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Öğe A miniaturized optical tomography platform for volumetric imaging of engineered living systems(Royal Soc Chemistry, 2019) Polat, Adem; Hassan, Shabir; Yildirim, Isa; Oliver, Luis Eduardo; Mostafaei, Maryam; Kumar, Siddharth; Maharjan, SushilaVolumetric optical microscopy approaches that enable acquisition of three-dimensional (3D) information from a biological sample are attractive for numerous non-invasive imaging applications. The unprecedented structural details that these techniques provide have helped in our understanding of different aspects of architecture of cells, tissues, and organ systems as they occur in their natural states. Nonetheless, the instrumentation for most of these techniques is sophisticated, bulky, and costly, and is less affordable to most laboratory settings. Several miniature imagers based on webcams or low-cost sensors featuring easy assembly have been reported, for in situ imaging of biological structures at low costs. However, they have not been able to achieve the ability of 3D imaging throughout the entire volumes for spatiotemporal analyses of the structural changes in these specimens. Here we present a miniaturized optical tomography (mini-Opto) platform for lowcost, volumetric characterization of engineered living systems through hardware optimizations as well as applications of an optimized algebraic algorithm for image reconstruction.Öğe A Novel Parametric Model for the Prediction and Analysis of the COVID-19 Casualties(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Tutsoy, Önder; Colak, Sule; Polat, Adem; Balikci, KemalCoronavirus disease (COVID-19) outbreak has affected billions of people, where millions of them have been infected and thousands of them have lost their lives. In addition, to constraint the spread of the virus, economies have been shut down, curfews and restrictions have interrupted the social lives. Currently, the key question in minds is the future impacts of the virus on the people. It is a fact that the parametric modelling and analyses of the pandemic viruses are able to provide crucial information about the character and also future behaviour of the viruses. This paper initially reviews and analyses the Susceptible-Infected-Recovered (SIR) model, which is extensively considered for the estimation of the COVID-19 casualties. Then, this paper introduces a novel comprehensive higher-order, multi-dimensional, strongly coupled, and parametric Suspicious-Infected-Death (SpID) model. The mathematical analysis results performed by using the casualties in Turkey show that the COVID-19 dynamics are inside the slightly oscillatory, stable (bounded) region, although some of the dynamics are close to the instability region (unbounded). However, analysis with the data just after lifting the restrictions reveals that the dynamics of the COVID-19 are moderately unstable, which would blow up if no actions are taken. The developed model estimates that the number of the infected and death individuals will converge zero around 300 days whereas the number of the suspicious individuals will require about a thousand days to be minimized under the current conditions. Even though the developed model is used to estimate the casualties in Turkey, it can be easily trained with the data from the other countries and used for the estimation of the corresponding COVID-19 casualties.Öğe An alternative approach to tracing the volumic proliferation development of an entire tumor spheroid in 3D through a mini-Opto tomography platform(Pergamon-Elsevier Science Ltd, 2022) Polat, Adem; Gokturk, 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 degrees to +25 degrees 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 tumomid to achieve 800 x 800-pixel 50-layer images at resolutions of 5-25 mu m. 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 mm(3) at the first imaging time point and 46.899 mm(3) 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 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 Development of a Multi-Dimensional Parametric Model With Non-Pharmacological Policies for Predicting the COVID-19 Pandemic Casualties(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Tutsoy, Önder; Polat, Adem; Colak, Sule; Balikci, KemalCoronavirus Disease 2019 (COVID-19) has spread the world resulting in detrimental effects on human health, lives, societies, and economies. The state authorities mostly take non-pharmacological actions against the outbreak since there are no confirmed vaccines or treatments yet. In this paper, we developed Suspicious-Infected-Death with Non-Pharmacological policies (SpID-N) model to analyze the properties of the COVID-19 casualties and also estimate the future behavior of the outbreak. We can state the key contributions of the paper with three folds. Firstly, we propose the SpID-N model covering the higher-order internal dynamics which cause the peaks in the casualties. Secondly, we parametrize the non-pharmacological policies such as the curfews on people with chronic disease, people age over 65, people age under 20, restrictions on the weekends and holidays, and closure of the schools and universities. Thirdly, we explicitly incorporate the internal and coupled dynamics of the model with these multi-dimensional non-pharmacological policies. The corresponding higher-order and strongly coupled model has utterly unknown parameters and we construct a batch type Least Square (LS) based optimization algorithm to learn these unknown parameters from the available data. The parametric model and the predicted future casualties are analyzed extensively.