Automatic Segmentation, Counting, Size Determination and Classification of White Blood Cells

dc.contributor.author Nazlibilek, Sedat
dc.contributor.author Karacor, Deniz
dc.contributor.author Ercan, Tuncay
dc.contributor.author Sazli, Murat Husnu
dc.contributor.author Kalender, Osman
dc.contributor.author Ege, Yavuz
dc.date.accessioned 2024-07-05T14:26:44Z
dc.date.available 2024-07-05T14:26:44Z
dc.date.issued 2014
dc.description Sazli, Murat/0000-0001-9235-3679; Karacor, Deniz/0000-0001-6961-8966; Ercan, Tuncay/0000-0003-0014-5106; en_US
dc.description.abstract The counts, the so-called differential counts, and sizes of different types of white blood cells provide invaluable information to evaluate a wide range of important hematic pathologies from infections to leukemia. Today, the diagnosis of diseases can still be achieved mainly by manual techniques. However, this traditional method is very tedious and time-consuming. The accuracy of it depends on the operator's expertise. There are laser based cytometers used in laboratories. These advanced devices are costly and requires accurate hardware calibration. They also use actual blood samples. Thus there is always a need for a cost effective and robust automated system. The proposed system in this paper automatically counts the white blood cells, determine their sizes accurately and classifies them into five types such as basophil, lymphocyte, neutrophil, monocyte and eosinophil. The aim of the system is to help for diagnosing diseases. In our work, a new and completely automatic counting, segmentation and classification process is developed. The outputs of the system are the number of white blood cells, their sizes and types. (C) 2014 Elsevier Ltd. All rights reserved. en_US
dc.identifier.doi 10.1016/j.measurement.2014.04.008
dc.identifier.issn 0263-2241
dc.identifier.issn 1873-412X
dc.identifier.scopus 2-s2.0-84901417604
dc.identifier.uri https://doi.org/10.1016/j.measurement.2014.04.008
dc.identifier.uri https://hdl.handle.net/20.500.14411/152
dc.language.iso en en_US
dc.publisher Elsevier Sci Ltd en_US
dc.relation.ispartof Measurement
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject White blood cells en_US
dc.subject Neural network en_US
dc.subject Automatic counting en_US
dc.subject Principal Component Analysis (PCA) en_US
dc.title Automatic Segmentation, Counting, Size Determination and Classification of White Blood Cells en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Sazli, Murat/0000-0001-9235-3679
gdc.author.id Karacor, Deniz/0000-0001-6961-8966
gdc.author.id Ercan, Tuncay/0000-0003-0014-5106
gdc.author.scopusid 24473589800
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gdc.author.scopusid 19639054500
gdc.author.scopusid 19638410900
gdc.author.wosid Sazli, Murat/AAH-6663-2020
gdc.author.wosid Karacor, Deniz/IAO-9194-2023
gdc.author.wosid Ercan, Tuncay/F-9938-2011
gdc.author.wosid Ege, Yavuz/AAD-7800-2019
gdc.author.wosid Karacor, Deniz/AAH-3088-2020
gdc.bip.impulseclass C4
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gdc.bip.popularityclass C3
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department Atılım University en_US
gdc.description.departmenttemp [Nazlibilek, Sedat] Atilim Univ, Fac Engn, Dept Mechatron Engn, TR-06800 Ankara, Turkey; [Karacor, Deniz; Sazli, Murat Husnu] Ankara Univ, Fac Engn, Dept Elect Engn, TR-06100 Ankara, Turkey; [Ercan, Tuncay] Yasar Univ, Fac Engn, Dept Comp Engn, Izmir, Turkey; [Kalender, Osman] Bursa Orhangazi Univ, Fac Engn, Dept Elect Elect Engn, TR-16350 Bursa, Turkey; [Ege, Yavuz] Balikesir Univ, Dept Phys, Necatibey Fac Educ, TR-10100 Balikesir, Turkey en_US
gdc.description.endpage 65 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.startpage 58 en_US
gdc.description.volume 55 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W2012442592
gdc.identifier.wos WOS:000339814500007
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.diamondjournal false
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gdc.oaire.keywords White Blood Cells
gdc.oaire.keywords Neural Network
gdc.oaire.keywords Automatic Counting
gdc.oaire.keywords 006
gdc.oaire.keywords Principal Component Analysis (PCA)
gdc.oaire.popularity 7.005466E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0209 industrial biotechnology
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
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gdc.opencitations.count 125
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gdc.plumx.scopuscites 159
gdc.scopus.citedcount 159
gdc.virtual.author Nazlıbilek, Sedat
gdc.wos.citedcount 123
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