Compressive sampling in fast wavelet-encoded MRI

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3 Scopus citations

Abstract

Compressive sensing (CS) can be applied to fast wavelet-encoded MRI in order to reconstruct images from sparse sampling at sub-Nyquist sampling rates. In this paper, sparse MRI is achieved by a well-designed sampling matrix that satisfies the restricted isometry property (RIP) in CS. The wavelet-tree structure in k-space is utilized in order to reduce the RIP constant. The undersampling of k-space is implemented in a MRI simulator by spatially-selective RF excitation pulses, which are designed as Battle-Lemarie wavelet functions. The resulting undersampled k-space contains many significant wavelet-encoded samples and an improved RIP. The experimental results show that the proposed CS-MRI scheme reduced the number of necessary measurements significantly with the same reconstruction precision achieved by the current Fourier-encoded CS-MRI.

Original languageEnglish
Title of host publication2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012, Proceedings
Pages137-140
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012 - Santa Fe, NM, United States
Duration: Apr 22 2012Apr 24 2012

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation

Conference

Conference2012 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2012
CountryUnited States
CitySanta Fe, NM
Period04/22/1204/24/12

Keywords

  • Battle-Lemarie wavelet
  • RF excitation pulses
  • compressive sensing
  • fast wavelet-encoded MRI
  • restricted isometry property

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