{"id":12210,"date":"2023-12-08T14:45:18","date_gmt":"2023-12-08T11:45:18","guid":{"rendered":"https:\/\/umram.bilkent.edu.tr\/?p=12210"},"modified":"2023-12-08T14:45:18","modified_gmt":"2023-12-08T11:45:18","slug":"mrm-article-on-eddy-current-losses","status":"publish","type":"post","link":"https:\/\/umram.bilkent.edu.tr\/index.php\/2023\/12\/08\/mrm-article-on-eddy-current-losses\/","title":{"rendered":"MRM article on Eddy Current Losses"},"content":{"rendered":"<p>Manoucher Takrimi authored an <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/mrm.29921\">article<\/a> on the eddy current losses in Magnetic Resonance in Medince. The article is visible in the offical web page. In this research, a novel method is introduced to enhance the performance of gradient array coils used in medical imaging. The approach relies on a computational electromagnetic strategy to estimate and control power losses within the cryostat, the component that houses the coil. Compared to existing methods, the new approach results in a remarkable 280% reduction in eddy power loss. The advantages are manifold: firstly, it tackles power losses within the entire cryostat body rather than just its inner surface close to the coils; secondly, it speeds up the tuning of the array coil and accurately predicts power losses or stored magnetic energies; thirdly, its accuracy matches that of commercial software; and finally, it is adaptable to array coils of any shape or even traditional coils, extending its applicability across various imaging scenarios. In simpler terms, this research provides a more efficient and versatile method to optimize the performance of medical imaging equipment, reducing energy loss and enhancing imaging quality.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Manoucher Takrimi authored an article on the eddy current losses in Magnetic Resonance in Medince. The article is visible in the offical web page. In this research, a novel method is introduced to enhance the performance of gradient array coils used in medical imaging. The approach relies on a computational electromagnetic strategy to estimate and [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":12211,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[256],"tags":[],"_links":{"self":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12210"}],"collection":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/comments?post=12210"}],"version-history":[{"count":1,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12210\/revisions"}],"predecessor-version":[{"id":12212,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/posts\/12210\/revisions\/12212"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/media\/12211"}],"wp:attachment":[{"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/media?parent=12210"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/categories?post=12210"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/umram.bilkent.edu.tr\/index.php\/wp-json\/wp\/v2\/tags?post=12210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}