Pattern Recognition in Cytopathology for Papanicolaou Screening

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dc.contributor.authorBlackledge, Jonathanen_US
dc.contributor.authorDubovitskiy, D. A.en_US
dc.contributor.editorJohn Collomosse and Ian Grimsteaden_US
dc.date.accessioned2014-01-31T20:11:56Z
dc.date.available2014-01-31T20:11:56Z
dc.date.issued2010en_US
dc.description.abstractA unique space oriented filer is presented in order to detect and isolate the cell of a nucleus for applications in cytopathology. A classification method for nuclei is then considered based on the application of a set of features which includes certain fractal parameters. Segmentation algorithms are considered in which a self-adjustable sharpening filter is designed to enhance object location. Although the methods discussed and the algorithms developed have a range of applications, in this work we focus on the engineering of a system for automating a Papanicolaou screening test using standard optical imagesen_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-75-3en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG10/131-138en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.5.4 [Pattern recognition]: Segmentation, Contour detection, Decision making, Self-learning, Cytopathologyen_US
dc.titlePattern Recognition in Cytopathology for Papanicolaou Screeningen_US
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