{"id":553970,"date":"2021-06-28T16:42:52","date_gmt":"2021-06-28T20:42:52","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ece\/event\/dissertation-defense-jaewook-shin\/"},"modified":"2021-06-28T16:42:52","modified_gmt":"2021-06-28T20:42:52","slug":"dissertation-defense-jaewook-shin","status":"publish","type":"tribe_events","link":"https:\/\/engineering.jhu.edu\/ece\/event\/dissertation-defense-jaewook-shin\/","title":{"rendered":"Dissertation Defense: Jaewook Shin"},"content":{"rendered":"<p>Title: Minimally-Invasive Lens-free Computational Microendoscopy<br \/>Abstract: Ultra-miniaturized imaging tools are vital for numerous biomedical applications. Such minimally invasive imagers allow for navigation into hard-toreach regions and, for example, observation of deep brain activity in freely moving animals with minimal ancillary tissue damage. Conventional solutions employ distal microlenses. However, as lenses become smaller and thus less invasive they develop greater optical aberrations, requiring bulkier compound designs with restricted field-of-view. In addition, tools capable of 3-dimensional volumetric imaging require components that physically scan the focal plane, which ultimately increases the distal complexity, footprint, and weight. Simply put, minimally-invasive imaging systems have limited information capacity due to their given cross-sectional area.<br \/>This thesis explores minimally-invasive lens-free microendoscopy enabled by a successful integration of signal processing, optical hardware, and image reconstruction algorithms. Several computational microendoscopy architectures that simultaneously achieve miniaturization and high information content are presented. Leveraging the computational imaging techniques enables color-resolved imaging with wide field-of-view, and 3-dimensional volumetric reconstruction of an unknown scene using a single camera frame without any actuated parts, further advancing the performance versus invasiveness of microendoscopy.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Title: Minimally-Invasive Lens-free Computational MicroendoscopyAbstract: Ultra-miniaturized imaging tools are vital for numerous biomedical applications. Such minimally invasive imagers allow for navigation into hard-toreach regions and, for example, observation of deep&hellip;<\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[],"class_list":["post-553970","tribe_events","type-tribe_events","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Dissertation Defense: Jaewook Shin - Department of Electrical and Computer Engineering<\/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:\/\/engineering.jhu.edu\/ece\/event\/dissertation-defense-jaewook-shin\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Dissertation Defense: Jaewook Shin - Department of Electrical and Computer Engineering\" \/>\n<meta property=\"og:description\" content=\"Title: Minimally-Invasive Lens-free Computational MicroendoscopyAbstract: Ultra-miniaturized imaging tools are vital for numerous biomedical applications. Such minimally invasive imagers allow for navigation into hard-toreach regions and, for example, observation of deep&hellip;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/engineering.jhu.edu\/ece\/event\/dissertation-defense-jaewook-shin\/\" \/>\n<meta property=\"og:site_name\" content=\"Department of Electrical and Computer Engineering\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Dissertation Defense: Jaewook Shin - Department of Electrical and Computer Engineering","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/engineering.jhu.edu\/ece\/event\/dissertation-defense-jaewook-shin\/","og_locale":"en_US","og_type":"article","og_title":"Dissertation Defense: Jaewook Shin - Department of Electrical and Computer Engineering","og_description":"Title: Minimally-Invasive Lens-free Computational MicroendoscopyAbstract: Ultra-miniaturized imaging tools are vital for numerous biomedical applications. 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