Publication:
An automated method for the nuclei and cytoplasm of Acute Myeloid Leukemia detection in blood smear images

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dc.Conferencecode124163
dc.Conferencedate31 July 2016 through 4 August 2016
dc.Conferencename2016 World Automation Congress, WAC 2016
dc.citedby3
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsJapan Advanced Institute of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.affiliationsUniversiti Sains Malaysia (USM)
dc.contributor.authorTran V.-N.en_US
dc.contributor.authorIsmail W.en_US
dc.contributor.authorHassan R.en_US
dc.contributor.authorYoshitaka A.en_US
dc.date.accessioned2024-05-28T08:46:53Z
dc.date.available2024-05-28T08:46:53Z
dc.date.issued2016
dc.description.abstractLeukemia is a cancer of white blood cells that affect the blood forming cells in the body. Acute Myeloid Leukemia (AML) is a form of leukemia and are caused by replacement of normal bone marrows with leukemic cells, which cause a drop in red blood cells, platelets, and normal white blood cells. Early classification of the subtype of AML cells is necessary for proper treatment management. We classify the subtype based on the features of AML cells, which include the nuclei and cytoplasm. In this paper, we developed an automate method for the nuclei and cytoplasm detection from the blood cells images that are captured as microscope images. In contrast to other methods that focus on identifying the nuclei, we proposed a method based on the color conversion, intensity threshold and gradient magnitude. Our method detected both the nuclei and the cytoplasm at the same time. We test our method on 301 images, which contain 643 AML cells. The accuracy of both nuclei and cytoplasm detection is over 82.9% (increase 17% when was compared with the existent method). � 2016 TSI Enterprise Inc (TSI Press).
dc.description.natureFinalen_US
dc.identifier.ArtNo7583023
dc.identifier.doi10.1109/WAC.2016.7583023
dc.identifier.isbn9781890000000
dc.identifier.issn21544824
dc.identifier.scopus2-s2.0-84993978020
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84993978020&doi=10.1109%2fWAC.2016.7583023&partnerID=40&md5=fb1d26b0b4f2bd47bf438164609ff141
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9446
dc.identifier.volume2016-October
dc.languageEnglish
dc.language.isoen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofWorld Automation Congress Proceedings
dc.sourceScopus
dc.subjectAcute Myeloid Leukemia (AML)en_US
dc.subjectcytoplasmen_US
dc.subjectgradient magnitudeen_US
dc.subjectnucleien_US
dc.subjectAutomationen_US
dc.subjectBlooden_US
dc.subjectCytologyen_US
dc.subjectDiseasesen_US
dc.subjectAcute myeloid leukemiaen_US
dc.subjectAutomated methodsen_US
dc.subjectcytoplasmen_US
dc.subjectGradient magnitudeen_US
dc.subjectIntensity thresholden_US
dc.subjectnucleien_US
dc.subjectTreatment managementen_US
dc.subjectWhite blood cellsen_US
dc.subjectCellsen_US
dc.titleAn automated method for the nuclei and cytoplasm of Acute Myeloid Leukemia detection in blood smear images
dc.typeConference Paperen_US
dspace.entity.typePublication

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