Nazlıbilek, Sedat

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S.,Nazlibilek
N., Sedat
Nazlıbilek,S.
Sedat, Nazlıbilek
N.,Sedat
Nazlibilek,S.
S., Nazlibilek
S.,Nazlıbilek
Sedat, Nazlibilek
Nazlıbilek, Sedat
Nazlibilek, Sedat
Job Title
Doçent Doktor
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Main Affiliation
Department of Mechatronics Engineering
Status
Former Staff
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Scopus Author ID
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WoS Researcher ID

Sustainable Development Goals

5

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0

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14

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2

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10

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3

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1

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2

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0

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9

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16

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11

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8

DECENT WORK AND ECONOMIC GROWTH
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13

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4

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6

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1

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15

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17

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1

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7

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This researcher does not have a Scopus ID.
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Scholarly Output

22

Articles

14

Views / Downloads

5/0

Supervised MSc Theses

3

Supervised PhD Theses

3

WoS Citation Count

245

Scopus Citation Count

302

WoS h-index

7

Scopus h-index

8

Patents

0

Projects

0

WoS Citations per Publication

11.14

Scopus Citations per Publication

13.73

Open Access Source

1

Supervised Theses

6

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JournalCount
Measurement7
Indian Journal of Pure and Applied Physics2
IEEE Transactions on Instrumentation and Measurement2
20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20 September 2013 through 20 September 2013 -- Ankara -- 1022761
International Conference of Control, Dynamic Systems, and Robotics -- 4th International Conference of Control, Dynamic Systems, and Robotics, CDSR 2017 -- 21 August 2017 through 23 August 2017 -- Toronto -- 1399181
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Now showing 1 - 1 of 1
  • Article
    Citation - WoS: 128
    Citation - Scopus: 163
    Automatic Segmentation, Counting, Size Determination and Classification of White Blood Cells
    (Elsevier Sci Ltd, 2014) Nazlibilek, Sedat; Karacor, Deniz; Ercan, Tuncay; Sazli, Murat Husnu; Kalender, Osman; Ege, Yavuz
    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.