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Automated segmentation of erythrocytes from Giemsa-stained thin blood films

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dc.contributor.authorPuttapirat P.
dc.contributor.authorPhothisonothai M.
dc.contributor.authorTantisatirapong S.
dc.date.accessioned2021-04-05T03:24:00Z
dc.date.available2021-04-05T03:24:00Z
dc.date.issued2016
dc.date.issuedBE2559
dc.description.abstractThis paper investigates automated segmentation of malaria parasites in images of Giemsa-stained thin blood film specimens. The Giemsa staining exhibits not only on the malaria parasites, but also platelets and artifacts. We aim to extract erythrocytes both normal and infected cells from other particles and separate overlapping cells. Our approach is compared with manual cell counting and existing program named CELLCOUNTER. Our processing framework provides 97% accuracy, which yields predominant detection more accurate than the CELLCOUNTER. The results also indicate high correlation between our proposed method and the manual cell counting. © 2016 IEEE.
dc.format.mimetypeapplication/pdf
dc.identifier.citation2016 8th International Conference on Knowledge and Smart Technology, KST 2016. (2016), p.219-223
dc.identifier.doi10.1109/KST.2016.7440503
dc.identifier.other2-s2.0-84966600728
dc.identifier.urihttps://hdl.handle.net/20.500.14740/5544
dc.rights.holderมหาวิทยาลัยศรีนครินทรวิโรฒ
dc.subject.otherCells
dc.subject.otherCytology
dc.subject.otherDiseases
dc.subject.otherImage segmentation
dc.subject.otherAutomated segmentation
dc.subject.otherCell counting
dc.subject.otherInfected cells
dc.subject.otherMalaria parasite
dc.subject.otherMultichannel images
dc.subject.otherOverlapping cells
dc.subject.otherBlood
dc.titleAutomated segmentation of erythrocytes from Giemsa-stained thin blood films
dc.typeConference Paper
dspace.entity.typePublication
swu.datasource.scopushttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84966600728&doi=10.1109%2fKST.2016.7440503&partnerID=40&md5=059d16c34acf729c512289cb60460d6c

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