Evidence map›Paper›PMID 28185433›Full record

ArticleMagnetic resonance in medicine2017

Model-based iterative reconstruction for single-shot EPI at 7T.

Uten Yarach, Myung-Ho In, Itthi Chatnuntawech, Berkin Bilgic, Frank Godenschweger, Hendrik Mattern, Alessandro Sciarra, Oliver Speck

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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  7. Characterization of Brain Metabolism by Nuclear Magnetic Resonance.Chemphyschem : a European journal of chemical physics and physical chemistry · 2019
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Uten YarachDepartment of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.
Myung-Ho InDepartment of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Itthi ChatnuntawechNational Nanotechnology Center (NANOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand.
Berkin BilgicDepartment of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
Frank GodenschwegerDepartment of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.
Hendrik MatternDepartment of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.
Alessandro SciarraDepartment of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.
Oliver SpeckDepartment of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.

Funding

RGR-based motion tracking for real-time adaptive MR imaging and spectroscopyR01DA021146 · NIDA · UNIVERSITY OF MARYLAND BALTIMORE · PI ERNST, THOMAS M · 2007 to 2018
$8.6M
NIDA NIH HHS R01 DA021146
6 · The paper itself

Abstract

purposeTo describe a model-based reconstruction strategy for single-shot echo planar imaging (EPI) that intrinsically accounts for k-space nonuniformity, Nyquist ghosting, and geometric distortions during rather than before or after image reconstruction.

methodsRamp sampling and inhomogeneous B0 field-induced distortion cause the EPI samples to lie on a non-Cartesian grid, thus requiring the nonuniform fast Fourier transform. Additionally, a 2D Nyquist ghost phase correction without the need for extra navigator acquisition is included in the proposed reconstruction. Coil compression is also incorporated to reduce the computational load. The proposed method is applied to phantom and human brain MRI data.

resultsThe results demonstrate that Nyquist ghosting and geometric distortions are reduced by the proposed reconstruction. The proposed 2D phase correction is superior to a conventional 1D correction. The reductions of both artifacts lead to improved temporal signal-to-noise ratio (tSNR). The virtual coil results suggest that the processing time can be reduced by up to 75%, with a mean tSNR loss of only 3.2% when using 8-virtual instead of 32-physical coils for twofold undersampled data.

conclusionThe proposed reconstruction improves the quality (ghosting, geometry, and tSNR) of EPI without requiring calibration data for Nyquist ghost correction. Magn Reson Med 78:2250-2264, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Indexed as

AdultAlgorithmsArtifactsBrainCalibrationComputer SimulationEcho-Planar ImagingEquipment DesignFemaleFourier AnalysisHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleModels, StatisticalPhantoms, Imaginggeometric distortionmodel-based reconstructionNyquist ghostsingle-shot EPI

Identifiers

PMID28185433
PMCPMC5552473

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.