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Öğe 3 dimensional monomodal intensity based medical image registration for brain tumor progression analysis(Karabük Üniversitesi, 2018) Irmak, Emrah; Türköz, Mustafa BurakBeynin Manyetik Rezonans (MR) görüntüleri nörolojik araştırma, tanı ve tedavi için anatomik bir anlam içerir. Bu nedenle, MR görüntülerinin seri taramalarındaki değişimleri değerlendirmek kanser araştırmaları alanında önemli bir konu haline gelmiştir. Tümörün hacim ilerlemesi ve tümör değişim hacmi hesaplanması, kanser araştırmalarında çok yaygın bir yer teşkil etmektedir. Tümör hacim değişim analizi iki şekilde gerçekleştirilebilir. Birincisi, literatürdeki çeşitli matematiksel formülleri kullanmak, ikincisi ise görüntü çakıştırma-bölütleme yöntemlerini kullanmaktır. Görüntü çakıştırma farklı zamanlarda, farklı makinelerden veya sensörlerden veya farklı bakış açılarından elde edilen iki veya ikiden fazla görüntüyü üst üste getirmek için kullanılan temel bir işlemdir. Bu tezde, beyin tümörü büyümesini 3 boyutlu (3B) bir şekilde araştırmak için, çoklu beyin görüntüleme taramalarının çakıştırılması ve bölütlenmesi suretiyle objektif bir uygulama yapılmıştır. 3B tıbbi görüntü çakıştırma-bölütleme algoritması kullanılarak, beyin tümörü bulunan bir hastanın MR görüntüleri, aynı hastadan farklı bir zamanda elde edilen farklı MR görüntüleriyle çakıştırılır, böylece hastanın beynindeki tümörün büyümesi araştırılmaktadır. Beyin tümörü hacim değişim ölçümü, aynı zamanda bu tezde matematiksel formüllerle de yapılarak önerilen uygulama test edilmektedir. 19 hastaya tıbbi görüntü çakıştırma-bölütleme yöntemi uygulanmış ve tatmin edici sonuçlar elde edilmiştir. Bu çalışmanın bir diğer ilgi çekici yanı hastaların büyümüş, azalmış ve değişmemiş beyin tümörü parçalarının zaman içinde üç boyutlu (3B) bir şekilde bireysel olarak araştırılıp hacimlerinin hesaplanmasıdır. Bu çalışma MR tarafından elde edilen anatomik bilgilerinin klinik ve araştırma amaçlı korelasyonu için kritik bir uygulamadır. Bu tez, tıbbi görüntü çakıştırma ve tümör hacmi değişim analizi ile ilgilenen araştırmacılar için kapsamlı bir referans kaynağı sağlamayı amaçlamaktadır.Öğe Brain tumor detection using monomodal intensity based medical image registration and matlab(2016) Irmak, Emrah; ErÇelebi, Ergun; Ertaş, Ahmet H.The registration concept is one of the most important and popular aspects of digital image processing. Using suitable computer programming techniques and transformation between two images, a new much more informative image can be found. In this paper, three important and basic medical image registration (MIR) methods, namely MIR by maximization of mutual information, MIR using cross correlation (Fourier transform approach), and MIR by minimization of similarity metric, were proposed and accordingly two comprehensive applications were performed using MIR by minimization of the similarity metric, which uses the sum of the squared differences metric as a metric and the regular step gradient descent optimizer as an optimizer. What is more, MR images of two patients who had brain tumors are registered with different MR images of the same patients at a different time so that growthiness of the tumor inside the patient s brain can be investigated. It is thought that this paper will provide a comprehensive reference source for researchers involved in MIR because this paper contains not only a powerful explanation of three methods of medical image registration but also provides two experimental results using MIR by minimization of the similarity metric.Öğe Brain tumor detection using monomodal intensity based medical image registration and MATLAB(Tubitak Scientific & Technological Research Council Turkey, 2016) Irmak, Emrah; Ercelebi, Ergun; Ertas, Ahmet H.The registration concept is one of the most important and popular aspects of digital image processing. Using suitable computer programming techniques and transformation between two images, a new much more informative image can be found. In this paper, three important and basic medical image registration (MIR) methods, namely MIR by maximization of mutual information, MIR using cross correlation (Fourier transform approach), and MIR by minimization of similarity metric, were proposed and accordingly two comprehensive applications were performed using MIR by minimization of the similarity metric, which uses the sum of the squared differences metric as a metric and the regular step gradient descent optimizer as an optimizer. What is more, MR images of two patients who had brain tumors are registered with different MR images of the same patients at a different time so that growthiness of the tumor inside the patient's brain can be investigated. It is thought that this paper will provide a comprehensive reference source for researchers involved in MIR because this paper contains not only a powerful explanation of three methods of medical image registration but also provides two experimental results using MIR by minimization of the similarity metric.