Automatic segmentation counting size determination and classification of white blood cells

dc.contributor.author Sedat Nazlibilek
dc.contributor.author Deniz Karacor
dc.contributor.author Tuncay Ercan
dc.contributor.author Murat Hüsnü Sazli
dc.contributor.author Osman Kalender
dc.contributor.author Yavuz Ege
dc.contributor.author Ercan, Tuncay
dc.contributor.author Ege, Yavuz
dc.contributor.author Karacor, Deniz
dc.contributor.author Nazlibilek, Sedat
dc.contributor.author Kalender, Osman
dc.contributor.author Sazli, Murat Husnu
dc.date.accessioned 2025-10-06T17:52:37Z
dc.date.issued 2014
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. © 2014 Elsevier Ltd. All rights reserved. © 2017 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1016/j.measurement.2014.04.008
dc.identifier.issn 02632241
dc.identifier.issn 0263-2241
dc.identifier.issn 1873-412X
dc.identifier.scopus 2-s2.0-84901417604
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901417604&doi=10.1016%2Fj.measurement.2014.04.008&partnerID=40&md5=22b985dba7875aad51cc7ab28f4cf924
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/10039
dc.identifier.uri https://doi.org/10.1016/j.measurement.2014.04.008
dc.language.iso English
dc.publisher Elsevier B.V.
dc.relation.ispartof Measurement
dc.rights info:eu-repo/semantics/closedAccess
dc.source Measurement: Journal of the International Measurement Confederation
dc.subject Automatic Counting, Neural Network, Principal Component Analysis (pca), White Blood Cells, Automation, Blood, Cells, Neural Networks, Principal Component Analysis, Automated Systems, Automatic Counting, Automatic Segmentations, Blood Samples, Classification Process, Cost Effective, Manual Techniques, White Blood Cells, Diagnosis
dc.subject Automation, Blood, Cells, Neural networks, Principal component analysis, Automated systems, Automatic counting, Automatic segmentations, Blood samples, Classification process, Cost effective, Manual techniques, White blood cells, Diagnosis
dc.subject White Blood Cells
dc.subject Automatic Counting
dc.subject Neural Network
dc.subject Principal Component Analysis (PCA)
dc.title Automatic segmentation counting size determination and classification of white blood cells
dc.type Article
dspace.entity.type Publication
gdc.author.id Ercan, Tuncay/0000-0003-0014-5106
gdc.author.id Karacor, Deniz/0000-0001-6961-8966
gdc.author.id SAZLI, Murat Hüsnü/0000-0001-9235-3679
gdc.author.scopusid 19639054500
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gdc.author.wosid Ege, Yavuz/AAD-7800-2019
gdc.author.wosid Karacor, Deniz/AAH-3088-2020
gdc.author.wosid SAZLI, Murat Hüsnü/AAH-6663-2020
gdc.author.wosid Ercan, Tuncay/F-9938-2011
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gdc.description.department
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
gdc.description.endpage 65
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
gdc.description.startpage 58
gdc.description.volume 55
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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)
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gdc.oaire.sciencefields 0209 industrial biotechnology
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
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gdc.virtual.author Ercan, Ahmet Tuncay
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person.identifier.scopus-author-id Nazlibilek- Sedat (24473589800), Karacor- Deniz (54909245800), Ercan- Tuncay (21933416500), Sazli- Murat Hüsnü (15078749000), Kalender- Osman (19639054500), Ege- Yavuz (19638410900)
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