{"id":7826,"date":"2021-03-24T13:43:46","date_gmt":"2021-03-24T13:43:46","guid":{"rendered":"https:\/\/vicorob.udg.edu\/?p=7826"},"modified":"2021-03-24T13:43:46","modified_gmt":"2021-03-24T13:43:46","slug":"vicorob-team-has-obtained-the-third-position-at-the-digital-breast-tomosynthesis-lesion-detection-grant-challenge","status":"publish","type":"post","link":"https:\/\/vicorob.udg.edu\/ca\/vicorob-team-has-obtained-the-third-position-at-the-digital-breast-tomosynthesis-lesion-detection-grant-challenge\/","title":{"rendered":"VICOROB team has obtained the third position at the Digital Breast Tomosynthesis Lesion Detection Grant Challenge"},"content":{"rendered":"<p>The <strong>Medical Image Analysis Lab<\/strong> participated this last January in the <strong>Digital Breast Tomosynthesis Lesion detection Challenged<\/strong>, jointly organized by the <a href=\"https:\/\/spie.org\/\" target=\"_blank\" rel=\"noopener\">International Society for Optics and Photonics (SPIE),<\/a> <a href=\"https:\/\/www.aapm.org\/\" target=\"_blank\" rel=\"noopener\">the American Association of Physicists in Medicine (AAPM)<\/a>, <a href=\"https:\/\/www.cancer.gov\/\" target=\"_blank\" rel=\"noopener\">the National Cancer Institute (NCI)<\/a> and the <em>Duke Center for Artificial Intelligence in Radiology (DAIR)<\/em>.<\/p>\n<p>&nbsp;<\/p>\n<p>The team achieved a well deserved third place in the challenge, after the teams from <em>New York University<\/em> (USA) and<em> IBM Haifa Research Lab<\/em> (Israel), and had the chance to present their lesion detection approach at the SPIE Medical Imaging Conference, usually celebrated in the USA but this time held online due to COVID-19 pandemic.<\/p>\n<p>&nbsp;<\/p>\n<p>You can check the presentation at <a href=\"https:\/\/spie.org\/conferences-and-exhibitions\/medical-imaging\/digital-detection-challenge\" target=\"_blank\" rel=\"noopener\">https:\/\/spie.org\/conferences-and-exhibitions\/medical-imaging\/digital-detection-challenge<\/a> and you can find the results of challenge at <a href=\"http:\/\/spie-aapm-nci-dair.westus2.cloudapp.azure.com\/competitions\/4#results\" target=\"_blank\" rel=\"noopener\">http:\/\/spie-aapm-nci-dair.westus2.cloudapp.azure.com\/competitions\/4#results<\/a><\/p>\n<p>The research presented in the challenge is a result of the ongoing research in the ICEBERG research project on Image Computing for Enhancing Breast Cancer Radiomics, leaded by Robert Mart\u00ed in VICOROB and with the collaboration of the Universidad Complutense de Madrid, Parc Taul\u00ed, Hospital Josep Trueta and Cl\u00ednica Girona.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Medical Image Analysis Lab participated this last January in the Digital Breast Tomosynthesis Lesion detection Challenged, jointly organized by the International Society for Optics and Photonics (SPIE), the American Association of Physicists in Medicine (AAPM), the National Cancer Institute (NCI) and the Duke Center for Artificial Intelligence in Radiology (DAIR). &nbsp; The team achieved&hellip;&nbsp;<a href=\"https:\/\/vicorob.udg.edu\/ca\/vicorob-team-has-obtained-the-third-position-at-the-digital-breast-tomosynthesis-lesion-detection-grant-challenge\/\" rel=\"bookmark\"><span class=\"screen-reader-text\">VICOROB team has obtained the third position at the Digital Breast Tomosynthesis Lesion Detection Grant Challenge<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":7830,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"categories":[75,12],"tags":[],"class_list":["post-7826","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-medical-imaging-lab","category-news"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.9 - 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