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Статті в журналах з теми "Tomographic reconstruction algorithms":

1

Lǖck, Sebastian, Andreas Kupsch, Axel Lange, Manfred P. Hentschel, and Volker Schmidt. "STATISTICAL ANALYSIS OF TOMOGRAPHIC RECONSTRUCTION ALGORITHMS BY MORPHOLOGICAL IMAGE CHARACTERISTICS." Image Analysis & Stereology 29, no. 2 (May 3, 2011): 61. http://dx.doi.org/10.5566/ias.v29.p61-77.

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We suggest a procedure for quantitative quality control of tomographic reconstruction algorithms. Our task-oriented evaluation focuses on the correct reproduction of phase boundary length and has thus a clear implication for morphological image analysis of tomographic data. Indirectly the method monitors accurate reproduction of a variety of locally defined critical image features within tomograms such as interface positions and microstructures, debonding, cracks and pores. Tomographic errors of such local nature are neglected if only global integral characteristics such as mean squared deviation are considered for the evaluation of an algorithm. The significance of differences in reconstruction quality between algorithms is assessed using a sample of independent random scenes to be reconstructed. These are generated by a Boolean model and thus exhibit a substantial stochastic variability with respect to image morphology. It is demonstrated that phase boundaries in standard reconstructions by filtered backprojection exhibit substantial errors. In the setting of our simulations, these could be significantly reduced by the use of the innovative reconstruction algorithm DIRECTT.
2

Ganguly, Poulami Somanya, Daniël M. Pelt, Doga Gürsoy, Francesco de Carlo, and K. Joost Batenburg. "Improving reproducibility in synchrotron tomography using implementation-adapted filters." Journal of Synchrotron Radiation 28, no. 5 (August 12, 2021): 1583–97. http://dx.doi.org/10.1107/s1600577521007153.

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For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation-adapted filters for several open-source implementations and applying them to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline.
3

Wu, Juan, Mirna Lerotic, Sean Collins, Rowan Leary, Zineb Saghi, Paul Midgley, Slava Berejnov, et al. "Optimization of Three-Dimensional (3D) Chemical Imaging by Soft X-Ray Spectro-Tomography Using a Compressed Sensing Algorithm." Microscopy and Microanalysis 23, no. 5 (September 12, 2017): 951–66. http://dx.doi.org/10.1017/s1431927617012466.

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AbstractSoft X-ray spectro-tomography provides three-dimensional (3D) chemical mapping based on natural X-ray absorption properties. Since radiation damage is intrinsic to X-ray absorption, it is important to find ways to maximize signal within a given dose. For tomography, using the smallest number of tilt series images that gives a faithful reconstruction is one such method. Compressed sensing (CS) methods have relatively recently been applied to tomographic reconstruction algorithms, providing faithful 3D reconstructions with a much smaller number of projection images than when conventional reconstruction methods are used. Here, CS is applied in the context of scanning transmission X-ray microscopy tomography. Reconstructions by weighted back-projection, the simultaneous iterative reconstruction technique, and CS are compared. The effects of varying tilt angle increment and angular range for the tomographic reconstructions are examined. Optimization of the regularization parameter in the CS reconstruction is explored and discussed. The comparisons show that CS can provide improved reconstruction fidelity relative to weighted back-projection and simultaneous iterative reconstruction techniques, with increasingly pronounced advantages as the angular sampling is reduced. In particular, missing wedge artifacts are significantly reduced and there is enhanced recovery of sharp edges. Examples of using CS for low-dose scanning transmission X-ray microscopy spectroscopic tomography are presented.
4

Pelt, Daniël, Kees Batenburg, and James Sethian. "Improving Tomographic Reconstruction from Limited Data Using Mixed-Scale Dense Convolutional Neural Networks." Journal of Imaging 4, no. 11 (October 30, 2018): 128. http://dx.doi.org/10.3390/jimaging4110128.

