[1] Scherzinger A L, Hendee W R. Basic principles of magnetic resonance imaging-an update. Western Journal of Medicine, 1985, 143(6): 782-792 http://d.old.wanfangdata.com.cn/OAPaper/oai_pubmedcentral.nih.gov_1306488
[2] Rodríguez A O. Principles of magnetic resonance imaging. Revista Mexicana de Fisica, 2004, 50(3): 272-286 http://d.old.wanfangdata.com.cn/OAPaper/oai_doaj-articles_02f6967cefd576b25e0eb9635a942d51
[3] 翁卓, 谢国喜, 刘新, 熊承义, 郑海荣, 邱本胜.基于K空间加速采集的磁共振成像技术.中国生物医学工程学报, 2010, 29(5): 785-792 doi: 10.3969/j.issn.0258-8021.2010.05.023

Weng Zhuo, Xie Guo-Xi, Liu Xin, Xiong Cheng-Yi, Zheng Hai-Rong, Qiu Ben-Sheng. Development of fast magnetic resonance imaging techniques based on K-space accelerated collection. Chinese Journal of Biomedical Engineering, 2010, 29(5): 785-792 doi: 10.3969/j.issn.0258-8021.2010.05.023
[4] Twieg D B. The K-trajectory formulation of the NMR imaging process with applications in analysis and synthesis of imaging methods. Medical Physics, 1983, 10(5): 610-621 doi: 10.1118/1.595331
[5] McGibney G, Smith M R, Nichols S T, Crawley A. Quantitative evaluation of several partial Fourier reconstruction algorithms used in MRI. Magnetic Resonance in Medicine, 1993, 30(1): 51-59 doi: 10.1002/mrm.1910300109
[6] Pruessmann K P, Weiger M, Scheidegger M B, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magnetic Resonance in Medicine, 1999, 42(5): 952-962 doi: 10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S
[7] Noll D C, Nishimura D G, Macovski A. Homodyne detection in magnetic resonance imaging. IEEE Transactions on Medical Imaging, 1991, 10(2): 154-163 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1ef5322f42b7461f3ec54c2d442df2f0
[8] Haacke E M, Lindskogj E D, Lin W. A fast, iterative, partial-fourier technique capable of local phase recovery. Journal of Magnetic Resonance, 1991, 92(1): 126-145 http://cn.bing.com/academic/profile?id=4459f8b50b0db6b11a25d9d2e32c8b1f&encoded=0&v=paper_preview&mkt=zh-cn
[9] Griswold M A, Jakob P M, Heidemann R M, Nittka M, Jellus V, Wang J M, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magnetic Resonance in Medicine, 2002, 47(6): 1202-1210 doi: 10.1002/mrm.10171
[10] Donoho D L. Compressed sensing. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306 http://d.old.wanfangdata.com.cn/Periodical/hwyhmb200904014
[11] Lustig M, Donoho D L, Santos J M, Pauly J M. Compressed sensing MRI. IEEE Signal Processing Magazine, 2008, 25(2): 72-82 doi: 10.1109/MSP.2007.914728
[12] Grossmann A, Morlet J. Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM Journal on Mathematical Analysis, 1984, 15(4): 723-736 doi: 10.1137-0515056/
[13] Starck J L, Candes E J, Donoho D L. The curvelet transform for image denoising. IEEE Transactions on Image Processing, 2002, 11(6): 670-684 doi: 10.1109/TIP.2002.1014998
[14] Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation. IEEE Transactions on Image Processing, 2005, 14(12): 2091-2106 doi: 10.1109/TIP.2005.859376
[15] Lu Y, Do M N. A new contourlet transform with sharp frequency localization. In: Proceedings of the 2006 IEEE International Conference on Image Processing. Atlanta, GA, USA: IEEE, 2006. 1629-1632
[16] Meng Y L, Lin W, Li C L, Chen S C. Fast two-snapshot structured illumination for temporal focusing microscopy with enhanced axial resolution. Optics Express, 2017, 25(19): 23109 http://cn.bing.com/academic/profile?id=9987168816e08b02571442a0d6e6fe69&encoded=0&v=paper_preview&mkt=zh-cn
[17] Mathew R S, Paul J S. Sparsity promoting adaptive regularization for compressed sensing parallel MRI. IEEE Transactions on Computational Imaging, 2018, 4(1): 147-159 doi: 10.1109/TCI.2017.2787911
[18] Chen Y M, Ye X J, Huang F. A novel method and fast algorithm for MR image reconstruction with significantly under-sampled data. Inverse Problems & Imaging, 2017, 4(2): 223-240 https://people.clas.ufl.edu/yun/files/article-7.pdf
[19] 董家林, 洪明坚, 张海标, 葛永新.联合相邻帧预测的心脏磁共振电影成像方法.自动化学报, 2018, 44(3): 490-505 doi: 10.16383/j.aas.2018.c160420

Dong Jia-Lin, Hong Ming-Jian, Zhang Hai-Biao, Ge Yong-Xin. Joint adjacent-frame prediction for cardiac cine MR imaging. Acta Automatica Sinica, 2018, 44(3): 490-505 doi: 10.16383/j.aas.2018.c160420
[20] 熊娇娇, 卢红阳, 张明辉, 刘且根.基于梯度域的卷积稀疏编码磁共振成像重建.自动化学报, 2017, 43(10): 1841-1849 doi: 10.16383/j.aas.2017.e160135

