Transformer meets boundary value inverse problem
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 …
Learning nonlinear electrical impedance tomography
Electrical impedance tomography (EIT) is the problem of determining the electrical
conductivity distribution of an unknown medium by making voltage and current …
conductivity distribution of an unknown medium by making voltage and current …
Construct deep neural networks based on direct sampling methods for solving electrical impedance tomography
This work investigates the electrical impedance tomography problem when only limited
boundary measurements are available, which is known to be challenging due to the extreme …
boundary measurements are available, which is known to be challenging due to the extreme …
Deep D-bar: Real-time electrical impedance tomography imaging with deep neural networks
SJ Hamilton, A Hauptmann - IEEE transactions on medical …, 2018 - ieeexplore.ieee.org
The mathematical problem for electrical impedance tomography (EIT) is a highly nonlinear ill-
posed inverse problem requiring carefully designed reconstruction procedures to ensure …
posed inverse problem requiring carefully designed reconstruction procedures to ensure …
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches
Electrical Impedance Tomography (EIT) is a powerful imaging technique with diverse
applications, eg, medical diagnosis, industrial monitoring, and environmental studies. The …
applications, eg, medical diagnosis, industrial monitoring, and environmental studies. The …
Improved training of physics-informed neural networks using energy-based priors: a study on electrical impedance tomography
Physics-informed neural networks (PINNs) are attracting significant attention for solving
partial differential equation (PDE) based inverse problems, including electrical impedance …
partial differential equation (PDE) based inverse problems, including electrical impedance …
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 …
DeepEIT: Deep image prior enabled electrical impedance tomography
Neural networks (NNs) have been widely applied in tomographic imaging through data-
driven training and image processing. One of the main challenges in using NNs in real …
driven training and image processing. One of the main challenges in using NNs in real …
A comparative study of variational autoencoders, normalizing flows, and score-based diffusion models for electrical impedance tomography
H Wang, G Xu, Q Zhou - Journal of Inverse and Ill-posed Problems, 2024 - degruyter.com
Abstract Electrical Impedance Tomography (EIT) is a widely employed imaging technique in
industrial inspection, geophysical prospecting, and medical imaging. However, the inherent …
industrial inspection, geophysical prospecting, and medical imaging. However, the inherent …
An image reconstruction framework based on deep neural network for electrical impedance tomography
X Li, Y Lu, J Wang, X Dang, Q Wang… - … Conference on Image …, 2017 - ieeexplore.ieee.org
Electrical impedance tomography (EIT) reconstructs the internal impedance distribution by
making voltage and current measurements on the object's boundary. The image …
making voltage and current measurements on the object's boundary. The image …