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In many applications of tomography, the acquired data are limited in one or more ways due to unavoidable experimental constraints. In such cases, popular direct reconstruction algorithms tend to produce inaccurate images, and more accurate iterative algorithms often have prohibitively high computational costs. Using machine learning to improve the image quality of direct algorithms is a recently proposed alternative, for which promising results have been shown. However, previous attempts have focused on using encoder–decoder networks, which have several disadvantages when applied to large tomographic images, preventing wide application in practice. Here, we propose the use of the Mixed-Scale Dense convolutional neural network architecture, which was specifically designed to avoid these disadvantages, to improve tomographic reconstruction from limited data. Results are shown for various types of data limitations and object types, for both simulated data and large-scale real-world experimental data. The results are compared with popular tomographic reconstruction algorithms and machine learning algorithms, showing that Mixed-Scale Dense networks are able to significantly improve reconstruction quality even with severely limited data, and produce more accurate results than existing algorithms.
5

Sipkens, T. A., S. J. Grauer, A. M. Steinberg, S. N. Rogak, and P. Kirchen. "New transform to project axisymmetric deflection fields along arbitrary rays." Measurement Science and Technology 33, no. 3 (December 21, 2021): 035201. http://dx.doi.org/10.1088/1361-6501/ac3f83.

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Abstract Axisymmetric tomography is used to extract quantitative information from line-of-sight measurements of gas flow and combustion fields. For instance, background-oriented schlieren (BOS) measurements are typically inverted by tomographic reconstruction to estimate the density field of a high-speed or high-temperature flow. Conventional reconstruction algorithms are based on the inverse Abel transform, which assumes that rays are parallel throughout the target object. However, camera rays are not parallel, and this discrepancy can result in significant errors in many practical imaging scenarios. We present a generalization of the Abel transform for use in tomographic reconstruction of light-ray deflections through an axisymmetric target. The new transform models the exact path of camera rays instead of assuming parallel paths, thereby improving the accuracy of estimates. We demonstrate our approach with a simulated BOS scenario in which we reconstruct noisy synthetic deflection data across a range of camera positions. Results are compared to state-of-the-art Abel-based algorithms. Reconstructions computed using the new transform are consistently more stable and accurate than conventional reconstructions.
6

Venkatakrishnan, Singanallur, Yuxuan Zhang, Luc Dessieux, Christina Hoffmann, Philip Bingham, and Hassina Bilheux. "Improved Acquisition and Reconstruction for Wavelength-Resolved Neutron Tomography." Journal of Imaging 7, no. 1 (January 15, 2021): 10. http://dx.doi.org/10.3390/jimaging7010010.

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Wavelength-resolved neutron tomography (WRNT) is an emerging technique for characterizing samples relevant to the materials sciences in 3D. WRNT studies can be carried out at beam lines in spallation neutron or reactor-based user facilities. Because of the limited availability of experimental time, potential imperfections in the neutron source, or constraints placed on the acquisition time by the type of sample, the data can be extremely noisy resulting in tomographic reconstructions with significant artifacts when standard reconstruction algorithms are used. Furthermore, making a full tomographic measurement even with a low signal-to-noise ratio can take several days, resulting in a long wait time before the user can receive feedback from the experiment when traditional acquisition protocols are used. In this paper, we propose an interlaced scanning technique and combine it with a model-based image reconstruction algorithm to produce high-quality WRNT reconstructions concurrent with the measurements being made. The interlaced scan is designed to acquire data so that successive measurements are more diverse in contrast to typical sequential scanning protocols. The model-based reconstruction algorithm combines a data-fidelity term with a regularization term to formulate the wavelength-resolved reconstruction as minimizing a high-dimensional cost-function. Using an experimental dataset of a magnetite sample acquired over a span of about two days, we demonstrate that our technique can produce high-quality reconstructions even during the experiment compared to traditional acquisition and reconstruction techniques. In summary, the combination of the proposed acquisition strategy with an advanced reconstruction algorithm provides a novel guideline for designing WRNT systems at user facilities.
7

Sorzano, C. O. S., J. Vargas, J. Otón, J. M. de la Rosa-Trevín, J. L. Vilas, M. Kazemi, R. Melero, et al. "A Survey of the Use of Iterative Reconstruction Algorithms in Electron Microscopy." BioMed Research International 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/6482567.

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One of the key steps in Electron Microscopy is the tomographic reconstruction of a three-dimensional (3D) map of the specimen being studied from a set of two-dimensional (2D) projections acquired at the microscope. This tomographic reconstruction may be performed with different reconstruction algorithms that can be grouped into several large families: direct Fourier inversion methods, back-projection methods, Radon methods, or iterative algorithms. In this review, we focus on the latter family of algorithms, explaining the mathematical rationale behind the different algorithms in this family as they have been introduced in the field of Electron Microscopy. We cover their use in Single Particle Analysis (SPA) as well as in Electron Tomography (ET).
8

Müller, Jan, Dirk Fimmel, Renate Merker, and Rainer Schaffer. "A Hardware–Software System for Tomographic Reconstruction." Journal of Circuits, Systems and Computers 12, no. 02 (April 2003): 203–29. http://dx.doi.org/10.1142/s021812660300074x.

