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UID:calendar.296631.field_event_date.0@www.wright.edu
DTSTAMP:20260219T215227Z
CREATED:20180226T194434Z
DESCRIPTION:Ph.D. Committee:  Drs. Thomas Wischgoll (advisor)\, Mark E. Haa
 cke (Wayne State University)\, Nasser H. Kashou\, Arthur Goshtasby\, and T
 anvi BanerjeeABSTRACT:Brain diseases\, in addition to the human suffering\
 , have a huge economic burden to the world’s economy. This will grow in th
 e future due to the relation of brain diseases with aging and increase in 
 life expectancy. Therefore\, the need for the diagnostic tools that enable
  doctors to provide more accurate and faster diagnosis is critical.One of 
 the widely used imaging tools for brain diseases diagnosis is Magnetic Res
 onance Imaging (MRI). MRI is a structural modality that provides excellent
  soft tissue contrast. Furthermore\, MRI is an ideal technique to study th
 e development of fetal brain due to being harmless since it does not invol
 ve radiation.In spite of all these unbeatable advantages\, MRI suffers fro
 m limited spatial resolution which may result in reducing the accuracy of 
 diagnosis and precision of any measurements of the size and morphology of 
 the specific structure. For acquiring a high-resolution MRI\, the patient 
 needs to remain still in the MRI scanner for a longer period of time. In s
 ome applications such as fetal brain development\, longer scans might not 
 be possible. Therefore\, the need for post-acquisition resolution enhancem
 ent is important.Super Resolution reconstruction techniques are the soluti
 on to this problem. In this study\, we are proposing a constraint-based su
 per resolution technique to reconstruct the high-resolution MRI from singl
 e low-resolution MRI. Results of this research are beneficial to clinical 
 applications in reducing the scan time and providing better visualizations
  of the brain to increase the accuracy of the diseases diagnosis\, treatme
 nt process\, and surgical planning.
DTSTART;TZID=America/New_York:20180305T140000
DTEND;TZID=America/New_York:20180305T160000
LAST-MODIFIED:20180226T200554Z
LOCATION:304 Russ Engineering
SUMMARY:Ph.D. Dissertation Proposal Defense 'Super-Resolution Reconstructio
 n of Magnetic Resonance Imaging' By Sara Gharabaghi
URL;TYPE=URI:/events/phd-dissertation-proposal-defens
 e-super-resolution-reconstruction-magnetic-resonance-imaging
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