Yazar "Turan, M. Kamil" seçeneğine göre listele

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    Classifying white blood cells using machine learning algorithms
    (2019) Elen, Abdullah; Turan, M. Kamil
    Blood and its components have an important place in human life and are the best indicator tool in determining many pathologicalconditions. In particular, the classification of white blood cells is of great importance for the diagnosis of hematological diseases.In this study, 350 microscopic blood smear images were tested with 6 different machine learning algorithms for the classificationof white blood cells and their performances were compared. 35 different geometric and statistical (texture) features have beenextracted from blood images for training and test parameters of machine learning algorithms. According to the results, theMultinomial Logistic Regression (MLR) algorithm performed better than the other methods with an average 95% test success.The MLR can be used for automatic classification of white blood cells. It can be used especially as a source for diagnosis ofdiseases for hematologists and internal medicine specialists.
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    Design of a low-cost and fully automated digital microscope system
    (Springer, 2023) Elen, Abdullah; Turan, M. Kamil
    Microscopes are indispensable devices of laboratories. They are widely used in industry and science, such as medicine, geology, biology, chemistry and so on. Thanks to the developing technology, manual microscopes are leaving their place to automatic systems. However, automatic microscopy systems are difficult to obtain due to their high costs. The best way to circumvent this problem is to reduce device costs as much as possible. Based on this idea, a fully automated digital microscope system (FADMS) has been proposed as a low-cost prototype. The FADMS can scan and autofocus for various microscopic samples. In addition, it can be controlled over the internet thanks to a developed software and can store scanned microscopic images. The total cost of the developed system is around 2500 US dollars. In experimental studies, mechanical motion sensitivity and focusing tests of the FADMS were performed. Five different methods were tested on peripheral blood smear images for autofocus. According to the results obtained based on six different measurement criteria, Brenner's and Geusebroek's method showed the best performance. In positioning tests for the mechanical stage (X and Y axes), the motors in the driving system were moved forward and backward for a distance of 100 mu m. The results obtained showed a deviation of 2.6 mu m for the X-axis and 3.6 mu m for the Y-axis. Experimental results show that micron-sized biological cells can be observed in detail. The FADMS has been designed in a modular structure that allows it to be replaced with lighting, optical system and imaging device alternatives. In terms of performance/cost ratio, the FADMS is attractive for high-throughput microscopy applications ranging from digital pathology to health screening in low-income countries and is considered to be an alternative solution for many industries.
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    FahamecV1:A Low Cost Automated Metaphase Detection System
    (Eos Assoc, 2017) Yilmaz, Hakan; Turan, M. Kamil
    In this study, FahamecV1 is introduced and investigated as a low cost and high accuracy solution for metaphase detection. Chromosome analysis is performed at the metaphase stage and high accuracy and automated detection of the metaphase stage plays an active role in decreasing analysis time. FahamecV1 includes an optic microscope, a motorized microscope stage, an electronic control unit, a camera, a computer and a software application. Printing components of the motorized microscope stage (using a 3D printer) is of the main reasons for cost reduction. Operations such as stepper motor calibration, are detection, focusing, scanning, metaphase detection and saving of coordinates into a database are automatically performed. To detect metaphases, a filter named Metafilter is developed and applied. Average scanning time per preparate is 77 sec/cm(2). True positive rate is calculated as 95.1%, true negative rate is calculated as 99.0% and accuracy is calculated as 98.8%.
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    Filter Development for Automatic Detection of Analyzable Metaphases
    (Ieee, 2018) Yilmaz, Hakan; Turan, M. Kamil
    Abnormalities in the structure of chromosomes cause fetal deaths or developmental disorders. Chromosome analysis is a method used to diagnose many chromosomal disorders such as Down syndrome. Metaphase images are needed for chromosome analysis. Objective selections must be made during the acquisition of these images. Selecting of non-analyzable images could directly affect the results of chromosome analysis. In this study, a filter was developed that automatically detects analyzable metaphase images. The developed filter was used with the motorized microscope table and the analyzable metaphase images were detected. After expert evaluation on the results obtained, the average success rate of the filter was calculated as 98.9%. The filter performed an average run time of 76 milliseconds per square.
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    A Randomized Automated Thresholding Method to Identify Comet Objects on Comet Assay Images
    (Assoc Computing Machinery, 2017) Sehirli, Eftal; Turan, M. Kamil; Demiral, Emrullah
    Deoxyribonucleic acid (DNA) is an important molecule which has a tendency to easily have damage. Etiology of many diseases like cancer, cardiovascular disease, and immune deficiency is asserted to be based on DNA damage. Comet assay is a reliable, cheap and easy method to specify whether DNA has damage or not. The fact that the number of developing software applications on demand increases day by day comes into prominence of obtaining quick and accurate results in medicine field. In this study, a software application is developed which single comet objects on comet assay images are identified to perform analysis, calculation of comet parameters and decision regarding whether DNA has damage or not. Comet images are converted to red channel images, the randomized automated thresholding method is applied on red channel images and connected component labeling obtains each single comet object. This paper mainly focuses on specifications and mathematical model of the thresholding method.