Automated Seed Point Selection in Confocal Image Stacks of Neuron Cells

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dc.contributor.authorBilodeau, Gregory Peteren
dc.contributor.committeechairEgyhazy, Csaba J.en
dc.contributor.committeememberKulczycki, Gregory W.en
dc.contributor.committeememberChen, Ing-Rayen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-07-26T08:00:12Zen
dc.date.available2013-07-26T08:00:12Zen
dc.date.issued2013-07-25en
dc.description.abstractThis paper provides a fully automated method of finding high-quality seed points in 3D space from a stack of images of neuron cells. These seed points may then be used as initial starting points for automated local tracing algorithms, removing a time consuming required user interaction in current methodologies. Methods to collapse the search space and provide rudimentary topology estimates are also presented.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:315en
dc.identifier.urihttp://hdl.handle.net/10919/23328en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNeuron tracingen
dc.subjectDIADEMen
dc.subjectimage analysisen
dc.titleAutomated Seed Point Selection in Confocal Image Stacks of Neuron Cellsen
dc.typeThesisen
thesis.degree.disciplineComputer Science and Applicationsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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