Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/38003
DC FieldValueLanguage
dc.contributor.authorLai, C.H.en_US
dc.contributor.author喻石生zh_TW
dc.contributor.authorWang, H.Y.en_US
dc.contributor.authorTsai, Y.C.en_US
dc.contributor.authorYu, S.S.en_US
dc.date2009zh_TW
dc.date.accessioned2014-06-06T08:00:23Z-
dc.date.available2014-06-06T08:00:23Z-
dc.identifier.issn1349-4198zh_TW
dc.identifier.urihttp://hdl.handle.net/11455/38003-
dc.description.abstractProtozoan parasites cause many diseases, such as malaria, EHEC infection, shigellosis, amoebiasis, etc. Different kinds and growing stages of protozoan parasites would lead to different treatments. The most significant characteristic of different growing stages is the number of nuclei. But some nuclei in a cell could be unclear causing the missing in nucleus detection. Common and traditional segmentation methods can not be used to obtain satisfied results directly. This paper presents a novel multi-nucleus detection scheme which is composed from adaptive protozoan parasite boundary erasure, iterative gamma equalization, two-means clustering algorithm, modified connected component detection method, and circle mask scoring method. Except the two-means clustering algorithm, all other parts are modified methods or new methods designed for nucleus extraction, Experiments show that the proposed scheme can detect the nuclei with indistinct boundaries effectively and can obtain better results than other commonly used image segmentation methods.en_US
dc.language.isoen_USzh_TW
dc.relationInternational Journal of Innovative Computing Information and Controlen_US
dc.relation.ispartofseriesInternational Journal of Innovative Computing Information and Control, Volume 5, Issue 11A, Page(s) 3875-3886.en_US
dc.subjectProtozoan parasitesen_US
dc.subjectMicroscope imagesen_US
dc.subjectNucleus detectionen_US
dc.subjectGammaen_US
dc.subjectequalizationen_US
dc.subjectBoundary erasureen_US
dc.subjectConnected componenten_US
dc.subjectCircular masksen_US
dc.subjectsegmentationen_US
dc.subjectchildrenen_US
dc.subjectregionsen_US
dc.titleAN ITERATIVE BASED NOVEL MULTI-NUCLEUS DETECTION SCHEME FOR PROTOZOAN PARASITE MICROSCOPIC IMAGESen_US
dc.typeJournal Articlezh_TW
item.grantfulltextnone-
item.openairetypeJournal Article-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept資訊科學與工程學系所-
crisitem.author.parentorg理學院-
Appears in Collections:資訊科學與工程學系所
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