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We present the design of a hardware–software system for the reconstruction of tomographic images. In a systematic approach we developed the parallel processor array, a reconfigurable hardware controller and processing kernel, and the software control up to the integration into a graphical user interface. The processor array acting as a hardware accelerator, is constructed using theoretical results and methods of application-specific hardware design. The reconfigurability of the system allows one to utilize a much wider realm of algorithms than the three reconstruction algorithms implemented so far. In the paper we discuss the system design at different levels from algorithm transformations to board development.
9

Heidrich, G., C. O. Sahlmann, U. Siefker, H. Luig, C. Werner, E. Brunner, J. Meller, and M. Schünemann. "Improvement of tomographic reconstruction in bone SPECT." Nuklearmedizin 45, no. 01 (2006): 35–40. http://dx.doi.org/10.1055/s-0038-1623932.

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Summary Aim: The comparison between iterative reconstruction and filtered backprojection in the reconstruction of bone SPECT in the diagnosis of skeletal metastases. Patients, methods: 47 consecutive patients (vertebral segments: n = 435), with suspected malignancy of the vertebral column, were examined by bone scintigraphy and MRI (maximal interval between the two procedures ± 5 weeks). The SPECT-data were reconstructed with an iterative algorithm (ISA) and with filtered backprojection. We defined semiquantitative criteria in order to assess the quality of the tomograms. Conventional reconstruction was performed both by a Wiener-filter and a low-pass-filter. Iterative reconstruction was performed by the ISA algorithm. The clinical evaluation of the different reconstruction algorithms was performed by MRI as the gold-standard. Results: Sensitivity (%): 87.3 (ISA), 86.4 (low-pass), 79.7 (Wiener); specificity (%): 95.3 (ISA), 95 (low-pass), 85.4 (Wiener). The sensitivity of iterative reconstructed SPECT and low-pass reconstructed SPECT was significantly higher (p <0.05) compared with the sensitivity of SPECT reconstructed by the Wiener-filter. The specificity of iterative reconstruction ISA and low-pass-filter reconstructed SPECT were significantly higher compared with the SPECT data reconstructed by the Wiener-filter. ISA was significantly superior to the Wiener- SPECT relating to all criteria of quality. Iterative reconstruction was significantly superior to the low-pass-SPECT relating to 2 of 3 criteria. In addition the Wiener-SPECT was significantly inferior to the low-pass-SPECT regarding to 2 of 3 criteria. Conclusion: In our series the iterative algorithm ISA was the method of choice in the reconstruction of bone SPECT data. In comparison with conventional algorithms ISA offers a significantly higher quality of the tomograms and yields a high diagnostic accuracy.
10

Yorkey, T. J., and J. G. Webster. "A comparison of impedance tomographic reconstruction algorithms." Clinical Physics and Physiological Measurement 8, no. 4A (November 1987): 55–62. http://dx.doi.org/10.1088/0143-0815/8/4a/007.

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Дисертації з теми "Tomographic reconstruction algorithms":

1

Kim, Chuyoung. "Algorithms for Tomographic Reconstruction of Rectangular Temperature Distributions using Orthogonal Acoustic Rays." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/73754.

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Non-intrusive acoustic thermometry using an acoustic impulse generator and two microphones is developed and integrated with tomographic techniques to reconstruct temperature contours. A low velocity plume at around 450 °F exiting through a rectangular duct (3.25 by 10 inches) was used for validation and reconstruction. 0.3 % static temperature relative error compared with thermocouple-measured data was achieved using a cross-correlation algorithm to calculate speed of sound. Tomographic reconstruction algorithms, the simplified multiplicative algebraic reconstruction technique (SMART) and least squares method (LSQR), are investigated for visualizing temperature contours of the heated plume. A rectangular arrangement of transmitter and microphones with a traversing mechanism collected two orthogonal sets of acoustic projection data. Both reconstruction techniques have successfully recreated the overall characteristic of the contour; however, for the future work, the integration of the refraction effect and implementation of additional angled projections are required to improve local temperature estimation accuracy. The root-mean-square percentage errors of reconstructing non-uniform, asymmetric temperature contours using the SMART and LSQR method are calculated as 20% and 19%, respectively.
Master of Science
2

MALALLA, NUHAD ABDULWAHED YOUNIS. "C-ARM TOMOGRAPHIC IMAGING TECHNIQUE FOR DETECTION OF KIDNEY STONES." OpenSIUC, 2016. https://opensiuc.lib.siu.edu/dissertations/1278.

