Evidence map›Paper›PMID 35877787›Full record

ArticleMagnetic resonance in medicine2022

SENSE EPI reconstruction with 2D phase error correction and channel-wise noise removal.

Elizabeth Powell, Torben Schneider, Marco Battiston, Francesco Grussu, Ahmed Toosy, Jonathan D Clayden, Claudia A M Gandini Wheeler-Kingshott

Abstract read
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Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Elizabeth PowellQueen Square MS Centre, UCL Institute of Neurology, University College London, London, UK.ORCID 0000-0002-1059-1188
Torben SchneiderPhilips Healthcare UK, Guildford, UK.
Marco BattistonQueen Square MS Centre, UCL Institute of Neurology, University College London, London, UK.ORCID 0000-0003-2231-2251
Francesco GrussuQueen Square MS Centre, UCL Institute of Neurology, University College London, London, UK.ORCID 0000-0002-0945-3909
Ahmed ToosyQueen Square MS Centre, UCL Institute of Neurology, University College London, London, UK.
Jonathan D ClaydenDevelopmental Imaging and Biophysics Section, Great Ormond Street Institute of Child Health, University College London, London, UK.
Claudia A M Gandini Wheeler-KingshottQueen Square MS Centre, UCL Institute of Neurology, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop a robust reconstruction pipeline for EPI data that enables 2D Nyquist phase error correction using sensitivity encoding without incurring major noise artifacts in low SNR data.

methodsSENSE with 2D phase error correction (PEC-SENSE) was combined with channel-wise noise removal using Marcenko-Pastur principal component analysis (MPPCA) to simultaneously eliminate Nyquist ghost artifacts in EPI data and mitigate the noise amplification associated with phase correction using parallel imaging. The proposed pipeline (coined SPECTRE) was validated in phantom DW-EPI data using the accuracy and precision of diffusion metrics; ground truth values were obtained from data acquired with a spin echo readout. Results from the SPECTRE pipeline were compared against PEC-SENSE reconstructions with three alternate denoising strategies: (i) no denoising; (ii) denoising of magnitude data after image formation; (iii) denoising of complex data after image formation. SPECTRE was then tested using high

resultsNoise amplification associated with phase error correction incurred a 23% bias in phantom mean diffusivity (MD) measurements. Phantom MD estimates using the SPECTRE pipeline were within 8% of the ground truth value. In healthy volunteers, the SPECTRE pipeline visibly corrected Nyquist ghost artifacts and reduced associated noise amplification in high

conclusionThe proposed reconstruction pipeline is effective in correcting low SNR data, and improves the accuracy and precision of derived diffusion metrics.

Indexed as

Echo-Planar ImagingImage Processing, Computer-AssistedAlgorithmsArtifactsBrainHumansPhantoms, ImagingdenoisingdiffusionEPINyquist ghostSENSE

Identifiers

PMID35877787
PMCPMC9545987

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