{"id":715012,"date":"2026-08-17T09:11:54","date_gmt":"2026-08-17T13:11:54","guid":{"rendered":"https:\/\/www.rochester.edu\/newscenter\/?p=715012"},"modified":"2026-08-17T09:20:30","modified_gmt":"2026-08-17T13:20:30","slug":"lidar-systems-cancer-imaging-time-gating-technology-715012","status":"publish","type":"post","link":"https:\/\/www.rochester.edu\/newscenter\/lidar-systems-cancer-imaging-time-gating-technology-715012\/","title":{"rendered":"New imaging technique sees through deep tissue, dense fog, and other obstacles"},"content":{"rendered":"<h2>The AI-enhanced technology could improve noninvasive cancer imaging, lower costs, and make LiDAR systems more effective in poor visibility.<\/h2>\n","protected":false},"excerpt":{"rendered":"<p>The AI-enhanced technology could improve noninvasive cancer imaging, lower costs, and make LiDAR systems more effective in poor visibility.<\/p>\n","protected":false},"author":1242,"featured_media":715082,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[24292,18632,18652,18572,43052,19062],"class_list":["post-715012","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sci-tech","tag-artificial-intelligence","tag-hajim-school-of-engineering-and-applied-sciences","tag-institute-of-optics","tag-research-finding","tag-research-impact-accelerates","tag-robert-boyd"],"acf":{"external":"","hide_featured_image":false,"related":"show_related","style":"","content_modules":[{"acf_fc_layout":"text","anchor":"","css_class":"","title":"","content":"<h3>Why this matters:<\/h3>\r\n<ul>\r\n \t<li>The new imaging system <strong>produces clearer images<\/strong> taken through deep tissue, dense fog, or other environments where existing imaging systems struggle.<\/li>\r\n \t<li>Unlike standard near-infrared systems, it <strong>uses low-cost silicon-based detectors<\/strong>.<\/li>\r\n \t<li>The system leverages an ultrafast time-gating technique that <strong>uses light to control light<\/strong>.<\/li>\r\n \t<li>Machine learning dramatically <strong>expands the system\u2019s field of view<\/strong>.<\/li>\r\n \t<li>The method could help <strong>improve cancer diagnosis and imaging systems<\/strong> used in self-driving cars.<\/li>\r\n<\/ul>","background_color":"#f4f4f4","width":"width-medium"},{"acf_fc_layout":"text","anchor":"","css_class":"","title":"","content":"From helping doctors detect cancer to guiding self-driving cars through traffic, many modern imaging systems rely on near-infrared light, producing a crisp picture when visible light would scatter and yield a blurry picture. But near-infrared systems struggle when light passes through materials like deep tissue or dense fog, succumbing to the same scattering effect where photons deviate from their path. Existing near-infrared imaging systems also rely on specialized detectors made from expensive materials, limiting their affordability and widespread use.\r\n\r\n<a href=\"https:\/\/www.rochester.edu\/\">University of Rochester<\/a> researchers have now developed a lower-cost imaging system that overcomes both challenges. Using inexpensive silicon-based detectors, the system quickly converts near-infrared light to visible light while producing clearer images through these difficult environments. The technology, outlined in a recent <a href=\"https:\/\/doi.org\/10.1038\/s41467-026-71039-1\"><em>Nature Communications<\/em> paper<\/a>, uses a technique called time-gating that the laboratory of <a href=\"https:\/\/managedlists.ur.rochester.edu\/trk\/click?ref=zul360ron_7-626ex31f53bx0563&amp;\">Robert Boyd<\/a>, the William F. Krupke Distinguished Professor in Optics, has spent more than a decade refining.\r\n<h3><strong>Light controlling light<\/strong><\/h3>\r\n\u201cTime-gating essentially works like the shutter in a camera,\u201d says Yang Xu \u201926 (PhD), the lead author of the paper. \u201cIn a traditional camera, the shutter is mechanical\u2014when it opens, light comes in, and when it closes, light is rejected. In this case, we use light to control light.\u201d\r\n\r\nUltrafast bursts of light act as the shutter, letting infrared particles through the gate for only about a picosecond. For reference, a picosecond is the time it takes for light to travel a distance of the size of a period at the end of a sentence.\r\n\r\nThe gate is a thin film made of indium tin oxide, and any near-infrared photons that hit it are converted to visible light for a clear picture in real-time.\r\n\r\nThe approach could improve image quality for applications ranging from biomedical imaging for cancer detection to LiDAR (light detection and ranging) systems used in autonomous vehicles, where fog and other light-scattering conditions can limit performance.