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Nephrolithiasis can be a painful problem due to presence of kidney stones. Kidney stone is among the common painful disorders of the urinary system. Various imaging modalities are used to diagnose patients with symptoms of renal or urinary tract disease such as plain kidney, ureter, bladder x-ray (KUB), intravenous pyelography (IVP), and computed tomography (CT). As a traditional three-dimensional (3D) nephrolithiasis and kidney stones detection technique, computed tomography (CT) provides detailed cross-sectional images as well as 3D structure of kidney from moving the x-ray beam in a circle around the body. However, the risk of CT scans of the kidney is relatively higher exposure to radiation which is more than regular x-rays. C-arm technique is a new x-ray imaging modality that uses 2D array detector and cone shaped x-ray beam to create 3D information about the scanned object. Both x-ray source and 2D array detector cells mounted on C-shaped wheeled structure (C-arm). A series of projection images are acquired by rotating the C-arm around the patient in along circular path with a single rotation. The characteristic structure of C-arm allows to provide wide variety of movements around the patient that helps to remain the patient stationary during scanning time. In this work, we investigated a C-arm technique to generate a series of tomographic images for nephrolithiasis and detection of kidney stones. C-arm tomographic technique (C-arm tomosynthesis) as a new three dimensional (3D) kidney imaging method that provides a series of two dimensional (2D) images along partial circular orbit over limited view angle. Our experiments were done with kidney phantom which formed from a pig kidney with two embedded kidney stones inside it and low radiation dosage. Radiation dose and scanning time needed for kidney imaging are all dramatically reduced due to the cone beam geometry and also to limitation of angular rotation. To demonstrate the capability of our C-arm tomosynthesis to generate 3D kidney information for kidney stone detection, two groups of tomographic image reconstruction algorithms were developed for C-arm tomosynthesis: direct algorithms such as filtered back projection (FBP) and iterative algorithms such as simultaneous algebraic reconstruction technique (SART), maximum likelihood expectation maximization (MLEM), ordered- subset maximum likelihood expectation maximization (OS-MLEM) and Pre-computed penalized likelihood reconstruction (PPL). Three reconstruction methods were investigated including: pixel-driven method (PDM), ray-driven method (RDM) and distance driven method (DDM). Each method differs in their efficiency of calculation accuracy per computing time. Preliminary results demonstrated the capability of proposed technique to generate volumetric data about the kidney for nephrolithiasis and kidney stone detection by using all investigated reconstruction algorithms. In spite of each algorithms differs in their strategies, embedded kidney stone can be clearly visualized in all reconstruction results. Computer simulation studies were also done on simulated phantom to evaluate the results for each reconstruction algorithm. To mimic kidney phantom, simulated phantom was simulated with two different size kidney stones. Dataset of projection images was collated by using a virtual C-arm tomosynthesis with geometric configuration similar to real technique. All investigated algorithms were used to reconstruct 3D information. Different of image quality functions were applied to evaluate the imaging system and the reconstruction algorithms. The results show the capability of C-arm tomosynthesis to generate 3D information of kidney structures and to identify the size and location of kidney stones with limited amount of radiation dose.
3

Millardet, Maël. "Amélioration de la quantification des images TEP à l'yttrium 90." Thesis, Ecole centrale de Nantes, 2022. https://tel.archives-ouvertes.fr/tel-03871632.

