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Готові списки джерел за темами / Permittivity reconstruction

Добірка наукової літератури з теми "Permittivity reconstruction"

Автор: Grafiati

Опубліковано: 7 липня 2024

Оновлено: 7 липня 2024

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Статті в журналах
Дисертації
Частини книг
Тези доповідей конференцій

Статті в журналах з теми "Permittivity reconstruction":

1

Khoshdel, Vahab, Ahmed Ashraf, and Joe LoVetri. "Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique." Sensors 19, no. 18 (September 19, 2019): 4050. http://dx.doi.org/10.3390/s19184050.

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We present a deep learning method used in conjunction with dual-modal microwave-ultrasound imaging to produce tomographic reconstructions of the complex-valued permittivity of numerical breast phantoms. We also assess tumor segmentation performance using the reconstructed permittivity as a feature. The contrast source inversion (CSI) technique is used to create the complex-permittivity images of the breast with ultrasound-derived tissue regions utilized as prior information. However, imaging artifacts make the detection of tumors difficult. To overcome this issue we train a convolutional neural network (CNN) that takes in, as input, the dual-modal CSI reconstruction and attempts to produce the true image of the complex tissue permittivity. The neural network consists of successive convolutional and downsampling layers, followed by successive deconvolutional and upsampling layers based on the U-Net architecture. To train the neural network, the input-output pairs consist of CSI’s dual-modal reconstructions, along with the true numerical phantom images from which the microwave scattered field was synthetically generated. The reconstructed permittivity images produced by the CNN show that the network is not only able to remove the artifacts that are typical of CSI reconstructions, but can also improve the detectability of tumors. The performance of the CNN is assessed using a four-fold cross-validation on our dataset that shows improvement over CSI both in terms of reconstruction error and tumor segmentation performance.

2

Al Hosani, E., and M. Soleimani. "Multiphase permittivity imaging using absolute value electrical capacitance tomography data and a level set algorithm." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2070 (June 28, 2016): 20150332. http://dx.doi.org/10.1098/rsta.2015.0332.

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Multiphase flow imaging is a very challenging and critical topic in industrial process tomography. In this article, simulation and experimental results of reconstructing the permittivity profile of multiphase material from data collected in electrical capacitance tomography (ECT) are presented. A multiphase narrowband level set algorithm is developed to reconstruct the interfaces between three- or four-phase permittivity values. The level set algorithm is capable of imaging multiphase permittivity by using one set of ECT measurement data, so-called absolute value ECT reconstruction, and this is tested with high-contrast and low-contrast multiphase data. Simulation and experimental results showed the superiority of this algorithm over classical pixel-based image reconstruction methods. The multiphase level set algorithm and absolute ECT reconstruction are presented for the first time, to the best of our knowledge, in this paper and critically evaluated. This article is part of the themed issue ‘Supersensing through industrial process tomography’.

3

KIDERA, Shouhei. "Complex Permittivity Reconstruction for Microwave Imaging." Journal of the Visualization Society of Japan 40, no. 159 (2020): 22–25. http://dx.doi.org/10.3154/jvs.40.159_22.

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4

Beilina, Larisa, and Eric Lindström. "An Adaptive Finite Element/Finite Difference Domain Decomposition Method for Applications in Microwave Imaging." Electronics 11, no. 9 (April 24, 2022): 1359. http://dx.doi.org/10.3390/electronics11091359.

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A new domain decomposition method for Maxwell’s equations in conductive media is presented. Using this method, reconstruction algorithms are developed for the determination of the dielectric permittivity function using time-dependent scattered data of an electric field. All reconstruction algorithms are based on an optimization approach to find the stationary point of the Lagrangian. Adaptive reconstruction algorithms and space-mesh refinement indicators are also presented. Our computational tests show the qualitative reconstruction of the dielectric permittivity function using an anatomically realistic breast phantom.

