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PRODID:-//BioMedIA - ECPv6.15.11//NONSGML v1.0//EN
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METHOD:PUBLISH
X-WR-CALNAME:BioMedIA
X-ORIGINAL-URL:https://biomedia.doc.ic.ac.uk
X-WR-CALDESC:Events for BioMedIA
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20150101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20160525T120000
DTEND;TZID=UTC:20160525T130000
DTSTAMP:20260502T120855
CREATED:20160520T171139Z
LAST-MODIFIED:20160520T171139Z
UID:2809-1464177600-1464181200@biomedia.doc.ic.ac.uk
SUMMARY:BioMedIA Talk: Archontis Giannakidis (Royal Brompton)
DESCRIPTION:Improving clinical application of cardiac diffusion tensor MRI\nAbstract  Magnetic resonance diffusion tensor imaging (MRDTI)\, also known as DTI\, has emerged as a powerful non-invasive tool for mapping the orientation-dependent microanatomical organization of fibrous organs such as brain white matter and myocardium. To do so\, it elegantly relates the self-diffusion of water molecules that undergo Brownian motion to proton spin relaxation MR signals. In this talk it will be shown how DTI can shed some light on the left-ventricular micro-structural remodeling following hypertensive disease. A framework for the voxelwise registration-based characterization of cardiac disease will be considered. Population and longitudinal studies may benefit from such a scheme. Results from a comparison study will be presented juxtaposing the performance of three tensor distance functions. The selection of a tensor distance function resides in the foundation of the tensor-variate framework\, critically affecting many operations in the six-dimensional space of diffusion tensors. This seminar will end by discussing how sparsifying transforms can be used in conjunction with compressive sensing reconstruction to shorten acquisition times.
URL:https://biomedia.doc.ic.ac.uk/event/biomedia-talk-archontis-giannakidis-royal-brompton/
LOCATION:Huxley 144
CATEGORIES:Talks & Seminars
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