\r\n\r\n[caption id=\"attachment_715092\" align=\"aligncenter\" width=\"2000\"]<img class=\"size-full wp-image-715092\" src=\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2026\/08\/2026-08-03_Boyd_lab_1071.jpg\" alt=\"Long Nguyen, Yang Xu, and Robert Boyd in Boyd's lab. \" width=\"2000\" height=\"1200\" \/> <strong>PUT TO THE TEST<\/strong>: The lab of Robert Boyd, right, the William F. Krupke Distinguished Professor in Optics, has spent more than a decade refining the new imaging system, with contributions from PhD students including Yang Xu \u201926 (PhD), center, and physics doctoral student Long Nguyen, left. (URochester photo \/ J. Adam Fenster)[\/caption]\r\n<h3><strong>AI broadens the view<\/strong><\/h3>\r\nWhile the time-gating technique produced remarkably clear images, Boyd, Xu, and their colleagues found a way to make the system even more useful. Working with researchers at UCLA, they combined their approach with machine learning to dramatically expand the system\u2019s field of view. Their findings appear in a <a href=\"https:\/\/doi.org\/10.1038\/s41377-026-02375-6\">recent paper<\/a> published in <em>Light: Science and Applications<\/em>.\r\n\r\n\u201cBefore applying artificial intelligence, we could see only a limited field of view,\u201d says Xu. \u201cBy adding our collaborators\u2019 methods, we can essentially reconstruct a much larger target area, enlarging the field of view our ultrafast time-gating technique can capture.\u201d\r\n\r\nOther University of Rochester collaborators involved in the studies include optics alumna Saumya Choudhary \u201923 (PhD) and physics doctoral student Long Nguyen. The US Office of Naval Research, the National Science Foundation, and the Department of Energy provided funding for the research.","background_color":"#ffffff","width":"width-medium"}]},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>New imaging technique sees through deep tissue, dense fog, and other obstacles<\/title>\n<meta name=\"description\" content=\"The AI-enhanced technology could improve noninvasive cancer imaging, lower costs, and make LiDAR systems more effective in poor visibility.\" \/>\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.rochester.edu\/newscenter\/lidar-systems-cancer-imaging-time-gating-technology-715012\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New imaging technique sees through deep tissue, dense fog, and other obstacles\" \/>\n<meta property=\"og:description\" content=\"The AI-enhanced technology could improve noninvasive cancer imaging, lower costs, and make LiDAR systems more effective in poor visibility.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.rochester.edu\/newscenter\/lidar-systems-cancer-imaging-time-gating-technology-715012\/\" \/>\n<meta property=\"og:site_name\" content=\"News Center\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-17T13:11:54+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-17T13:20:30+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2026\/08\/fea-2026-08-03-boyd-lab-time-gate-1200x630.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Luke Auburn\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Luke Auburn\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/lidar-systems-cancer-imaging-time-gating-technology-715012\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/lidar-systems-cancer-imaging-time-gating-technology-715012\\\/\"},\"author\":{\"name\":\"Luke Auburn\",\"@id\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/#\\\/schema\\\/person\\\/e928dc2863b53a89ece6d40c7992a4e1\"},\"headline\":\"New imaging technique sees through deep tissue, dense fog, and other obstacles\",\"datePublished\":\"2026-08-17T13:11:54+00:00\",\"dateModified\":\"2026-08-17T13:20:30+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/lidar-systems-cancer-imaging-time-gating-technology-715012\\\/\"},\"wordCount\":31,\"image\":{\"@id\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/lidar-systems-cancer-imaging-time-gating-technology-715012\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.rochester.edu\\\/newscenter\\\/wp-content\\\/uploads\\\/2026\\\/08\\\/fea-2026-08-03-boyd-lab-time-gate.jpg\",\"keywords\":[\"artificial intelligence\",\"Hajim School of Engineering and Applied Sciences\",\"Institute of Optics\",\"research finding\",\"Research Impact Accelerates\",\"Robert Boyd\"],\"articleSection\":[\"Science &amp; 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