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dc.contributor.advisorEdward S. Boyden.en_US
dc.contributor.authorLinghu, Changyangen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2016-07-18T20:05:59Z
dc.date.available2016-07-18T20:05:59Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/103747
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 23-25).en_US
dc.description.abstractIn this work we developed a comprehensive and structured geometric model of human cerebral vasculature for quantitative anatomical analysis. We first proposed a general and structured geometric representation of the interconnected vascular network as a framework. We then described an image processing pipeline for the segmentation of vascular anatomy from discrete scalar field images, and applied the pipeline to segment the anatomical structures of cerebral vasculatures from whole brain magnetic resonance angiography (MRA) scans of healthy adult subjects. Next, we employed the proposed geometric representation to generate the comprehensive geometric model of human cerebral vasculature from those segmented anatomies. In the end, we performed quantitative anatomical analysis to the anterior cerebral arteries (ACA) and internal carotid arteries (ICA), and characterized their varying size and tortuosity in the cerebral arterial circulation.en_US
dc.description.statementofresponsibilityby Changyang Linghu.en_US
dc.format.extent25 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleComprehensive geometric modeling of human cerebral vasculature for quantitative vascular analysisen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc953583160en_US


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