoding for fast MRI Magn. Reson. Med
1999
Earlier work this paper cites.
[] D.L. Donoho 2004 For most large underdetermined systems of linear equations the minimal 1-norm solution is also the sparsest solution Communications on pure and applied mathematics
2004
Earlier work this paper cites.
[] Z. Wang, A. C. Bovik, H.R. Sheikh, E.P. Simoncelli 2004 Image Quality Assessment: From Error Visibility to Structural Similarity IEEE Trans. on Image Processing
2004
Earlier work this paper cites.
[] E.J. Candès, J. Romberg and T. Tao 2006 Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information IEEE Trans. Inf. Theory
2006
Earlier work this paper cites.
[] D.L. Donoho 2006 Compressed sensing IEEE Trans. Inf. Theory
2006
Cited alongside, same era.
[] D.J. Larkman and R.G. Nunes 2007 Parallel magnetic resonance imaging Phys. Med. Biol
2007
Cited alongside, same era.
[] M. Lustig, D.L. Donoho and J.M. Pauly 2007 Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging Magnetic Resonance in Medicine
2007
Cited alongside, same era.
[] X. Glorot, A. Bordes and Y. Bengio 2011 Deep Sparse Rectifier Neural Networks Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics PMLR 15
2011
Cited alongside, same era.
[] C.P. Loizou, V. Murray, M.S. Pattichis, I. Seimenis, M. Pantziaris, C.S. Pattichis 2011 Multi-scale amplitude modulation-frequency modulation (AM-FM) texture analysis of multiple sclerosis in brain MRI images, IEEE Trans. Inform. Tech. Biomed
2011
[] J.K. Seo, E.J. Woo, U. Katscher, and Y. Wang 2014 Electro-Magnetic Tissue Properties MRI Imperial College Press
2014
Later among the works it cites.
[] Y. Bengio, I. Goodfellow and A. Courville 2015 Deep Learning Book in preparation for MIT Press, Available: http://www.deeplearningbook.org/version-2015-10-03
2015
Later among the works it cites.
[] Google 2015 TensorFlow: Large-scale machine learning on heterogeneous systems URL http://tensorflow.org/
2015
Later among the works it cites.
[] O. Ronneberger, P. Fischer, and T. Brox 2015 U-net: Convolutional networks for biomedical image segmentation in Int. Conf. on Medical Image Computing and Computer-Assisted Intervention, Springer
2015
Later among the works it cites.
[] K. Hammernik, T. Klatzer, E. Kobler, M.P. Recht, D.K. Sodickson, T. Pock and F. Knoll 2017 Learning ad Variational Network for Reconstruction of Accelerated MRI Data Magn. Reson. Med
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
[] T. Tieleman and G. Hinton 2012 Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude COURSERA: Neural Networks for Machine Learning
2012
Cited alongside, same era.
[] J.K. Seo and E.J. Woo 2013 Nonlinear inverse problems in imaging Chichester, U.K.: John Wiley & Sons
2013
Cited alongside, same era.
2017
Closest in time.
[] K. Kwon, D. Kim and H. Park 2017 A parallel MR imaging method using multilayer perceptron Med. Phy
2017
Closest in time.