Calibration-Less Multi-coil MR image reconstruction

Majumdar, Angshul; Ward, Rabab K.

doi:10.1016/j.mri.2012.02.025

Cited by 74 publications

(34 citation statements)

References 42 publications

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“…(12), the SSIM is a function of central pixels x i and x i . For a whole image, we use the mean SSIM (MSSIM) to evaluate the preserved structures in reconstruction.…”

Section: Resultsmentioning

confidence: 99%

Patch-Based Directional Redundant Wavelets in Compressed Sensing Parallel Magnetic Resonance Imaging with Radial Sampling Trajectory

Ye¹,

Qu²,

Guo³

et al. 2016

j med imaging hlth inform

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Compressed sensing has been shown promising to speed up magnetic resonance imaging, and its combination with partially parallel imaging can further accelerate the data acquisition. For compressed sensing, a sparser representation of an image usually leads to lower reconstruction errors. Recently, a patch-based directional wavelets (PBDW), providing an adaptive sparse representation of image patches with geometric information, has been proposed in compressed sensing MRI to improve the edge reconstruction. However, it is still unknown how to incorporate PBDW into partially parallel imaging. In this work, we propose to use patch-based directional redundant wavelets (PBDRW) as an adaptive sparsifying transform in compressed sensing sensitivity encoding, and wed the new method with radial sampling to achieve higher acceleration factors. Results from simulation and in vivo data indicate that PBDRW in sensitivity encoding achieves lower reconstruction errors and preserves more image details than traditional total variation and wavelets.

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“…(12), the SSIM is a function of central pixels x i and x i . For a whole image, we use the mean SSIM (MSSIM) to evaluate the preserved structures in reconstruction.…”

Section: Resultsmentioning

confidence: 99%

Patch-Based Directional Redundant Wavelets in Compressed Sensing Parallel Magnetic Resonance Imaging with Radial Sampling Trajectory

Ye¹,

Qu²,

Guo³

et al. 2016

j med imaging hlth inform

View full text Add to dashboard Cite

show abstract

“…Prior to this work, we proposed a naive version of the CaLM MRI technique [18]. There in, instead of stacking the coil images/transform coefficients as columns of a MMV matrix (as done here), were concatenated to a long vector, i.e.…”

Section: Proposed Reconstruction Techniquementioning

confidence: 99%

“…In [18] a convex group-sparse recovery problem is proposed to recover the coil images. Even though the reconstruction philosophy is the same in [18] and the proposed approach; the approach proposed in this work is more general since we can handle both convex and non-convex formulations. Also the data acquisition model Equation (4) is more natural than Equation (11).…”

Section: Proposed Reconstruction Techniquementioning

confidence: 99%

“…None of the previous studies [14,18] have carried out such an analysis. Over all this work is a more generalized, thorough and in-depth extension to the prior studies.…”

Section: Proposed Reconstruction Techniquementioning

confidence: 99%

“…In [18] the low-rank structure is exploited to recover the coil images. This is a good intuitive approach, but the main problem with this approach is that the Hankel matrix thus formed is huge owing to overlap of the blocks.…”

Section: Proposed Reconstruction Techniquementioning

confidence: 99%

See 2 more Smart Citations

Calibrationless Parallel Magnetic Resonance Imaging: A Joint Sparsity Model

Majumdar

Chaudhury

Ward

2013

Sensors

Self Cite

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State-of-the-art parallel MRI techniques either explicitly or implicitly require certain parameters to be estimated, e.g., the sensitivity map for SENSE, SMASH and interpolation weights for GRAPPA, SPIRiT. Thus all these techniques are sensitive to the calibration (parameter estimation) stage. In this work, we have proposed a parallel MRI technique that does not require any calibration but yields reconstruction results that are at par with (or even better than) state-of-the-art methods in parallel MRI. Our proposed method required solving non-convex analysis and synthesis prior joint-sparsity problems. This work also derives the algorithms for solving them. Experimental validation was carried out on two datasets—eight channel brain and eight channel Shepp-Logan phantom. Two sampling methods were used—Variable Density Random sampling and non-Cartesian Radial sampling. For the brain data, acceleration factor of 4 was used and for the other an acceleration factor of 6 was used. The reconstruction results were quantitatively evaluated based on the Normalised Mean Squared Error between the reconstructed image and the originals. The qualitative evaluation was based on the actual reconstructed images. We compared our work with four state-of-the-art parallel imaging techniques; two calibrated methods—CS SENSE and l1SPIRiT and two calibration free techniques—Distributed CS and SAKE. Our method yields better reconstruction results than all of them.

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Phased array coil for implementing parallel MRI in intravascular imaging: A feasibility study

Omer

Dickinson

Awan

2014

Concepts Magnetic Resonance

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The use of intravascular MRI imaging of vessels will provide high quality images for improved diagnosis and treatment. An intravascular MR receive coil provides high SNR because of proximity to the tissue but respiratory and cardiovascular motion may affect the quality of acquired images. Parallel MRI provides a framework to reduce the scan time using multiple coils. This article presents a novel design of a Phased Array MR receive coil for intravascular imaging which can implement Parallel MRI. Cartesian and Radial GRAPPA are used as the main reconstruction algorithms. We demonstrate that Moving Segment Radial GRAPPA provides good image reconstruction with minimum artifacts when data is under-sampled by a factor of 16.

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Calibration-Less Multi-coil MR image reconstruction

Cited by 74 publications

References 42 publications

Patch-Based Directional Redundant Wavelets in Compressed Sensing Parallel Magnetic Resonance Imaging with Radial Sampling Trajectory

Patch-Based Directional Redundant Wavelets in Compressed Sensing Parallel Magnetic Resonance Imaging with Radial Sampling Trajectory

Calibrationless Parallel Magnetic Resonance Imaging: A Joint Sparsity Model

Phased array coil for implementing parallel MRI in intravascular imaging: A feasibility study

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