Model-based segmentation of CT Images

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dc.contributor.authorMarte, O.
dc.contributor.authorMarais, P.
dc.date.accessioned2015-12-14T09:49:24Z
dc.date.available2015-12-14T09:49:24Z
dc.date.issued2002
dc.date.updated2015-12-14T09:43:41Z
dc.description.abstractThis paper presents preliminary work on the segmentation of Computed Tomography data using a model-based approach. Conventional image processing of CT data is aimed at the production of simple iso-surfaces for surgical planning or diagnosis — such methods are not suitable for the automated detection of fractures, which is the ultimate application of our work. To address these deficiencies a surface-based technique with appropriate constraints is introduced. The output of the segmentation phase is a triangulated surface representing the bone or bones of interest. We illustrate the method applied to low resolution CT test data and discuss its robustness and performance.en_ZA
dc.identifier.apacitationMarte, O., & Marais, P. (2002). Model-based segmentation of CT Images. <i>South African Computer Journal</i>, http://hdl.handle.net/11427/15817en_ZA
dc.identifier.chicagocitationMarte, O., and P. Marais "Model-based segmentation of CT Images." <i>South African Computer Journal</i> (2002) http://hdl.handle.net/11427/15817en_ZA
dc.identifier.citationMarte, O. C., & Marais, P. (2002). Model-based segmentation of CT images. South African Computer Journal, (28), p-54.en_ZA
dc.identifier.ris TY - Journal Article AU - Marte, O. AU - Marais, P. AB - This paper presents preliminary work on the segmentation of Computed Tomography data using a model-based approach. Conventional image processing of CT data is aimed at the production of simple iso-surfaces for surgical planning or diagnosis — such methods are not suitable for the automated detection of fractures, which is the ultimate application of our work. To address these deficiencies a surface-based technique with appropriate constraints is introduced. The output of the segmentation phase is a triangulated surface representing the bone or bones of interest. We illustrate the method applied to low resolution CT test data and discuss its robustness and performance. DA - 2002 DB - OpenUCT DP - University of Cape Town J1 - South African Computer Journal LK - https://open.uct.ac.za PB - University of Cape Town PY - 2002 T1 - Model-based segmentation of CT Images TI - Model-based segmentation of CT Images UR - http://hdl.handle.net/11427/15817 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/15817
dc.identifier.vancouvercitationMarte O, Marais P. Model-based segmentation of CT Images. South African Computer Journal. 2002; http://hdl.handle.net/11427/15817.en_ZA
dc.languageengen_ZA
dc.publisherUniversity of Cape Townen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsCreative Commons Attribution 4.0 International (CC BY 4.0)*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_ZA
dc.sourceSouth African Computer Journalen_ZA
dc.source.urihttp://sacj.cs.uct.ac.za/index.php/sacj/index
dc.subject.otherimage processing, computer vision, registration, segmentation, medical imaging, radiology, CT
dc.titleModel-based segmentation of CT Imagesen_ZA
dc.typeJournal Articleen_ZA
uct.subject.keywordsimage processingen_ZA
uct.subject.keywordscomputer visionen_ZA
uct.subject.keywordsregistrationen_ZA
uct.subject.keywordssegmentationen_ZA
uct.subject.keywordsmedical imagingen_ZA
uct.type.filetype
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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