Xiong Jiao-Jiao, Lu Hong-Yang, Zhang Ming-Hui, Liu Qie-Gen. Convolutional sparse coding in gradient domain for MRI reconstruction. Acta Automatica Sinica, 2017, 43(10): 1841-1849 doi: 10.16383/j.aas.2017.e160135
[21] Quan T M, Nguyen-Quc T, Jeong W K. Compressed sensing MRI reconstruction using a generative adversarial network with a cyclic loss. IEEE Transactions on Medical Imaging, 2018, 37(6): 1488-1497 doi: 10.1109/TMI.2018.2820120
[22] Yang G, Yu S M, Dong H, Slabaugh G, Dragotti P L, Ye X J, et al. DAGAN: deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction. IEEE Transactions on Medical Imaging, 2018, 37(6): 1310-1321 doi: 10.1109/TMI.2017.2785879
[23] Kim D, Jung S, Park H W. DRF-GRAPPA: a parallel MRI Method with a direct reconstruction filter. Journal of the Korean Physical Society, 2018, 73(1): 130-137 doi: 10.3938/jkps.73.130
[24] Wang S S, Su Z H, Ying L, Peng X, Zhu S, Liang F, et al. Accelerating magnetic resonance imaging via deep learning. In: Proceedings of the IEEE 13th International Symposium on Biomedical Imaging. Prague, Czech Republic: IEEE, 2016. 514-517
[25] Schlemper J, Caballero J, Hajnal J V, Price A, Rueckert D. A deep cascade of convolutional neural networks for MR image reconstruction. International Conference on Information Processing in Medical Imaging. Cham: Springer, 2017. 647-658
[26] Hyun C M, Kim H P, Lee S M, Lee S, Seo J K. Deep learning for undersampled MRI reconstruction. Physics in Medicine and Biology, 2018, 63(13): 135007 doi: 10.1088/1361-6560/aac71a
[27] King K F, Angelos L. SENSE with partial Fourier homodyne reconstruction. In: Proceedings of the 8th Annual Meeting of ISMRM. Denver, 2000. 153
[28] 黄鑫, 陈武凡, 冯衍秋.基于鲁棒估计的并行磁共振成像中部分数据重建算法.计算机学报, 2011, 34(9): 1732-1738 http://d.old.wanfangdata.com.cn/Periodical/jsjxb201109019

Huang Xin, Chen Wu-Fan, Feng Yan-Qiu. An effective algorithm in partial fourier parallel MRI based on robust estimator. Chinese Journal of Computers, 2011, 34(9): 1732-1738 http://d.old.wanfangdata.com.cn/Periodical/jsjxb201109019
[29] Bydder M, Robson M D. Partial fourier partially parallel imaging. Magnetic Resonance in Medicine, 2005, 53(6): 1393-1401 doi: 10.1002/mrm.20492
[30] King K F. Combining compressed sensing and parallel imaging. In: Proceedings of the 16th annual meeting of ISMRM. Toronto, 2008. 1488
[31] Liu B, Sebert F M, Zou Y, Ying L. SparseSENSE: randomly-sampled parallel imaging using compressed sensing. In: Proceedings of the 16th Annual Meeting of ISMRM. 2008.
[32] Liang D, Liu B, Wang J J, Ying L. Accelerating SENSE using compressed sensing. Magnetic Resonance in Medicine, 2009, 62(6): 1574-1584 doi: 10.1002/mrm.22161
[33] Doneva M, Börnert P, Eggers H, Stehning C, Sénégas J, Mertins A. Compressed sensing reconstruction for magnetic resonance parameter mapping. Magnetic Resonance in Medicine, 2010, 64(4): 1114-1120 doi: 10.1002/mrm.22483
[34] Liu F, Duan Y, Peterson B S, Kangarlu A. Compressed sensing MRI combined with SENSE in partial k-space. Physics in Medicine & Biology, 2012, 57(21): N391-N403 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1033ff5f36c60de34f7cd73078c3914e
[35] 张春梅, 尹忠科, 肖明霞.基于冗余字典的信号超完备表示与稀疏分解.科学通报, 2006, 51(6): 628-633 doi: 10.3321/j.issn:0023-074X.2006.06.002

Zhang Chun-Mei, Yin Zhong-Ke, Xiao Ming-Xia. Signal overcomplete representation and sparse decomposition based on redundant dictionaries. Chinese Science Bulletin, 2006, 51(6): 628-633 doi: 10.3321/j.issn:0023-074X.2006.06.002
[36] Candés E J, Eldar Y C, Needell D, Randall P. Compressed sensing with coherent and redundant dictionaries. Applied and Computational Harmonic Analysis, 2011, 31(1): 59-73 doi: 10.1016/j.acha.2010.10.002
[37] Qu X B, Zhang W R, Guo D, Cai C B, Cai S H, Chen Z. Iterative thresholding compressed sensing MRI based on contourlet transform. Inverse Problems in Science and Engineering, 2010, 18(6): 737-758 doi: 10.1080/17415977.2010.492509
[38] Hao W L, Li J W, Qu X B, Dong Z C. Fast iterative contourlet thresholding for compressed sensing MRI. Electronics Letters, 2013, 49(19): 1206-1208 doi: 10.1049/el.2013.1483
[39] Huang J Z, Zhang S T, Metaxas D. Efficient MR image reconstruction for compressed MR imaging. Medical Image Analysis, 2011, 15(5): 670-679 doi: 10.1016/j.media.2011.06.001
[40] Beck A, Teboulle M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM Journal on Imaging Sciences, 2009, 2(1): 183-202 doi: 10.1137/080716542
[41] 周金鹏. MRI快速成像若干研究[硕士学位论文], 北京理工大学, 中国, 2015. 36-41

Zhou Jin-Peng. Research on Rapid MRI [Master thesis], Beijing Institution of Technology, China, 2015. 36-41