Quantitative tract integrity profiles (Q-TIPs): a novel neuroimaging toolbox for assessing tract-based white matter integrity

dc.contributor.authorYounas, Sohail
dc.contributor.examiningcommitteeKornelsen, Jennifer (Physiology and Pathophysiology) Sherif, Sherif (Electrical and Computer Engineering) Wang, Yang (Computer Science)en_US
dc.contributor.supervisorFigley, Chase (Physiology and Pathophysiology) Martin, Melanie (Physics and Astronomy)en_US
dc.date.accessioned2017-02-07T15:45:19Z
dc.date.available2017-02-07T15:45:19Z
dc.date.issued2017
dc.degree.disciplineBiomedical Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractIn this thesis, I have sought to address these issues by developing a toolbox called “Quantitative Tract Integrity Profiles (Q-TIPs)” that: is purely MATLAB-based (making it compatible with most operating systems), has a flexible and user-friendly interface, and will be distributed as a standalone toolbox for the popular Statistical Parametric Mapping (SPM) software package. This toolbox extracts the orientation of any ROI mask by calculating the medial axis using Voronoi and Delaunay algorithms, and then cross-sectional segments along the extracted medial axis are used to create profiles based on any quantitative white matter magnetic resonance imaging metric (e.g., diffusion tensor imaging, myelin water imaging, magnetization transfer imaging, etc.). As a result, this toolbox will enable future neuroimaging studies to more easily and flexibly quantify white matter imaging signals along individual tracts as a function of neural development, healthy aging, traumatic brain injury, or neurodegenerative disease.en_US
dc.description.noteFebruary 2017en_US
dc.identifier.urihttp://hdl.handle.net/1993/32109
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectAlong-tract Analysesen_US
dc.subjectWhite Matteren_US
dc.titleQuantitative tract integrity profiles (Q-TIPs): a novel neuroimaging toolbox for assessing tract-based white matter integrityen_US
dc.typemaster thesisen_US
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