Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models

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dc.contributor.advisorDouglas, Tania Sen_ZA
dc.contributor.authorDendere, Ronalden_ZA
dc.date.accessioned2014-07-28T18:16:16Z
dc.date.available2014-07-28T18:16:16Z
dc.date.issued2009en_ZA
dc.descriptionIncludes abstract.
dc.descriptionIncludes bibliographical references (leaves 83-88).
dc.description.abstractAutomated microscopy for the detection of tuberculosis (TB) in sputum smears seeks to address the strain on technicians and to achieve faster diagnosis in order to cope with the rising number of TB cases. Image processing techniques provide a useful alternative to the conventional, manual analysis of sputum smears for diagnosis. In the project described here, the use of parametric and geometric deformable models was explored for segmentation of TB bacilli in images of Ziehl-Neelsen-stained sputum smears for automated TB diagnosis. The goal of segmentation is to produce candidate bacillus objects for input into a classifier.en_ZA
dc.identifier.apacitationDendere, R. (2009). <i>Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models</i>. (Thesis). University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering. Retrieved from http://hdl.handle.net/11427/3232en_ZA
dc.identifier.chicagocitationDendere, Ronald. <i>"Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models."</i> Thesis., University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2009. http://hdl.handle.net/11427/3232en_ZA
dc.identifier.citationDendere, R. 2009. Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Dendere, Ronald AB - Automated microscopy for the detection of tuberculosis (TB) in sputum smears seeks to address the strain on technicians and to achieve faster diagnosis in order to cope with the rising number of TB cases. Image processing techniques provide a useful alternative to the conventional, manual analysis of sputum smears for diagnosis. In the project described here, the use of parametric and geometric deformable models was explored for segmentation of TB bacilli in images of Ziehl-Neelsen-stained sputum smears for automated TB diagnosis. The goal of segmentation is to produce candidate bacillus objects for input into a classifier. DA - 2009 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2009 T1 - Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models TI - Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models UR - http://hdl.handle.net/11427/3232 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/3232
dc.identifier.vancouvercitationDendere R. Segmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable models. [Thesis]. University of Cape Town ,Faculty of Health Sciences ,Division of Biomedical Engineering, 2009 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/3232en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDivision of Biomedical Engineeringen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherBiomedical Engineeringen_ZA
dc.titleSegmentation of candidate bacillus objects in images of Ziehl-Neelsen-stained sputum smears using deformable modelsen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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