5

Sena, Arcangelo G., and M. Nafi Toksöz. "Simultaneous reconstruction of permittivity and conductivity for crosshole geometries." GEOPHYSICS 55, no. 10 (October 1990): 1302–11. http://dx.doi.org/10.1190/1.1442777.

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We develop the theory and algorithm for the simultaneous inversion of permittivity and conductivity maps in the region between two boreholes in the earth. The three‐dimensional region is modeled as an inhomogeneous annulus of known thickness and height with radial and vertical variations of the electrical properties. The medium of interest is probed by a vertical magnetic dipole located on the axis of the cylindrical geometry and the receivers can be placed anywhere outside the inhomogeneous annulus. The inversion procedure is formulated in terms of a source‐type integral equation using monochromatic data. The integral equation is solved using an iterative approach where a Born approximation is applied at each iteration step. The nonuniqueness of the problem is overcome by imposing additional constraints on the solution using the method of regularization of Tikhonov. The distribution of electrical properties is obtained directly by this method. Numerical simulations, including multisource inversions, show that good results can be obtained for smoothly varying electrical properties, even for large contrast cases. In the case of rapid local variations of such properties, convergence can still be reached but at a slower rate and the reconstructions are smoothed versions of the original properties. In the presence of noise, the permittivity reconstruction is more robust than the conductivity reconstruction for the model considered here.

6

Yakovlev, Vadim V., Ethan K. Murphy, and E. Eugene Eves. "Neural networks for FDTD‐backed permittivity reconstruction." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 24, no. 1 (March 2005): 291–304. http://dx.doi.org/10.1108/03321640510571318.

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7

Moll, Jochen, Thomas N. Kelly, Dallan Byrne, Mantalena Sarafianou, Viktor Krozer, and Ian J. Craddock. "Microwave Radar Imaging of Heterogeneous Breast Tissue Integrating A Priori Information." International Journal of Biomedical Imaging 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/943549.

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Conventional radar-based image reconstruction techniques fail when they are applied to heterogeneous breast tissue, since the underlying in-breast relative permittivity is unknown or assumed to be constant. This results in a systematic error during the process of image formation. A recent trend in microwave biomedical imaging is to extract the relative permittivity from the object under test to improve the image reconstruction quality and thereby to enhance the diagnostic assessment. In this paper, we present a novel radar-based methodology for microwave breast cancer detection in heterogeneous breast tissue integrating a 3D map of relative permittivity as a priori information. This leads to a novel image reconstruction formulation where the delay-and-sum focusing takes place in time rather than range domain. Results are shown for a heterogeneous dense (class-4) and a scattered fibroglandular (class-2) numerical breast phantom using Bristol’s 31-element array configuration.

8

Ren, Shangjie, and Feng Dong. "Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2070 (June 28, 2016): 20150333. http://dx.doi.org/10.1098/rsta.2015.0333.

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Electrical capacitance tomography (ECT) is a non-destructive detection technique for imaging the permittivity distributions inside an observed domain from the capacitances measurements on its boundary. Owing to its advantages of non-contact, non-radiation, high speed and low cost, ECT is promising in the measurements of many industrial or biological processes. However, in the practical industrial or biological systems, a deposit is normally seen in the inner wall of its pipe or vessel. As the actual region of interest (ROI) of ECT is surrounded by the deposit layer, the capacitance measurements become weakly sensitive to the permittivity perturbation occurring at the ROI. When there is a major permittivity difference between the deposit and the ROI, this kind of shielding effect is significant, and the permittivity reconstruction becomes challenging. To deal with the issue, an interface and permittivity simultaneous reconstruction approach is proposed. Both the permittivity at the ROI and the geometry of the deposit layer are recovered using the block coordinate descent method. The boundary and finite-elements coupling method is employed to improve the computational efficiency. The performance of the proposed method is evaluated with the simulation tests. This article is part of the themed issue ‘Supersensing through industrial process tomography’.