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La popularité de l'imagerie TEP à l'yttrium 90 va grandissante. Cependant, la probabilité qu'une désintégration d'un noyau d'yttrium 90 mène à l'émission d'un positon n'est que de 3,2 × 10-5, et les images reconstruites sont par conséquent caractérisées par un niveau de bruit élevé, ainsi que par un biais positif dans les régions de faible activité. Pour corriger ces problèmes, les méthodes classiques consistent à utiliser des algorithmes pénalisés, ou autorisant des valeurs négatives dans l'image. Cependant, une étude comparant et combinant ces différentes méthodes dans le contexte spécifique de l'yttrium 90 manquait encore à l'appel au début de cette thèse. Cette dernière vise donc à combler ce manque. Malheureusement, les méthodes autorisant les valeurs négatives ne peuvent pas être utilisées directement dans le cadre d'une étude dosimétrique, et cette thèse commence donc par proposer une nouvelle méthode de posttraitement des images, visant à en supprimer les valeurs négatives en en conservant les valeurs moyennes le plus localement possible. Une analyse complète multi-objectifs de ces différentes méthodes est ensuite proposée. Cette thèse se termine en posant les prémices de ce qui pourra devenir un algorithme permettant de proposer un jeu d'hyperparamètres de reconstruction adéquats, à partir des seuls sinogrammes
Yttrium-90 PET imaging is becoming increasingly popular. However, the probability that decay of a yttrium-90 nucleus will lead to the emission of a positron is only 3.2 × 10-5, and the reconstructed images are therefore characterised by a high level of noise, as well as a positive bias in low activity regions. To correct these problems, classical methods use penalised algorithms or allow negative values in the image. However, a study comparing and combining these different methods in the specific context of yttrium-90 was still missing at the beginning of this thesis. This thesis, therefore, aims to fill this gap. Unfortunately, the methods allowing negative values cannot be used directly in a dosimetric study. Therefore, this thesis starts by proposing a new method of post-processing the images, aiming to remove the negative values while keeping the average values as locally as possible. A complete multi-objective analysis of these different methods is then proposed. This thesis ends by laying the foundations of what could become an algorithm providing a set of adequate reconstruction hyper parameters from sinograms alone
4

Defontaine-Caritu, Marielle. "Reconstruction optique de tomographies : application à la tomographie ultrasonore en réflexion." Compiègne, 1995. http://www.theses.fr/1995COMPD814.

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Les techniques de reconstruction tomographique sont toujours un sujet de recherche d'actualité. Des algorithmes de plus en plus sophistiqués s'adaptent de mieux en mieux aux techniques d'acquisition associées. Ces méthodes de reconstruction, malgré les énormes progrès de l'informatique, sont encore dépendantes du temps de calcul des machines, de leur encombrement et de leur coût élevé. Nous présentons un système de reconstruction optique, basé sur l'algorithme de rétroprojection en faisceaux droits parallèles. Les informations des projections sont codées optiquement, grâce à un ensemble modulateur et déflecteur acousto-optiques. Elles forment instantanément les images de rétroprojection optiques. Une caméra CCD placée au foyer image en fin de chaîne optique, assure l'intégration. La même séquence est mise en œuvre pour toutes les projections, et après une révolution complète de la caméra, restée en pause, on obtient sur la cellule l'image reconstruite de la coupe. Le seul facteur limitatif dans le temps concerne le temps d'acquisition des projections, qui est environ d'une seconde dans notre cas. Après avoir validé cette méthode à l'aide de projections simulées, nous avons entrepris de l'associer à un système d'acquisition ultrasonore. L'algorithme mis en œuvre sur la chaîne optique ne correspond pas à une méthode de reconstruction exacte. Cependant les images obtenues restituent correctement les structures explorées. Par ailleurs, dans le but de conduire à une reconstruction exacte, une dernière partie est consacrée aux améliorations envisagées concernant la chaîne optique.
5

Vallot, Delphine. "Reconstruction adaptative optimisée pour la quantification en tomographie de positons couplée à un tomodensitomètre." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30188.

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L'étude a été initiée à l'occasion de la disponibilité d'un algorithme itératif de reconstruction en tomographie par émission de positons, qui présente l'avantage d'atteindre la convergence grâce à une méthode de régularisation. Il a donc fallu évaluer ses performances et son éventuel apport en comparaison aux algorithmes de référence, puis étudier l'influence du seul paramètre accessible aux utilisateurs pour une optimisation en clinique. Pour cela, plusieurs tests ont été réalisés, sur fantômes d'abord, puis sur patients car les résultats obtenus n'étaient pas directement transposables en clinique. Cet algorithme a de nombreux avantages par rapport au standard actuel OSEM-MLEM (moins de bruit, meilleur contraste, meilleure détectabilité des lésions) mais pourrait encore être amélioré pour diminuer les artéfacts et la surestimation de certaines métriques, grâce à l'utilisation de fantômes plus anthropomorphiques et l'accès à plus de paramètres de reconstruction. Des travaux sont encore en cours avec l'éditeur
This study was initiated to evaluate an iterative reconstruction algorithm in positron emission tomography based on a regularization method to obtain convergence. Our aim was to assess its performance, in comparison with other currently available algorithms and to study the impact of the only parameter available to users for eventual optimization, both using anthropomorphic phantoms and clinical data. We confirm that this algorithm shows several advantages compared to the traditional OSEM-MLEM concerning noise, contrast and detectability. By using anthropomorphic phantoms and with access to more reconstruction parameters, the performance could be further improved to decrease the artefacts and the overestimation of certain metrics. Work in progress
6

Velo, Alexandre França. "Análise da aplicação de diferentes algoritmos de reconstrução de imagens tomográficas de objetos industriais." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/85/85131/tde-08022019-142220/.

