Location constrained approximate message passing for compressed sensing MRI

Magn Reson Med. 2013 Aug;70(2):370-81. doi: 10.1002/mrm.24468. Epub 2012 Oct 5.

Abstract

Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization methods for solving large-sized problems in compressed sensing. A novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) is presented for reducing computational complexity and improving reconstruction accuracy when a nonzero location (or sparse support) constraint can be obtained from view shared images. LCAMP modifies the existing approximate message passing algorithm by replacing the thresholding stage with a location constraint, which avoids adjusting regularization parameters or thresholding levels. This work is first compared with other conventional reconstruction methods using random one-dimention signals and then applied to dynamic contrast-enhanced breast magnetic resonance imaging to demonstrate the excellent reconstruction accuracy (less than 2% absolute difference) and low computation time (5-10 s using Matlab) with highly undersampled three-dimentional data (244 × 128 × 48; overall reduction factor = 10).

Keywords: compressed sensing; image reconstruction; iterative reconstruction; quantitative DCE MRI; wavelet transformation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Brain / anatomy & histology*
  • Data Compression / methods*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Reproducibility of Results
  • Sample Size
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*