{"id":1133,"date":"2024-01-10T14:29:02","date_gmt":"2024-01-10T13:29:02","guid":{"rendered":"https:\/\/www.hsu-hh.de\/statistik\/?post_type=tribe_events&#038;p=1133"},"modified":"2024-01-24T10:42:27","modified_gmt":"2024-01-24T09:42:27","slug":"yannis-schumann-hsu","status":"publish","type":"tribe_events","link":"https:\/\/www.hsu-hh.de\/statistik\/event\/yannis-schumann-hsu","title":{"rendered":"Yannis Schumann (HSU)"},"content":{"rendered":"<h1>Molecular Classification of Ependymomas Using Histological Images and Deep Neural Networks <\/h1>\n<p>Ependymomas represent a rare type of tumor in the central nervous system that affects both<br \/>\nchildren and adults. For these tumors, strong differences in quality of diagnostic healthcare exist<br \/>\nbetween medical centers in Germany. Thus, molecular analyses (e.g., DNA methylation profiling)<br \/>\nare increasingly used to validate the pathological diagnoses from traditional examination of<br \/>\nhistological images. However, these molecular analyses are expensive and are not readily available<br \/>\nworldwide. Thus, we employ deep neural networks to predict the molecular properties of<br \/>\nependymomas from large-scale, histological image data and aim to support neuropathologists in the<br \/>\nintegrated diagnosis of this challenging tumor entity.<\/p>\n<p>Key findings:<\/p>\n<ul>\n<li>Using histological image data, the molecular (DNA methylation) type can be accurately predicted for ependymomas from all major anatomical compartments<\/li>\n<li>Color normalization, color augmentation and the choice of multiple-instance pooling operation are major factors that determine domain-adaptation to other imaging facilities<\/li>\n<li>Simple code optimization steps facilitate highly efficient data processing on the supercomputer HSUper<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Molecular Classification of Ependymomas Using Histological Images and Deep Neural Networks Ependymomas represent a rare type of tumor in the central nervous system that affects both children and adults. For [&hellip;]<\/p>\n","protected":false},"author":102,"featured_media":0,"template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[],"class_list":["post-1133","tribe_events","type-tribe_events","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tribe_events\/1133","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/users\/102"}],"version-history":[{"count":3,"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tribe_events\/1133\/revisions"}],"predecessor-version":[{"id":1160,"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tribe_events\/1133\/revisions\/1160"}],"wp:attachment":[{"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/media?parent=1133"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tags?post=1133"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.hsu-hh.de\/statistik\/wp-json\/wp\/v2\/tribe_events_cat?post=1133"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}