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Automated quantification and classification of human kidney microstructures obtained by optical coherence tomography

dc.contributor.advisorChen, Yuen_US
dc.contributor.authorLi, Qianen_US
dc.date.accessioned2010-02-19T07:07:04Z
dc.date.available2010-02-19T07:07:04Z
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1903/9994
dc.description.abstractOptical coherence tomography (OCT) is a rapidly emerging imaging modality that can non-invasively provide cross-sectional, high-resolution images of tissue morphology such as kidney in situ and in real-time. Because the viability of a donor kidney is closely correlated with its tubular morphology, and a large amount of image datasets are expected when using OCT to scan the entire kidney, it is necessary to develop automated image analysis methods to quantify the spatially-resolved morphometric parameters such as tubular diameter, and to classify various microstructures. In this study, we imaged the human kidney in vitro, quantified the diameters of hollow structures such as blood vessels and uriniferous tubules, and classified those structures automatically. The quantification accuracy was validated. This work can enable studies to determine the clinical utility of OCT for kidney imaging, as well as studies to evaluate kidney morphology as a biomarker for assessing kidney's viability prior to transplantation.en_US
dc.titleAutomated quantification and classification of human kidney microstructures obtained by optical coherence tomographyen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentBioengineeringen_US
dc.subject.pqcontrolledEngineering, Biomedicalen_US
dc.subject.pquncontrolledclassificationen_US
dc.subject.pquncontrolledhuman kidneyen_US
dc.subject.pquncontrolledimage processingen_US
dc.subject.pquncontrolledoptical coherence tomographyen_US
dc.subject.pquncontrolledquantificationen_US


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