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http://hdl.handle.net/11375/10439
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DC Field | Value | Language |
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dc.contributor.advisor | Anand, Christopher | en_US |
dc.contributor.author | Chinta, Venkateswarao Yogesh | en_US |
dc.date.accessioned | 2014-06-18T16:51:24Z | - |
dc.date.available | 2014-06-18T16:51:24Z | - |
dc.date.created | 2011-07-20 | en_US |
dc.date.issued | 2011-10 | en_US |
dc.identifier.other | opendissertations/5487 | en_US |
dc.identifier.other | 6486 | en_US |
dc.identifier.other | 2108602 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/10439 | - |
dc.description.abstract | <p>Standard MRI is used to image objects at rest. In addition to standard MRI images, which measure tissues at rest, Phase Contrast MRI can be used to quantify the motion of blood and tissue in the human body. The current method used in Phase Contrast MRI is time consuming. The development of new trajectories has minimized imaging time, but creates sub-sampling errors. The proposed method uses regularization of velocities and proton densities to eliminate errors arising from k-space under-sampling.</p> | en_US |
dc.subject | Optimization | en_US |
dc.subject | Velocity MRI | en_US |
dc.subject | Sparse sampling | en_US |
dc.subject | k-space | en_US |
dc.subject | Computational Engineering | en_US |
dc.subject | Computational Engineering | en_US |
dc.title | Sparse Sampling of Velocity MRI | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Computational Engineering and Science | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 1.77 MB | Adobe PDF | View/Open |
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