Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/8684
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dc.contributor.authorOpoku-Ansah, Jerry-
dc.contributor.authorAnderson, Benjamin-
dc.contributor.authorEghan, M.J.-
dc.contributor.authorAkyea, Angela-
dc.contributor.authorBoampong, Johnson Nyarko-
dc.contributor.authorAmuah, C.L.Y-
dc.contributor.authorAdueming, P. Osei-Owusu-
dc.date.accessioned2023-09-29T10:27:37Z-
dc.date.available2023-09-29T10:27:37Z-
dc.date.issued2013-11-
dc.identifier.urihttp://hdl.handle.net/123456789/8684-
dc.language.isoenen_US
dc.publisherUniversity of Cape Coasten_US
dc.subjectmalaria parasitesen_US
dc.subjectimage processingen_US
dc.subjectsegmentationen_US
dc.subjectK-meansen_US
dc.subjectL*a*b* colouren_US
dc.titleAutomated Protocol for Counting Malaria Parasites (P. falciparum) from Digital Microscopic Image Based on L*a*b* Colour Model and K-Means Clusteringen_US
dc.typeArticleen_US
Appears in Collections:School of Allied Health Sciences



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