Parallel variable-density spiral imaging using nonlocal total variation reconstruction

doi:10.1088/1674-1056/23/5/057401

Abstract The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging method based on parallel variable-density spiral acquisition, which combines undersampling optimization and nonlocal total variation reconstruction. The undersampling optimization promotes the incoherence of resultant aliasing artifact via the “worst-case” residual error metric, and thus accelerates the data acquisition. Moreover, nonlocal total variation reconstruction is utilized to remove such an incoherent aliasing artifact and so improve image quality. The feasibility of the proposed method is demonstrated by both numerical phantom simulation and in vivo experiment. The experimental results show that the proposed method can achieve high acceleration factor and effectively remove an aliasing artifact from data undersampling with well-preserved image details. The image quality is better than that achieved with the total variation method.

Keywords: magnetic resonance imaging variable-density spiral parallel imaging nonlocal total variation

Received: 25 November 2013
Revised: 19 December 2013
Accepted manuscript online:

PACS:	74.25.nj	(Nuclear magnetic resonance)
	61.05.Tv	(Neutron imaging; neutron tomography)
	42.30.Wb	(Image reconstruction; tomography)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 81101030 and 61271132).

Corresponding Authors: Guo Hua
E-mail: huaguo@tsinghua.edu.cn

About author: 74.25.nj; 61.05.Tv; 42.30.Wb

Cite this article:

Fang Sheng (方晟), Guo Hua (郭华) Parallel variable-density spiral imaging using nonlocal total variation reconstruction 2014 Chin. Phys. B 23 057401

[1]	Pruessmann K P, Weiger M, Scheidegger M B and Boesiger P 1999 Magn. Reson. Med. 42 952
[2]	Griswold M A, Jakob P M, Nittka M, Goldfarb J W and Haase A 2000 Magn. Reson. Med. 44 602
[3]	Liu C, Bammer R and Moseley M E 2007 Magn. Reson. Med. C 58 1171
[4]	Sodickson D K and Manning W J 1997 Magn. Reson. Med. C 38 591
[5]	Griswold M A, Jakob P M, Heidemann R M, Nittka M, Jellus V, Wang J, Kiefer B and Haase A 2002 Magn. Reson. Med. 47 1202
[6]	Yeh E N, McKenzie C A, Ohliger M A, Sodickson D K and Foundation W 2005 Magn. Reson. Med. 53 1383
[7]	Kyriakos W E, Panych L P, Kacher D F, Westin C F, Bao S M, Mulkern R V and Jolesz F A 2000 Magn. Reson. Med. 44 301
[8]	Pruessmann K P, Weiger M, Bornert P and Boesiger P 2001 Magn. Reson. Med. 46 638
[9]	Lin F H, Kwong K K, Belliveau J W and Wald L L 2004 Magn. Reson. Med. 51 559
[10]	Tsai C M and Nishimura D G 2000 Magn. Reson. Med. 43 452
[11]	Kim D H, Adalsteinsson E and Spielman D M 2003 Magn. Reson. Med. 50 214
[12]	Spielman D M, Pauly J M and Meyer C H 1995 Magn. Reson. Med. 34 388
[13]	Lee J H, Hargreaves B A, Hu B S and Nishimura D G 2003 Magn. Reson. Med. 50 1276
[14]	Santos J M, Cunningham C H, Lustig M, Hargreaves B A, Hu B S, Nishimura D G and Pauly J M 2006 Magn. Reson. Med. 55 371
[15]	Donoho D L 2006 IEEE Trans. Inf. Theory 52 1298
[16]	Lustig M, Donoho D L and Pauly J M 2007 Magn. Reson. Med. 58 1182
[17]	Liu B, King K, Steckner M, Xie J, Sheng J and Ying L 2009 Magn. Reson. Med. 61 145
[18]	Ying L, Liu B, Steckner M C, Wu G, Wu M and Li S J 2008 Magn. Reson. Med. 60 414
[19]	Fang S, Ying K, Zhao L and Cheng J P 2010 Magn. Reson. Med. 64 1413
[20]	Rudin L, Osher S and Fatemi E 1992 Magn. Reson. Med. 60 259
[21]	Block K T, Uecker M and Frahm J 2007 Magn. Reson. Med. 57 1086
[22]	Zhang X Q, Burger M, Bresson X and Osher S 2010 SIAM J. Imag. Sci. 3 253
[23]	Buades A, Coll B and Morel J M 2006 Multiscale Model. Simul. 4 490
[24]	Liang D, Wang H, Chang Y and Ying L 2011 Magn. Reson. Med. 56 1384
[25]	Jackson J I, Meyer C H, Nishimura D G and Macovski A 1991 IEEE Trans. Med. Imag. 10 473
[26]	Winkelmann S, Schaeffter T, Koehler T, Eggers H and Doessel O 2007 IEEE Trans. Med. Imag. 26 68
[27]	Osher S, Burger M, Goldfarb D, Xu J and Yin W 2006 Multiscale Model. Simul. 4 460
[28]	Fessler J A and Sutton B P 2003 IEEE Trans. Sig. Proc. 51 560
[29]	Combettes P and Wajs V 2006 Multiscale Model. Simul. 4 1168
[30]	Fang S, Wu W C, Ying K and Guo H 2013 Acta Phys. Sin. 62 048702 (in Chinese)
[31]	Man L C, Pauly J M and Macovski A 1997 Magn. Reson. Med. 37 906
[32]	Qu P, Zhong K, Zhang B, Wang J and Shen G 2005 Magn. Reson. Med. 54 1040

