{"id":30727,"date":"2024-10-11T17:56:41","date_gmt":"2024-10-11T12:26:41","guid":{"rendered":"https:\/\/www.nextias.com\/ca\/?p=30727"},"modified":"2024-10-11T17:56:43","modified_gmt":"2024-10-11T12:26:43","slug":"synthetic-medical-images","status":"publish","type":"post","link":"https:\/\/www.nextias.com\/ca\/current-affairs\/11-10-2024\/synthetic-medical-images","title":{"rendered":"Synthetic Medical Images"},"content":{"rendered":"\n<p><strong>Syllabus :GS 3\/Science and Tech&nbsp;<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>In News<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The rise of AI-generated synthetic medical images has been observed.\u00a0<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>About Synthetic medical images<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>They are generated by AI or computer algorithms without being captured by traditional imaging devices such as MRI, CT scans, or X-rays.\u00a0<\/li>\n\n\n\n<li>These images are entirely constructed using mathematical models or AI techniques like generative adversarial networks (GANs), diffusion models, and autoencoders.\n<ul class=\"wp-block-list\">\n<li><strong>GANs <\/strong>involve a generator creating images and a discriminator assessing their authenticity, improving through competition.<\/li>\n\n\n\n<li><strong>VAEs <\/strong>compress images into latent spaces and reconstruct them.<\/li>\n\n\n\n<li><strong>Diffusion models <\/strong>transform random noise into realistic images step-by-step.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Advantages:<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>It allows intra- and inter-modality translation, helping generate missing scans from available data.\n<ul class=\"wp-block-list\">\n<li><strong>Intramodality Translation<\/strong>: Generates synthetic images within the same imaging modality (e.g., reconstructing MRI scans).<\/li>\n\n\n\n<li><strong>Inter-Modality Translation:<\/strong> Creates synthetic images by converting data between different modalities (e.g., generating CT scans from MRI data).<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>It is generated without real patient data, reducing privacy concerns and facilitating data sharing.<\/li>\n\n\n\n<li>It addresses the time and expense associated with collecting real medical images.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Challenges:<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Risk of creating deepfakes that could impersonate patients, leading to incorrect diagnoses and fraudulent claims.<\/li>\n\n\n\n<li>Synthetic images may not capture the subtle nuances of real-world medical data, risking the accuracy of AI diagnoses.<\/li>\n\n\n\n<li>Over-reliance on synthetic images could blur the lines between reality and fabrication, potentially leading to diagnostic models that misalign with actual patient cases.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Solutions:<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>While synthetic medical images offer innovation opportunities, reliance on them poses regulatory and ethical challenges. Human oversight is crucial to maintain the integrity of healthcare decisions.<\/li>\n\n\n\n<li>Collaboration between clinicians and AI engineers is essential to enhance the quality of synthetic images and ensure they reflect real-world medical complexities.<\/li>\n\n\n\n<li>The use of synthetic images should be approached with optimism and caution to maximize benefits without undermining real-world healthcare understanding.<\/li>\n<\/ul>\n\n\n\n<p><strong>Source:TH<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The rise of AI-generated synthetic medical images has been observed.\u00a0<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[],"class_list":["post-30727","post","type-post","status-publish","format-standard","hentry","category-current-affairs"],"acf":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/30727","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/comments?post=30727"}],"version-history":[{"count":1,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/30727\/revisions"}],"predecessor-version":[{"id":30728,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/posts\/30727\/revisions\/30728"}],"wp:attachment":[{"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/media?parent=30727"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/categories?post=30727"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.nextias.com\/ca\/wp-json\/wp\/v2\/tags?post=30727"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}