367 citations · 460 across the 11 of their papers we have counts for
13 papers
Domain independent post-processing with graph U-nets: Applications to Electrical Impedance Tomographic Imaging
William Herzberg, Andreas Hauptmann, Sarah J. Hamilton
Reconstruction of tomographic images from boundary measurements requires flexibility with respect to target domains. For instance, when the system equations are modeled by partial…
Fast Absolute 3D CGO-Based Electrical Impedance Tomography on Experimental Tank Data
S. J. Hamilton, P. A. Muller, D. Isaacson +5
Objective: To present the first 3D CGO-based absolute EIT reconstructions from experimental tank data. Approach: CGO-based methods for absolute EIT imaging are compared to traditio…
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems
William Herzberg, Daniel B. Rowe, Andreas Hauptmann +1
The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains, such as pixelated images. If the underlying model is solve…
3D EIT Reconstructions from Electrode Data using Direct Inversion D-bar and Calderon Methods
Sarah J. Hamilton, David Isaacson, Ville Kolehmainen +3
The first numerical implementation of a D-bar method in 3D using electrode data is presented. Results are compared to Calderón's method as well as more common TV and smoothness reg…
Beltrami-Net: Domain Independent Deep D-bar Learning for Absolute Imaging with Electrical Impedance Tomography (a-EIT)
S. J. Hamilton, A. Hänninen, A. Hauptmann +1
Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction method for absolute Electrical Impedance Tomography (a-EIT) that pairs deep learning techniq…
Robust Computation in 2D Absolute EIT (a-EIT) Using D-bar Methods with the `exp' Approximation
S. J. Hamilton, J. L. Mueller, T. R. Santos
Objective: Absolute images have important applications in medical Electrical Impedance Tomography (EIT) imaging, but the traditional minimization and statistical based computations…
Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks
Sarah Jane Hamilton, Andreas Hauptmann
The mathematical problem for Electrical Impedance Tomography (EIT) is a highly nonlinear ill-posed inverse problem requiring carefully designed reconstruction procedures to ensure…
Incorporating a Spatial Prior into Nonlinear D-Bar EIT imaging for Complex Admittivities
Sarah Jane Hamilton, Jennifer L. Mueller, Melody Alsaker
Electrical Impedance Tomography (EIT) aims to recover the internal conductivity and permittivity distributions of a body from electrical measurements taken on electrodes on the sur…
A Hybrid Segmentation and D-bar Method for Electrical Impedance Tomography
Sarah Hamilton, Juan Manuel Reyes, Samuli Siltanen +1
The Regularized D-bar method for Electrical Impedance Tomography provides a rigorous mathematical approach for solving the full nonlinear inverse problem directly, i.e. without ite…
A Direct Reconstruction Method for Anisotropic Electrical Impedance Tomography
Sarah Jane Hamilton, Matti Lassas, Samuli Siltanen
A novel computational, non-iterative and noise-robust reconstruction method is introduced for the planar anisotropic inverse conductivity problem. The method is based on bypassing…
A Data-Driven Edge-Preserving D-bar Method for Electrical Impedance Tomography
Sarah Hamilton, Andreas Hauptmann, Samuli Siltanen
In Electrical Impedance Tomography (EIT), the internal conductivity of a body is recovered via current and voltage measurements taken at its surface. The reconstruction task is a h…
Nonlinear Inversion from Partial EIT Data: Computational Experiments
Sarah Jane Hamilton, Samuli Siltanen
Electrical impedance tomography (EIT) is a non-invasive imaging method in which an unknown physical body is probed with electric currents applied on the boundary, and the internal…
A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2-D
S. J. Hamilton, C. N. L. Herrera, J. L. Mueller +1
A direct reconstruction algorithm for complex conductivities in , where is a bounded, simply connected Lipschitz domain in , is presented. The fr…