Search results for: geometric imaging relationship

Authors: A. Bentabet, A. Aydin, N. Fenineche

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The mean penetration depth has a most important in the absorption transport phenomena. Analytical model of light ion backscattering coefficients from solid targets have been made by Vicanek and Urbassek. In the present work, we showed a mathematical expression (deterministic model) for Z1/2. In advantage, in the best of our knowledge, relatively only one analytical model exit for electron or positron mean penetration depth in solid targets. In this work, we have presented a simple geometric spherical model of absorbed particles based on CSDA scheme. In advantage, we have showed an analytical expression of the mean penetration depth by combination between our model and the Vicanek and Urbassek theory. For this, we have used the Relativistic Partial Wave Expansion Method (RPWEM) and the optical dielectric model to calculate the elastic cross sections and the ranges respectively. Good agreement was found with the experimental and theoretical data.

Keywords: Bentabet spherical geometric model, continuous slowing down approximation, stopping powers, ranges, mean penetration depth

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Authors: Yanni Chang, Dezhi Dai, Albert Y. Tong

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Piecewise linear interface calculation (PLIC) schemes are widely used in the volume-of-fluid (VOF) method to capture interfaces in numerical simulations of multiphase flows. Dynamic overset meshes can be especially useful in applications involving component motions and complex geometric shapes. In the present study, the VOF value of an acceptor cell is evaluated in a geometric way that transfers the fraction field between the meshes precisely with reconstructed interfaces from the corresponding donor elements. The acceptor cell value is evaluated by using a weighted average of its donors for most of the overset interpolation schemes for continuous flow variables. The weighting factors are obtained by different algebraic methods. Unlike the continuous flow variables, the VOF equation is a step function near the interfaces, which ranges from zero to unity rapidly. A geometric interpolation scheme of the VOF field in overset meshes for the PLIC-VOF method has been proposed in the paper. It has been tested successfully in quadrilateral/hexahedral overset meshes by employing several VOF advection tests with imposed solenoidal velocity fields. The proposed algorithm has been shown to yield higher accuracy in mass conservation and interface reconstruction compared with three other algebraic ones.

Keywords: interpolation scheme, multiphase flows, overset meshes, PLIC-VOF method

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Authors: Ersin Bozkurt

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The aim of the study is to develop materials for understanding image formations through virtual objects in geometric optics. The images in physics course books are formed by using real objects. This results in mistakes in the features of images because of generalizations which leads to conceptual misunderstandings in learning. In this study it was intended to identify pre-service physics teachers misunderstandings arising from false generalizations. Focused group interview was used as a qualitative method. The findings of the study show that students have several misconceptions such as "the image in a plain mirror is always virtual". However a real image can be formed in a plain mirror. To explain a virtual object's image formation in a more understandable way an overhead projector and episcope and their design was illustrated. The illustrations are original and several computer simulations will be suggested.

Keywords: computer simulations, geometric optics, physics education, students' misconceptions in physics

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Authors: I-Huan Chiu, Kazuhiko Ninomiya, Shin’ichiro Takeda, Meito Kajino, Miho Katsuragawa, Shunsaku Nagasawa, Atsushi Shinohara, Tadayuki Takahashi, Ryota Tomaru, Shin Watanabe, Goro Yabu

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In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical observation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the non-destructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.

Keywords: DSSD, muon, muonic X-ray, imaging, non-destructive analysis

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Authors: Ihab Elaff

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Simulating the heart’s electrical stimulation is essential in modeling and evaluating the electrophysiology behavior of the heart. For achieving that, there are two structures in concern: the ventricles’ Myocardium, and the ventricles’ Conduction Network. Ventricles’ Myocardium has been modeled as anisotropic material from Diffusion Tensor Imaging (DTI) scan, and the Conduction Network has been extracted from DTI as a case-based structure based on the biological properties of the heart tissues and the working methodology of the Magnetic Resonance Imaging (MRI) scanner. Results of the produced activation were much similar to real measurements of the reference model that was presented in the literature.

