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Öğe A Realistic Breast Phantom Proposal for 3D Image Reconstruction in Digital Breast Tomosynthesis(Sage Publications Inc, 2022) Polat, Adem; Kumrular, Raziye KubraObjectives: Iterative (eg, simultaneous algebraic reconstruction technique [SART]) and analytical (eg, filtered back projection [FBP]) image reconstruction techniques have been suggested to provide adequate three-dimensional (3D) images of the breast for capturing microcalcifications in digital breast tomosynthesis (DBT). To decide on the reconstruction method in clinical DBT, it must first be tested in a simulation resembling the real clinical environment. The purpose of this study is to introduce a 3D realistic breast phantom for determining the reconstruction method in clinical applications. Methods: We designed a 3D realistic breast phantom with varying dimensions (64(3)-512(3)) mimicking some structures of a real breast such as milk ducts, lobules, and ribs using TomoPhantom software. We generated microcalcifications, which mimic cancerous cells, with a separate MATLAB code and embedded them into the phantom for testing and benchmark studies in DBT. To validate the characterization of the phantom, we tested the distinguishability of microcalcifications by performing 3D image reconstruction methods (SART and FBP) using Laboratory of Computer Vision (LAVI) open-source reconstruction toolbox. Results: The creation times of the proposed realistic breast phantom were seconds of 2.5916, 8.4626, 57.6858, and 472.1734 for 64(3), 128(3), 256(3), and 512(3), respectively. We presented reconstructed images and quantitative results of the phantom for SART (1-2-4-8 iterations) and FBP, with 11 to 23 projections. We determined qualitatively and quantitatively that SART (2-4 iter.) yields better results than FBP. For example, for 23 projections, the contrast-to-noise ratio (CNR) values of SART (2 iter.) and FBP were 2.871 and 0.497, respectively. Conclusions: We created a computationally efficient realistic breast phantom that is eligible for reconstruction and includes anatomical structures and microcalcifications, successfully. By proposing this breast phantom, we provided the opportunity to test which reconstruction methods can be used in clinical applications vary according to various parameters such as the No. of iterations and projections in DBT.Öğe An alternative approach to tracing the volumic proliferation development of an entire tumor spheroid in 3D through a mini-Opto tomography platform(Elsevier Ltd, 2022) Polat, Adem; Gökturk, DilekMicroscopy, which is listed among the major in-situ imaging applications, allows to derive information from a biological sample on the existing architectural structures of cells and tissues and their changes over time. Large biological samples such as tumor spheroids cannot be imaged within one field of view, regional imaging in different areas and subsequent stitching are required to attain the full picture. Microscopy is not typically used to produce full-size visualization of tumor spheroids measuring a few millimeters in size. In this study, we propose a 3D volume imaging technique for tracing the growth of an entire tumor spheroid measuring up to 10 mm using a miniaturized optical (mini-Opto) tomography platform. We performed a primary analysis of the 3D imaging for the MIA PaCa-2 pancreatic tumoroid employing its 2D images produced with the mini-Opto tomography from different angles ranging from -25 ° to +25 ° at six different three-day-apart time points of consecutive image acquisition. These 2D images were reconstructed by using a 3D image reconstruction algorithm that we developed based on the algebraic reconstruction technique (ART). We were able to reconstruct the 3D images of the tumoroid to achieve 800 × 800-pixel 50-layer images at resolutions of 5–25 μm. We also created its 3D visuals to understand more clearly how its volume changed and how it looked over weeks. The volume of the tumor was calculated to be 6.761 mm3 at the first imaging time point and 46.899 mm3 15 days after the first (at the sixth time point), which is 6.94 times larger in volume. The mini-Opto tomography can be considered more advantageous than commercial microscopy because it is portable, more cost-effective, and easier to use, and enables full-size visualization of biological samples measuring a few millimeters in size.