9

Garnero, L., A. Franchois, J. P. Hugonin, C. Pichot, and N. Joachimowicz. "Microwave imaging-complex permittivity reconstruction-by simulated annealing." IEEE Transactions on Microwave Theory and Techniques 39, no. 11 (1991): 1801–7. http://dx.doi.org/10.1109/22.97480.

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10

Fang, Weifu. "Reconstruction of permittivity profile from boundary capacitance data." Applied Mathematics and Computation 177, no. 1 (June 2006): 178–88. http://dx.doi.org/10.1016/j.amc.2005.10.046.

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Більше джерел

Дисертації з теми "Permittivity reconstruction":

1

Akhtar, Jaleel. "Controlled resolution reconstruction of one-dimensional permittivity profiles." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=971682518.

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2

Cousin, Théau. "Modélisation et simulation numérique du problème inverse en tomographie électromagnétique." Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMIR03.

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Cette thèse s'inscrit dans un projet de recherche qui a pour ambition de développer, dans une démarche écologique, une méthodologie permettant de retrouver la densité des matériaux du génie civil. L'objectif est de remplacer une méthode invasive et nucléaire par une approche non destructive et électromagnétique. Les travaux de cette thèse sont issues d'une collaboration Cifre entre le Cerema, Routes de France et le Laboratoire de Mathématiques de l'INSA de Rouen Normandie (LMI). Des premiers travaux ont permis d'établir un lien entre la densité et la permittivité diélectrique d'un matériau, ce qui a conduit l'équipe ENDSUM du Cerema Normandie à réaliser un banc permettant d'émettre et de recevoir des ondes électromagnétiques. Il est équipé de moteurs pas à pas pour les antennes et un moteur pour le support, permettant d'accéder à des mesures de type tomographie. L'objectif de cette thèse est de mettre en place un solveur permettant de réaliser une inversion sur les données générées par ce banc afin de retrouver la permittivité et in fine la compacité. Cela implique la modélisation et la simulation numérique de ce système, basée sur la diffraction des ondes électromagnétiques régie par les équations de Maxwell que nous avons étudiés en ordre 2. La réalisation de ce solveur 3D a nécessité l'implémentation d'une méthode type Élément Finis, basée sur les Éléments Finis de Nédelec. La prise en compte du caractère non borné du domaine a été réalisée grâce à l'implémentation de Perfectly Matched Layers. Afin d'optimiser l'implémentation, nous avons également mis en place une vectorisation de l'assemblage des matrices de discrétisation et implémenté une méthode de décomposition de domaine. Finalement, la résolution du problème de minimisation s'est faite par une approche de type Gauss-Newton utilisant la méthode d'état adjoints pour le calcul de la matrice Hessienne. Cette résolution est combinée avec une régularisation de Tikhonov dite semi-quadratique permettant d'accentuer le contraste dans la permittivité recherchée. La modélisation du banc a également nécessité des travaux sur le calibrage des antennes utilisées. Nous avons réadapté les travaux dans le but de considérer les antennes comme une source ponctuelle associée à une onde sphérique et mis en place un procédé expérimental permettant de corriger les signaux reçus
This thesis is part of a research project aiming to develop, in an ecological approach, a methodology for retrieving the density of civil engineering materials. The objective is to replace an invasive and nuclear method with a non-destructive and electromagnetic approach. The work of this thesis stems from a CIFRE collaboration between Cerema, Routes de France, and the Laboratory of Mathematics at INSA Rouen Normandie (LMI).The initial work has established a relationship between the density and the dielectric permittivity of a material, leading the ENDSUM team at Cerema Normandie to develop a bench capable of emitting and receiving electromagnetic waves. It is equipped with stepper motors for the antennas and a motor for the support, enabling tomography-type measurements. The objective of this thesis is to implement a solver capable of performing inversion on the data generated by this bench to retrieve the permittivity and ultimately the compactness. This involves the numerical modeling and simulation of this system, based on the diffraction of electromagnetic waves governed by the Maxwell equations we studied in second order. The development of this 3D solver required the implementation of a Finite Element type method, based on Nedelec Finite Elements. The consideration of the unbounded nature of the domain was achieved through the implementation of Perfectly Matched Layers. To optimize the implementation, we also introduced vectorization of the discretization matrix assembly and implemented a domain decomposition method. Finally, the resolution of the minimization problem was carried out using a Gauss-Newton approach utilizing the adjoint state method for computing the Hessian matrix. This resolution is combined with a semi-quadratic Tikhonov regularization method to enhance the contrast in the desired permittivity.The modeling of the bench also required work on the calibration of the antennas used. We have readapted previous work to consider the antennas as a point source associated with a spherical wave and implemented an experimental process to correct the received signals

