Gotowe bibliografie tematyczne / Impedance reconstruction

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  5. Streszczenia konferencji

Gotowa bibliografia na temat „Impedance reconstruction”

Autor: Grafiati
Data publikacji: 2 czerwca 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Impedance reconstruction"

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Basak, Rinku, and Khan A. Wahid. "A Rapid, Low-Cost, and High-Precision Multifrequency Electrical Impedance Tomography Data Acquisition System for Plant Phenotyping." Remote Sensing 14, no. 13 (2022): 3214. http://dx.doi.org/10.3390/rs14133214.

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Plant phenotyping plays an important role for the thorough assessment of plant traits such as growth, development, and physiological processes with the target of achieving higher crop yields by the proper crop management. The assessment can be done by utilizing two- and three-dimensional image reconstructions of the inhomogeneities. The quality of the reconstructed image is required to maintain a high accuracy and a good resolution, and it is desirable to reconstruct the images with the lowest possible noise. In this work, an electrical impedance tomography (EIT) data acquisition system is dev
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Tchórzewski, Paweł, Małgorzata Lalak - Dybała, Bartosz Przysucha, and Paweł Olszewski. "Use of electrical impedance tomography for lung volume reconstruction." Journal of Modern Science 57, no. 3 (2024): 622–36. http://dx.doi.org/10.13166/jms/191357.

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The article presents a study of the application of electro-impedance tomography (EIT) in diagnosing lung capacity using the Tikhonov regularization method. The possibility of reconstructing the lungs to monitor the degree of air filling was investigated. The experiment included a series of tests using a torso phantom designed to simulate different states of the lungs - from fully inflated to fully deflated. Lung-filling states were manipulated in controlled scenarios to test nine main experimental conditions reflecting different lung-filling states. In addition, the quality of reconstruction w
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Wang, Qi, Pengcheng Zhang, Jianming Wang, et al. "Patch-based sparse reconstruction for electrical impedance tomography." Sensor Review 37, no. 3 (2017): 257–69. http://dx.doi.org/10.1108/sr-07-2016-0126.

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Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary opti
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Zheng, Hai-Ying, Yang Li, Nan Wang, et al. "A novel framework for three-dimensional electrical impedance tomography reconstruction of maize ear via feature reconfiguration and residual networks." PeerJ Computer Science 10 (April 11, 2024): e1944. http://dx.doi.org/10.7717/peerj-cs.1944.

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Electrical impedance tomography (EIT) provides an indirect measure of the physiological state and growth of the maize ear by reconstructing the distribution of electrical impedance. However, the two-dimensional (2D) EIT within the electrode plane finds it challenging to comprehensively represent the spatial distribution of conductivity of the intact maize ear, including the husk, kernels, and cob. Therefore, an effective method for 3D conductivity reconstruction is necessary. In practical applications, fluctuations in the contact impedance of the maize ear occur, particularly with the increase
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Nguyen Diep, Quoc Tuan, Hoang Nhut Huynh, Thanh Ven Huynh, Minh Quan Cao Dinh, Anh Tu Tran, and Trung Nghia Tran. "Impact of ISTA and FISTA iterative optimization algorithms on electrical impedance tomography image reconstruction." Journal of Electrical Bioimpedance 16, no. 1 (2025): 11–22. https://doi.org/10.2478/joeb-2025-0003.

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Abstract Electrical Impedance Tomography (EIT) is a non-invasive method for imaging conductivity distributions within a target area. The inverse problem associated with EIT is nonlinear and ill-posed, leading to low spatial resolution reconstructions. Iterative algorithms are widely employed to address complex inverse problems. However, current iterative methods have notable limitations, such as the arbitrary and subjective selection of initial parameters, lengthy computational times due to numerous iterations, and the generation of reconstructions that suffer from shape blurring and a lack of
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Azzouz, Mustapha, Martin Hanke, Chantal Oesterlein, and Karl Schilcher. "The Factorization Method for Electrical Impedance Tomography Data from a New Planar Device." International Journal of Biomedical Imaging 2007 (2007): 1–7. http://dx.doi.org/10.1155/2007/83016.

