Özkan, Akın

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https://hdl.handle.net/20.500.14411/7674
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Ö.,Akın
Özkan,A.
Akin, Ozkan
Akın, Özkan
A.,Özkan
Ozkan,A.
A.,Ozkan
O.,Akin
O., Akin
A., Ozkan
Özkan, Akın
Ozkan, Akin
Job Title
Araştırma Görevlisi
Email Address
akin.ozkan@atilim.edu.tr
Main Affiliation
Department of Electrical & Electronics Engineering
Status
Former Staff
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10

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3

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2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 20 April 2011 through 22 April 2011 -- Antalya -- 855281
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings -- 24th Signal Processing and Communication Application Conference, SIU 2016 -- 16 May 2016 through 19 May 2016 -- Zonguldak -- 1226051
24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY1
25th IEEE International Conference on Image Processing (ICIP) -- OCT 07-10, 2018 -- Athens, GREECE1
Biomedical Research (India)1
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Start date: 2011Subject: Hemocytometer

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Conference Object
    Citation - WoS: 1
    Method Proposal for Distinction of Microscope Objectives on Hemocytometer Images
    (Ieee, 2016) Ozkan, Akin; Isgor, S. Belgin; Sengul, Gokhan
    Hemocytometer is a special glass plate apparatus used for cell counting that has straight lines (counting chamber) in certain size. Leveraging this special lam and microscope, a cell concentration on an available cell suspension can be estimated. The automation process of hemocytometer images will assist several research disciplines to improve consistency of results and to reduce human labor. Different objective measurements can be utilized to analyze a cell sample on microscope. These differences affect the detail of image content. Basically, while the objective value is getting increased, image scale and detail level taken from image will increase, yet visible area becomes narrower. Due to this variation, different self-cell counting approaches should be developed for images taken with different objective values. In this paper, using the hemocytometer images gathered from a microscope, a novel approach is introduced for which can estimate objective values of a microscope with machine learning methods automatically. For this purpose, a frequency-based visual feature is proposed which embraces hemocytometer structure well. As a result of the conducted tests, %100 distinction accuracy is achieved with the proposed method.
  • Thumbnail Image
    Article
    Citation - Scopus: 1
    Computer Vision Based Automated Cell Counting Pipeline: a Case Study for Hl60 Cancer Cell on Hemocytometer
    (Scientific Publishers of India, 2018) Özkan,A.; İşgör,S.B.; Şengül,G.; İşgör,Y.G.
    Counting of cells can give useful information about the cell density to understand the concerning cell culture condition. Usually, cell counting can be achieved manually with the help of the microscope and hemocytometer by the domain experts. The main drawback of the manual counting procedure is that the reliability highly depends on the experience and concentration of the examiners. Therefore, computer vision based automated cell counting is an essential tool to improve the accuracy. Although the commercial automated cell counting systems are available in the literature, their high cost limits their broader usage. In this study, we present a cell counting pipeline for light microscope images based on hemocytometer that can be easily adapted to the various cell types. The proposed method is robust to adverse image and cell culture conditions such as cell shape deformations, lightning conditions and brightness differences. In addition, we collect a novel human promyelocytic leukemia (HL60) cancer cell dataset to test our pipeline. The experimental results are presented in three measures: recall, precision and F-measure. The method reaches up to 98%, 92%, and 95% based on these three measures respectively by combining Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG). © 2018, Scientific Publishers of India. All rights reserved.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    Method Proposal for Distinction of Microscope Objectives on Hemocytometer Images;
    (Institute of Electrical and Electronics Engineers Inc., 2016) Ozkan,A.; Isgor,S.B.; Sengul,G.
    Hemocytometer is a special glass plate apparatus used for cell counting that has straight lines (counting chamber) in certain size. Leveraging this special lam and microscope, a cell concentration on an available cell suspension can be estimated. The automation process of hemocytometer images will assist several research disciplines to improve consistency of results and to reduce human labor. Different objective measurements can be utilized to analyze a cell sample on microscope. These differences affect the detail of image content. Basically, while the objective value is getting increased, image scale and detail level taken from image will increase, yet visible area becomes narrower. Due to this variation, different self-cell counting approaches should be developed for images taken with different objective values. In this paper, using the hemocytometer images gathered from a microscope, a novel approach is introduced for which can estimate objective values of a microscope with machine learning methods automatically. For this purpose, a frequency-based visual feature is proposed which embraces hemocytometer structure well. As a result of the conducted tests, %100 distinction accuracy is achieved with the proposed method. © 2016 IEEE.