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Existe na indústria o interesse em utilizar as informações da tomografia computadorizada a fim de conhecer o interior (i) dos objetos industriais fabricados ou (ii) das máquinas e seus meios de produção. Nestes casos, a tomografia tem como finalidade (a) controlar a qualidade do produto final e (b) otimizar a produção, contribuindo na fase piloto dos projetos e na análise da qualidade dos meios sem interromper a produção. O contínuo controle de qualidade dos meios de produção é a chave mestra para garantir a qualidade e a competitividade dos produtos. O Centro de Tecnologia das Radiações (CTR), do Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP) vem desenvolvendo esta tecnologia para fins de análises de processos industriais há algum tempo. Atualmente, o laboratório tem desenvolvido três gerações de tomógrafos: (i) primeira geração; (ii) terceira geração; e (iii) tomógrafo Instant Non-Scanning. Os algoritmos de reconstrução de imagens tomográficas tem uma importância relevante para o funcionamento ideal desta tecnologia. Nesta tese, foram desenvolvidos e analisados os algoritmos de reconstrução de imagens tomográficas para serem implementados aos protocolos experimentais dos tomógrafos. Os métodos de reconstrução de imagem analítico e iterativo foram desenvolvidos utilizando o software Matlab® r2013b. Os algoritmos iterativos apresentaram imagens com melhor resolução espacial comparado com as obtidas pelo método analítico. Entretanto as imagens por método analítico apresentaram menos ruídos. O tempo para obtenção de imagem pelo método iterativo é relativamente elevado, e aumenta conforme aumenta a matriz de pixels da imagem. Já o método analítico fornece imagens instantâneas. Para as reconstruções de imagens utilizando o tomógrafo Instant Non-Scanning, as imagens pelo método analítico não apresentaram qualidade de imagem satisfatória comparada aos métodos iterativos.
There is an interest in the industry to use the CT information in order to know the interior (i) of the manufactured industrial objects or (ii) the machines and their means of production. In these cases, the purpose of the tomography systems is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and to analyze the quality of the means without interrupting he line production. Continuous quality assurance of the means of production is the key to ensuring product quality and competitiveness. The Radiation Technology Center of the Nuclear and Energy Research Institute (IPEN/CNEN-SP) has been developing this technology for the purpose of industrial analysis. Currently the laboratory has developed three generations of tomography systems: (i) first generation; (ii) third generation; and (iii) Instant Non-Scanning tomography. The algorithms for the reconstruction of tomographic images are of relevant importance for the optimal functioning of this technology. In this PhD thesis, the reconstruction algorithms of tomographic images were developed and analyzed to be implemented to the tomography systems developed. The analytical and iterative image reconstruction methods were developed using the software Matlab® r2013b. The iterative algorithms presented images with better spatial resolution compared to those obtained by the analytical method; however the images of the analytical method presented be less image noisy. The time to obtain the image by the iterative method is high, and increases as the image matrix increases, while the analytical method provides fast images. For images reconstructions using the Instant Non-Scanning tomography system, the images by the analytical method did not present satisfactory image quality compared to the iterative methods.
7

Belward, Catherine. "Reconstruction algorithms for electrical empedance tomography /." St. Lucia, Qld, 2003. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe17243.pdf.

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8

Polydorides, Nicholas. "Image reconstruction algorithms for soft-field tomography." Thesis, University of Manchester, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488242.

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林吉雄 and Kat-hung Lam. "Geometric object reconstruction from orthogonal ray sum data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31210855.

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Lam, Kat-hung. "Geometric object reconstruction from orthogonal ray sum data /." [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13458747.

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Книги з теми "Tomographic reconstruction algorithms":

1

Paulo A. Da Torre Pinheiro. A three-dimensional reconstruction algorithm for electrical resistance tomography. Manchester: UMIST, 1998.

