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dc.contributor.advisorAnastasia Yendiki.en_US
dc.contributor.authorGrisot, Giorgia.en_US
dc.contributor.otherHarvard--MIT Program in Health Sciences and Technology.en_US
dc.date.accessioned2019-09-17T16:28:44Z
dc.date.available2019-09-17T16:28:44Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122194
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionThesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2019en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 201-222).en_US
dc.description.abstractDiffusion magnetic resonance imaging (dMRI) tractography is the only non-invasive tool for studying the connectional architecture of the brain in vivo. By measuring the diffusion of water molecules dMRI provides unique information about white matter pathways and their integrity, making it an invaluable neuroimaging tool that has improved our understanding of the human brain and how it is affected by disease. A major roadblock to its acceptance into clinical practice has been the difficulty in assessing its anatomical accuracy and reliability. In fact, obtaining a map of brain pathways is a multi-step process with numerous variables, assumptions and approximations that can influence the veracity of the generated pathways. Validation is, thus, necessary and yet challenging because there is no gold standard which dMRI can be compared to, since the configuration of human brain connections is largely unknown. Which aspects of tractography processing have the greatest effect on its performance? How do mapping methods compare? Which one is the most anatomically accurate? We tackle these questions with a multi-modal approach that capitalizes on the complementary strengths of available validation strategies to probe dMRI performance on different scales and across a wide range of acquisition and analysis parameters. The outcome is a multi-layered validation of dMRI tractography that 1) quantifies dMRI tractography accuracy both on the level of brain connections and tissue microstructure; 2) highlights the strengths and weaknesses of different modeling and tractography approaches, offering guidance on the issues that need to be resolved to achieve a more accurate mapping of the human brain.en_US
dc.description.statementofresponsibilityby Giorgia Grisot.en_US
dc.format.extent222 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectHarvard--MIT Program in Health Sciences and Technology.en_US
dc.titleValidation of dMRI techniques for mapping brain pathwaysen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentHarvard--MIT Program in Health Sciences and Technologyen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.identifier.oclc1102051583en_US
dc.description.collectionPh.D. Harvard-MIT Program in Health Sciences and Technologyen_US
dspace.imported2019-09-17T16:28:44Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentHSTen_US


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