{"id":2286,"date":"2021-08-13T10:55:09","date_gmt":"2021-08-13T10:55:09","guid":{"rendered":"http:\/\/medgift.hevs.ch\/wordpress\/?p=2286"},"modified":"2021-08-13T10:55:28","modified_gmt":"2021-08-13T10:55:28","slug":"paper-accepted-in-frontiers-in-computer-science","status":"publish","type":"post","link":"https:\/\/medgift.hevs.ch\/wordpress\/paper-accepted-in-frontiers-in-computer-science\/","title":{"rendered":"Paper accepted in Frontiers in Computer Science"},"content":{"rendered":"\n<p>Our paper on &#8220;<a href=\"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcomp.2021.684521\/full\">Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images<\/a>&#8221; by Niccol\u00f2 Marini et al.  has been published in Frontiers in Computer Science, section Digital Public Health.<\/p>\n\n\n\n<p>This paper describes our python library called <em>Multi_Scale_Tools<\/em>. It includes four components: <\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>a pre-processing component with two methods&nbsp;to split the WSIs in patches from arbitrary magnification levels, <\/li><li>a&nbsp;CNN-based&nbsp;scale regressor&nbsp;to predict the magnification in a continuous&nbsp;range between 5-40x, <\/li><li>two multi-scale CNN architectures&nbsp;to make predictions at patch-level and <\/li><li>a multi-scale CNN architecture called HookNet to segment WSIs.<br><\/li><\/ul>\n\n\n\n<p>The code is available on GitHub: <a href=\"https:\/\/github.com\/sara-nl\/multi-scale-tools\">https:\/\/github.com\/sara-nl\/multi-scale-tools<\/a><\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im1.jpg\" alt=\"\" class=\"wp-image-2287\" width=\"195\" height=\"112\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im1.jpg 512w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im1-300x173.jpg 300w\" sizes=\"auto, (max-width: 195px) 100vw, 195px\" \/><figcaption>An example of WSI format including multiple magnification levels.<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im2.jpg\" alt=\"\" class=\"wp-image-2288\" width=\"191\" height=\"233\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im2.jpg 512w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im2-246x300.jpg 246w\" sizes=\"auto, (max-width: 191px) 100vw, 191px\" \/><figcaption>An example of tissue represented at multiple magnification level (5x, 10x, 20x, 40x).<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im3.jpg\" alt=\"\" class=\"wp-image-2289\" width=\"181\" height=\"212\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im3.jpg 671w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im3-255x300.jpg 255w\" sizes=\"auto, (max-width: 181px) 100vw, 181px\" \/><figcaption>An example of the&nbsp;<em>multi<\/em>\u2212<em>center<\/em>&nbsp;extraction method.<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im4-1024x637.jpg\" alt=\"\" class=\"wp-image-2290\" width=\"514\" height=\"320\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im4-1024x637.jpg 1024w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im4-300x187.jpg 300w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im4-768x478.jpg 768w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2021\/08\/post_im4.jpg 1072w\" sizes=\"auto, (max-width: 514px) 100vw, 514px\" \/><figcaption>Overview of a multi-scale CNN architecture.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Our paper on &#8220;Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images&#8221; by Niccol\u00f2 Marini et al. has been published in Frontiers in Computer Science, section Digital Public Health. This paper describes our python library called Multi_Scale_Tools. It includes four components: a pre-processing component with two methods&nbsp;to split the WSIs in patches from arbitrary &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/medgift.hevs.ch\/wordpress\/paper-accepted-in-frontiers-in-computer-science\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Paper accepted in Frontiers in Computer Science&#8221;<\/span><\/a><\/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-2286","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p8AP2d-AS","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2286","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=2286"}],"version-history":[{"count":3,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2286\/revisions"}],"predecessor-version":[{"id":2293,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2286\/revisions\/2293"}],"wp:attachment":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/media?parent=2286"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/categories?post=2286"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/tags?post=2286"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}