Automated Filter Selection for Suppression of Gibbs Ringing Artefacts in MRI

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Title: Automated Filter Selection for Suppression of Gibbs Ringing Artefacts in MRI
Authors: Wang, YueHealy, John J.
Permanent link: http://hdl.handle.net/10197/13122
Date: Nov-2022
Online since: 2022-09-20T11:38:49Z
Abstract: Gibbs ringing creates artefacts in magnetic resonance images that can mislead clinicians. Reconstruction algorithms attempt to suppress Gibbs ringing, or an additional ringing suppression algorithm may be applied post reconstruction. Novel reconstruction algorithms are often compared with filtered Fourier reconstruction, but the choices of filters and filter parameters can be arbitrary and sub-optimal. Evaluation of different reconstruction and post-processing algorithms is difficult to automate or subjective: many metrics have been used in the literature. In this paper, we evaluate twelve of those metrics and demonstrate that none of them are fit for purpose. We propose a novel metric and demonstrate its efficacy in 1D and 2D simulations. We use our new metric to optimise and compare 17 smoothing filters for suppression of Gibbs artefacts. We examine the transfer functions of the optimised filters, with counter-intuitive results regarding the highest-performing filters. Our results will simplify and improve the comparison of novel MRI reconstruction and post-processing algorithms, and lead to the automation of ringing suppression in MRI. They also apply more generally to other applications in which data is captured in the Fourier domain.
Funding Details: Irish Research Council
Funding Details: GliMR EU COST Action CA18206
Type of material: Journal Article
Publisher: Elsevier
Journal: Magnetic Resonance Imaging
Volume: 93
Start page: 3
End page: 10
Keywords: Image quality metricsMR image reconstructionDark rim artefactGibbs ringing artefactMagnetic resonance imagingFiltered Fourier reconstructionFilter comparison
DOI: https://doi.org/10.1016/j.mri.2022.07.007
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Electrical and Electronic Engineering Research Collection

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