Yazar "Erbas, Ali" seçeneğine göre listele

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    Convolutional Neural Network and Fuzzy Logic-based Hybrid Melanoma Diagnosis System
    (Kaunas Univ Technology, 2021) Yalcinkaya, Fikret; Erbas, Ali
    Studies on the detection of early stage melanoma have recently gained significant interest. Computer aided diagnosis systems based on neural networks, machine learning, convolutional neural networks (CNNs), and deep learning help early stage detection considerably. The colour and shapes of the images created by the pixels are crucial for the CNNs, as the pixels and associated pictures are interrelated just as a person's fingerprint is unique. By observing this relationship, the pixel values of each picture with its neighborhoods were determined by a fuzzy logic-based system and a unique fingerprint matrix named Fuzzy Correlation Map (FCov-Map) was produced. The fuzzy logic system has four inputs and one output. The advantage of CNNs trained with fuzzy covariance maps is to eliminate both the limited availability of medical grade training data and the need for extensive image preprocessing. The fuzzy logic output is fed to the pretrained AlexNet CNN algorithm. To deliver a reliable result, a deep CNN needs a large amount of data to process. However, to obtain and use the required sufficient data for diseases is not cost- and time-effective. Therefore, the suggested fuzzy logic-based fuzzy correlation map is tackling this issue to solve the limitedness of training CNN data set.
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    The design of an embedded spinal cord stimulator
    (Tubitak Scientific & Technical Research Council Turkey, 2014) Yalcinkaya, Fikret; Erbas, Ali
    Spinal cord stimulation is a physical therapy methodology utilizing electrical impulses, pulses, or a combination of various standard electrical waveforms to block pain. However, standard forms are not functioning effectively for each illness due to the unique conditions of the patient. Therefore, patient-specific waveforms (or user-defined waveforms) integrated with nondestructive, complete, or partially noninvasive and effective medical instruments to help relieve pain are required. In the literature, 2 different designs have been discussed: the bedside/portable and the implantable/surgical types. This work is introducing a new hybrid type: a portable touch-screen multichannel embedded spinal cord stimulator. This work is made of 3 parts: the hardware and the software designs, and an embedded interface introducing the system to external medical systems or patients. The hardware and software designs are explained in detail. The S3C2440 microprocessor-based embedded spinal cord stimulator generates not only 6 standards types of signals, but also user defined waveform(s). This requires medical experts' close relation, consultation, and cooperation with biomedical engineers who are able to design and develop new instruments with new requirements. In this paper, a microprocessor-based spinal cord stimulator is developed in the Samsung S3C2440 environment and PIC18F452-based channel boards. The S3C2440 environment is the main controller unit and the therapy signal is produced by the channel boards as a signal generator. The software is prepared by MS Visual Studio 2008 and Hi-Tech C. The frequency, duty-cycle, and amplitudes of the pulses can be altered by software control. The architecture of the stimulators is designed to be modular; therefore, its different blocks can be reused as standard building blocks. The designed and developed embedded spinal cord stimulator enables both home and bedside health care. The system is battery-operated, portable, user-friendly, and cost-effective.
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    Image Masking and Enhancement System for Melanoma Early Stage Detection
    (Tech Science Press, 2022) Yalcinkaya, Fikret; Erbas, Ali
    Early stage melanoma detection (ESMD) is crucial as late detection kills Computer aided diagnosis systems (CADS) integrated with high level algorithms are major tools capable of ESMD with high degree of accuracy, specificity, and sensitivity. CADS use the image and the information within the pixels of the image. Pixels' characteristics and orientations determine the colour and shapes of the images as the pixels and associated environment are closely interrelated with the lesion. CADS integrated with Convolutional Neural Networks (CNN) specifically play a major role for ESMD with high degree of accuracy. The proposed system has two steps to produce high degree of accuracy; the first is the Fuzzy-Logic (FL) based maskProd and pixel Enhancement vectors and the second is integration with deep CNN algorithms. The vectors, maskProd and pixel Enhancement, are based on lesion masking and image enhancement via fuzzy logic as hSvMask production has three inputs; sChannel, entropyFilter and distanceVector. The originality of this paper is based on the regional enhancement of each pixel of the image by fuzzy-logic. To change the brightness of an image by the conventional methods (CM), it is required to multiply the value of all and each pixels of the image by the same constant or weight value in order to generate new values of the pixels. But in the proposed method, FL determines a special and specific constant or weight value for every single pixel of the image; called a variable weight value. Secondly via conventional or classical methods of image processing, mask production is realized based on the threshold value predetermined, and this threshold value decides whether the image lesion is melanoma or not. CM use constant weight values but in the method suggested, FL determines a specific variable weight value for every single pixel of the image. Secondly CMs realize the mask production using predetermined threshold values, but proposed method suggests a new way capable of detecting pixels in the lesion-free regions, to do that, a system using FL was developed for each and every single pixel via the data obtained from three sources: the s-channel of the HSV (Hue, Saturation and Value) colour space, distance vector, and image entropy vector. The proposed method and its integration with algorithms; such as AlexNet, GoogLeNet, Resnetl8, VGG-16, VGG-19, Inception-V3, ShuffleNet and Xception, detected the melanoma with an accuracy of 86.95, 85.60, 86.45, 86.70, 85.47, 86.76, 86.45 and 85.30 percentages, respectively.
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    Mathematical Modelling of Human Heart as a Hydroelectromechanical System
    (Ieee, 2013) Yalcinkaya, Fikret; Kizilkaplan, Ertem; Erbas, Ali
    Different electrical models of human heart, partial or complete, with linear or nonlinear models have been developed. In the literature, there are some applications of mathematical and physical analog models of total artificial heart (TAH), a baroreceptor model, a state-space model, an electromechanical biventricular model of the heart, and a mathematical model for the artificial generation of electrocardiogram (ECG) signals. Physical models are suitable to simulate real physiological data based on proper experimental set up present. This paper introduces a new mathematical modelling of human heart as a hydroelectromechanical system (HEMS). This paper simulates the human heart based on three main functions: hydraulic, electrical and mechanical parameters. Hydro-mechanical model developed then has been transformed into electrical domain and simulation has been carried out according to the mathematical model or formulations obtained using Laplace transform. This electrical model / circuit is then tested by MATLAB based simulations and results found are comparable with the normal ECG waveforms so that these simulated results may be useful in clinical experiments. In this model basic electrical components have been used to simulate the physiological functions of the human heart. The result is a simple electrical circuit consisting of main electrical parameters that are transformed from hydraulic models and medical physiological values. Developed MATLAB based mathematical model will primarely help to understand the proper functioning of an artificial heart and its simulated ECG signals. A comprehensive model for generating a wide variety of such signals has been targeted for future in this paper. This research especially focuses on modelling human heart as a hydro-electro-mechanical system with three case studies.