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17
FAST REGULARIZED RECONSTRUCTION OF NONUNIFORMLY SUBSAMPLED PARALLEL MRI DATA
"... Parallel MR imaging is an effective approach to reduce MR image acquisition time. Nonuniform subsampling allows one to tailor the subsampling scheme for improved image quality at high acceleration factors. However, nonuniform subsampling precludes fast reconstruction schemes such as SENSE, and is ..."
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Cited by 2 (1 self)
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Parallel MR imaging is an effective approach to reduce MR image acquisition time. Nonuniform subsampling allows one to tailor the subsampling scheme for improved image quality at high acceleration factors. However, nonuniform subsampling precludes fast reconstruction schemes such as SENSE, and is more likely to require a regularized solution than reconstruction of uniformly subsampled data demands. This means that one needs to choose a good regularization parameter, typically requiring multiple expensive system solves. Here, we present an efficient LSQRHybrid algorithm which simultaneously addresses the need for rapid regularization parameter selection and fast reconstruction. This algorithm can reconstruct nonuniformly subsampled parallel MRI data, with automatic regularization and good image quality, in a time competitive with Cartesian SENSE. 1.
Single Echo Acquistion of MR Images Using RF Coil Arrays
 in Proceedings of the Second Joint EMBS/BMES Conference
, 2002
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Dynamic Compressive Sensing: SPARSE RECOVERY ALGORITHMS FOR STREAMING SIGNALS AND VIDEO
, 2013
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Spread spectrum for chaotic compressed sensing techniques in parallel magnetic resonance imaging
 in Proceedings of the 8th International Conference on Information, Communication and Signal Processing (ICICS'11
, 2011
"... Abstract—We consider the fast acquisition problem in magnetic resonance imaging (MRI). Often, fast acquisition is achieved using parallel imaging (pMRI) techniques. It has been shown recently that compressed sensing (CS), which enables exact reconstruction of sparse or compressible signals from a sm ..."
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Abstract—We consider the fast acquisition problem in magnetic resonance imaging (MRI). Often, fast acquisition is achieved using parallel imaging (pMRI) techniques. It has been shown recently that compressed sensing (CS), which enables exact reconstruction of sparse or compressible signals from a small number of random measurements, can accelerate the speed of MRI acquisition because the number of measurements was small. Recently, the spread spectrum (SS) has been utilized to enhance the quality of reconstructed CS image. Also recently, chaotic CS approach potentially offers simpler hardware implementation. In this paper, we combine chaotic CS and spread spectrum technique in order to obtain a fast acquisition in MRI with enhanced quality of reconstructed image. The performance of the proposed method is analyzed using numerical simulation. Key words – fast acquisition, magnetic resonance imaging (MRI), compressed sensing (CS), deterministic chaos, I.
Running head: SPIRiT: Iterative Selfconsistent Parallel Imaging Reconstruction Address correspondence to:
"... A new approach to autocalibrating, coilbycoil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisit ..."
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A new approach to autocalibrating, coilbycoil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary kspace sampling patterns. The formulation can flexibly incorporate additional image priors such as off resonance correction and regularization terms. Several iterative strategies to solve the posed reconstruction problem in both image and kspace domain are presented. These are based on projection over convex sets (POCS) and conjugate gradient (CG) algorithms. Phantom and invivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include offresonance correction and nonlinear regularization are also demonstrated.
ON THE COMPLEMENTARITY OF SENSE AND GRAPPA IN PARALLEL MR IMAGING
"... Two image reconstruction methods currently dominate parallel MR imaging: SENSE and GRAPPA. While both seek to reconstruct images from subsampled multichannel MRI data, there exist fundamental differences between the two. In particular, SENSE reconstructs an image of the excited spindensity directly ..."
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Two image reconstruction methods currently dominate parallel MR imaging: SENSE and GRAPPA. While both seek to reconstruct images from subsampled multichannel MRI data, there exist fundamental differences between the two. In particular, SENSE reconstructs an image of the excited spindensity directly whereas GRAPPA reconstructs estimates of the fully sampled raw coil data and then combines them to obtain an image. In this work we show that these differences can be exploited such that each method can compliment the other. In the case of SENSE, which requires an estimate of the coil sensitivity map before reconstruction, one can use GRAPPA to improve the coil sensitivity estimates. Alternatively, using coil sensitivity estimates and the SENSE reconstruction equations, one can improve the GRAPPA reconstruction parameter estimation. Together, these approaches can provide higher image quality than either method alone. 1.
A Study of Parallel MRI Reconstruction Approaches for SubSampled PartialFourier Acquisitions
"... Abstract—We compare here two approaches to reconstruct subsampled partial Fourier MRI data acquired with multiple receiver coils. The first approach combines homodyne detection with SENSElike reconstructions. The second approach employs separate regularization of the real and imaginary components ( ..."
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Abstract—We compare here two approaches to reconstruct subsampled partial Fourier MRI data acquired with multiple receiver coils. The first approach combines homodyne detection with SENSElike reconstructions. The second approach employs separate regularization of the real and imaginary components (twoparameters) of the parallel MRI linear system to constrain the magnitude of phase variation in the reconstructed image. We show that both methods robustly reconstruct images from several sampling patterns. The dominant difference is the number of symmetric lines of kspace needed to provide high quality reconstructions. The two parameter approach can reconstruct good images using only two symmetric lines, whereas the homodyne approach requires significantly more. We present a method for automatic selection of the two parameters, and results from both high resolution and low contrast phantom data. I.
Acknowledgement
"... In the time of “network economy”, industries and the public have stressed several “battles for dominance ” between two or more rival technologies, often involving wellknown firms operating in highly visible industries. In this paper, we are going to focus on the Chinese selfdeveloped standard TDS ..."
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In the time of “network economy”, industries and the public have stressed several “battles for dominance ” between two or more rival technologies, often involving wellknown firms operating in highly visible industries. In this paper, we are going to focus on the Chinese selfdeveloped standard TDSCDMA to perceive the implication and target of the nation’s policy and strategy. The motivation of the research starts from the interesting fact we observed: TDSCDMA is named as the Chinese made standard, however the Chinese hold core patent technology is still about 7%, while most of the rest part is still taken by other foreign companies. The “faultage ” between the small share reality and a self made standard sweet dream implies a well plotted strategy. In order to understand it, we firstly raise the question of why the Chinese government postpones the 3G decision again and again. Then we go further to probe why the standardsetting of TDSCDMA has aroused wide attention as a strategic tool to fulfill “indigenous innovation”, and finally becomes part of national science and technology policy to increase international competitiveness? We are going to use economics theories to understand the essence of the creation of TDSCDMA, and its relation to China’s interests.