LEE- Telekomünikasyon Mühendisliği-Doktora
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ÖgeClinical assessment of the microwave imaging system forbreast cancer screening and early detection(Graduate School, 2023-04-26) Janjic, Aleksandar ; Çayören, Mehmet ; Akduman, İbrahim ; 504182310 ; Telecommunication EngineeringFemale breast cancer has surpased lung cancer, as the most diagnosed cancer in women population, with around 2.3 million cases arising each year. If diagnosed in late stages, it can be highly lethal, with the survival rate of only 25%. Thus, detecting the cancer in an early stage can have a major impact on decreasing the death rate of the patients. Nowadays, mammography is considered as a gold standard for breast cancer screening and diagnostics. Beside mammography, ultrasound, and magnetic resonance imaging can be used to detect the cancer. However, there are several risk factors that are limiting mentioned imaging modalities, such as: ionizing radiation exposure, pain induced by breast compression, overdiagnosis, false-positive examinations, falsenegativity in dense breasts, operator dependancy, prolonged procedures, high hospital costs, and special facility requirements. Microwave breast imaging emerged as a promising novel imaging technology that can, potentially, contribute to the field of breast cancer early screening and diagnostics, mostly because of its non-ionizing and non-invasive nature. Harmless radiation offers the opportunity of frequent scanning, even for the women of an early age, such as 18. Early-age and routine tests are crucial, especially for women with hereditary genetic mutations, where there is a considerable risk of breast cancer appearance. Beside its non-ionizing, and non-invasive nature, microwave imaging offers fast and painless scans, which can significantly increase the number of breast check-up tests, consequently increasing the number of detected early-stage cancers. Consequently, microwave breast imaging can have can substantially impact on the long-term breast cancer survival rate. The technology itself utilizes the difference in electromagnetic properties of healthy and cancerous tissue, as well as the dielectric difference between different type of cancerous tissues (benign or malignant), to detect the presence of anomalies inside the patient's breast and provide their pathology. In the first part of the thesis, we integrated inverse scattering algorithm to acquire the microwave images, and provide information about breast cancer location (detect the breast cancer), from the data collected with the microwave breast imaging device, namely SAFE, developed by the joint work of Mitos Medikal Technologies A.S. and the Medical Device Research, Development, and Application Laboratory of Istanbul Technical University. Dataset used in the study (scans from 115 patients), was acquired through the clinical trials performed by the Marmara University School of Medicine. In addition to the breast lesion detection, we analyzed the effect of the factors of interest, such as: breast density and size, tumor size, as well as patient's age, on the SAFE clinical capabilities. Results show, that we were able to detect 63% of breast lesions, where the breast size had a high impact on the overall score. Significantly lower number of lesions were detected in smaller breasts (51%), compared to the large ones (74%). Density also influenced our inverse scattering approach, as the overal rate of 76%, we achieved in fatty breasts, decreased to 56% in dense breasts. Second part of the thesis is reserved for the machine learning approach, namely adaptive boosting, we implemented on the SAFE dataset, to classify breast lesions, based on their pathology. We used the same dataset as in the first part of the thesis. As in the previous study, we analyze the effect of breast density and size, tumor size, and patient's age, on the used data. In addition, we perform statistical analysis (two-sample t-test) to determine if the difference between the benign and malignant dataset exists. In the existing dataset, 70 benign, and 43 malignant lesions were present. We exclude two cases, due to the unknown pathology. Our machine learning approach achieved the accuracy of 78%, sensitivity of 79% and specificity of 77%. The results indicate that we were able to classify both, benign and malignant lesions, at similar rate. Participant's age was the only factor that highly affected our approach outcome, where the overall rate (accuracy) of the device in young patient group was 84%, compared to the 76% achieved in older patient group. In the third part of the thesis, we implement another machine learning approach, namely Gradient Boosting, to distinguish benign from malignant lesions, considering new dataset, acquired from latest SAFE clinical trials. Additionally, compared to the previous studies, we changed the measurement unit component of the device. Fiftyfour patients were analyzed, where 29 of them had benign, and 25 malignat findings. As in the previous study, we apply statistical analysis (two-sample t-test), to determine if the difference between the benign and malignant dataset exists. Sensitivity, specificity and accuracy we achieved were 80%, 83% and 81%, showing that, in this study as well, we were able to classify both benign and malignant lesions at similar rate, despite of the hardware and software changes implemented. Contrary to the previous studies, multiple factors (breast size, density and age) affected our approach outcome. We achieved significantly higher accuracy in larger breasts (86%), compared to the smaller ones (78%). Additionally, accuracy acquired in dense breast (67%) was significantly lower than in fatty ones (93%). At the end, our method accuracy was 88% in older patient group, compared to the 71% in younger group.
