ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA

  title={ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA},
  author={Martin Uecker and Peng Lai and M. J. Murphy and Patrick Virtue and Michael Elad and John M. Pauly and Shreyas S. Vasanawala and Michael Lustig},
  journal={Magnetic Resonance in Medicine},
Parallel imaging allows the reconstruction of images from undersampled multicoil data. The two main approaches are: SENSE, which explicitly uses coil sensitivities, and GRAPPA, which makes use of learned correlations in k‐space. The purpose of this work is to clarify their relationship and to develop and evaluate an improved algorithm. 

LORAKS makes better SENSE: Phase‐constrained partial fourier SENSE reconstruction without phase calibration

This work proposes and evaluates SENSE‐LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information.

T2 shuffling: Sharp, multicontrast, volumetric fast spin‐echo imaging

A new acquisition and reconstruction method called T2 Shuffling is presented for volumetric fast spin‐echo (three‐dimensional [3D] FSE) imaging. T2 Shuffling reduces blurring and recovers many images

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A coil compression method is proposed that works with concentric ring non‐Cartesian SMS imaging and should work with Cartesian SMS as well and is evaluated on fMRI scans of several subjects and compared to standard coil compression methods.

Time‐domain principal component reconstruction (tPCR): A more efficient and stable iterative reconstruction framework for non‐Cartesian functional MRI

To improve the reconstruction efficiency and stability of iterative reconstruction for non‐Cartesian fMRI when using high undersampling rates and/or in the presence of strong off‐resonance effects.

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    M. Herbst
    Magnetic resonance in medicine
  • 2021
This work investigates an algorithm to enable reconstruction of interleaved segmented acquisitions without the need of additional calibration or navigator measurements.

Over‐discretized SENSE reconstruction and B0 correction for accelerated non‐lipid‐suppressed 1H FID MRSI of the human brain at 9.4 T

Post‐processing methods are used to improve the data quality of metabolite maps acquired on the human brain at 9.4 T with accelerated acquisition schemes by combining an improved sensitivity encoding (SENSE) reconstruction with a B0 correction of spatially over‐discretized magnetic resonance spectroscopic imaging (MRSI) data.

Regularization in parallel magnetic resonance imaging

    Amel Korti
    Computer Science
    Int. J. Imaging Syst. Technol.
  • 2018
A regularized SPIRiT reconstruction based on steerable pyramid decomposition is proposed, with directionally filter banks leading to a better separation of signal and noise compared to a discrete wavelet transform (DWT).

Accelerated T2 mapping combining parallel MRI and model‐based reconstruction: GRAPPATINI

Quantitative T2 measurements are sensitive to intra‐ and extracellular water accumulation and myelin loss and promise to be a good biomarker of disease, however, they require long acquisition times.

Robust autocalibrated structured low‐rank EPI ghost correction

A new structured low‐rank method for echo‐planar imaging (EPI) ghost correction called Robust Autocalibrated LORAKs (RAC‐LORAKS) is proposed and evaluated, which does not require conventional EPI navigator signals, and is robust to imperfect autocalibration data.

Autocalibrated wave‐CAIPI reconstruction; Joint optimization of k‐space trajectory and parallel imaging reconstruction

An autocalibrated technique is proposed to determine discrepancies in the k‐space trajectory of fast MRI acquisitions that are dependent on the image prescription and protocol parameters.

Calibrationless parallel imaging reconstruction based on structured low‐rank matrix completion

A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k‐space estimation (SAKE), is presented. It is a data‐driven, coil‐by‐coil reconstruction method that

Nonlinear Reconstruction Methods for Parallel Magnetic Resonance Imaging

The problem of inaccurate coil sensitivities is addressed with a new non-linear algorithm for auto-calibrated parallel imaging, which allows for a reconstruction of artefact-free images with higher acceleration factors and less reference data than previous linear approaches.

Generalized autocalibrating partially parallel acquisitions (GRAPPA)

This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD‐AUTO‐SMASH reconstruction techniques and provides unaliased images from each component coil prior to image combination.

Improved parallel MR imaging using a coefficient penalized regularization for GRAPPA reconstruction

The imaging data demonstrate that the coefficient penalized regularization method in GRAPPA reconstruction is able to reduce noise amplification to a greater degree and enhances the quality of images significantly when compared to the previous least squares and Tikhonov regularization methods.

An EigenVector Approach to AutoCalibrating Parallel MRI , Where SENSE Meets GRAPPA

A new way to compute the explicit sensitivity maps that are (implicitly) used by acPI methods is presented, which estimates them directly from the calibration matrix by Eigen-vector analysis of the k-space filtering in acPI algorithms.


    R. MorrisonM. JacobM. Do
    2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
  • 2007
A subspace-based framework is obtained for directly solving for receiver coil sensitivity functions in parallel MRI by exploiting the multichannel nature of the problem, where multiple acquisitions of the same image function are obtained with different sensitivity weightings.

Image reconstruction by regularized nonlinear inversion—Joint estimation of coil sensitivities and image content

A respective algorithm based on a Newton‐type method with appropriate regularization terms is demonstrated to improve the performance of autocalibrating parallel MRI—mainly due to a better estimation of the coil sensitivity profiles.

Fast imaging using subencoding data sets from multiple detectors

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    Physics, Geology
    Magnetic resonance in medicine
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A new fast imaging method using a subencoding data acquisition scheme and a multiple coil receiver system is proposed and demonstrated, which can be easily adapted to conventional imaging methods including fast imaging to further reduce the scan time.

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.

SPIRiT: Iterative self‐consistent parallel imaging reconstruction from arbitrary k‐space

A new approach to autocalibrating, coil‐by‐coil parallel imaging reconstruction, is presented, a generalized reconstruction framework based on self‐consistency that can accurately reconstruct images from arbitrary k‐space sampling patterns.