Literature DB >> 21571661

An image-based approach to understanding the physics of MR artifacts.

John N Morelli1, Val M Runge, Fei Ai, Ulrike Attenberger, Lan Vu, Stuart H Schmeets, Wolfgang R Nitz, John E Kirsch.   

Abstract

As clinical magnetic resonance (MR) imaging becomes more versatile and more complex, it is increasingly difficult to develop and maintain a thorough understanding of the physical principles that govern the changing technology. This is particularly true for practicing radiologists, whose primary obligation is to interpret clinical images and not necessarily to understand complex equations describing the underlying physics. Nevertheless, the physics of MR imaging plays an important role in clinical practice because it determines image quality, and suboptimal image quality may hinder accurate diagnosis. This article provides an image-based explanation of the physics underlying common MR imaging artifacts, offering simple solutions for remedying each type of artifact. Solutions that have emerged from recent technologic advances with which radiologists may not yet be familiar are described in detail. Types of artifacts discussed include those resulting from voluntary and involuntary patient motion, magnetic susceptibility, magnetic field inhomogeneities, gradient nonlinearity, standing waves, aliasing, chemical shift, and signal truncation. With an improved awareness and understanding of these artifacts, radiologists will be better able to modify MR imaging protocols so as to optimize clinical image quality, allowing greater confidence in diagnosis.
Copyright © RSNA, 2011.

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Year:  2011        PMID: 21571661     DOI: 10.1148/rg.313105115

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  38 in total

1.  Magnetic resonance imaging (MRI) artefacts in hip prostheses: a comparison of different prosthetic compositions.

Authors:  Elisabetta Panfili; Laura Pierdicca; Luca Salvolini; Luigi Imperiale; Jeffrey Dubbini; Andrea Giovagnoni
Journal:  Radiol Med       Date:  2013-12-03       Impact factor: 3.469

2.  A comparison of five standard methods for evaluating image intensity uniformity in partially parallel imaging MRI.

Authors:  Frank L Goerner; Timothy Duong; R Jason Stafford; Geoffrey D Clarke
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

Review 3.  Body MR Imaging: Artifacts, k-Space, and Solutions.

Authors:  Susie Y Huang; Ravi T Seethamraju; Pritesh Patel; Peter F Hahn; John E Kirsch; Alexander R Guimaraes
Journal:  Radiographics       Date:  2015-07-24       Impact factor: 5.333

Review 4.  Towards a mechanistic understanding of the human subcortex.

Authors:  Birte U Forstmann; Gilles de Hollander; Leendert van Maanen; Anneke Alkemade; Max C Keuken
Journal:  Nat Rev Neurosci       Date:  2016-12-15       Impact factor: 34.870

5.  Will Artificial Intelligence Replace Radiologists?

Authors:  Curtis P Langlotz
Journal:  Radiol Artif Intell       Date:  2019-05-15

6.  Inferring pathobiology from structural MRI in schizophrenia and bipolar disorder: Modeling head motion and neuroanatomical specificity.

Authors:  Nailin Yao; Anderson M Winkler; Jennifer Barrett; Gregory A Book; Tamara Beetham; Rachel Horseman; Olivia Leach; Karen Hodgson; Emma E Knowles; Samuel Mathias; Michael C Stevens; Michal Assaf; Theo G M van Erp; Godfrey D Pearlson; David C Glahn
Journal:  Hum Brain Mapp       Date:  2017-05-08       Impact factor: 5.038

7.  Test-retest reliability of freesurfer measurements within and between sites: Effects of visual approval process.

Authors:  Zafer Iscan; Tony B Jin; Alexandria Kendrick; Bryan Szeglin; Hanzhang Lu; Madhukar Trivedi; Maurizio Fava; Patrick J McGrath; Myrna Weissman; Benji T Kurian; Phillip Adams; Sarah Weyandt; Marisa Toups; Thomas Carmody; Melvin McInnis; Cristina Cusin; Crystal Cooper; Maria A Oquendo; Ramin V Parsey; Christine DeLorenzo
Journal:  Hum Brain Mapp       Date:  2015-05-28       Impact factor: 5.038

8.  Training a neural network for Gibbs and noise removal in diffusion MRI.

Authors:  Matthew J Muckley; Benjamin Ades-Aron; Antonios Papaioannou; Gregory Lemberskiy; Eddy Solomon; Yvonne W Lui; Daniel K Sodickson; Els Fieremans; Dmitry S Novikov; Florian Knoll
Journal:  Magn Reson Med       Date:  2020-07-14       Impact factor: 4.668

9.  Radiofrequency artefacts in echoplanar imaging induced by two 1.5 T MR scanners in close proximity.

Authors:  X Li; J Cui; S P Christopasak; A Kumar; Z-G Peng
Journal:  Br J Radiol       Date:  2014-04-09       Impact factor: 3.039

Review 10.  Image reconstruction: an overview for clinicians.

Authors:  Michael S Hansen; Peter Kellman
Journal:  J Magn Reson Imaging       Date:  2014-06-25       Impact factor: 4.813

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