Öğe Bozulmuş İnsansız Hava Araçları İçin Minimum Mesafe Ve Minimum Zaman Optimal Yol Planlamalarının Çok Boyutlu Makine Öğrenmesi Yaklaşımları Ile Başarımı(2023) Tutsoy, Önder; Polat, Adem; Hendoustanı, Davood Asadıİnsansız Hava Araçları (İHA) bilinmeyen ortamlarda, dinamik çevre koşullarında görev yapabilmekte ve beklenen ya da beklenmeyen birçok arızalarla karşılaşabilmektedirler. Bu sebeplerden dolayı otonom bir İHA, acil durumlarda minimum mesafe veya minimum sürede en uygun konuma inebilecek özellikler ile donatılmalıdırlar. Hasarlar ve bozulmalar, kararsız (unstable) ve belirsiz (uncertain) İHA dinamiklerini (dynamics) değiştirdiğinden, yol planlama (path planning) algoritmaları uyarlanabilir (adaptive) ve modelden bağımsız (model free) olmalıdır. Bunların yanında, İHA için tasarlanan yol planlama optimizasyon problemleri, gerçek zamanlı uygulamaların başarımı için hayati olan, aktüatör doygunluklarını (actuator saturations), kinematik ve dinamik kısıtlamaları (kinematic and dynamic constraints) dikkate almalıdır. Bu nedenle bu projede, bir İHA?nın bozulması sonucu ortaya çıkan parametrik belirsizlikleri (parametric uncertainties) ve çeşitli kısıtlamaları dikkate alan üç boyutlu yol planlama algoritmaları quadrotorlar için geliştirmiştir. Bu projede, öteleme (translation), dönme (rotation), Euler açıları (Euler angle), ilgili minimum zaman ve minimum mesafe kontrol sinyalleri çok boyutlu parçacık sürü optimizasyonu (multi-dimensional particle swarm optimization) ve çok boyutlu genetik algoritması (multi-dimensional genetic algorithm) meta-sezgisel makine öğrenmesi yaklaşımları ile elde edilmiştir. Algoritmalar hem simülasyon ortamında hem de deneysel ortamlarda değerlendirilmiş ve performansları karşılaştırılmıştır. Bu projenin bütçesi ile sadece lisans, yüksek lisans ve doktora öğrencilerine burs sağlanmış ve bu alanda yeni projelerimizin alt yapısı oluşturularak yeni projeler sunulmuştur. Projenin sonuçlarında, çok boyutlu genetik algoritmanın kısıtlamalar altında daha kısa minimum mesafe ve minimum zaman yolları üretebildiği gösterilip doğrulanmıştır. Gerçek zamanlı deneyler, quadrotorun mevcut maksimum rotor hızlarını kullanarak üretilen hedef yolu tam olarak izleyebildiği ayrıca kanıtlanmıştır.Öğe Comprehensive Analysis of Alpha-Parametric Set for the Calculation of Intersection Lengths of Radiological Ray Path in Siddon's Algorithm Used in 3D Image Reconstruction(2021) Polat, AdemThe Siddon algorithm is one of the radiological ray path (x-ray) calculation tools used in 3D image reconstruction in medical imaging. In the algorithm, a set of alpha-parametric values is computed containing the length and index values where the voxel array of the x-ray intersects the x-y-z axes. In the alpha-set creation section of the Siddon algorithm, the set elements are sorted from small to large, but some elements have been noticed to have the same value in simulations. These elements are used to calculate which voxels are hit by the ray along the radiological path and at what ratio, but it was recognized that some values of the set were zero, which means some rays did not intersect some voxels at all. This situation may lead to data loss in 3D image reconstructions in medical imaging such as digital breast tomosynthesis (DBT) and computed tomography (CT) especially for huge dimensions such as size up to 800×800×50. Considering the mentioned problems, in this study, the effect of using or eliminating the same repetitive values in the alpha parametric set of the Siddon algorithm on calculations was investigated. To prove our proposal, we performed 3D image reconstruction (lossless and lossy) of a synthetic phantom at a size of 100×100×50. Using special functions that do not take into account the duplicate values in the algorithm, excluding the duplicate values from the calculation solved the stated problems (lossless reconstruction). In this way, data loss that may occur in 3D image reconstruction was reduced since voxel indices and intersection lengths were matched correctly and meaningfully.Öğe Determination of Appropriate Thresholding Method in Segmenta-tion Stage in Detecting Breast Cancer Cells(2022) Akbaba, Cihat Ediz; Polat, AdemAs in all cancer types, the early detection of breast cancer is vital in terms of patients hold- ing on to life. Today, computer-aided image processing systems play an important role in the detection of diseases. Analyzing the imag-es with accurate image processing methods is very important for professionals to interpret the images and to devel-op the treatment methods for diseases appropriately. The images containing cancer cells (tumoroid) used in this study were obtained from the mini-Opto to- mography device that creates 3D images by reconstruction of 2D imag-es taken from different angles. It is an electronic, mechanical, and software-based device capable of 3D imaging of tumoroids up to 1 cm in diameter in size. Observing an entire tumor spheroid that has the size of several centi-meters in size in a single square image with a microscope is not possible, but with mini-Opto tomography it is possi-ble. In our study, a few layers of 3D images of the tumoroid produced by MCF-7 breast cancer cells obtained on the different days from the mini-Opto device were used. Image thresholding offers many advantages at the seg-mentation stage in order to distinguish the target objects. In this study, the determination of the most appropriate thresholding method for detecting the main tumor masses in the layered images was investigated. Moreover, the contours of the tumoroid were determined in the original images based on applying the outcomes of thresholding. While various thresholding methods have been applied on diverse images in the literature, we have applied a few thresholding methods to small tumors up to 2 mm in size. As a result of the qualitative assessment based on the results of the contour drawings on the thresholded images, the global thresholding and adaptive thresholding meth- ods gave the best results.