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ÖgeMicrowave imaging of breast cancer with contrast agents(Fen Bilimleri Enstitüsü, 2020) Yıldırım, Sema ; Çayören, Mehmet ; 648935 ; Elektronik ve Haberleşme Mühendisliği Ana Bilim DalıThe prevalence of breast cancer is seen in both sexes worldwide, however, it is the second type of cancer, which is diagnosed especially in women and results with a fatal outcome among cancer types. Breast cancer like other types of cancer manifests itself by changing breast cells for various reasons, firstly spreading to the surrounding cells and then to the tissues in the body. The spread of other cells under the influence of changing breast cells causes malignant tumors to appear. Hence, it is great of importance to control or stop the spread of from breast cells to other cells in the body. For this purpose, early-stage diagnosis studies for breast cancer have been a working area in which researchers showed great interest. In other words, early diagnosis techniques play a key role in determining the course of the disease. In this point, mammography technologies containing ionizing x-ray radiation are most frequently used for the early-stage breast cancer detection. The usage of x-ray radiation can damage to the body tissues. These technologies, which contain x-rays that can ionize tissues, bring along various limitations during measurement due to the prevalence of the disease especially in elderly people. The disadvantages of mammography techniques exhibit the need for new and alternative imaging methods. In recent years, many researchers have worked on breast imaging systems to handle the particular disadvantages of mammography technologies. In this context, the non-ionizing microwave imaging (MWI) method, reducing the risk of patient health, is seen as a more reliable and alternative imaging technology for the early-stage breast cancer detection. The breast imaging with MWI methods is based on the reconstruction of the dielectric permittivity profile of cancerous and healthy breast tissues. After completed the breast reconstruction, the cancerous tissues are diagnosed due to illustrate a higher dielectric permittivity profile than other healthy tissues in the breast. The purpose of these methods is to diagnose and display any cases other than normal that occur in the body. The most important feature of MWI methods is to carry a low-level risk of harm to the patient because of using non-ionizing electromagnetic waves. In addition to this, it can be used in ambulances and many other emergency points for early diagnosis. Notwithstanding all these advantages, the clinical acceptance of MWI methods for breast cancer has not been realized yet. Hence, MWI methods need to improve with new approaches to receive clinical acceptance. The process of imaging or reconstructing the electromagnetic properties of tissues is based on the inverse scattering theory, and there are several quantitative and qualitative imaging methods developed in this area. Benefit from these methods, the positions, shapes, and electromagnetic properties of diseased tissues in the body are obtained in two or three dimensions. The qualitative imaging methods generally give information about the positions and shapes of diseased tissues. The scattered fields from tumors are higher than other normal tissues allows the qualitative imaging methods to be easily applied. While the quantitative imaging methods provide information about the geometric shapes and positions of tumors, as well as numerical information about the dielectric properties. The most widely used the quantitative imaging methods available in the literature are contrast source inversion (CSI) and Newton-based methods. Within the scope of this thesis, all studies have been realized mainly on the solution methods of the inverse scattering problems. In other words, the alternative methods based on enhanced contrast agents are recommended for scatterer objects with different relative dielectric permittivity and magnetic permeability constants, especially for the microwave imaging methods used in breast cancer. The main purpose of these studies is to eliminate the resolution limitation of microwave imaging methods by using dielectric and magnetic contrast agents and to enable the proposed method to be used more efficiently for the diagnose of early-stage breast cancer. All studies can be categorized under three main headings: i) the reconstruction of dielectric permittivity profile based on quasi-Newton method ii) the enhanced-dielectric contrast agents based on the quasi-Newton method for microwave imaging, ii) the enhanced-magnetic