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dc.contributor.authorMelonakos, Johnen_US
dc.date.accessioned2009-06-08T19:02:34Z
dc.date.available2009-06-08T19:02:34Z
dc.date.issued2008-12-17en_US
dc.identifier.urihttp://hdl.handle.net/1853/28139
dc.descriptionAcknowledgements page removed per author's request, 01/06/2014.en_US
dc.description.abstractGeodesic Tractography Segmentation is the two component approach presented in this thesis for the analysis of imagery in oriented domains, with emphasis on the application to diffusion-weighted magnetic resonance imagery (DW-MRI). The computeraided analysis of DW-MRI data presents a new set of problems and opportunities for the application of mathematical and computer vision techniques. The goal is to develop a set of tools that enable clinicians to better understand DW-MRI data and ultimately shed new light on biological processes. This thesis presents a few techniques and tools which may be used to automatically find and segment major neural fiber bundles from DW-MRI data. For each technique, we provide a brief overview of the advantages and limitations of our approach relative to other available approaches.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectMedical image analysisen_US
dc.subjectMRIen_US
dc.subjectTractographyen_US
dc.subjectImage processingen_US
dc.subject.lcshDiagnostic imaging
dc.subject.lcshGeodesics (Mathematics)
dc.subject.lcshGeodesic flows
dc.titleGeodesic tractography segmentation for directional medical image analysisen_US
dc.typeDissertationen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.advisorCommittee Chair: Tannenbaum, Allen; Committee Member: Barnes, Christopher F.; Committee Member: Niethammer, Marc; Committee Member: Shamma, Jeff; Committee Member: Vela, Patricioen_US


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