Keywords: diffusion tensor, DTI, heart, conduction network, excitation propagation

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Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Kolja Them, Priyal Chikhaliwala, Sudeshna Chandra

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Purpose: The purpose of this work is to examine possibilities for noninvasive imaging and identification of tumor markers for cancer diagnosis. The proposed method uses antibody conjugated iron oxide nanoparticles and multicolor Magnetic Particle Imaging (mMPI). The method has the potential for radiation exposure free real-time estimation of local tumor marker concentrations in vivo. In this study, the method is applied to human Alpha-1-Fetoprotein. Materials and Methods: As tracer material AFP antibody-conjugated Dendrimer-Fe3O4 nanoparticles were used. The nanoparticle bioconjugates were then incubated with bovine serum albumin (BSA) to block any possible nonspecific binding sites. Parts of the resulting solution were then incubated with AFP antigen. MPI measurements were done using the preclinical MPI scanner (Bruker Biospin MRI GmbH) and the multicolor method was used for image reconstruction. Results: In multicolor MPI images the nanoparticles incubated only with BSA were clearly distinguished from nanoparticles incubated with BSA and AFP antigens. Conclusion: Tomographic imaging of human tumor marker Alpha-1-Fetoprotein is possible using AFP antibody conjugated iron oxide nanoparticles in presence of BSA. This opens interesting perspectives for cancer diagnosis.

Keywords: noninvasive imaging, tumor antigens, antibody conjugated iron oxide nanoparticles, multicolor magnetic particle imaging, cancer diagnosis

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

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Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, resovist, field strength, relaxivity, signal intensity

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Marcelo Hayashi, João Lima, Bruno Chieregatti, Ernani Volpe

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The adjoint method has been used as a successful tool to obtain sensitivity gradients in aerodynamic design and optimisation for many years. This work presents an alternative approach to the continuous adjoint formulation that enables one to compute gradients of a given measure of merit with respect to control parameters other than those pertaining to geometry. The procedure is then applied to the steady 2–D compressible Euler and incompressible Navier–Stokes flow equations. Finally, the results are compared with sensitivities obtained by finite differences and theoretical values for validation.

Keywords: adjoint method, aerodynamics, sensitivity theory, non-geometric sensitivities

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Authors: Janet Wing-Chong Wai, Alex Chiu-Wing Lee, Hailey Hoi-Ching Tsang, Jeffrey Chiu, Kwok-Wing Tang

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Background: Mammography has limited sensitivity and specificity though it is the primary imaging technique for detection of early breast cancer. Ultrasound imaging and contrast-enhanced MRI are useful adjunct tools to mammography. The advantage of breast MRI is high sensitivity for invasive breast cancer. Therefore, indications for and use of breast magnetic resonance imaging have increased over the past decade. Objectives: 1. Cases demonstration on different indications for breast MR imaging. 2. To review of the common artifacts and pitfalls in breast MR imaging. Materials and Methods: This is a retrospective study including all patients underwent dynamic contrast-enhanced breast MRI examination in our centre, performed from Jan 2011 to Dec 2017. The clinical data and radiological images were retrieved from the EPR (electronic patient record), RIS (Radiology Information System) and PACS (Picture Archiving and Communication System). Results and Discussion: Cases including (1) Screening of the contralateral breast in patient with a new breast malignancy (2) Breast augmentation with free injection of unknown foreign materials (3) Finding of axillary adenopathy with an unknown site of primary malignancy (4) Neo-adjuvant chemotherapy: before, during, and after chemotherapy to evaluate treatment response and extent of residual disease prior to operation. Relevant images will be included and illustrated in the presentation. As with other types of MR imaging, there are different artifacts and pitfalls that can potentially limit interpretation of the images. Because of the coils and software specific to breast MR imaging, there are some other technical considerations that are unique to MR imaging of breast regions. Case demonstration images will be available in presentation. Conclusion: Breast MR imaging is a highly sensitive and reasonably specific method for the detection of breast cancer. Adherent to appropriate clinical indications and technical optimization are crucial for achieving satisfactory images for interpretation.

Keywords: MRI, breast, clinical, cancer

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Authors: Morteza Shayan Arani, Mohammadamin Esmailzadehazimi, Mohammadreza Moeini, Mohammad Toorani, Aouni A. Lakis

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This paper investigates the nonlinear response of thin, incompressible, hyperelastic cylindrical shells in the presence of a time-varying temperature field while considering initial geometric imperfections. The governing equations of motion are derived using an improved Donnell's shallow shell theory. The hyperelastic material is modeled using the Mooney-Rivlin model with two parameters, incorporating temperature-dependent terms. The Lagrangian method is applied to obtain the equation of motion. The resulting governing equation is addressed through the Lindstedt-Poincaré and Multiple Scale methods. The linear and nonlinear models presented in this study are verified against existing open literature, demonstrating the accuracy and reliability of the presented model. The study focuses on understanding the influence of temperature variations and geometrical imperfections on the natural frequency and amplitude-frequency response of the systems. Notably, the investigation reveals the coexistence of hardening and softening peaks in the amplitude-frequency response, which vary in magnitude depending on these parameters. Additionally, resonance peaks exhibit changes as a result of temperature and geometric imperfections.

