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<meta name="DC.Title" content="Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network" />
<meta name="DC.Identifier" content="10.3174/ajnr.A6436" />
<meta name="DC.Date" content="2020-03-01" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Motion artifacts are a frequent source of image degradation in the clinical application of MR imaging (MRI). Here we implement and validate an MRI motion-artifact correction method using a multiscale fully convolutional neural network.

MATERIALS AND METHODS: The network was trained to identify motion artifacts in axial T2-weighted spin-echo images of the brain. Using an extensive data augmentation scheme and a motion artifact simulation pipeline, we created a synthetic training dataset of 93,600 images based on only 16 artifact-free clinical MRI cases. A blinded reader study using a unique test dataset of 28 additional clinical MRI cases with real patient motion was conducted to evaluate the performance of the network.

RESULTS: Application of the network resulted in notably improved image quality without the loss of morphologic information. For synthetic test data, the average reduction in mean squared error was 41.84%. The blinded reader study on the real-world test data resulted in significant reduction in mean artifact scores across all cases ( P  &lt; .03).

CONCLUSIONS: Retrospective correction of motion artifacts using a multiscale fully convolutional network is promising and may mitigate the substantial motion-related problems in the clinical MRI workflow.

FCN
:   fully convolutional neural network
MSE
:   mean squared error
SSIM
:   structural similarity index" />
<meta name="DC.Contributor" content="K. Sommer" />
<meta name="DC.Contributor" content="A. Saalbach" />
<meta name="DC.Contributor" content="T. Brosch" />
<meta name="DC.Contributor" content="C. Hall" />
<meta name="DC.Contributor" content="N.M. Cross" />
<meta name="DC.Contributor" content="J.B. Andre" />
<meta name="article:published_time" content="2020-03-01" />
<meta name="article:section" content="Adult Brain" />
<meta name="citation_title" content="Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Motion artifacts are a frequent source of image degradation in the clinical application of MR imaging (MRI). Here we implement and validate an MRI motion-artifact correction method using a multiscale fully convolutional neural network.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;The network was trained to identify motion artifacts in axial T2-weighted spin-echo images of the brain. Using an extensive data augmentation scheme and a motion artifact simulation pipeline, we created a synthetic training dataset of 93,600 images based on only 16 artifact-free clinical MRI cases. A blinded reader study using a unique test dataset of 28 additional clinical MRI cases with real patient motion was conducted to evaluate the performance of the network.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Application of the network resulted in notably improved image quality without the loss of morphologic information. For synthetic test data, the average reduction in mean squared error was 41.84%. The blinded reader study on the real-world test data resulted in significant reduction in mean artifact scores across all cases (&lt;i&gt;P &lt;/i&gt;&amp;lt; .03).&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Retrospective correction of motion artifacts using a multiscale fully convolutional network is promising and may mitigate the substantial motion-related problems in the clinical MRI workflow.&lt;/p&gt;" />
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<meta name="twitter:title" content="Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Motion artifacts are a frequent source of image degradation in the clinical application of MR imaging (MRI). Here we implement and validate an MRI motion-artifact correction method using a multiscale fully convolutional neural network.

MATERIALS AND METHODS: The network was trained to identify motion artifacts in axial T2-weighted spin-echo images of the brain. Using an extensive data augmentation scheme and a motion artifact simulation pipeline, we created a synthetic training dataset of 93,600 images based on only 16 artifact-free clinical MRI cases. A blinded reader study using a unique test dataset of 28 additional clinical MRI cases with real patient motion was conducted to evaluate the performance of the network.

RESULTS: Application of the network resulted in notably improved image quality without the loss of morphologic information. For synthetic test data, the average reduction in mean squared error was 41.84%. The blinded reader study on the real-world test data resulted in significant reduction in mean artifact scores across all cases ( P  &lt; .03).

CONCLUSIONS: Retrospective correction of motion artifacts using a multiscale fully convolutional network is promising and may mitigate the substantial motion-related problems in the clinical MRI workflow.

