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BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Penn Engineering Events - ECPv6.18.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Penn Engineering Events X-ORIGINAL-URL:https://seasevents.nmsdev7.com X-WR-CALDESC:Events for Penn Engineering Events REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20180311T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20181104T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20190310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20191103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20201101T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20191203T110000 DTEND;TZID=America/New_York:20191203T120000 DTSTAMP:20190828T155001Z CREATED:20190828T155001Z LAST-MODIFIED:20190828T155001Z UID:1923-1575370800-1575374400@seasevents.nmsdev7.com SUMMARY:ESE Seminar: "Beyond Supervised Learning for Biomedical Imaging" DESCRIPTION:Abstract: Today\, many biomedical imaging tasks\, such as 3D reconstruction\, denoising\, detection\, registration\, and segmentation\, are solved with machine learning techniques. In this talk\, I will present a flexible learning-based framework that has allowed us to derive efficient solutions for a variety of such problems\, without relying on heavy supervision. I will primarily employ image registration as a concrete application and present the details of VoxelMorph\, our unsupervised learning-based image registration tool. I will show empirical results obtained by co-registering thousands of brain MRI scans where VoxelMorph has yielded state-of-the-art accuracy with runtimes that are orders of magnitude faster than conventional tools. Finally\, I will present some recent results where we used VoxelMorph to learn conditional deformable templates that can reveal population variation as a function of factors of interest\, such as aging or genetics. Our code is freely available at https://github.com/voxelmorph/voxelmorph. URL:https://seasevents.nmsdev7.com/event/ese-seminar-mert-sabuncu/ LOCATION:Smilow Center Auditorium\, 3400 Civic Center Blvd\, Philadelphia\, PA\, 19104\, United States CATEGORIES:Seminar END:VEVENT END:VCALENDAR