{"id":4299,"date":"2021-07-23T19:35:52","date_gmt":"2021-07-23T19:35:52","guid":{"rendered":"https:\/\/www.saince.com\/?p=4299"},"modified":"2023-04-28T09:41:45","modified_gmt":"2023-04-28T13:41:45","slug":"researchers-automate-brain-mri-image-labelling-more-than-100000-exams-labelled-in-under-30-minutes","status":"publish","type":"post","link":"https:\/\/www.saince.com\/blog\/researchers-automate-brain-mri-image-labelling-more-than-100000-exams-labelled-in-under-30-minutes\/","title":{"rendered":"Researchers automate brain MRI image labelling, more than 100,000 exams labelled in under 30 minutes"},"content":{"rendered":"<p dir=\"ltr\"><span style=\"font-weight: 400\">Researchers from the School of Biomedical Engineering &amp; Imaging Sciences at King&#8217;s College London have automated brain MRI image labeling, needed to teach machine learning image recognition models, by deriving important labels from radiology reports and accurately assigning them to the corresponding MRI examinations. They can now label more than 100,00 MRI examinations in less than half an hour.<\/span><\/p>\n<p dir=\"ltr\"><span style=\"font-weight: 400\">The further challenges for them will be to perform the deep learning image recognition tasks to ensure the developed models can still perform accurately across different hospitals using different scanners.<\/span><\/p>\n<p dir=\"ltr\">Read the full article:\u00a0<a href=\"https:\/\/www.eurekalert.org\/pub_releases\/2021-07\/kcl-rab072221.php\" class=\"broken_link\">https:\/\/www.eurekalert.org\/pub_releases\/2021-07\/kcl-rab072221.php<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers from the School of Biomedical Engineering &amp; Imaging Sciences at King&#8217;s College London have automated brain MRI image labeling, needed to teach machine learning image recognition models, by deriving important labels from radiology reports and accurately assigning them to the corresponding MRI examinations. They can now label more than 100,00 MRI examinations in less [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[],"class_list":["post-4299","post","type-post","status-publish","format-standard","hentry","category-radiology-updates"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.13 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Researchers automate brain MRI image labelling, more than 100,000 exams labelled in under 30 minutes -<\/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:\/\/www.saince.com\/blog\/researchers-automate-brain-mri-image-labelling-more-than-100000-exams-labelled-in-under-30-minutes\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Researchers automate brain MRI image labelling, more than 100,000 exams labelled in under 30 minutes -\" \/>\n<meta property=\"og:description\" content=\"Researchers from the School of Biomedical Engineering &amp; Imaging Sciences at King&#8217;s College London have automated brain MRI image labeling, needed to teach machine learning image recognition models, by deriving important labels from radiology reports and accurately assigning them to the corresponding MRI examinations. They can now label more than 100,00 MRI examinations in less [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.saince.com\/blog\/researchers-automate-brain-mri-image-labelling-more-than-100000-exams-labelled-in-under-30-minutes\/\" \/>\n<meta property=\"article:published_time\" content=\"2021-07-23T19:35:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-04-28T13:41:45+00:00\" \/>\n<meta name=\"author\" content=\"Raghu Vir\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Raghu Vir\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" 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