3

Chen, Ying-Feng, and 陳穎鋒. "Permittivity Distribution Reconstruction of Dielectric Objects by a Cascaded Method." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/71538440445099170844.

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碩士
淡江大學
電機工程學系碩士班
94
In this paper, we propose a method, which combines a genetic algorithm (GA) with a Newton-type iteration for the reconstruction of permittivity distribution of two-dimensional (2-D) dielectric objects. The method is based on a multi-illumination multiview processing. In particular, by taking account into the complete nonlinear formulations, the permittivity distribution of the objects could be highly-contrasted and complicated inhomogeneous. First, the inverse problem is recast as a global nonlinear optimization problem, which is solved by a GA. Then, the solution obtained by the GA is taken as an initial guess for the Newton-type iteration method. This method is tested by considering several numerical examples, and it is found that the performance of this combination method is better than the individual GA and the individual Newton-type iteration method. Numerical results show that satisfactory reconstruction has been obtained.

4

Ying-Feng and 陳穎鋒. "Permittivity Distribution Reconstruction of Dielectric Objects by a Cascaded Method." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/12170308198895442668.

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碩士
淡江大學
電機工程學系碩士班
94
In this paper, we propose a method, which combines a genetic algorithm (GA) with a Newton-type iteration for the reconstruction of permittivity distribution of two-dimensional (2-D) dielectric objects. The method is based on a multi-illumination multiview processing. In particular, by taking account into the complete nonlinear formulations, the permittivity distribution of the objects could be highly-contrasted and complicated inhomogeneous. First, the inverse problem is recast as a global nonlinear optimization problem, which is solved by a GA. Then, the solution obtained by the GA is taken as an initial guess for the Newton-type iteration method. This method is tested by considering several numerical examples, and it is found that the performance of this combination method is better than the individual GA and the individual Newton-type iteration method. Numerical results show that satisfactory reconstruction has been obtained.

5

Akhtar, Jaleel [Verfasser]. "Controlled resolution reconstruction of one-dimensional permittivity profiles / von Jaleel Akhtar." 2003. http://d-nb.info/971682518/34.

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6

Tiede, Tyler. "Inversion of surface contacting antenna measurements for sea ice complex permittivity reconstruction." 2017. http://hdl.handle.net/1993/32238.

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The need to monitor geophysical properties of first year ice (FYI) in the Arctic is increasing as this type of sea ice becomes more prevalent. One such method of monitoring the Arctic is the use of electromagnetic remote sensing techniques. These methods determine dielectric properties of the illuminated sea ice by interpreting how the electromagnetic waves interact within the medium. In the literature, there are empirical formulas relating these dielectric properties to the geophysical properties of the sea ice. The contributions of this research are the development and testing of a surface based active microwave remote sensor to monitor sea ice growth in the winter through the reconstruction of the time series complex permittivity profile of FYI.
October 2017

Частини книг з теми "Permittivity reconstruction":

1

Hugonin, J. P., N. Joachimowicz, and Ch Pichot. "Quantitative Reconstruction of Complex Permittivity Distributions by Means of Microwave Tomography." In Inverse Problems and Theoretical Imaging, 302–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75298-8_37.

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2

Beilina, L., and E. Lindström. "A Posteriori Error Estimates and Adaptive Error Control for Permittivity Reconstruction in Conductive Media." In Springer Proceedings in Mathematics & Statistics, 117–41. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35871-5_7.

