{"id":2020,"date":"2020-10-06T12:51:14","date_gmt":"2020-10-06T12:51:14","guid":{"rendered":"http:\/\/medgift.hevs.ch\/wordpress\/?p=2020"},"modified":"2020-10-06T12:51:17","modified_gmt":"2020-10-06T12:51:17","slug":"best-paper-award-at-miccai-mlmi","status":"publish","type":"post","link":"https:\/\/medgift.hevs.ch\/wordpress\/best-paper-award-at-miccai-mlmi\/","title":{"rendered":"Best Paper Award at MICCAI MLMI"},"content":{"rendered":"\n<p>Congratulations to Marek Wodzinski and Henning M\u00fcller for receiving the <strong>best paper award<\/strong> for their work on \u201c<a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-030-59861-7_49\">Unsupervised Learning-based Nonrigid Registration of High Resolution Histology Images<\/a>\u201d at <a href=\"https:\/\/mlmi2020.web.unc.edu\/\">MICCAI-MLMI<\/a> workshop. Their deep learning-based unsupervised nonrigid registration method provides excellent registration results with fast inference time.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"717\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski-1024x717.png\" alt=\"\" class=\"wp-image-2021\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski-1024x717.png 1024w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski-300x210.png 300w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski-768x538.png 768w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski-1536x1075.png 1536w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2020\/10\/BestPaper_MLMI2020_MarekWodzinski.png 1771w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><\/figure>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Congratulations to Marek Wodzinski and Henning M\u00fcller for receiving the best paper award for their work on \u201cUnsupervised Learning-based Nonrigid Registration of High Resolution Histology Images\u201d at MICCAI-MLMI workshop. Their deep learning-based unsupervised nonrigid registration method provides excellent registration results with fast inference time.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2020","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p8AP2d-wA","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2020","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/comments?post=2020"}],"version-history":[{"count":1,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2020\/revisions"}],"predecessor-version":[{"id":2022,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2020\/revisions\/2022"}],"wp:attachment":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/media?parent=2020"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/categories?post=2020"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/tags?post=2020"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}