{"id":218,"date":"2019-07-11T08:00:09","date_gmt":"2019-07-11T07:00:09","guid":{"rendered":"https:\/\/journals.myesr.org\/eur-radiol-exp\/2019\/07\/11\/generative-models-an-innovation-in-musculoskeletal-radiology\/"},"modified":"2025-10-22T13:04:07","modified_gmt":"2025-10-22T12:04:07","slug":"generative-models-an-innovation-in-musculoskeletal-radiology","status":"publish","type":"post","link":"https:\/\/journals.myesr.org\/eur-radiol-exp\/blog\/generative-models-an-innovation-in-musculoskeletal-radiology\/","title":{"rendered":"Generative models: an innovation in musculoskeletal radiology?"},"content":{"rendered":"

\"\"New innovative technology, deep learning, is revolutionising many research and industrial fields. Growing interest in generative models inspired the authors to explore their potential in the field of magnetic resonance imaging of the spine. Tests showed that the performance of the models was generally positive and promising, albeit several limitations should be taken into account.<\/p>\n

Article<\/strong>: Generative models: an upcoming innovation in musculoskeletal radiology? A preliminary test in spine imaging<\/a><\/p>\n

Authors<\/strong>: Fabio Galbusera, Tito Bassani, Gloria Casaroli, Salvatore Gitto, Edoardo Zanchetta, Francesco Costa and Luca Maria Sconfienza<\/p>\n","protected":false},"excerpt":{"rendered":"

New innovative technology, deep learning, is revolutionising many research and industrial fields. Growing interest in generative models inspired the authors to explore their potential in the field of magnetic resonance imaging of the spine. Tests showed that the performance of the models was generally positive and promising, albeit several limitations should be taken into account. […]<\/p>\n","protected":false},"author":1,"featured_media":27,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[4],"tags":[],"class_list":["post-218","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"\nGenerative models: an innovation in musculoskeletal radiology? - European Radiology Experimental<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/journals.myesr.org\/eur-radiol-exp\/blog\/generative-models-an-innovation-in-musculoskeletal-radiology\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Generative models: an innovation in musculoskeletal radiology? - European Radiology Experimental\" \/>\n<meta property=\"og:description\" content=\"New innovative technology, deep learning, is revolutionising many research and industrial fields. Growing interest in generative models inspired the authors to explore their potential in the field of magnetic resonance imaging of the spine. Tests showed that the performance of the models was generally positive and promising, albeit several limitations should be taken into account. 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