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Reconstruction of Magnetic Resonance Phase Images using the Compressed Sensing Technique

압축 센싱 기법을 이용한 MRI 위상 영상의 재구성

  • Lee, J.E. (Dept. of Biomedical Engineering, Kyung Hee University) ;
  • Cho, M.H. (Dept. of Biomedical Engineering, Kyung Hee University) ;
  • Lee, S.Y. (Dept. of Biomedical Engineering, Kyung Hee University)
  • 이정은 (경희대학교 동서의료공학과) ;
  • 조민형 (경희대학교 동서의료공학과) ;
  • 이수열 (경희대학교 동서의료공학과)
  • Received : 2010.09.06
  • Accepted : 2010.11.17
  • Published : 2010.12.31

Abstract

Compressed sensing can be used to reduce scan time or to enhance spatial resolution in MRI. It is now recognized that compressed sensing works well in reconstructing magnitude images if the sampling mask and the sparsifying transform are well chosen. Phase images also play important roles in MRI particularly in chemical shift imaging and magnetic resonance electrical impedance tomography (MREIT). We reconstruct MRI phase images using the compressed sensing technique. Through computer simulation and real MRI experiments, we reconstructed phase images using the compressed sensing technique and we compared them with the ones reconstructed by conventional Fourier reconstruction technique. As compared to conventional Fourier reconstruction with the same number of phase encoding steps, compressed sensing shows better performance in terms of mean squared phase error and edge preservation. We expect compressed sensing can be used to reduce the scan time or to enhance spatial resolution of MREIT.

Keywords

References

  1. M. Lustig, D. Donoho, J.M. Pauly, "Sparse MRI: The application of compressed sensing for rapid MR imaging," Magn. Reson. Med., vol. 58, pp. 1182-1195, 2007. https://doi.org/10.1002/mrm.21391
  2. D. Donoho, M. Elad, V. Temlyakov, "Stable recovery of sparse overcomplete representation in the presence of noise," IEEE Trans. Inf. Theory, vol. 52, pp. 6-18, 2006. https://doi.org/10.1109/TIT.2005.860430
  3. D. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol. 52, pp. 1289-1306, 2006. https://doi.org/10.1109/TIT.2006.871582
  4. J.C. Ye, S. Tak, Y. Han, H.W. Park, "Projection reconstruction MR imaging using FOCUSS," Magn. Reson. Med., vol. 57, pp. 764-775, 2007. https://doi.org/10.1002/mrm.21202
  5. G.C. Scott et al, "Measurement of nonuniform current density by magnetic resonance", IEEE Trans. Med. Imag., vol. 10, pp. 362-374, 1989.
  6. I. Sersa et al, "Electric current density imaging of mice tumors", Magn. Reson. Med., vol. 37, pp. 404-409, 1997. https://doi.org/10.1002/mrm.1910370318
  7. S.H. Oh, T.S. Park, J.Y. Han, S.Y. Lee, " Magnetic resonance imaging of a current density component", J. of Biomed. Eng. Res., vol. 25, no. 3, pp. 183-188, 2004.
  8. O. Kwon, E.J. Woo, J.R. Yoon, J.K. Seo, "Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm," IEEE Trans. Biomed. Eng., vol. 49, pp. 160-167, 2002. https://doi.org/10.1109/10.979355
  9. S.H. Oh et al, "Magnetic resonance electrical impedance tomography at 3 Tesla field strength," Mag. Reson. Med., vol. 51, pp. 1292-1296, 2004. https://doi.org/10.1002/mrm.20091
  10. A. S. Minhas, Y.T. Kim, W.C. Jeong, H.J. Kim, S.Y. Lee, E.J. Woo, "Chemical shift artifact correction in MREIT", vol. 30, pp. 461-468, 2009.
  11. H.J. Kim, Y.T. Kim, W.C. Jeong, A.S. Minhas, T.H. Lee, C.Y. Lim, H.M. Park, O.J. Kwon, E.J. Woo, "MREIT conductivity imaging of pneumonic canine lungs: preliminary post-mortem study", vol. 31, pp. 94-98, 2010.