Search

Article

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

A new fast magnetic resonance imaging method based on variabledensity spiral data acquisition and Bregman iterative reconstruction

Fang Sheng Wu Wen-Chuan Ying Kui Guo Hua

A new fast magnetic resonance imaging method based on variabledensity spiral data acquisition and Bregman iterative reconstruction

Fang Sheng, Wu Wen-Chuan, Ying Kui, Guo Hua
PDF
Get Citation
  • Data acquisition time is a bottle neck for increasing imaging speed of magnetic resonance imaging. To solve the problem, a new fast magnetic resonance imaging method based on variable-density spiral acquisition and Bregman iterative reconstruction is proposed in this paper, under the framework of compressed sensing. The proposed method increases the acquisition speed by data undersampling. The resulting undersampling aliasing artifact is removed by utilizing the intrinsic property of variable-density spiral and Bregman iterative recosntruction. The proposed method is validated by both phantom experiemnt and in vivo experiment. The experimental results demonstrate that the proposed method can effectively remove aliasing artifact from data undersampling, and achieve an image with well-preserved image structure information. Therefore this method can be used for reducing data acquisition time.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 81101030).
    [1]

    Candés E J, Romberg J, Tao T 2006 IEEE Tran. Inform. Theory 52 489

    [2]

    Donoho D L 2006 IEEE Tran. Inform. Theory 52 1289

    [3]

    Lustig M, Donoho D, Pauly J M 2007 Magn Reson. Med. 58 1182

    [4]

    Lustig M, Donoho D L, Santos J M, Pauly J M 2008 IEEE Signal Proc. Mag. 25 72

    [5]

    Kim D, Adalsteinsson E, Spielman D M 2003 Magnet. Reson. Med. 50 214

    [6]

    Tsai C M, Nishimura D G 2000 Magnet. Reson. Med. 43 452

    [7]

    Lee J H, Hargreaves B A, Hu B S, Nishimura D G 2003 Magnet. Reson. Med. 50 1276

    [8]

    Lu G, Liu M L, Li L Y, Ye C H 2002 Chin. Phys. Lett. 19 1385

    [9]

    Bensamoun S F, Glaser K J, Ringleb S I, Chen Q, Ehman R L, An K N 2008 J. Magn. Reson. Imaging. 27 1083

    [10]

    Wang H Z, Xu L F, Yu J, Huang Q M, Wang X Y, Lu L 2010 Acta Phys. Sin. 59 7463 (in Chinese) [汪红志, 许凌峰, 俞捷, 黄清明, 王晓琰, 陆伦 2010物理学报 59 7463]

    [11]

    Rudin L, Osher S, Fatemi E 1992 Physica D 60 259

    [12]

    Chan T, Esedoglu S, Park F, Yip A 2006 Mathematical Models of Computer Vision: the Handbook (Boston, MA: Springer) p176

    [13]

    Block K T, Uecker M, Frahm J 2007 Magnet. Reson. Med. 57 1086

    [14]

    Osher S, Burger M, Goldfarb D, Xu J, Yin W 2005 Multiscale Model. Sim. 4 460

    [15]

    Sha L, Guo H, Song A W 2003 J. Magnet. Reson. 162 250

    [16]

    Jackson J I, Meyer C H, Nishimura D G, Macovski A 1991 IEEE Trans. Med. Imaging. 10 473

  • [1]

    Candés E J, Romberg J, Tao T 2006 IEEE Tran. Inform. Theory 52 489

    [2]

    Donoho D L 2006 IEEE Tran. Inform. Theory 52 1289

    [3]

    Lustig M, Donoho D, Pauly J M 2007 Magn Reson. Med. 58 1182

    [4]

    Lustig M, Donoho D L, Santos J M, Pauly J M 2008 IEEE Signal Proc. Mag. 25 72

    [5]

    Kim D, Adalsteinsson E, Spielman D M 2003 Magnet. Reson. Med. 50 214

    [6]

    Tsai C M, Nishimura D G 2000 Magnet. Reson. Med. 43 452

    [7]

    Lee J H, Hargreaves B A, Hu B S, Nishimura D G 2003 Magnet. Reson. Med. 50 1276

    [8]

    Lu G, Liu M L, Li L Y, Ye C H 2002 Chin. Phys. Lett. 19 1385

    [9]

    Bensamoun S F, Glaser K J, Ringleb S I, Chen Q, Ehman R L, An K N 2008 J. Magn. Reson. Imaging. 27 1083

    [10]

    Wang H Z, Xu L F, Yu J, Huang Q M, Wang X Y, Lu L 2010 Acta Phys. Sin. 59 7463 (in Chinese) [汪红志, 许凌峰, 俞捷, 黄清明, 王晓琰, 陆伦 2010物理学报 59 7463]

    [11]

    Rudin L, Osher S, Fatemi E 1992 Physica D 60 259

    [12]

    Chan T, Esedoglu S, Park F, Yip A 2006 Mathematical Models of Computer Vision: the Handbook (Boston, MA: Springer) p176

    [13]

    Block K T, Uecker M, Frahm J 2007 Magnet. Reson. Med. 57 1086

    [14]

    Osher S, Burger M, Goldfarb D, Xu J, Yin W 2005 Multiscale Model. Sim. 4 460

    [15]

    Sha L, Guo H, Song A W 2003 J. Magnet. Reson. 162 250

    [16]

    Jackson J I, Meyer C H, Nishimura D G, Macovski A 1991 IEEE Trans. Med. Imaging. 10 473

  • Citation:
Metrics
  • Abstract views:  991
  • PDF Downloads:  707
  • Cited By: 0
Publishing process
  • Received Date:  29 October 2012
  • Accepted Date:  15 November 2012
  • Published Online:  20 February 2013

A new fast magnetic resonance imaging method based on variabledensity spiral data acquisition and Bregman iterative reconstruction

  • 1. Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China;
  • 2. Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China;
  • 3. Department of Engineering Physics, Tsinghua University, Beijing 100084, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant No. 81101030).

Abstract: Data acquisition time is a bottle neck for increasing imaging speed of magnetic resonance imaging. To solve the problem, a new fast magnetic resonance imaging method based on variable-density spiral acquisition and Bregman iterative reconstruction is proposed in this paper, under the framework of compressed sensing. The proposed method increases the acquisition speed by data undersampling. The resulting undersampling aliasing artifact is removed by utilizing the intrinsic property of variable-density spiral and Bregman iterative recosntruction. The proposed method is validated by both phantom experiemnt and in vivo experiment. The experimental results demonstrate that the proposed method can effectively remove aliasing artifact from data undersampling, and achieve an image with well-preserved image structure information. Therefore this method can be used for reducing data acquisition time.

Reference (16)

Catalog

    /

    返回文章
    返回