8,053 research outputs found
EIT Reconstruction Algorithms: Pitfalls, Challenges and Recent Developments
We review developments, issues and challenges in Electrical Impedance
Tomography (EIT), for the 4th Workshop on Biomedical Applications of EIT,
Manchester 2003. We focus on the necessity for three dimensional data
collection and reconstruction, efficient solution of the forward problem and
present and future reconstruction algorithms. We also suggest common pitfalls
or ``inverse crimes'' to avoid.Comment: A review paper for the 4th Workshop on Biomedical Applications of
EIT, Manchester, UK, 200
Incorporating a Spatial Prior into Nonlinear D-Bar EIT imaging for Complex Admittivities
Electrical Impedance Tomography (EIT) aims to recover the internal
conductivity and permittivity distributions of a body from electrical
measurements taken on electrodes on the surface of the body. The reconstruction
task is a severely ill-posed nonlinear inverse problem that is highly sensitive
to measurement noise and modeling errors. Regularized D-bar methods have shown
great promise in producing noise-robust algorithms by employing a low-pass
filtering of nonlinear (nonphysical) Fourier transform data specific to the EIT
problem. Including prior data with the approximate locations of major organ
boundaries in the scattering transform provides a means of extending the radius
of the low-pass filter to include higher frequency components in the
reconstruction, in particular, features that are known with high confidence.
This information is additionally included in the system of D-bar equations with
an independent regularization parameter from that of the extended scattering
transform. In this paper, this approach is used in the 2-D D-bar method for
admittivity (conductivity as well as permittivity) EIT imaging. Noise-robust
reconstructions are presented for simulated EIT data on chest-shaped phantoms
with a simulated pneumothorax and pleural effusion. No assumption of the
pathology is used in the construction of the prior, yet the method still
produces significant enhancements of the underlying pathology (pneumothorax or
pleural effusion) even in the presence of strong noise.Comment: 18 pages, 10 figure
A Direct D-Bar Method for Partial Boundary Data Electrical Impedance Tomography With a Priori Information
Electrical Impedance Tomography (EIT) is a non-invasive imaging modality that uses surface electrical measurements to determine the internal conductivity of a body. The mathematical formulation of the EIT problem is a nonlinear and severely ill-posed inverse problem for which direct D-bar methods have proved useful in providing noise-robust conductivity reconstructions. Recent advances in D-bar methods allow for conductivity reconstructions using EIT measurement data from only part of the domain (e.g., a patient lying on their back could be imaged using only data gathered on the accessible part of the body). However, D-bar reconstructions suffer from a loss of sharp edges due to a nonlinear low-pass filtering of the measured data, and this problem becomes especially marked in the case of partial boundary data. Including a priori data directly into the D-bar solution method greatly enhances the spatial resolution, allowing for detection of underlying pathologies or defects, even with no assumption of their presence in the prior. This work combines partial data D-bar with a priori data, allowing for noise-robust conductivity reconstructions with greatly improved spatial resolution. The method is demonstrated to be effective on noisy simulated EIT measurement data simulating both medical and industrial imaging scenarios
Direct EIT Reconstructions of Complex Admittivities on a Chest-Shaped Domain in 2-D
Electrical impedance tomography (EIT) is a medical imaging technique in which current is applied on electrodes on the surface of the body, the resulting voltage is measured, and an inverse problem is solved to recover the conductivity and/or permittivity in the interior. Images are then formed from the reconstructed conductivity and permittivity distributions. In the 2-D geometry, EIT is clinically useful for chest imaging. In this work, an implementation of a D-bar method for complex admittivities on a general 2-D domain is presented. In particular, reconstructions are computed on a chest-shaped domain for several realistic phantoms including a simulated pneumothorax, hyperinflation, and pleural effusion. The method demonstrates robustness in the presence of noise. Reconstructions from trigonometric and pairwise current injection patterns are included
Acousto-electrical speckle pattern in Lorentz force electrical impedance tomography
Ultrasound speckle is a granular texture pattern appearing in ultrasound
imaging. It can be used to distinguish tissues and identify pathologies.
Lorentz force electrical impedance tomography is an ultrasound-based medical
imaging technique of the tissue electrical conductivity. It is based on the
application of an ultrasound wave in a medium placed in a magnetic field and on
the measurement of the induced electric current due to Lorentz force. Similarly
to ultrasound imaging, we hypothesized that a speckle could be observed with
Lorentz force electrical impedance tomography imaging. In this study, we first
assessed the theoretical similarity between the measured signals in Lorentz
force electrical impedance tomography and in ultrasound imaging modalities. We
then compared experimentally the signal measured in both methods using an
acoustic and electrical impedance interface. Finally, a bovine muscle sample
was imaged using the two methods. Similar speckle patterns were observed. This
indicates the existence of an "acousto-electrical speckle" in the Lorentz force
electrical impedance tomography with spatial characteristics driven by the
acoustic parameters but due to electrical impedance inhomogeneities instead of
acoustic ones as is the case of ultrasound imaging
A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2-D
A direct reconstruction algorithm for complex conductivities in
, where is a bounded, simply connected Lipschitz
domain in , is presented. The framework is based on the
uniqueness proof by Francini [Inverse Problems 20 2000], but equations relating
the Dirichlet-to-Neumann to the scattering transform and the exponentially
growing solutions are not present in that work, and are derived here. The
algorithm constitutes the first D-bar method for the reconstruction of
conductivities and permittivities in two dimensions. Reconstructions of
numerically simulated chest phantoms with discontinuities at the organ
boundaries are included.Comment: This is an author-created, un-copyedited version of an article
accepted for publication in [insert name of journal]. IOP Publishing Ltd is
not responsible for any errors or omissions in this version of the manuscript
or any version derived from it. The Version of Record is available online at
10.1088/0266-5611/28/9/09500
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