{"id":388,"date":"2021-07-20T00:07:00","date_gmt":"2021-07-20T00:07:00","guid":{"rendered":"https:\/\/mri.sbollmann.net\/?p=388"},"modified":"2021-08-05T00:26:58","modified_gmt":"2021-08-05T00:26:58","slug":"nextqsm-preprint","status":"publish","type":"post","link":"https:\/\/mri.sbollmann.net\/index.php\/2021\/07\/20\/nextqsm-preprint\/","title":{"rendered":"NeXtQSM preprint"},"content":{"rendered":"\n<p>Our new preprint is online. NeXtQSM is a deep learning pipeline for data-consistent quantitative susceptibility mapping trained with simulated data build by our <a rel=\"noreferrer noopener\" href=\"https:\/\/www.uq.edu.au\/news\/article\/2018\/09\/arc-training-centre-deliver-innovation-biomedical-imaging\" target=\"_blank\">CIBIT <\/a>MPhil student Francesco Cognolato: <a href=\"https:\/\/arxiv.org\/abs\/2107.07752\">[2107.07752] NeXtQSM &#8212; A complete deep learning pipeline for data-consistent quantitative susceptibility mapping trained with hybrid data (arxiv.org)<\/a><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"541\" height=\"393\" src=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/image-7.png\" alt=\"\" class=\"wp-image-390\" srcset=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/image-7.png 541w, https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/image-7-300x218.png 300w\" sizes=\"auto, (max-width: 541px) 100vw, 541px\" \/><figcaption>The NeXtQSM pipeline aims to provide a robust Deep Learning QSM solution incorporating background field correction and dipole inversion.<\/figcaption><\/figure>\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\/Cognolato-et-al.-2021-NeXtQSM-A-complete-deep-learning-pipeline-for-d.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Embed of Cognolato-et-al.-2021-NeXtQSM-A-complete-deep-learning-pipeline-for-d..\"><\/object><a href=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/Cognolato-et-al.-2021-NeXtQSM-A-complete-deep-learning-pipeline-for-d.pdf\">Cognolato-et-al.-2021-NeXtQSM-A-complete-deep-learning-pipeline-for-d<\/a><a href=\"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/Cognolato-et-al.-2021-NeXtQSM-A-complete-deep-learning-pipeline-for-d.pdf\" class=\"wp-block-file__button\" download>Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Our new preprint is online. NeXtQSM is a deep learning pipeline for data-consistent quantitative susceptibility mapping trained with simulated data build by our CIBIT MPhil student Francesco Cognolato: [2107.07752] NeXtQSM &#8212; A complete deep learning pipeline for data-consistent quantitative susceptibility mapping trained with hybrid data (arxiv.org)<\/p>\n","protected":false},"author":1,"featured_media":390,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6,22,13,4,14,5],"tags":[],"class_list":["post-388","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-deep-learning","category-deepqsm","category-publications","category-python","category-quantitative-susceptibility-mapping","category-tensorflow"],"jetpack_featured_media_url":"https:\/\/mri.sbollmann.net\/wp-content\/uploads\/2021\/08\/image-7.png","_links":{"self":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/388","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=388"}],"version-history":[{"count":2,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/388\/revisions"}],"predecessor-version":[{"id":400,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/posts\/388\/revisions\/400"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/media\/390"}],"wp:attachment":[{"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/media?parent=388"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/categories?post=388"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mri.sbollmann.net\/index.php\/wp-json\/wp\/v2\/tags?post=388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}