Keywords: hyperelastic material, cylindrical shell, geometrical nonlinearity, material naolinearity, initial geometric imperfection, temperature gradient, hardening and softening

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Authors: Xin Wang, Munkbayar Munkhjargal, Kumiko Miyajima, Takahiro Arakawa, Kohji Mitsubayashi

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The measurement of gaseous ethanol plays an important role of evaluation of alcohol metabolic capacity in clinical and forensic analysis. A 2-dimensional visualization system for gaseous ethanol was constructed and tested in visualization of breath and transdermal alcohol. We demonstrated breath ethanol measurement using developed high-sensitive visualization system. The concentration of breath ethanol calculated with the imaging signal was significantly different between the volunteer subjects of ALDH2 (+) and (-).

Keywords: breath ethanol, ethnaol imaging, biochemical luminescence, alcohol metabolism

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Authors: Anshul Raja

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Cystic lesions of the spleen are rare and splenic hydatid cysts account for only 0.5% to 8% of all hydatidosis. Authors hereby report a case where a 50-year-old female presented to our hospital with the complains of heaviness and pain over left upper abdomen over the past 8-10 years. On radiological examination, ultrasonography revealed findings consistent with isolated splenic hydatid cyst and was later on confirmed on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). No other organ or system involvement was seen. The patient underwent splenectomy and hydatid cyst was confirmed on histopathology. Owing to its rarity, it offers a diagnostic challenge to physicians but can reliably be diagnosed with great confidence employing various imaging modalities like CT and MRI.

Keywords: gastrointestinal radiology, abdominal imaging, hydatid cyst, medical and health sciences

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Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

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A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Zafar Iqbal, Nigel P. Grigg, K. Govindaraju, Nicola M. Campbell-Allen

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Quality Function Deployment (QFD) is structured approach. It has been used to improve the quality of products and process in a wide range of fields. Using this systematic tool, practitioners normally rank Voice of Customer ratings (VoCs) in order to produce Improvement Ratios (IRs) which become the basis for prioritising process / product design or improvement activities. In one matrix of the House of Quality (HOQ) competitors are rated. The method of obtaining improvement ratios (IRs) does not always integrate the competitors’ rating in a systematic way that fully utilises competitor rating information. This can have the effect of diverting QFD practitioners’ attention from a potentially important VOC to less important VOC. In order to enhance QFD analysis, we present a more systematic method for integrating competitor ratings, utilising the geometric mean of the customer rating matrix. In this paper we develop a new approach, based on the Analytic Hierarchy Process (AHP), in which we generating a matrix of multiple comparisons of all competitors, and derive a geometric mean for each competitor. For each VOC an improved IR is derived which-we argue herein - enhances the initial VOC importance ratings by integrating more information about competitor performance. In this way, our method can help overcome one of the possible shortcomings of QFD. We then use a published QFD example from literature as a case study to demonstrate the use of the new AHP-based IRs, and show how these can be used to re-rank existing VOCs to -arguably- better achieve the goal of customer satisfaction in relation VOC ratings and competitors’ rankings. We demonstrate how two dimensional AHP-based geometric mean derived from the multiple competitor comparisons matrix can be useful for analysing competitors’ rankings. Our method utilises an established methodology (AHP) applied within an established application (QFD), but in an original way (through the competitor analysis matrix), to achieve a novel improvement.

Keywords: quality function deployment, geometric mean, improvement ratio, AHP, competitors ratings

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Authors: Amir Davood Elmi

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From the earliest light microscope to the most innovative X-ray imaging techniques, all of them have refined and improved our knowledge about the organization and composition of living tissues. The old techniques are time consuming and ultimately destructive to the tissues under the examination. In recent few decades, thanks to the boost of technology, non-destructive visualization techniques, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), selective plane illumination microscopy (SPIM), and optical projection tomography (OPT), have come to the forefront. Among these techniques, CT is excellent for mineralized tissues such as bone or dentine. In addition, CT it is faster than other aforementioned techniques and the sample remains intact. In this article, applications, advantages, and limitations of micro-CT is discussed, in addition to some information about micro-CT of soft tissue.