Öğe Digital Breast Tomosynthesis imaging using compressed sensing based reconstruction for 10 radiation doses real data(Elsevier Sci Ltd, 2019) Polat, Adem; Matela, Nuno; Dinler, Ali; Zhang, Yu Shrike; Yildirim, IsaPurpose: Digital Breast Tomosynthesis (DBT) has recently proved promising in producing three-dimensional (3D) images of a breast. Algebraic reconstruction technique (ART), which is one of the most frequently used iterative image reconstruction techniques, has been proposed to provide satisfactory images of the breast in detecting masses and micro-calcifications. However, the greatest limitation of DBT imaging is the level of radiation dose due to the very sensitive nature of the breast. Recently, the effect of total variation (TV) minimization to enhance the image quality and to reduce the noise has been investigated in DBT imaging. Studies dealing with 3D TV minimization with ART have attracted increasing attention in the field of image reconstruction. This work investigates if iterative reconstruction techniques applied without and with TV (ART and ART + TV3D) can help reduce the level of dose in DBT imaging. Methods: Projections of a realistic breast phantom (CD Pasmam 1054) were acquired with a Siemens MAMMOMAT DBT scanner at 10 different doses. The effect of dose and the methods in the reconstruction quality was assessed both quantitatively and qualitatively. Results: ART+ TV3D showed superior results in terms of visual assessment, contrast-to-noise ratio (CNR) and full width at half maximum (FWHM) values, and one-dimensional (1D) profiles compared with ART. CNR values were evaluated for two different regions of interest (ROls). For instance, CNR values of ROI-1 of ART and of ART + TV3D were 46.380 and 47.675 at 63 mAs, 48.945 and 50.632 at 90 mAs, and 51.248 and 52.867 at 199 mAs, respectively. Additionally, FWHM values for ART and ART + TV3D were 2.373 and 1.758 at 63 mAs, 1.930 and 1.467 at 90 mAs, and 1.591 and 1.223 at 199 mAs, respectively. Conclusions: The results suggested that a compressed sensing based iterative reconstruction method (ART +TV3D) could help decrease the radiation dose level that is one of the most critical limitations of DBT imaging. (C) 2018 Published by Elsevier Ltd.Öğe Kanser hücrelerini 3-boyutlu görüntüleyebilen yapay zekâ temelli robotik mini-opto biyotomografi cihazı için 3-boyutlu görüntüleme yazılımı geliştirme(2020) Polat, AdemÇesitli türleri bulunan kanser, günümüzde en yaygın ve en ölümcül hastalıkların basında gelmektedir. Kanseri yenmek için gen ve doku mühendisligi alanında hücresel boyutlarda çesitli çalısmalar yapılmaktadır. Kanserin erken teshisi, hastalıgın tedavisinde çok önemli yer tutmaktadır. Bu kapsamda hem bilimsel arastırmalar seviyesinde hem de hastanelerde tanı, teshis ve tedavi uygulama noktasında kanserle mücadele edilmektedir. Görüntüleme, hastada kanseri erken teshis etmek için kullanılan en önemli yöntemlerden biri oldugu gibi aynı zamanda kanser üzerine yapılan bilimsel çalısmaların performansını da ölçen güçlü bir yöntemdir. Organ düzeyindeki görüntüleme araçları arasında MR (magnetic resonans), PET (positron emission tomography), CT (computed tomography), DBT (digital breast tomosynthesis), mammografi gibi cihazlar sayılırken hücre düzeyindeki görüntüleme araçlarından yaygın olarak kullanılanlarından biri mikroskop sayılabilir. CT ve DBT gibi organ görüntüleyen cihazlarda görüntüleme metodu olarak genellikle FBP (filtered back projection) metodu kullanılmaktadır. Çesitli arastırmalarda ve klinik uygulamalarda hücre görüntüleme için hâlihazırda kullanılan mikroskop çesitleri arasında konfokal mikroskop, elektron mikroskobu ve floresan mikroskop bulunmaktadır. Elektron ve floresan mikroskoplarla 2-boyutlu görüntüleme yapılabilirken, konfokal mikroskopla 3-boyutlu stereo görüntüleme yapılabilmektedir. Ancak konfokal mikroskop, kullanımı uzmanlık isteyen, tasınması kolay olmayan ve çok pahalı bir cihaz oldugundan arastırma laboratuvarlarında yaygın olarak bulunamamaktadır. Bu proje kapsamında; konfokal mikroskopa alternatif olarak kullanımı kolay, tasınabilir ve pahalı olmayan, kanser hücrelerini açısal tarama ile 3-boyutlu görüntüleyebilen yapay zekâ temelli robotik mini-opto biyotomografi cihazı için 3-boyutlu ileri görüntüleme yazılımı gelistirilmistir. Bu projenin nihai çıktısı olarak; parametreleri ve geometrisi 800x800x50 boyutlarında katmanlar halinde 3B görüntü geri çatabilen bir iteratif görüntü geri çatma yazılımı (Algebraic reconstruction techniques + 3-dimensional total variation: ART+TV3D) Matlab ortamında gelistirilmistir.Öğe Linear and non-linear dynamics of the epidemics: System identification based parametric prediction models for the pandemic outbreaks(Elsevier Science Inc, 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 (SIIID)-I-p-I-n-I-t-D-b-N (suspicious S-p, infected I-n, intensive care I-t, intubated I-b, 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 (SIIID)-I-p-I-n-I-t-D-b-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 (SIIID)-I-p-I-n-I-t-D-b-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. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.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; Gokturk, 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 mm(2), 1.047 mm(2), and 0.530 mm(2) in the imaging time point-1 and 33.535 mm(2), 4.538 mm(2), and 2.017 mm(2) 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.