contrast agents based on factorization method for microwave imaging. are higher than other normal tissues allows the qualitative imaging methods to be easily applied. While the quantitative imaging methods provide information about the geometric shapes and positions of tumors, as well as numerical information about the dielectric properties. The most widely used the quantitative imaging methods available in the literature are contrast source inversion (CSI) and Newton-based methods. Within the scope of this thesis, all studies have been realized mainly on the solution methods of the inverse scattering problems. In other words, the alternative methods based on enhanced contrast agents are recommended for scatterer objects with different relative dielectric permittivity and magnetic permeability constants, especially for the microwave imaging methods used in breast cancer. The main purpose of these studies is to eliminate the resolution limitation of microwave imaging methods by using dielectric and magnetic contrast agents and to enable the proposed method to be used more efficiently for the diagnose of early-stage breast cancer. All studies can be categorized under three main headings: i) the reconstruction of dielectric permittivity profile based on quasi-Newton method ii) the enhanced-dielectric contrast agents based on the quasi-Newton method for microwave imaging, ii) the enhanced-magnetic contrast agents based on factorization method for microwave imaging. In the second part of the thesis, all studies on the use of dielectric contrast agents for breast cancer have been conducted. Unlike the first part here, the QN-CSI method by using the dielectric contrast agents is explored in more different and realistic cases. Firstly, a canonical breast model is designed using the HFSS electromagnetic 3-D simulation program. The designed breast model consists of structures had different dielectric permittivity and conductivity values, which are lined up from the outermost muscle, skin, glandular breast tissue, and tumor respectively. Firstly, the breast model is simulated to generate the forward scattering solution for two different cases, which are the presence and absence of dielectric contrast agents. After that, the scattered fields from the breast model are collected from different illumination angles and the field difference is calculated by using these two simulation results. The proposed QN-CSI method realizes the inverse scattering solution with this difference dataset and in this manner, the tumorous tissues placed in the breast model are imaged. Within the scope of this section, the image acquisition skill of the proposed method for different status parameters is examined. In this context, all simulations are operated at f = 2GHz, and two spherical tumors with radius of 1cm are located at (x1, y1,z1) = (3cm,4cm,−2cm) and (x2, y2,z2) = (3cm,4cm,2cm). The dielectric permittivity and conductivity constants of the placed tumors are selected as εr = 43 and σ = 1S/m. Later, the values of these dielectric constants are increased up to 37% under the assumption of using contrast agents at the second simulation. After completed these two simulations, the difference dataset is calculated and the tumors are imaged by the QN-CSI method. The fact notwithstanding that this image is not an anatomical breast model, it contains the expected tumorous tissues. At the end of this section, several simulations according to different status parameters are performed by changing the number of plane waves, the radiuses of tumors, and the conductivities of tumors In this chapter, all numerical results are given by comparison with the CSI method. In the third and last part of the thesis, the magnetic contrast agents are carried out instead of the dielectric contrast agents. Similar to the second part, but here, the changing of magnetic permeability constant (µr) depended on the frequency and the effect of an externally applied magnetic field are taken into account. Namely, magnetic nanoparticles(MNPs) are employed for the magnetic contrast enhancement. The different types of MNPs such as superparamagnetic iron oxide nanoparticles (SPIONs), which are most often preferred, are used to detect abnormality in several medical imaging methods. Since the biocompatible SPIONs are functionalized by the effect of the polarized magnetic field externally applied from the outside. While normal tissue cells do not react to the external magnetic fields, the magnetic nanoparticles nonlinearly behave depending on the value of the applied magnetic field. As a result of this, the changing of magnetic contrast is displayed. In