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2

Dunmore, A. Development of algebraic reconstruction algorithms for a real time optical process tomography system. Manchester: UMIST, 1993.

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3

Cierniak, Robert. Nowe algorytmy rekonstrukcji obrazu z projekcji z zastosowaniem sieci neuronowych typu Hopfielda. Częstochowa: Wydawn. Politechniki Częstochowskiej, 2006.

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4

Chang, Ji-Ho. Image reconstruction algorithms for achieving high-resolution positron emission tomography images. 2004.

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Частини книг з теми "Tomographic reconstruction algorithms":

1

Schmitt, Thomas, Dirk Fimmel, Mathias Kortke, and Renate Merker. "Parallel Processor Array for Tomographic Reconstruction Algorithms." In Computer Aided Systems Theory - EUROCAST’99, 127–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10720123_12.

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Tischenko, Oleg, and Christoph Hoeschen. "Reconstruction Algorithms and Scanning Geometries in Tomographic Imaging." In Imaging in Nuclear Medicine, 99–125. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31415-5_6.

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Kodali, Shyam P., Kalyanmoy Deb, Sunith Bandaru, Prabhat Munshi, and N. N. Kishore. "Simulation Studies on a Genetic Algorithm Based Tomographic Reconstruction Using Time-of-Flight Data from Ultrasound Transmission Tomography." In Adaptive and Natural Computing Algorithms, 253–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04921-7_26.

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Rajan, K., and L. M. Patnaik. "Parallel Implementation of Tomographic Reconstruction Algorithms on Bus-Based Extended Hypercube." In Lecture Notes in Computer Science, 279–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-540-46642-0_41.

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Van Dijke, M. C. A., H. A. van der Vorst, and M. A. Viergever. "Iterative Solution Methods for Large, Sparse Systems of Linear Equations Arising from Tomographic Image Reconstruction." In Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms, 649–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-75536-1_53.

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6

Jiang, Huabei. "Reconstruction Algorithms." In Fluorescence Molecular Tomography, 7–17. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10004-8_2.

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Natterer, F. "Reconstruction Algorithms." In The Mathematics of Computerized Tomography, 102–57. Wiesbaden: Vieweg+Teubner Verlag, 1986. http://dx.doi.org/10.1007/978-3-663-01409-6_5.

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Herman, Gabor T., and Dewey Odhner. "Evaluation of reconstruction algorithms." In Mathematical Methods in Tomography, 215–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/bfb0084520.

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Vardi, Yehuda, and Cun-Hui Zhang. "Reconstruction of Binary Images via the EM Algorithm." In Discrete Tomography, 297–316. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1568-4_13.

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Garderet, Ph. "Strategies of Reconstruction Algorithms for Computerized Tomography." In Physics and Engineering of Medical Imaging, 73–92. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3537-2_4.

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Тези доповідей конференцій з теми "Tomographic reconstruction algorithms":

1

Mishra, Debasish, K. Muralidhar, and P. Munshi. "Three Dimensional Reconstruction From Limited Projection Data Using a Novel MART Algorithm." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-1101.

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Анотація:
Abstract The present work is concerned with the development of a robust three dimensional reconstruction algorithm for applications involving tomography. In an earlier study it was shown that among the ART family of algorithms the multiplicative algebraic reconstruction algorithm (MART) was the most appropriate for tomographic reconstruction. In the present work, the MART algorithm has been extended so that (a) its performance is acceptable over a wider range of relaxation factors, (b) the time requirement for convergence to a solution is lower and (c) its performance is less sensitive to noise in the projection data. Two applications have been considered for evaluating the proposed algorithms namely a circular region with holes and experimental data recorded in a differentially heated fluid layer using an interferometer. The algorithms proposed are seen to be clearly an improvement over those presently available.
2

Liu Heng, Wang Zheng-huan, Bu Xiang-yuan, and An Jian-ping. "Image reconstruction algorithms for radio tomographic imaging." In 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE, 2012. http://dx.doi.org/10.1109/cyber.2012.6392525.

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3

Danisor, Cosmin, Gianfranco Fornaro, and Mihai Datcu. "Comparative study of SAR tomographic reconstruction algorithms." In 2015 23rd Telecommunications Forum Telfor (TELFOR). IEEE, 2015. http://dx.doi.org/10.1109/telfor.2015.7377501.