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We present numerical results for two reconstruction methods for a new planar electrical impedance tomography device. This prototype allows noninvasive medical imaging techniques if only one side of a patient is accessible for electric measurements. The two reconstruction methods have different properties: one is a linearization-type method that allows quantitative reconstructions; the other one, that is, the factorization method, is a qualitative one, and is designed to detect anomalies within the body.
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Cieplak, Tomasz, Tomasz Rymarczyk, and Grzegorz Kłosowski. "USING MICROSERVICES ARCHITECTURE AS ANALYTICAL SYSTEM FOR ELECTRICAL IMPEDANCE TOMOGRAPHY IMAGING." Informatics Control Measurement in Economy and Environment Protection 8, no. 1 (2018): 52–55. http://dx.doi.org/10.5604/01.3001.0010.8652.

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An image reconstruction with use of EIT method has been found useful in many areas of medical, industrial and environmental applications. Papers show that computational systems used for image reconstructions are utilizing parallel and distributed computations and multi-tier architecture, as well as monolithic architecture. The aim of our research is to define an analytical system architecture that will be able to combine a variety of image reconstruction algorithms with their representations in different programming languages. Based on examples described in different proceedings and research p
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Chen, Rongqing, Sabine Krueger-Ziolek, Alberto Battistel, Stefan J. Rupitsch, and Knut Moeller. "Effect of a Patient-Specific Structural Prior Mask on Electrical Impedance Tomography Image Reconstructions." Sensors 23, no. 9 (2023): 4551. http://dx.doi.org/10.3390/s23094551.

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Electrical Impedance Tomography (EIT) is a low-cost imaging method which reconstructs two-dimensional cross-sectional images, visualising the impedance change within the thorax. However, the reconstruction of an EIT image is an ill-posed inverse problem. In addition, blurring, anatomical alignment, and reconstruction artefacts can hinder the interpretation of EIT images. In this contribution, we introduce a patient-specific structural prior mask into the EIT reconstruction process, with the aim of improving image interpretability. Such a prior mask ensures that only conductivity changes within
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Padilha Leitzke, Juliana, and Hubert Zangl. "Low-power electrical impedance tomography spectroscopy." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 5 (2019): 1480–92. http://dx.doi.org/10.1108/compel-12-2018-0530.

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Purpose This paper aims to present an approach based on electrical impedance tomography spectroscopy (EITS) for the determination of water and ice fraction in low-power applications such as autarkic wireless sensors, which require a low computational complexity reconstruction approach and a low number of electrodes. This paper also investigates how the electrode design can affect the reconstruction results in tomography. Design/methodology/approach EITS is performed by using a non-iterative method called optimal first order approximation. In addition to that, a planar electrode geometry is use
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Grayr, Aleksanyan, Katsupeev Andrey, Sulyz Andrey, Pyatnitsin Stanislav, and Peregorodiev Danil. "DEVELOPMENT OF THE WEB PORTAL FOR RESEARCH SUPPORT IN THE AREA OF ELECTRICAL IMPEDANCE TOMOGRAPHY." Eastern-European Journal of Enterprise Technologies 6, no. 2 (102) (2019): 6–15. https://doi.org/10.15587/1729-4061.2019.184318.

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The concept of electrical impedance tomography is considered. Modern software solutions implementing the methods and algorithms of electrical impedance tomography are studied. It is concluded that existing solutions for applied research and development in the field of electrical impedance tomography either do not implement differential reconstruction methods, or do not provide multi-user access. This imposes a number of limitations when conducting research and creates barriers to obtaining new results in the field of electrical impedance tomography. Given the current state of development of sc
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Rozprawy doktorskie na temat "Impedance reconstruction"

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Breckon, W. R. "Image reconstruction in Electrical Impedance Tomography." Thesis, Oxford Brookes University, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292254.

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Tang, Mengxing. "Image reconstruction in electrical impedance mammography." Thesis, De Montfort University, 2003. http://hdl.handle.net/2086/6260.

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Breast cancer continues to be a leading cause of death in Western countries. One of the most important approaches to reduce this mortality is to detect the cancer as early as possible. Although current diagnostic imaging modalities are able to give useful information for diagnosis, development of new imaging technique is highly desirable in order to detect breast cancer in an earlier stage. This is the motive of the present study of Electrical Impedance Mammography (ElM), which applies Electrical Impedance Tomography (EIT) to image human breasts. The overall aim of the whole project is to deve
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Scrivanti, Gabriele Luca Giovanni. "Nonsmooth Nonconvex Variational Reconstruction for Electrical Impedance Tomography." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20700/.