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3

Smirnov, Yu G., Yu V. Shestopalov, and E. D. Derevyanchuk. "Permittivity Reconstruction of Layered Dielectrics in a Rectangular Waveguide from the Transmission Coefficients at Different Frequencies." In Springer Proceedings in Mathematics & Statistics, 169–81. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00660-4_11.

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4

Abrosimov, Mikhail, Alexander Brovko, Ruslan Pakharev, Anton Pudikov, and Konstantin Reznikov. "Reconstruction of 3D Permittivity Profile of a Dielectric Sample Using Artificial Neural Network Mathematical Model and FDTD Simulation." In Advances in Intelligent Systems and Computing, 272–79. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91192-2_27.

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5

Smirnov, Yuri G., Yuri V. Shestopalov, and Ekaterina D. Derevyanchuk. "Solution to the Inverse Problem of Reconstructing Permittivity of an $$n$$ -Sectional Diaphragm in a Rectangular Waveguide." In Springer Proceedings in Mathematics & Statistics, 555–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55361-5_32.

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Тези доповідей конференцій з теми "Permittivity reconstruction":

1

Pinard, H., M. Dietrich, S. Garambois, F. Lavoué, L. Métivier, and J. M. Virieux. "Simultaneous GPR Reconstruction of Electrical Conductivity and Permittivity." In 77th EAGE Conference and Exhibition - Workshops. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201413536.

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2

Yilmaz, Tuba, and Yang Hao. "Compact Resonators for Permittivity Reconstruction of Biological Tissues." In 2011 XXXth URSI General Assembly and Scientific Symposium. IEEE, 2011. http://dx.doi.org/10.1109/ursigass.2011.6123735.

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3

G. Gorriti, A., E. C. Slob, and J. Bruining. "Accurate reconstruction of permittivity from coaxial transmission line measurements." In 8th EEGS-ES Meeting. European Association of Geoscientists & Engineers, 2002. http://dx.doi.org/10.3997/2214-4609.201406274.

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4

Tomasek, Pavel. "Reconstruction of permittivity of unknown materials in free space." In 2016 17th International Carpathian Control Conference (ICCC). IEEE, 2016. http://dx.doi.org/10.1109/carpathiancc.2016.7501194.

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5

Tomasek, P., Y. V. Shestopalov, and V. Kresalek. "Reconstruction of permittivity of multiple layers in free space." In 2015 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2015. http://dx.doi.org/10.1109/iceaa.2015.7297188.

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6

Zhu, Zengyan, and Yutao Wang. "Simultaneous Reconstruction of Conductivity and Permittivity in Electrical Impedance Tomography." In 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8833397.

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7

Vogelzang, E., H. A. Ferwerda, and D. Yevick. "Reconstruction Of The Permittivity Profile Of A Stratified Dielectric Layer." In 1984 European Conference on Optics, Optical Systems and Applications, edited by Bouwe Bolger and Hedzer A. Ferwerda. SPIE, 1985. http://dx.doi.org/10.1117/12.943736.

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8

Zhang, Wenji, and Ahmad Hoorfar. "Two-dimensional permittivity profile reconstruction with distorted Rytov iterative method." In Computational Electromagnetics (ICMTCE). IEEE, 2011. http://dx.doi.org/10.1109/icmtce.2011.5915171.

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9

Tomasek, P., Y. V. Shestopalov, and V. Kresalek. "Comparison of selected evolutionary techniques used in reconstruction of permittivity." In 2015 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2015. http://dx.doi.org/10.1109/iceaa.2015.7297189.

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10

Derevyanchuk, E. D., and Yu G. Smirnov. "Tensor permittivity reconstruction of two-sectional diaphragm in a rectangular waveguide." In Days on Diffraction 2014 (DD). IEEE, 2014. http://dx.doi.org/10.1109/dd.2014.7036425.

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