FCN
:   fully convolutional neural network
MSE
:   mean squared error
SSIM
:   structural similarity index" />
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<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: Motion artifacts are a frequent source of image degradation in the clinical application of MR imaging (MRI). Here we implement and validate an MRI motion-artifact correction method using a multiscale fully convolutional neural network.

MATERIALS AND METHODS: The network was trained to identify motion artifacts in axial T2-weighted spin-echo images of the brain. Using an extensive data augmentation scheme and a motion artifact simulation pipeline, we created a synthetic training dataset of 93,600 images based on only 16 artifact-free clinical MRI cases. A blinded reader study using a unique test dataset of 28 additional clinical MRI cases with real patient motion was conducted to evaluate the performance of the network.

RESULTS: Application of the network resulted in notably improved image quality without the loss of morphologic information. For synthetic test data, the average reduction in mean squared error was 41.84%. The blinded reader study on the real-world test data resulted in significant reduction in mean artifact scores across all cases ( P  &lt; .03).

CONCLUSIONS: Retrospective correction of motion artifacts using a multiscale fully convolutional network is promising and may mitigate the substantial motion-related problems in the clinical MRI workflow.

FCN
:   fully convolutional neural network
MSE
:   mean squared error
SSIM
:   structural similarity index" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node73872--5" data-node-nid="73872" id="top-node-73872--6202470693" data-pisa="ajnr;41/3/416" data-pisa-master="ajnr;ajnr.A6436" data-apath="/ajnr/41/3/416.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-article-title-complete clearfix has-author-tooltip highwire-citation-highwire-article-top-a">
  
  
      <div class="highwire-cite-overline"><span  class="highwire-cite-metadata-article-type highwire-cite-metadata">Research Article</span><span class="separator-pipe"></span><span  class="highwire-cite-metadata-art-cat highwire-cite-metadata"><span class="wrapper">Adult Brain</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">K. Sommer</span>, <span class="highwire-citation-author" data-delta="1">A. Saalbach</span>, <span class="highwire-citation-author" data-delta="2">T. Brosch</span>, <span class="highwire-citation-author" data-delta="3">C. Hall</span>, <span class="highwire-citation-author" data-delta="4">N.M. Cross</span> and <span class="highwire-citation-author" data-delta="5">J.B. Andre</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">March 2020,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">41 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(3) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">416-423; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A6436 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-73872--6202470693" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">K. Sommer </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From Philips Research, (K.S., A.S., T.B.) Hamburg, Germany</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=K.%2BSommer%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Sommer%20K&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AK.%2BSommer%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-5904-7514" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for K. Sommer</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">A. Saalbach </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From Philips Research, (K.S., A.S., T.B.) Hamburg, Germany</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=A.%2BSaalbach%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Saalbach%20A&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AA.%2BSaalbach%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-1535-2100" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. Saalbach</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">T. Brosch </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From Philips Research, (K.S., A.S., T.B.) Hamburg, Germany</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=T.%2BBrosch%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Brosch%20T&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AT.%2BBrosch%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-3543-1930" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for T. Brosch</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">C. Hall </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Radiology Solutions (C.H.), Philips, Seattle, Washington</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=C.%2BHall%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Hall%20C&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AC.%2BHall%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-9577-6888" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for C. Hall</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">N.M. Cross </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Radiology (N.M.C., J.B.A.), University of Washington, Seattle, Washington.</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=N.M.%2BCross%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Cross%20N&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AN.M.%2BCross%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-5040-4340" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for N.M. Cross</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">J.B. Andre </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Radiology (N.M.C., J.B.A.), University of Washington, Seattle, Washington.</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.B.%2BAndre%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Andre%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AJ.B.%2BAndre%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-0896-183X" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J.B. 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    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">K.</span> <span class="nlm-surname">Sommer</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Saalbach</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">T.</span> <span class="nlm-surname">Brosch</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">C.</span> <span class="nlm-surname">Hall</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">N.M.</span> <span class="nlm-surname">Cross</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">J.B.</span> <span class="nlm-surname">Andre</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Mar 2020, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">41 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(3) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">416-423; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A6436 </span></div>
  
  
  
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