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      • Department of Electrical and Electronics Engineering
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      Accelerated phase-cycled SSFP imaging with compressed sensing

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      Author(s)
      Çukur, T.
      Date
      2015
      Source Title
      IEEE Transactions on Medical Imaging
      Print ISSN
      0278-0062
      Publisher
      Institute of Electrical and Electronics Engineers Inc.
      Volume
      34
      Issue
      1
      Pages
      107 - 115
      Language
      English
      Type
      Article
      Item Usage Stats
      228
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      242
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      Abstract
      Balanced steady-state free precession (SSFP) imaging suffers from irrecoverable signal losses, known as banding artifacts, in regions of large B0 field inhomogeneity. A common solution is to acquire multiple phase-cycled images each with a different frequency sensitivity, such that the location of banding artifacts are shifted in space. These images are then combined to alleviate signal loss across the entire field-of-view. Although high levels of artifact suppression are viable using a large number of images, this is a time costly process that limits clinical utility. Here, we propose to accelerate individual acquisitions such that the overall scan time is equal to that of a single SSFP acquisition. Aliasing artifacts and noise are minimized by using a variable-density random sampling pattern in k-space, and by generating disjoint sampling patterns for separate acquisitions. A sparsity-enforcing method is then used for image reconstruction. Demonstrations on realistic brain phantom images, and in vivo brain and knee images are provided. In all cases, the proposed technique enables robust SSFP imaging in the presence of field inhomogeneities without prolonging scan times. © 2014 IEEE.
      Keywords
      Banding artifact
      Compressed sensing
      Magnetic resonance imaging (MRI)
      Phase cycling
      Random undersampling
      Steady - state free precession (SSFP)
      Variable density
      Compressed sensing
      Signal reconstruction
      Banding artifact
      Phase cycling
      Random under samplings
      Steady state free precessions
      Variable density
      Magnetic resonance imaging
      Acceleration
      Artifact reduction
      Brain size
      Density
      Gray matter
      Image quality
      Image reconstruction
      Imaging
      Neuroimaging
      Nuclear magnetic resonance imaging
      Phantom
      Radiological procedures
      Signal noise ratio
      Steady state free precession imaging
      White matter
      Algorithm
      Anatomy and histology
      Image processing
      Knee
      Procedures
      Algorithms
      Artifacts
      Brain
      Humans
      Image Processing, Computer-Assisted
      Magnetic Resonance Imaging
      Phantoms
      Signal - To - Noise Ratio
      Permalink
      http://hdl.handle.net/11693/24658
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/TMI.2014.2346814
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      • Department of Electrical and Electronics Engineering 4011
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