Compressed sensing parallel magnetic resonance imaging

Jim Ji, Chen Zhao, Tao Lang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Both parallel Magnetic Resonance Imaging (pMRI) and Compressed Sensing (CS) can significantly reduce imaging time in MRI, the former by utilizing multiple channel receivers and the latter by utilizing the sparsity of MR images in a transformed domain. In this work, pMRI and CS are integrated to take advantages of the sensitivity information from multiple coils and sparsity characteristics of MR images. Specifically, CS is used as a regularizaron method for the inverse problem raised by pMRI based on the L1 norm and a Total Variation (TV) term. We test the new method with a set of 8-channel, in-vivo brain MRI data at reduction factors from 2 to 8. Reconstruction results show that the proposed method outperforms several other regularized parallel MRI reconstruction such as the truncated Singular Value Decomposition (SVD) and Tikhonov regularization methods, in terms of residual artifacts and SNR, especially at reduction factors larger than 4.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages1671-1674
Number of pages4
Publication statusPublished - 2008
Externally publishedYes
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period20/8/0825/8/08

Fingerprint

Compressed sensing
Magnetic resonance
Magnetic resonance imaging
Magnetic Resonance Imaging
Imaging techniques
Singular value decomposition
Inverse problems
Brain
Artifacts

Keywords

  • Compressed sensing
  • Imaging reconstruction
  • Parallel MRI
  • Regularizaron

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Ji, J., Zhao, C., & Lang, T. (2008). Compressed sensing parallel magnetic resonance imaging. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 1671-1674). [4649496]

Compressed sensing parallel magnetic resonance imaging. / Ji, Jim; Zhao, Chen; Lang, Tao.

Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 1671-1674 4649496.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ji, J, Zhao, C & Lang, T 2008, Compressed sensing parallel magnetic resonance imaging. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4649496, pp. 1671-1674, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canada, 20/8/08.
Ji J, Zhao C, Lang T. Compressed sensing parallel magnetic resonance imaging. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 1671-1674. 4649496
Ji, Jim ; Zhao, Chen ; Lang, Tao. / Compressed sensing parallel magnetic resonance imaging. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. pp. 1671-1674
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