{"id":347,"date":"2025-08-27T11:10:42","date_gmt":"2025-08-27T09:10:42","guid":{"rendered":"https:\/\/www.msnobile.eu\/?page_id=347"},"modified":"2025-08-27T11:12:41","modified_gmt":"2025-08-27T09:12:41","slug":"medical-imaging","status":"publish","type":"page","link":"https:\/\/www.msnobile.eu\/index.php\/medical-imaging\/","title":{"rendered":"Medical Imaging"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">We have many years of experience with <strong>Deep Learning (DL) applied to Medical Imaging,<\/strong> in a very broad sense. In particular, we recently focused our efforts in the field of <strong>Digital Pathology<\/strong> and <strong>Cardiac Magnetic Resonance<\/strong>. We also develop tools for MIA-related algorithms and tasks, like <strong>feature extraction<\/strong>, <strong>pre-processing<\/strong> and <strong>post-hoc explainability<\/strong>. I have direct experience with MRI, CT scans, and X-rays.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Some projects:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0893395224001881\">NUTSHELL<\/a>: AI for Digital Pathology applied to the identification of tumors in thyroid WSI<\/li>\n\n\n\n<li><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0925231219309245\">DL for the segmentation of prostate<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/andreatangherloni\/MedGA\">MedGA<\/a>: evolutionary image enhancement<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/andreatangherloni\/HaraliCU\">HaraliCU<\/a>: GPU-powered Haralick features extraction<\/li>\n\n\n\n<li><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417422023144\">DSUUL<\/a>: MALDI-MSI unsupervised analysis<\/li>\n\n\n\n<li><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0169260722007027\">Scar detection and segmentation in Cardiac Magnetic Resonance<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/journals.plos.org\/plosone\/article?id=10.1371\/journal.pone.0285422\">Characterization of STIM1 tubular aggregate myopathy from Muscular Magnetic Resonance<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>We have many years of experience with Deep Learning (DL) applied to Medical Imaging, in a very broad sense. In particular, we recently focused our efforts in the field of Digital Pathology and Cardiac Magnetic Resonance. We also develop tools for MIA-related algorithms and tasks, like feature extraction, pre-processing and post-hoc explainability. I have direct&nbsp;&hellip;<\/p>\n","protected":false},"author":1,"featured_media":349,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-347","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/347","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/comments?post=347"}],"version-history":[{"count":3,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/347\/revisions"}],"predecessor-version":[{"id":351,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/pages\/347\/revisions\/351"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/media\/349"}],"wp:attachment":[{"href":"https:\/\/www.msnobile.eu\/index.php\/wp-json\/wp\/v2\/media?parent=347"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}