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dc.identifier.urihttp://hdl.handle.net/1951/59639
dc.identifier.urihttp://hdl.handle.net/11401/71212
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeDissertation
dcterms.abstractIntroduction of advantages of fluid dynamics simulations into clinical practice depends on ability to quickly create patient-specific computational models from computed tomography or magnetic resonance images with minimal human interaction. Our research addresses three steps in this process. First is identifying lung airways in radiological images. Our approach is based on a combination of geometric analysis of gradient vector flow and graph-based algorithms. Second is a novel method for robust and efficient computation of medial curves for complex biomedical geometries. This algorithm is based on three key concepts: a local orthogonal decomposition of geometry into substructures, a differential concept called the interior center of curvature, and integrated stability and consistency tests. Finally, we introduce variational method for generating prismatic boundary-layer meshes. Compared to existing methods, our approach is novel in the following aspects: it relies on feature size to make resulting mesh scale invariant and prevent global self-intersections; it uses face-offsetting method to propagate surface mesh to generate the high-quality prismatic layers; finally, it allows to add prismatic boundary layer to any tetrahedral mesh while preserving structural qualities of original discretization.
dcterms.available2013-05-22T17:34:29Z
dcterms.available2015-04-24T14:46:31Z
dcterms.contributorJiao, Xiangminen_US
dcterms.contributorMitchell, Josephen_US
dcterms.contributorSamulyak, Romanen_US
dcterms.contributorEinstein, Daniel.en_US
dcterms.creatorDyedov, Volodymyr
dcterms.dateAccepted2013-05-22T17:34:29Z
dcterms.dateAccepted2015-04-24T14:46:31Z
dcterms.dateSubmitted2013-05-22T17:34:29Z
dcterms.dateSubmitted2015-04-24T14:46:31Z
dcterms.descriptionDepartment of Applied Mathematics and Statisticsen_US
dcterms.extent114 pg.en_US
dcterms.formatApplication/PDFen_US
dcterms.formatMonograph
dcterms.identifierDyedov_grad.sunysb_0771E_11087en_US
dcterms.identifierhttp://hdl.handle.net/1951/59639
dcterms.identifierhttp://hdl.handle.net/11401/71212
dcterms.issued2012-08-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2013-05-22T17:34:29Z (GMT). No. of bitstreams: 1 Dyedov_grad.sunysb_0771E_11087.pdf: 23079385 bytes, checksum: 017ea7360cfe0f66cd7dfd1267648453 (MD5) Previous issue date: 1en
dcterms.provenanceMade available in DSpace on 2015-04-24T14:46:31Z (GMT). No. of bitstreams: 3 Dyedov_grad.sunysb_0771E_11087.pdf.jpg: 1894 bytes, checksum: a6009c46e6ec8251b348085684cba80d (MD5) Dyedov_grad.sunysb_0771E_11087.pdf.txt: 221877 bytes, checksum: 18e20d96073f72234dddbaa03d64158b (MD5) Dyedov_grad.sunysb_0771E_11087.pdf: 23079385 bytes, checksum: 017ea7360cfe0f66cd7dfd1267648453 (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectApplied mathematics--Biomedical engineering
dcterms.titleAutomatic Mesh Generation and Processing for Biomedical Geometries
dcterms.typeDissertation


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