Compressive sensing imaging with randomized lattice sampling

applications to fast 3D MRI.

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Fast MRI makes it possible to visualize dynamic biological phenomena and can potentially reduce the cost of diagnostic imaging. Constrained imaging methods such as compressive sense (CS) and optimal lattice sampling (OLS) have proven to be effective for speeding up MRI. In doing so, CS takes advantage of the image sparsity or compressibility and OLS utilizes the known signal/spectrum support. Interestingly, while CS requires sampling to be "randomized" to obtain incoherent artifacts which is critical for reconstruction, OLS mandates sampling to be on a structured lattice. In this paper, we proposed a method to integrate CS with OLS so that both the sparsity and support constraints can be used simultaneously. The method randomizes the sampling on the lattice and minimizes a convex cost function with sparsity constraint and data fidelity terms. Computer simulations in 3D MRI show that the proposed method allows greater accelerations with minimal degradation of the image quality.

Original languageEnglish
Pages (from-to)3736-3739
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume2011
Publication statusPublished - 2011
Externally publishedYes

Fingerprint

Magnetic resonance imaging
Sampling
Imaging techniques
sampling
Biological Phenomena
Costs and Cost Analysis
Diagnostic Imaging
Computer Simulation
Artifacts
imaging method
compressibility
Compressibility
cost
Cost functions
computer simulation
Image quality
artifact
Degradation
Computer simulation
method

ASJC Scopus subject areas

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

Cite this

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