Model-Based Iterative Reconstruction for Radial Fast Spin-Echo MRI

@article{Block2009ModelBasedIR,
  title={Model-Based Iterative Reconstruction for Radial Fast Spin-Echo MRI},
  author={Kai Tobias Block and Martin Uecker and Jens Frahm},
  journal={IEEE Transactions on Medical Imaging},
  year={2009},
  volume={28},
  pages={1759-1769}
}
In radial fast spin-echo magnetic resonance imaging (MRI), a set of overlapping spokes with an inconsistent T2 weighting is acquired, which results in an averaged image contrast when employing conventional image reconstruction techniques. This work demonstrates that the problem may be overcome with the use of a dedicated reconstruction method that further allows for T2 quantification by extracting the embedded relaxation information. Thus, the proposed reconstruction method directly yields a… 

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References

SHOWING 1-10 OF 19 REFERENCES
Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint
TLDR
An iterative reconstruction method for undersampled radial MRI which is based on a nonlinear optimization, allows for the incorporation of prior knowledge with use of penalty functions, and deals with data from multiple coils is developed.
k‐Space weighted image contrast (KWIC) for contrast manipulation in projection reconstruction MRI
TLDR
A novel technique for manipulating contrast in projection reconstruction MRI is described, implemented into a fast spin‐echo (FSE) sequence, and it is shown that multiple T2‐weighted images can be reconstructed from a single image data set.
Radial turbo spin echo imaging
TLDR
The radial turbo spin echo (rTSE) approach combines TSE methods and projection reconstruction (PR) techniques and has been applied to abdominal imaging with acquisition times shorter than 30 s and to heart imaging in combination with cardiac triggering.
View‐ordering in radial fast spin‐echo imaging
TLDR
Four view‐ordering techniques are presented and evaluated for the radial FSE sequence and can easily be controlled to minimize artifacts due to T2 decay as well as motion.
Robust radial imaging with predetermined isotropic gradient delay correction
TLDR
The goal of this paper is to parameterize the delays between MG and ADC with sufficient accuracy for clinical radial imaging applications.
Processing of radial fast spin‐echo data for obtaining T2 estimates from a single k‐space data set
TLDR
Various k‐space data processing methods for reconstructing T2‐weighted images and T2 maps from a single radial fast spin‐echo k‐ space data set are analyzed in terms of the accuracy of T2 estimates.
Fast Joint Reconstruction of Dynamic $R_2^*$ and Field Maps in Functional MRI
TLDR
A new fast regularized iterative algorithm is proposed that jointly reconstructs R<sub>2</sub> <sup>*</sup> and field maps for all time frames in fMRI data and linearizes the MR signal model, enabling the use of fast regularization iterative reconstruction methods.
Iterative T 2 Estimation from Highly Undersampled Radial Fast Spin-Echo Data
C. Graff, Z. Li, A. Bilgin, M. Altbach, A. F. Gmitro, E. W. Clarkson Program in Applied Mathematics, University of Arizona, Tucson, AZ, United States, Electrical and Computer Engineering, University
Projection Reconstruction Techniques for Reduction of Motion Effects in MRI
TLDR
Projection reconstruction techniques are shown to have intrinsic advantages over spin‐warp methods with respect to diminished artifacts from respiratory motion, and respiratory‐ordered view angle (ROVA) acquisition is found to diminish residual streaking significantly by reducing interview inconsistencies.
Sparse MRI: The application of compressed sensing for rapid MR imaging
TLDR
Practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference and demonstrate improved spatial resolution and accelerated acquisition for multislice fast spin‐echo brain imaging and 3D contrast enhanced angiography.
...
1
2
...