this thesis, UWCEM numerical breast phantom repository, which includes several realistic experimental breast models, is used as a database to investigate the enhanced magnetic contrast agents. The phantom repository consists of numerical breast phantoms produced from anatomically realistic magnetic resonance imaging (MRI) for breast cancer detection and treatment applications. Here, the third phantom in ACR class 3, which contains heterogeneously dense fibroglandular breast phantom is selected and embedded into a 3D electromagnetic simulation program adding two tumors with a diameter of 0.5cm located into the model. The relative dielectric permittivity εr = 4 is chosen for the background medium. In the following step, the simulations are performed for two different cases over the 1.91GHz − 2.04GHz frequency band with N = 18 dipole antennas. After both simulations are completed for the given frequency range, the difference between the multi-static response matrices included reflection coefficients are calculated and the inverse problem solution is realized. In this part of the thesis, the factorization method is chosen to reconstruct the breast model. Eventually, the locations and shapes of the tumors are easily determined by the factorization method based on SPIONs contrast agents.
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ÖgeNovel complex dielectric permittivity measurement methods with open ended coaxial probes(Graduate School, 2022-12-02) Dilman, ismail ; Çayören, Mehmet ; 504162313 ; Telecommunications EngineeringNowadays, microwave dielectric spectroscopy is a popular research topic for scientists with use in a broad area. Microwave dielectric spectroscopy is realized with various methods. The most commonly applied methods are coaxial probe methods, transmission line methods, free space methods, resonant methods, and parallel plate capacitor methods. The open-ended coaxial probe method differs from microwave dielectric spectroscopy by being broadband, non-destructive technique. In addition, it is suitable for measuring lossy materials. The open-ended coaxial probe techniques are based on retrieving the complex dielectric permittivity (CDP) from the aperture admittance of the probe. This process is carried out by using the reflection coefficients from the vector network analyzer. These are realized in two steps. In the first step, real reflection coefficients are determined from the measured reflection coefficients from the calibration procedure. Next step, by using the relation between the aperture admittance and CDP, electrical properties are obtained. The main weakness of the technique is a high error rate that prevents accurate and stable results. This thesis first gives a brief overview of the realization of microwave dielectric measurement with an open-ended coaxial probe. It will then describe one of the previous methods, the rational functional model, for an open-ended probe technique. Validation of the method is tested in both simulation and measurement setups. Moreover, the effectiveness of methods is shown in retrieving the biological sample. In addition, the mentioned technique for a commercial probe improved in the third section. In the following section, a new method to reduce the error rate of dielectric measurements of the open-ended coaxial probe has been developed. This method takes advantage of the observation that electrical properties of materials variations are continuous functions of frequency. In particular, we derive a mathematical model that enforces spectral continuity by directly incorporating the Debye relaxation model. In addition, the robustness of the proposed methods is tested with a low-sensitive pocket network analyzer. Finally, a novel approximation in which measurement uncertainty and experimental noise are addressed in determining the CDP processes is presented. However, these effects are not considered in previous open-ended coaxial probe measurement studies. Take advantage of this extra information to enhance the improving measurement accuracy and results in similar problems. Benefit from statistical information; we define a new cost function based on maximum-likelihood estimation. The obtained results have been compared with the values given in the literature. The results of that studies demonstrated that mentioned methods are achievable in reducing errors. In addition to the open-ended coaxial probe, the proposed approach can accurately obtain the Debye parameters of the MUT. Furthermore, extending the method for different relaxation models is straightforward by introducing additional partial derivatives of the new parameters.