Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/80452
DC FieldValue
dc.titleFractal image analysis for automated kidney microscopy
dc.contributor.authorJin, X.C.
dc.contributor.authorOng, S.H.
dc.date.accessioned2014-10-07T02:57:42Z
dc.date.available2014-10-07T02:57:42Z
dc.date.issued1995-09
dc.identifier.citationJin, X.C.,Ong, S.H. (1995-09). Fractal image analysis for automated kidney microscopy. Journal of Computer-Assisted Microscopy 7 (3) : 127-133. ScholarBank@NUS Repository.
dc.identifier.issn10407286
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/80452
dc.description.abstractThis paper describes the implementation of an image analysis system for automated kidney microscopy. Autofocused images of kidney tissue sections, which differ in texture according to the severity of tissue damage, are evaluated. It is shown that fractal dimension varies according to the state of the kidney tissue, and is significantly different between normal and abnormal states. A linear classifier is designed based on the statistical properties of the experimental data. Satisfactory classification of normal and damaged kidney tissue is achieved.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleJournal of Computer-Assisted Microscopy
dc.description.volume7
dc.description.issue3
dc.description.page127-133
dc.description.codenJCMIE
dc.identifier.isiutNOT_IN_WOS
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