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[HTML][HTML] Review on electrical impedance tomography: Artificial intelligence methods and its applications
Electrical impedance tomography (EIT) has been a hot topic among researchers for the last
30 years. It is a new imaging method and has evolved over the last few decades. By …
30 years. It is a new imaging method and has evolved over the last few decades. By …
Machine learning in electromagnetics with applications to biomedical imaging: A review
Biomedical imaging is a relevant noninvasive technique aimed at generating an image of
the biological structure under analysis. The arising visual representation of the …
the biological structure under analysis. The arising visual representation of the …
Deep neural network based electrical impedance tomographic sensing methodology for large-area robotic tactile sensing
Electrical impedance tomography (EIT) based tactile sensor offers significant benefits on
practical deployment because of its sparse electrode allocation, including durability, large …
practical deployment because of its sparse electrode allocation, including durability, large …
Numerical solution of inverse problems by weak adversarial networks
In this paper, a weak adversarial network approach is developed to numerically solve a
class of inverse problems, including electrical impedance tomography and dynamic …
class of inverse problems, including electrical impedance tomography and dynamic …
Advances of deep learning in electrical impedance tomography image reconstruction
T Zhang, X Tian, XC Liu, JA Ye, F Fu, XT Shi… - … in Bioengineering and …, 2022 - frontiersin.org
Electrical impedance tomography (EIT) has been widely used in biomedical research
because of its advantages of real-time imaging and nature of being non-invasive and …
because of its advantages of real-time imaging and nature of being non-invasive and …
Transformer meets boundary value inverse problems
A Transformer-based deep direct sampling method is proposed for electrical impedance
tomography, a well-known severely ill-posed nonlinear boundary value inverse problem. A …
tomography, a well-known severely ill-posed nonlinear boundary value inverse problem. A …
A novel deep neural network method for electrical impedance tomography
X Li, Y Zhou, J Wang, Q Wang, Y Lu… - Transactions of the …, 2019 - journals.sagepub.com
Image reconstruction for Electrical Impedance Tomography (EIT) is a highly nonlinear and ill-
posed inverse problem. It requires the design and employment of feasible reconstruction …
posed inverse problem. It requires the design and employment of feasible reconstruction …
Image reconstruction for electrical impedance tomography using radial basis function neural network based on hybrid particle swarm optimization algorithm
H Wang, K Liu, Y Wu, S Wang, Z Zhang… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
A Hybrid Particle Swarm Optimization (HPSO) algorithm is proposed to optimize the Radial
Basis Function Neural Network (RBFNN) for the image reconstruction of Electrical …
Basis Function Neural Network (RBFNN) for the image reconstruction of Electrical …
Study and comparison of different machine learning-based approaches to solve the inverse problem in electrical impedance tomographies
Abstract Electrical Impedance Tomography (EIT) is a non-invasive technique used to obtain
the electrical internal conductivity distribution from the interior of bodies. This is a promising …
the electrical internal conductivity distribution from the interior of bodies. This is a promising …
Machine learning enhanced electrical impedance tomography for 2D materials
A Coxson, I Mihov, Z Wang, V Avramov… - Inverse …, 2022 - iopscience.iop.org
Electrical impedance tomography (EIT) is a non-invasive imaging technique that
reconstructs the interior conductivity distribution of samples from a set of voltage …
reconstructs the interior conductivity distribution of samples from a set of voltage …