Öğe Klinik Uygulamalarda İleri Biyomedikal Görüntüleme Teknolojileri(2021) Kumrular, Razıye Kubra; Polat, AdemHastalıkların tıbbi tanı ve tedavisinde görüntüleme çok önemli bir yer tutmaktadır. Biyomedikal görüntüleme teknolojileri sayesinde, vücudun içini invaziv olmayan yöntemlerle görüntüleyen tıbbi görüntüleme araçları geliştirilmiştir. Günümüz klinik uygulamalarındaki görüntüleme teknikleri ile iyonize ve iyonize olmayan radyasyonun, insan vücuduyla etkileşimi kullanılarak yüksek çözünürlükte tıbbi görüntüler üretilmektedir. Bu makalede hali hazırda kullanılan ileri biyomedikal görüntüleme teknolojileri kapsamında; Röntgen (X-ray) görüntüleme (X-ray radyografisi), bilgisayarlı tomografi (BT), sayısal meme tomosentezi (DBT), manyetik rezonans görüntüleme (MRI), fonksiyonel manyetik rezonans görüntüleme (fMRI), tek foton emisyonlu bilgisayarlı tomografi (SPECT), pozitron emisyon tomografi (PET), ultrason görüntüleme, Doppler ultrason, elektrik empedansı tomografisi (EIT) ve kızılötesi termal görüntüleme (IRT) sırasıyla incelenmiştir. Bu tekniklerin çalışma prensipleri, faydaları, riskleri, avantajları, dezavantajları ve uygulama alanları ayrıntılarıyla sunulmuştur. İncelenen teknikler için, görüntü kalitesi (mekânsal çözünürlük ve kontrast), radyasyonun vücuda etkisi (iyonizasyon seviyesi) ve sistemin kullanılabilirliği (gerçek zamanlı bilgi ve maliyeti) ve uygulama alanları hakkında karşılaştırmalı bilgiler verilmiştir.Öğe Linear and non-linear dynamics of the epidemics: System identification based parametric prediction models for the pandemic outbreaks(ISA - Instrumentation, Systems, and Automation Society, 2022) Tutsoy, Önder; Polat, AdemCoronavirus disease 2019 (COVID-19) has endured constituting formidable economic, social, educational, and phycological challenges for the societies. Moreover, during pandemic outbreaks, the hospitals are overwhelmed with patients requiring more intensive care units and intubation equipment. Therein, to cope with these urgent healthcare demands, the state authorities seek ways to develop policies based on the estimated future casualties. These policies are mainly non-pharmacological policies including the restrictions, curfews, closures, and lockdowns. In this paper, we construct three model structures of the SpInItIbD-N (suspicious Sp, infected In, intensive care It, intubated Ib, and dead D together with the non-pharmacological policies N) holding two key targets. The first one is to predict the future COVID-19 casualties including the intensive care and intubated ones, which directly determine the need for urgent healthcare facilities, and the second one is to analyse the linear and non-linear dynamics of the COVID-19 pandemic under the non-pharmacological policies. In this respect, we have modified the non-pharmacological policies and incorporated them within the models whose parameters are learned from the available data. The trained models with the data released by the Turkish Health Ministry confirmed that the linear SpInItIbD-N model yields more accurate results under the imposed non-pharmacological policies. It is important to note that the non-pharmacological policies have a damping effect on the pandemic casualties and this can dominate the non-linear dynamics. Herein, a model without pharmacological or non-pharmacological policies might have more dominant non-linear dynamics. In addition, the paper considers two machine learning approaches to optimize the unknown parameters of the constructed models. The results show that the recursive neural network has superior performance for learning nonlinear dynamics. However, the batch least squares outperforms in the presence of linear dynamics and stochastic data. The estimated future pandemic casualties with the linear SpInItIbD-N model confirm that the suspicious, infected, and dead casualties converge to zero from 200000, 1400, 200 casualties, respectively. The convergences occur in 120 days under the current conditions.