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Electrical Impedance Tomography is an imaging technique that aims to reconstruct the inner conductivity distribution of a medium starting from a set of measured voltages registered by a series of electrodes that are positioned on the surface of the medium. Such technique was used for the first time in geological studies in 1930 and then applied to industrial procedures. The first clinical use of EIT dates back to 1987. In 2018 EIT was validated in tissue engineering as a noninvasive and label-free imaging and monitoring tool for cell distribution (cell growth, differentiation and tissue forma
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Artola, Jose. "A study on electrical impedance tomography reconstruction algorithms." Thesis, University of York, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241077.

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Kalisse, Camille George Emile. "Reconstruction algorithms for the Aberdeen impedance imaging systems." Thesis, University of Aberdeen, 1993. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU055336.

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The backprojection method for electrical impedance image reconstruction has been adapted for the opposing current drive configuration implemented in the second generation of Aberdeen impedance imaging systems. The logarithmic conformal transformation is used to solve the Forward problem for a two-dimensional homogeneous medium of circular cross-section. Pixel weights of backprojection are calculated from the normalised distances of the pixel centres from the boundary side of backprojection. An experimental solution to the Forward problem is a homogeneous medium of irregular cross-section and t
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Kotre, Colin John. "Studies of image reconstruction methods for electrical impedance tomography." Thesis, University of Newcastle Upon Tyne, 1993. http://hdl.handle.net/10443/362.

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Electrical impedance tomography (EIT) is a technique in which images representing the cross-sectional distribution of electrical impedance within a threedimensional object are reconstructed from measurements on the object surface. In this work, some developments of image reconstruction algorithms aimed at increasing the value of this technique in the field of medical diagnosis are studied. The electrical properties of biological tissue and the possibilities for medical applications of EIT are first reviewed. The physical and mathematical basis for EIT is then. examined with particular regard f
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Bouallouche, Amar. "Development of novel reconstruction algorithms for induced current impedance imaging." Thesis, University of Sheffield, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387636.

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Zadehkoochak, Mohsen. "Image reconstruction and spectral expansion analysis in electrical impedance tomography." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385528.

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Meeson, Stuart. "An investigation of optimal performance criteria in electrical impedance tomography." Thesis, University of Southampton, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389013.

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Perez-Juste, Abascal Juan Felipe. "Improvements in reconstruction algorithms for electrical impedance tomography of brain function." Thesis, University College London (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444541.

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Książki na temat "Impedance reconstruction"

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Bryan, Kurt. Reconstruction of multiple cracks from experimental electrostatic boundary measurements. Institute for Computer Applications in Science and Engineering, 1993.

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Bryan, Kurt. Reconstruction of multiple cracks from experimental electrostatic boundary measurements. National Aeronautics and Space Administration, Langley Research Center, 1994.

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Części książek na temat "Impedance reconstruction"

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Lefebvre, Jean-Pierre. "Acoustic Impedance Tomography: Two Reconstruction Procedures." In Acoustical Imaging. Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2523-9_81.

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Tuman, Matthew J., Matthew S. Allen, Washington J. DeLima, Eric Dodgen, and Jonathan Hower. "Balancing Impedance and Controllability in Response Reconstruction." In Sensors and Instrumentation, Aircraft/Aerospace and Dynamic Environments Testing, Volume 7. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05415-0_12.

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Colibazzi, Francesco, Damiana Lazzaro, Serena Morigi, and Andrea Samorè. "Limited Electrodes Models in Electrical Impedance Tomography Reconstruction." In Lecture Notes in Computer Science. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-31975-4_6.

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Wu, Kejian, Jiqing Yang, Xiuzhen Dong, Feng Fu, Feng Tao, and Shuo Liu. "Comparative Study of Reconstruction Algorithms for Electrical Impedance Tomography." In IFMBE Proceedings. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29305-4_602.

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Kim, Ho-Chan, Chang-Jin Boo, and Min-Jae Kang. "Image Reconstruction Using Genetic Algorithm in Electrical Impedance Tomography." In Neural Information Processing. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11893295_103.

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Chang, Tiantian, and Xuyang Huo. "Modified Newton Raphson Algorithm for Electrical Impedance Image Reconstruction." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89698-0_95.

