Feature-Based Analysis of Microvasculature in High Resolution Microscopy Images of Mice Brains

dc.contributor.advisorHebert, Thomas J.
dc.contributor.committeeMemberMayerich, David
dc.contributor.committeeMemberLeasure, J. Leigh
dc.creatorVemuri, Venkata Naga Pranathi
dc.date.accessioned2018-07-10T18:50:02Z
dc.date.available2018-07-10T18:50:02Z
dc.date.createdMay 2016
dc.date.issued2016-05
dc.date.submittedMay 2016
dc.date.updated2018-07-10T18:50:02Z
dc.description.abstractQuantitative analysis of three dimensional image datasets in microscopy has the potential to assist histopathology researchers in understanding anatomy, in identifying the cause of diseases or disorder, in the development of new methods in medicine. This project presents steps for tracing, quantification, and analysis of mouse brain microvasculature in datasets obtained from a high throughput microscopy technique called Knife-Edge Scanning Microscopy (KESM). Identification and tracing of microvessels is achieved by segmenting the microvasculature from the surrounding tissue into binary images, obtaining the microvessel centerlines by thinning the segmented microvasculature using binary three dimensional structuring elements, then determining the unit width voxel curve skeleton from the result. This method overcomes computational limitations by forming a computational structure that is easily parallelized on disjoint blocks of data. The unit width skeleton is used to form the nodes of a graphs from which statistics, such as segment length, curvature, and orientation of segments, average branches in a network are computed.
dc.description.departmentElectrical and Computer Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/3195
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectSkeleton
dc.subjectTracing
dc.subjectBrain
dc.subjectMicrovessels
dc.titleFeature-Based Analysis of Microvasculature in High Resolution Microscopy Images of Mice Brains
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentElectrical and Computer Engineering, Department of
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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