FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease

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dc.contributor.advisorSpottiswoode, Bruce Shawnen_ZA
dc.contributor.advisorMorgan, Barak Elien_ZA
dc.contributor.authorBaasch, Rolanden_ZA
dc.date.accessioned2015-01-15T18:39:46Z
dc.date.available2015-01-15T18:39:46Z
dc.date.issued2011en_ZA
dc.descriptionIncludes abstract.en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractThe cerebral cortex is composed of a thin layer of Grey Matter (GM), functionally subdivided into discrete regions which are connected in a large scale network via White Matter (WM) tracts. With fMRI (Functional Magnetic Resonance Imaging) it is possible to identify cortical regions involved in specific tasks, and with DTI (Diffusion Tensor Imaging) the structural connections between these areas can be mapped. The aim of this thesis is to to identify and track only those WM tracts entering and leaving a GM Region Of Interest (ROI) defined by fMRI.en_ZA
dc.identifier.apacitationBaasch, R. (2011). <i>FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease</i>. (Thesis). University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering. Retrieved from http://hdl.handle.net/11427/12246en_ZA
dc.identifier.chicagocitationBaasch, Roland. <i>"FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease."</i> Thesis., University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2011. http://hdl.handle.net/11427/12246en_ZA
dc.identifier.citationBaasch, R. 2011. FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Baasch, Roland AB - The cerebral cortex is composed of a thin layer of Grey Matter (GM), functionally subdivided into discrete regions which are connected in a large scale network via White Matter (WM) tracts. With fMRI (Functional Magnetic Resonance Imaging) it is possible to identify cortical regions involved in specific tasks, and with DTI (Diffusion Tensor Imaging) the structural connections between these areas can be mapped. The aim of this thesis is to to identify and track only those WM tracts entering and leaving a GM Region Of Interest (ROI) defined by fMRI. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease TI - FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease UR - http://hdl.handle.net/11427/12246 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/12246
dc.identifier.vancouvercitationBaasch R. FMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe disease. [Thesis]. University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/12246en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDivision of Biomedical Engineeringen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherBiomedical Engineeringen_ZA
dc.titleFMRI guided DTI at the grey-white matter interface : with application to a connectivity analysis of the default mode network in Urbach-Wiethe diseaseen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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