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

  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},
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… 

Figures and Tables from this paper

Fast T2 Mapping With Improved Accuracy Using Undersampled Spin-Echo MRI and Model-Based Reconstructions With a Generating Function
A model-based reconstruction technique for accelerated T2 mapping with improved accuracy is proposed using undersampled Cartesian spin-echo magnetic resonance imaging (MRI) data and yields more accurate T2 values than the mono-exponential model and allows for retrospective undersampling factors of at least 6.
Real-Time Magnetic Resonance Imaging: Radial Gradient-Echo Sequences With Nonlinear Inverse Reconstruction.
Real-time gradient-echo MRI with extreme radial undersampling and nonlinear inverse reconstruction allows for direct monitoring of arbitrary physiological processes and body functions in a variety of clinical scenarios.
A model‐based reconstruction for undersampled radial spin‐echo DTI with variational penalties on the diffusion tensor
Improvements in terms of reduction of noise and streaking artifacts in the quantitative parameter maps, as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps are demonstrated.
Model-based reconstruction of accelerated quantitative magnetic resonance imaging (MRI)
Quantitative MRI refers to the determination of quantitative parameters (T1,T2,diffusion, perfusion etc.) in magnetic resonance imaging (MRI). The ’parameter maps’ are estimated from a set of
Model-Based Reconstruction for Quantitative MRI using the Bloch Equations
In this work a generic model-based reconstruction for the quantification of relaxation parameters is developed. In contrast to previous approaches that rely on simplified models derived from the
Title : Model-Based Super-Resolution Reconstruction of T 2 Maps
Purpose: High-resolution isotropic T2 mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2-D sequence, the resolution is limited by the slice
Model‐based reconstruction for T1 mapping using single‐shot inversion‐recovery radial FLASH
This work proposes a method that determines T1 maps directly from multi‐channel raw data as obtained by a single‐shot inversion‐recovery radial FLASH acquisition with a Golden Angle view order and demonstrates excellent accuracy and precision of model‐based T1 mapping.
Real-time MRI and model-based reconstruction techniques for parameter mapping of spin-lattice relaxation.
This thesis addresses the quantitative mapping of T1 relaxation times by developing new methods for fast and accurate T1 mapping at high spatial resolution by taking advantage of both the real-time MRI developments and the concept of a model-based reconstruction.
An efficient auxiliary variable method for quantification of spin density, R∗2 decay and field inhomogeneity maps in magnetic resonance imaging
  • Chenxi Hu, S. Reeves
  • Computer Science
    2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
  • 2015
A novel auxiliary variable method is proposed that is very efficient in solving the underlying optimization problem of spin density, R2* decay and off-resonance frequency maps by introducing an auxiliary variable in the spatial-temporal domain that separates the data fidelity term and the structure fidelity term.
Accelerated Parameter Mapping of Multiple-Echo Gradient-Echo Data Using Model-Based Iterative Reconstruction
Parameter maps estimated from reconstructed data using MIRAGE are shown to be accurate, with the mean absolute error reduced by up to 50% for in vivo results, which has the potential to improve the diagnostic utility of quantitative imaging techniques that rely on MEGE data.


Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint
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
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
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
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
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
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
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
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
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.