Keywords: Micro-CT, hard tissue, bone, attenuation coefficient, rapid prototyping

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Authors: Lukáš Klein, Karel Žídek

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Hyperspectral imaging counts among the most frequently used multidimensional sensing methods. While there are many approaches to capturing a hyperspectral data cube, optical compression is emerging as a valuable tool to reduce the setup complexity and the amount of data storage needed. Hyperspectral compressive imagers have been created in the past; however, they have primarily focused on relatively narrow sections of the electromagnetic spectrum. A broader spectral study of samples can provide helpful information, especially for applications involving the harmonic generation and advanced material characterizations. We demonstrate a broadband hyperspectral microscope based on the single-pixel camera principle. Captured spatially encoded data are processed to reconstruct a hyperspectral cube in a combined visible and near-infrared spectrum (from 400 to 2500 nm). Hyperspectral cubes can be reconstructed with a spectral resolution of up to 3 nm and spatial resolution of up to 7 µm (subject to diffraction) with a high compressive ratio.

Keywords: compressive imaging, hyperspectral imaging, near-infrared spectrum, single-pixel camera, visible spectrum

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Authors: Ranjith Menon, Abathar Aladi, Hans-Christean Nahser, Maneesh Bhojak, Sacha Nevin, Paul Eldridge

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Background: Spontaneous subarachnoid haemorrhage (SAH) accounts for approximately 5% of all strokes. Patients with spontaneous SAH (as shown by CT or lumbar puncture) undergo investigations to identify or exclude an underlying structural cause, typically cerebral aneurysm. However in 10 - 20% of cases, no structural cause is found. This includes more than one imaging modality (intracranial MRA, CTA, 4DCTA and/or DSA) and in some spinal MRI. Objective: To determine; 1) If an underlying structural or vascular cause can be identified in non-aneurysmal SAH patients by comparing different imaging modalities at presentation and at follow-up. 2) If MRI spine in patients with non-aneurysmal SAH reveals an underlying SAH cause. 3)The functional outcome at discharge. Results: We performed a retrospective analysis of all non-traumatic SAH patients admitted to the Walton centre from January 2009 to December 2015. There were 1457 patients with non-traumatic SAH admitted to the Walton centre of whom 21.8% (n=300) patients were diagnosed with non-aneurysmal SAH. Males were 65.6% and females were 43.3%. The presenting symptoms were sudden onset headache (93.6%), the focal neurological deficit (12%), loss of consciousness (10.6%) and others (6%). About 285 patients received 2 modalities of imaging (CTA & DSA), 192 received 3 modalities of imaging (CTA, MRA & DSA) and 137 received MRI spine (51/137 whole spine). The modified Rankin Score at discharge were: mRS 0 = 292 (97.33%), mRS 1-2 = 6, mRS 6 = 1 (cardiac arrest in IHD patient) and unknown in 1. Follow-up imaging at 3 to 6 months in 190 (63.3%) patients did not identify an underlying cause. Conclusion: This retrospective analysis concludes that non-aneurysmal SAH has a good functional outcome. A single imaging modality (CTA (4DCTA) or MRA or DSA) was adequate to exclude an underlying cause of SAH and a delayed imaging failed to identify a cause. Routinely performing MRI spine in this group of patients appears not to be necessary according to this evidence.

Keywords: stroke, non-aneurysmal subarachnoid haemorrhage, neuroimaging, modified rankin score

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Authors: Karthiyayini Nagarajan, P. V. Ramakrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar (SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System (Lab Bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench, imaging engineering

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Authors: N. Philipova

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The influence of the geometric parameters of trapezoidal labyrinth channel on the emitter discharge is investigated in this work. The impact of the dentate angle, the dentate spacing, and the dentate height are studied among the geometric parameters of the labyrinth channel. Numerical simulations of the water flow movement are performed according to central cubic composite design using Commercial codes GAMBIT and FLUENT. Inlet pressure of the dripper is set up to be 1 bar. The objective of this paper is to derive a mathematical model of the emitter discharge depending on the dentate angle, the dentate spacing, the dentate height of the labyrinth channel. As a result, the obtained mathematical model is a second-order polynomial reporting 2-way interactions among the geometric parameters. The dentate spacing has the most important and positive influence on the emitter discharge, followed by the simultaneous impact of the dentate spacing and the dentate height. The dentate angle in the observed interval has no significant effect on the emitter discharge. The obtained model can be used as a basis for a future emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model.

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Authors: Qasem A. Alyazji

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One of the main techniques for Positron emission tomography (PET), Single photon emission computed tomography (SPECT) is the development of radiation detectors. The NaI(Tl) scintillator crystal coupled to an array of photomultiplier tubes known as the Anger camera, is the most dominant detectors system in PET and SPECT devices. Technological advances in many materials, in addition to the emerging importance of specialized applications such as preclinical imaging and cardiac imaging, have encouraged innovation so that alternatives to the anger camera are now part in alternative imaging systems. In this paper we will discuss the main performance characteristics of detectors devices and scanning developments in both scintillation detectors, semiconductor (solid state) detectors, and Photon Transducers such as photomultiplier tubes (PMTs), position sensitive photomultiplier tubes (PSPMTs), Avalanche photodiodes (APDs) and Silicon photomultiplier (SiPMT). This paper discussed the detectors that showed promising results. This study is a review of recent developments in the detectors used in single photon emission computed tomography (SPECT) imaging system.