[1]	Three-dimensional clogging structures of granular spheres near hopper orifice Jing Yang(杨敬), Dianjinfeng Gong(宫殿锦丰), Xiaoxue Wang(汪晓雪), Zhichao Wang(王志超), Jianqi Li(李建奇), Bingwen Hu(胡炳文), and Chengjie Xia(夏成杰). Chin. Phys. B, 2022, 31(1): 014501.
[2]	Design of small-scale gradient coils in magnetic resonance imaging by using the topology optimization method Hui Pan(潘辉), Feng Jia(贾峰), Zhen-Yu Liu(刘震宇), Maxim Zaitsev, Juergen Hennig, Jan G Korvink. Chin. Phys. B, 2018, 27(5): 050201.
[3]	Performance study of aluminum shielded room for ultra-low-field magnetic resonance imaging based on SQUID: Simulations and experiments Bo Li(李波), Hui Dong(董慧), Xiao-Lei Huang(黄小磊), Yang Qiu(邱阳), Quan Tao(陶泉), Jian-Ming Zhu(朱建明). Chin. Phys. B, 2018, 27(2): 020701.
[4]	Multifractal analysis of white matter structural changes on 3D magnetic resonance imaging between normal aging and early Alzheimer's disease Ni Huang-Jing (倪黄晶), Zhou Lu-Ping (周泸萍), Zeng Peng (曾彭), Huang Xiao-Lin (黄晓林), Liu Hong-Xing (刘红星), Ning Xin-Bao (宁新宝), the Alzheimer's Disease Neuroimaging Initiative. Chin. Phys. B, 2015, 24(7): 070502.
[5]	Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T₂^*-w magnetic resonance imaging Yu Shao-De (余绍德), Wu Shi-Bin (伍世宾), Wang Hao-Yu (王浩宇), Wei Xin-Hua (魏新华), Chen Xin (陈鑫), Pan Wan-Long (潘万龙), Hu Jiani, Xie Yao-Qin (谢耀钦). Chin. Phys. B, 2015, 24(12): 128711.
[6]	Novel magnetic vortex nanorings/nanodiscs: Synthesis and theranostic applications Liu Xiao-Li (刘晓丽), Yang Yong (杨勇), Wu Jian-Peng (吴建鹏), Zhang Yi-Fan (张艺凡), Fan Hai-Ming (樊海明), Ding Jun (丁军). Chin. Phys. B, 2015, 24(12): 127505.
[7]	Self-assembled superparamagnetic nanoparticles as MRI contrast agents–A review Su Hong-Ying (苏红莹), Wu Chang-Qiang (吴昌强), Li Dan-Yang (李丹阳), Ai Hua (艾华). Chin. Phys. B, 2015, 24(12): 127506.
[8]	Flexible reduced field of view magnetic resonance imaging based on single-shot spatiotemporally encoded technique Li Jing (李敬), Cai Cong-Bo (蔡聪波), Chen Lin (陈林), Chen Ying (陈颖), Qu Xiao-Bo (屈小波), Cai Shu-Hui (蔡淑惠). Chin. Phys. B, 2015, 24(10): 108703.
[9]	Surface modification of magnetic nanoparticles in biomedicine Chu Xin (储鑫), Yu Jing (余靓), Hou Yang-Long (侯仰龙). Chin. Phys. B, 2015, 24(1): 014704.
[10]	Formation of multifunctional Fe₃O₄/Au composite nanoparticles for dual-mode MR/CT imaging applications Hu Yong (胡勇), Li Jing-Chao (李静超), Shen Ming-Wu (沈明武), Shi Xiang-Yang (史向阳). Chin. Phys. B, 2014, 23(7): 078704.
[11]	Nanomagnetism：Principles, nanostructures, and biomedical applications Yang Ce (杨策), Hou Yang-Long (侯仰龙), Gao Song (高松). Chin. Phys. B, 2014, 23(5): 057505.
[12]	Multifunctional magnetic nanoparticles for magnetic resonance image-guided photothermal therapy for cancer Yue Xiu-Li (岳秀丽), Ma Fang (马放), Dai Zhi-Fei (戴志飞). Chin. Phys. B, 2014, 23(4): 044301.
[13]	Multi-objective optimization of gradient coil for benchtop magnetic resonance imaging system with high-resolution Wang Long-Qing (王龙庆), Wang Wei-Min (王为民). Chin. Phys. B, 2014, 23(2): 028703.
[14]	Magnetic nanoparticle-based cancer therapy Yu Jing (余靓), Huang Dong-Yan (黄冬雁), Muhammad Zubair Yousaf, Hou Yang-Long (侯仰龙), Gao Song (高松). Chin. Phys. B, 2013, 22(2): 027506.
[15]	Designing shielded radio-frequency phased-array coils for magnetic resonance imaging Xu Wen-Long (徐文龙), Zhang Ju-Cheng (张鞠成), Li Xia (李霞), Xu Bing-Qiao (徐冰俏), Tao Gui-Sheng (陶贵生). Chin. Phys. B, 2013, 22(1): 010203.

No Suggested Reading articles found!

Viewed

Full text

Abstract

Cited

Metrics
Related Articles

Parallel variable-density spiral imaging using nonlocal total variation reconstruction

Cite this article:

Online attention