Browsing by Author "Ercan, Tuncay"

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Citation - WoS: 123
Citation - Scopus: 159
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.
Host Based Dynamic Throughput Maximization Model for Ieee 802.11 Wlan
(Springer-verlag Berlin, 2010) Koyuncu, Murat; Gercek, Mehmet Kazim; Ercan, Tuncay
As the demand for uninterrupted Internet access grows, the popularity of wireless communication increases. However, wireless communication has some problems compared to conventional wired communication. Especially, if widely used Wireless Local Area Network (WLAN) applications are taken into consideration, it becomes an important issue to balance the load among available access points. It is impossible to balance the load when wireless hosts associate with an access point by using the classical approach of Received Signal Strength Index (RSSI). Some solutions containing a central server, requiring a specific brand of access point or protocol revisions have been proposed previously, but none of them has been favored as a generally accepted solution. In this study, a proposal which is central server free and requires no modifications to the existing infrastructure is presented. The proposed model is based on a dynamic determination of the least loaded access point to associate with, in order to balance load and maximize throughput.
Citation - WoS: 8
Citation - Scopus: 13
White Blood Cells Classifications by SURF Image Matching, PCA and Dendrogram
(Allied Acad, 2015) Nazlibilek, Sedat; Karacor, Deniz; Erturk, Korhan Levent; Sengul, Gokhan; Ercan, Tuncay; Aliew, Fuad; Department of Mechatronics Engineering; Information Systems Engineering; Computer Engineering
Determination and classification of white blood cells are very important for diagnosing many diseases. The number of white blood cells and morphological changes or blasts of them provide valuable information for the positive results of the diseases such as Acute Lymphocytic Leucomia (ALL). Recognition and classification of white cells as basophils, lymphocytes, neutrophils, monocytes and eosinophils also give additional information for the diagnosis of many diseases. We are developing an automatic process for counting, size determination and classification of white blood cells. In this paper, we give the results of the classification process for which we experienced a study with hundreds of images of white blood cells. This process will help to diagnose especially ALL disease in a fast and automatic way. Three methods are used for classification of five types of white blood cells. The first one is a new algorithm utilizing image matching for classification that is called the Speed-Up Robust Feature detector (SURF). The second one is the PCA that gives the advantage of dimension reduction. The third is the classification tree called dendrogram following the PCA. Satisfactory results are obtained by two techniques.