{"id":447,"date":"2021-11-03T21:31:00","date_gmt":"2021-11-03T21:31:00","guid":{"rendered":"https:\/\/mri.sbollmann.net\/?p=447"},"modified":"2021-11-03T22:26:34","modified_gmt":"2021-11-03T22:26:34","slug":"qsmxt-robust-masking-and-artifact-reduction-for-quantitative-susceptibility-mapping","status":"publish","type":"post","link":"https:\/\/mri.sbollmann.net\/index.php\/2021\/11\/03\/qsmxt-robust-masking-and-artifact-reduction-for-quantitative-susceptibility-mapping\/","title":{"rendered":"QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping"},"content":{"rendered":"\n<p>Our article &#8220;QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping&#8221; was just published in MRM \ud83d\ude42<\/p>\n\n\n\n<p>In this article we developed an automated, scalable, and robust QSM workflow that starts from Dicom images and produces segmentations of regions of interest:<\/p>\n\n\n\n<p> <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"574\" src=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image-1024x574.png\" alt=\"\" class=\"wp-image-448\" srcset=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image-1024x574.png 1024w, https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image-300x168.png 300w, https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image-768x430.png 768w, https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image.png 1174w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>The code is here: <a href=\"https:\/\/github.com\/qsmxt\/qsmxt\" data-type=\"URL\" data-id=\"https:\/\/github.com\/qsmxt\/qsmxt\" target=\"_blank\" rel=\"noreferrer noopener\">QSMxT\/QSMxT (github.com)<\/a><\/figcaption><\/figure>\n\n\n\n<p>The full paper is here (unfortunately behind a paywall): <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/mrm.29048?saml_referrer\" target=\"_blank\" rel=\"noreferrer noopener\">QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping &#8211; Stewart &#8211; &#8211; Magnetic Resonance in Medicine &#8211; Wiley Online Library<\/a><\/p>\n\n\n\n<p>The openly accessible preprint is here: <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2021.05.05.442850v1\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/www.biorxiv.org\/content\/10.1101\/2021.05.05.442850v1<\/a><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/Stewart-et-al.-2021-QSMxT-Robust-Masking-and-Artefact-Reduction-for-Q.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Embed of Stewart-et-al.-2021-QSMxT-Robust-Masking-and-Artefact-Reduction-for-Q..\"><\/object><a href=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/Stewart-et-al.-2021-QSMxT-Robust-Masking-and-Artefact-Reduction-for-Q.pdf\">Stewart-et-al.-2021-QSMxT-Robust-Masking-and-Artefact-Reduction-for-Q<\/a><a href=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/Stewart-et-al.-2021-QSMxT-Robust-Masking-and-Artefact-Reduction-for-Q.pdf\" class=\"wp-block-file__button\" download>Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Our article &#8220;QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping&#8221; was just published in MRM \ud83d\ude42 In this article we developed an automated, scalable, and robust QSM workflow that starts from Dicom images and produces segmentations of regions of interest: The full paper is here (unfortunately behind a [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":448,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25,31,14,3],"tags":[],"class_list":["post-447","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-containers","category-high-performance-computing","category-quantitative-susceptibility-mapping","category-reproducibility"],"jetpack_featured_media_url":"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/11\/image.png","_links":{"self":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/447","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/comments?post=447"}],"version-history":[{"count":3,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/447\/revisions"}],"predecessor-version":[{"id":451,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/447\/revisions\/451"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/media\/448"}],"wp:attachment":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/media?parent=447"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/categories?post=447"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/tags?post=447"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}