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Boo, Chang-Jin, Ho-Chan Kim, Min-Jae Kang, and Kwang Y. Lee. "Stochastic Optimization Approaches to Image Reconstruction in Electrical Impedance Tomography." In Computational Science and Its Applications – ICCSA 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12165-4_8.

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Bowler, J. R., D. J. Harrison, and S. J. Norton. "Inversion of Eddy Current Probe Impedance Data for Crack Reconstruction." In Review of Progress in Quantitative Nondestructive Evaluation. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2848-7_30.

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Wolff, Julia Grasiela Busarello, David William Cordeiro Marcondes, Wellington P. dos Santos, and Pedro Bertemes-Filho. "Image Reconstruction for COVID-19 Using Multifrequency Electrical Impedance Tomography." In Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79753-9_19.

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Chen, Min-you, Gang Hu, Wei He, Yan-li Yang, and Jin-qian Zhai. "A Reconstruction Method for Electrical Impedance Tomography Using Particle Swarm Optimization." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15597-0_38.

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Streszczenia konferencji na temat "Impedance reconstruction"

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Bouchhima, Mejda, Oumaima Bader, Mariem Hafsa, Salwa Sahnoun, Najoua Essoukri Ben Amara, and Olfa Kanoun. "Evaluation of Adjacent and Opposite Current Injection Patterns for 3D Image Reconstruction of the Human Lung Based on a Realistic Model." In 2024 International Workshop on Impedance Spectroscopy (IWIS). IEEE, 2024. https://doi.org/10.1109/iwis63047.2024.10847107.

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Thönes, Jacob, and Sascha Spors. "Data-Driven 3D Reconstruction for Electrical Impedance Tomography." In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024. https://doi.org/10.1109/embc53108.2024.10781524.

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Wang, Kun, Shengwei Teng, Siying Lin, Keyu Chen, and Ruwen Zhao. "An Improved Super-Resolution Image Reconstruction for Electrical Impedance Tomography." In 2024 7th International Conference on Machine Learning and Natural Language Processing (MLNLP). IEEE, 2024. https://doi.org/10.1109/mlnlp63328.2024.10800348.

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Hafsa, Mariem, Kailun Lin, Najoua Essoukri Ben Amara, and Olfa Kanoun. "A Robust Convolutional Neural Network for Electrical Impedance Tomography Image Reconstruction." In 2025 IEEE 22nd International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2025. https://doi.org/10.1109/ssd64182.2025.10989815.

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Gorin, Nikita A., Evgenii A. Nabiulin, and Georgii Ye Plytkivich. "3D Reconstruction and Parameterization of Chest Anatomy for Electrical Impedance Analysis." In 2025 7th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2025. https://doi.org/10.1109/reepe63962.2025.10970912.

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Shi, Shuaikai, and Panos Liatsis. "Electrical Impedance Tomography Image Reconstruction Based on Graph Laplacian and Sparse Learning." In 2024 7th International Conference on Power and Energy Applications (ICPEA). IEEE, 2024. https://doi.org/10.1109/icpea63589.2024.10784665.

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Zhu, Hongxi, Dhiya Al-Jumeily, and Panos Liatsis. "A generative approach to Electrical Impedance Tomography image reconstruction using prior information." In 2024 31st International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE, 2024. http://dx.doi.org/10.1109/iwssip62407.2024.10634018.

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Dolgin, M., and P. D. Einziger. "Bessel Transform Electrical Impedance Tomography Method for Reconstruction of Layered Biological Tissues." In 16th International Zurich Symposium and Technical Exposition on Electromagnetic Compatibility. IEEE, 2005. https://doi.org/10.23919/emc.2005.10806394.

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Ivinskij, Vadimas, and Inga Morkvėnaitė-Vilkončienė. "Polynomial Approximation Degree Influence on Implicit Network Regularization for Impedance Signal Reconstruction." In 2025 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream). IEEE, 2025. https://doi.org/10.1109/estream66938.2025.11016831.

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Kahouli, Oumayma, Mariem Hafsa, Hiba Hellara, Imed Eddine Bennour, Najoua Essoukri Ben Amara, and Olfa Kanoun. "Enhanced Particle Swarm Optimization Algorithm for EIT Image Reconstruction." In 2022 International Workshop on Impedance Spectroscopy (IWIS). IEEE, 2022. http://dx.doi.org/10.1109/iwis57888.2022.9975123.

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