Öğe Optimization and alternative image processing approach for the comprehensive assessment of delamination and uncut fiber in drilling fiber metal laminate(Springer Heidelberg, 2022) Ekici, Ergun; Motorcu, Ali Rıza; Polat, AdemIn this study, hole exit delamination and uncut fiber (UCF) formation in the drilling of carbon fiber-reinforced aluminum laminates (CARALL) were investigated. The adjusted delamination factor (F-da) was used to assess delamination. The experiments were carried out using a brad spur drill (Tool 1), a twist drill (Tool 2), and a dagger drill (Tool 3) tool. A multi-mapped image processing model (MMIPM) was developed for an advanced and comprehensive delamination assessment in images by evaluating F-da and UCF parameters. In order to provide more information about the preferential orientation of delamination, in addition to F-da, conventional delamination factor (F-d) and minimum delamination factor (F-dmin) were calculated and a comparison of all delamination approaches was performed. Furthermore, the PROMETHEE-GAIA method was used to perform multi-objective optimization of F-da and UCF. The minimum F-da and UCF values were achieved with the twist drill (Tool 2). Vc = 118 m/min and f = 0.156 mm/rev were optimal conditions for minimum F-da and UCF.Öğe The comprehensive analysis of the determination of wavelet function-level pair for the decomposition and reconstruction of artificial S1 heart signals by using multi-resolution analysis(Çanakkale Onsekiz Mart Üniversitesi, 2021) Polat, AdemTwo major sounds of the normal heart sound like “lub dub”. The “lub” is the first heart sound, commonly termed S1 results from mitral (M1) and tricuspid (T1) valve closure at the start of systole. In this work, the noisy-S1 heart signal was investigated to separate M1 and T1 components of it by making the comprehensive analysis of the determination of wavelet function-level pair for the decomposition and reconstruction of artificial S1 by using multiresolution analysis (MRA) and discrete wavelet transform (DWT). For this purpose, a synthetic S1 and its three different noisy-S1 signals were created by using the linear chirp transient model and then decomposed to their approximations and details at three different decomposition levels (3,4,5). 86 daughter wavelets of Biorthogonal, Coiflet, Daubechies, and Symlet were used to reconstruct noisy-S1 signals using comprehensive MRA&DWT. S1 and reconstructed noisy-S1 were compared qualitatively and quantitatively. For quantitative assessment, signal-to-noise-ratio (SNR), peak-SNR (PSNR), root-mean-square-error (RMSE), and structural-similarity (SSIM(%)) metrics were used for noisy-S1 signals at 3–4-5 decomposition levels. In the final evaluation of 86 daughter wavelets, db5, bior3.3, and bior3.9 performed superior results both qualitatively and quantitatively. The db5 was the superior one qualitatively at level 5, and quantitatively, the SNR values of the reconstructed signal by db5 were 8.620, 8.009, and 6.333 for %5-,%10-, and %20-noisy heart signals, respectively. The study proved that MRA&DWT provides a comprehensive analysis opportunity consisting of 86 daughter wavelets for perfect reconstruction of the S1 heart signals and detecting transients between M1 and T1 components.Öğe Tracing 2D Growth of Pancreatic Tumoroids Using the Combination of Image Processing Techniques and Mini-Opto Tomography Imaging System(SAGE Publications Inc., 2023) Akbaba, Cihat Ediz; Polat, Adem; Göktürk, DilekObjectives: In this study, we aimed to trace the 2D growth development of tumoroids produced with MIA PaCa-2 pancreatic cancer cells at different time points. Methods We cultured 3 different tumoroids with 0.5%, 0.8%, and 1.5% agarose concentrations and calculated the growth rate of the tumoroids with their images acquired at 9 imaging time points by mini-Opto tomography imaging system applying image processing techniques. We used the metrics contrast-to-noise ratio (CNR), peak signal-to-noise ratio (PSNR), and mean squared error (MSE) to analyze the distinguishability of the tumoroid structure from its surroundings, quantitatively. Additionally, we calculated the increase of the radius, the perimeter, and the area of 3 tumoroids over a time period. Results In the quantitative assessment, the bilateral and Gaussian filters gave the highest CNR values (ie, Gaussian filter: at each of 9 imaging time points in range of 1.715 to 15.142 for image set-1). The median filter gave the highest values in PSNR in the range of 43.108 to 47.904 for image set-2 and gave the lowest values in MSE in the range of 0.604 to 2.599 for image set-3. The areas of tumoroids with 0.5%, 0.8%, and 1.5% agarose concentrations were 1.014 mm2, 1.047 mm2, and 0.530 mm2 in the imaging time point-1 and 33.535 mm2, 4.538 mm2, and 2.017 mm2 in the imaging time point-9. The tumoroids with 0.5%, 0.8%, and 1.5% agarose concentrations grew up to times of 33.07, 4.33, and 3.80 in area size over this period, respectively. Conclusions The growth rate and the widest borders of the different tumoroids in a time interval could be detected automatically and successfully. This study that combines the image processing techniques with mini-Opto tomography imaging system ensured significant results in observing the tumoroid's growth rate and enlarging border over time, which is very critical to provide an emerging methodology in vitro cancer studies.