Keywords: SPECT, scintillation, PMTs, SiPMT, PSPMTs, APDs, semiconductor (solid state)

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Authors: Abdullah Ali H. Ahmadini, Firoz Ahmad, Intekhab Alam

Abstract:

Geometric programming problem (GPP) is a well-known non-linear optimization problem having a wide range of applications in many engineering problems. The structure of GPP is quite dynamic and easily fit to the various decision-making processes. The aim of this paper is to highlight the bounded solution method for GPP with special reference to variation among right-hand side parameters. Thus this paper is taken the advantage of two-level mathematical programming problems and determines the solution of the objective function in a specified interval called lower and upper bounds. The beauty of the proposed bounded solution method is that it does not require sensitivity analyses of the obtained optimal solution. The value of the objective function is directly calculated under varying parameters. To show the validity and applicability of the proposed method, a numerical example is presented. The system reliability optimization problem is also illustrated and found that the value of the objective function lies between the range of lower and upper bounds, respectively. At last, conclusions and future research are depicted based on the discussed work.

Keywords: varying parameters, geometric programming problem, bounded solution method, system reliability optimization

Procedia PDF Downloads 105

Authors: Mustafa Taskin, Ozgur Demir, M. Mert Serveren

Abstract:

The precise study of the impact of underwater explosions on structures is of great importance in the design and engineering calculations of floating structures, especially those used for military purposes, as well as power generation facilities such as offshore platforms that can become a target in case of war. Considering that ship and submarine structures are mostly curved surfaces, it is extremely important and interesting to examine the destructive effects of underwater explosions on curvilinear surfaces. In this study, geometric nonlinear dynamic analysis of cylindrical composite sandwich shells subjected to instantaneous pressure load is performed. The instantaneous pressure load is defined as an underwater explosion and the effects of the liquid medium are taken into account. There are equations in the literature for pressure due to underwater explosions, but these equations have been obtained for flat plates. For this reason, the instantaneous pressure load equations are arranged to be suitable for curvilinear structures before proceeding with the analyses. Fluid-solid interaction is defined by using Taylor's Plate Theory. The lower and upper layers of the cylindrical composite sandwich shell are modeled as composite laminate and the middle layer consists of soft core. The geometric nonlinear dynamic equations of the shell are obtained by Hamilton's principle, taken into account the von Kàrmàn theory of large displacements. Then, time dependent geometric nonlinear equations of motion are solved with the help of generalized differential quadrature method (GDQM) and dynamic behavior of cylindrical composite sandwich shells exposed to underwater explosion is investigated. An algorithm that can work parametrically for the solution has been developed within the scope of the study.

Keywords: cylindrical composite sandwich shells, generalized differential quadrature method, geometric nonlinear dynamic analysis, underwater explosion

Procedia PDF Downloads 161

Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

Abstract:

Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound

Procedia PDF Downloads 416

Authors: A. Ikhlef

Abstract:

Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

Procedia PDF Downloads 96

Authors: Dibyendu Roy, V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

Abstract:

Imaging of underwater objects is primarily conducted by acoustic imagery due to the severe attenuation of electro-magnetic waves in water. Acoustic imagery underwater has varied range of significant applications such as side-scan sonar, mine hunting sonar. It also finds utility in other domains such as imaging of body tissues via ultrasonography and non-destructive testing of objects. In this paper, we explore the feasibility of using active acoustic imagery in air and simulate phased array beamforming techniques available in literature for various array designs to achieve a suitable acoustic sensor array design for a portable mobile robot which can be applied to detect the presence/absence of anomalous objects in a room. The multi-path reflection effects especially in enclosed rooms and environmental noise factors are currently not simulated and will be dealt with during the experimental phase. The related hardware is designed with the same feasibility criterion that the developed system needs to be deployed on a portable mobile robot. There is a trade of between image resolution and range with the array size, number of elements and the imaging frequency and has to be iteratively simulated to achieve the desired acoustic sensor array design. The designed acoustic imaging array system is to be mounted on a portable mobile robot and targeted for use in surveillance missions for intruder alerts and imaging objects during dark and smoky scenarios where conventional optic based systems do not function well.

Keywords: acoustic sensor array, acoustic imagery, anomaly detection, phased array beamforming

Procedia PDF Downloads 377