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4

Byunghyun Jang, David Kaeli, Synho Do, and Homer Pien. "Multi GPU implementation of iterative tomographic reconstruction algorithms." In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI). IEEE, 2009. http://dx.doi.org/10.1109/isbi.2009.5193014.

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Rajesh, A., K. D. Kihm, L. Yang, and J. Yen. "Hybrid Approach to Tomographic Reconstruction of Bubbles in Two-Phase Flows Using Algebraic Reconstruction Technique (ART), Genetic Algorithms (GA) and Simplex Method." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8172.

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Анотація:
Abstract Main hurdles in the application of genetic algorithms to complex problems are two fold. One is the high computational cost due to their slow convergence rate. The other is to reduce the number of input parameters of a conventional genetic algorithm as in the case of tomographic reconstruction of bubbles. In our present work great strides have been made to alleviate both the problems by using a Hybrid model of Algebraic Reconstruction Technique (ART), Simplex Method and Genetic Algorithm (GA). Our results showed that the hybrid approach is an effective and robust optimization image reconstruction technique.
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Rajesh, A., H. S. Ko, and Ken D. Kihm. "Hybrid Approach to Tomographic Reconstruction of Bubbles in Two-Phase Flows Using Genetic Algorithm." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0770.

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Анотація:
Abstract Main hurdles in the application of genetic algorithms to complex problems are two folds. One is the high computational cost due to their slow convergence rate. The other is to reduce the input parameters of a conventional genetic algorithm as in the case of tomographic reconstruction of bubbles. In our present work great strides have been made to alleviate both the problems by using a Hybrid model of Algebraic Reconstruction Technique (ART), Simplex Method and Genetic Algorithm (GA).
7

Arathi, T., Latha Parameswaran, and K. P. Soman. "A study of reconstruction algorithms in computerized tomographic images." In the 1st Amrita ACM-W Celebration. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1858378.1858447.

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8

Rougee, A., K. M. Hanson, and D. Saint-Felix. "Comparison Of 3-D Tomographic Algorithms For Vascular Reconstruction." In Medical Imaging II, edited by Roger H. Schneider and Samuel J. Dwyer III. SPIE, 1988. http://dx.doi.org/10.1117/12.968659.

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Lorenz, S., G. Grittani, L. V. N. Goncalves, C. M. Lazzarini, J. Limpouch, M. Nevrkla, S. Bulanov, and G. Korn. "Tomographic Reconstruction Algorithms for Laser Wakefield Acceleration Gas Targets." In Compact EUV & X-ray Light Sources. Washington, D.C.: OSA, 2020. http://dx.doi.org/10.1364/euvxray.2020.jm3a.33.

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Chamgoulov, Ravil, Michael Tsiroulnikov, Pierre Lane, and Calum MacAulay. "Limited-angle reconstruction algorithms in computed-tomographic microscopic imaging." In Medical Imaging, edited by J. Michael Fitzpatrick and Joseph M. Reinhardt. SPIE, 2005. http://dx.doi.org/10.1117/12.594708.

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Звіти організацій з теми "Tomographic reconstruction algorithms":

1

Martz, H. E., M. B. Aufderheide, D. Goodman, A. Schach von Wittenau, C. Logan, J. Hall, J. Jackson, and D. Slone. Quantitative tomography simulations and reconstruction algorithms. Office of Scientific and Technical Information (OSTI), November 2000. http://dx.doi.org/10.2172/15005122.

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Aufderheide, M. B., H. E. Martz, D. M. Slone, J. A. Jackson, A. E. Schach von Wittenau, D. M. Goodman, C. M. Logan, and J. M. Hall. Concluding Report: Quantitative Tomography Simulations and Reconstruction Algorithms. Office of Scientific and Technical Information (OSTI), February 2002. http://dx.doi.org/10.2172/15002511.

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Basu, Samit. Dynamic Imaging and Fast Reconstruction Algorithms in Tomography. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada368306.

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Ghosh Roy, D. N., K. Wilton, T. A. Cook, S. Chakrabarti, J. Qi, and G. T. Gullberg. Tomographic reconstructions using map algorithms - application to the SPIDR mission. Office of Scientific and Technical Information (OSTI), January 2004. http://dx.doi.org/10.2172/838183.

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Wilson, Mark P., Bridget K. Ford, Jose Salomon II Salazar, and ). Reconstruction algorithm development and assessment for a computed tomography based-spectral imager. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/882349.

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Jimenez, Edward S., Laurel J. Orr, and Kyle R. Thompson. High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1121931.

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