Öğe Investigation of Tribocorrosion Properties of Titanium Implant used in Orthopedics(Ieee, 2022) Irmak, Emrah; Ugurlu, Bilal; Incesu, AlperA titanium implant is a mechanical system that undergoes tribocorrosion at the interface between the implant and the abutment alloy, where material degradation is common. When various titanium implant materials, which are used to fix the bones broken by trauma or to replace a joint or bones, such as osteoporosis, are exposed to a simulated body fluid (SBF), the effects of wear and corrosion phenomena in these titanium implant materials are observed to be determined quantitatively. For the samples extracted from Titanium-Ti6Al4V screws belonging to two different companies (A and B), very important parameters for tribocorrosion such as wear rate, depth of wear and corrosion rate were determined experimentally in the laboratory environment. The results were examined how suitable titanium is to resist material loss in body implants due to both wear and corrosion. In addition, it was determined that the wear rates obtained from the sample belonging to company B were more stable than those of company A, and the corrosion rates (0.0047 mm/year) obtained from the sample of company A were lower than those of company B.Öğe A Review of Robust Image Enhancement Algorithms and Their Applications(Ieee, 2016) Irmak, Emrah; Ertas, Ahmet H.The essential target of image enhancement is to minimize noise from a digital image by keeping the intrinsic information of the image preserved. The main difficulty in image enhancement is determining the criteria for enhancement and, therefore, more than one image enhancement techniques are empirical and require interactive procedures to obtain satisfactory results. In this paper robust image enhancement algorithms are discussed, implemented to noisy images and compared according to their robustness. The algorithms are especially able to improve the contrast of medical images, fingerprint images and selenography images by means of software techniques. When deciding that one image has better quality than another image, quality measure metrics are needed. Otherwise comparing image quality just by visual appearance may not be objective because images could vary from person to person. That is why quantitative metrics are crucial to compare images for their qualities. In this paper Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) quality measure metrics are used to compare the image enhancement methods systematically. All the methods are validated by the performance measures with PSNR and MSE. It is believed that this paper will provide comprehensive reference source for the researchers involved in image enhancement field.Öğe A Useful Implementation of Medical Image Registration for Brain Tumor Growth Investigation in a Three Dimensional Manner(Int Journal Computer Science & Network Security-Ijcsns, 2017) Irmak, Emrah; Turkoz, Mustafa BurakImage registration or as sometimes called image matching is the operation of geometrically taking two or more than two images to the same coordinate system. Image registration is a fundamental job used to match two or more than two images acquired, for example, at different times, from different machines or sensors, or from different viewpoints. Aligning medical images for neurologic research, diagnosis and treatment can be considered as a specific example of image registration. Magnetic Resonance (MR) images of the brain contain anatomic sense for neurologic research, diagnosis and treatment. Therefore to evaluate changes in serial scans of MR images becomes an important issue in medical image registration field. In this paper an objective application of registration of multiple brain imaging scans is used to investigate brain tumor growth in a 3 dimensional (3D) manner. Using 3D medical image registration algorithm, multiple scans of MR images of a patient who has brain tumor are registered with different MR images of the same patient acquired at a different time so that growth of the tumor inside the patient's brain can be investigated. MR images are registered with 3D accuracy on the order of two corresponding images. Technique is implemented to 19 patients and satisfactory results are obtained. This study is a critical application for correlation of anatomic information obtained by MR for clinical and research purposes. This paper is intended to provide a comprehensive reference source for researchers involved in medical image registration and tumor growth investigation.
