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 …
Robust imaging using electrical impedance tomography: review of current tools
Electrical impedance tomography (EIT) is a medical imaging technique with many
advantages and great potential for development in the coming years. Currently, some …
advantages and great potential for development in the coming years. Currently, some …
Efficient multitask structure-aware sparse Bayesian learning for frequency-difference electrical impedance tomography
Frequency-difference electrical impedance tomography (fdEIT) was originally developed to
mitigate the systematic artifacts induced by modeling errors when a baseline dataset is …
mitigate the systematic artifacts induced by modeling errors when a baseline dataset is …
Active surveillance via group sparse Bayesian learning
The key to the effective control of a diffusion system lies in how accurately we could predict
its unfolding dynamics based on the observation of its current state. However, in the real …
its unfolding dynamics based on the observation of its current state. However, in the real …
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 …
[PDF][PDF] Survey on medical imaging of electrical impedance tomography (EIT) by variable current pattern methods
EEB Adam, E Babikir - Journal of ISMAC, 2021 - researchgate.net
Recently, the image reconstruction study on EIT plays a vital role in the medical application
field for validation and calibration purpose. This research article analyzes the different types …
field for validation and calibration purpose. This research article analyzes the different types …
Maximum likelihood-based gridless doa estimation using structured covariance matrix recovery and sbl with grid refinement
We consider the parametric measurement model employed in applications such as line
spectral or direction-of-arrival estimation with the goal to estimate the underlying parameter …
spectral or direction-of-arrival estimation with the goal to estimate the underlying parameter …
Comparison of selected machine learning algorithms for industrial electrical tomography
The main goal of this work was to compare the selected machine learning methods with the
classic deterministic method in the industrial field of electrical impedance tomography. The …
classic deterministic method in the industrial field of electrical impedance tomography. The …
[HTML][HTML] Optimising the use of Machine learning algorithms in electrical tomography of building Walls: Pixel oriented ensemble approach
This paper presents the results of research on identifying moisture inside the walls of
buildings with the use of electrical impedance tomography (EIT). The original, complex pixel …
buildings with the use of electrical impedance tomography (EIT). The original, complex pixel …
Comparison of machine learning methods in electrical tomography for detecting moisture in building walls
This paper presents the results of research on the use of machine learning algorithms and
electrical tomography in detecting humidity inside the walls of old buildings and structures …
electrical tomography in detecting humidity inside the walls of old buildings and structures …