205 research outputs found
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
Lorentz Force Electrical Impedance Tomography
This article describes a method called Lorentz Force Electrical Impedance
Tomography. The electrical conductivity of biological tissues can be measured
through their sonication in a magnetic field: the vibration of the tissues
inside the field induces an electrical current by Lorentz force. This current,
detected by electrodes placed around the sample, is proportional to the
ultrasonic pressure, to the strength of the magnetic field and to the
electrical conductivity gradient along the acoustic axis. By focusing at
different places inside the sample, a map of the electrical conductivity
gradient can be established. In this study experiments were conducted on a
gelatin phantom and on a beef sample, successively placed in a 300 mT magnetic
field and sonicated with an ultrasonic transducer focused at 21 cm emitting 500
kHz bursts. Although all interfaces are not visible, in this exploratory study
a good correlation is observed between the electrical conductivity image and
the ultrasonic image. This method offers an alternative to detecting
pathologies invisible to standard ultrasonography
A mathematical and numerical framework for ultrasonically-induced Lorentz force electrical impedance tomography
We provide a mathematical analysis and a numerical framework for Lorentz
force electrical conductivity imaging. Ultrasonic vibration of a tissue in the
presence of a static magnetic field induces an electrical current by the
Lorentz force. This current can be detected by electrodes placed around the
tissue; it is proportional to the velocity of the ultrasonic pulse, but depends
nonlinearly on the conductivity distribution. The imaging problem is to
reconstruct the conductivity distribution from measurements of the induced
current. To solve this nonlinear inverse problem, we first make use of a
virtual potential to relate explicitly the current measurements to the
conductivity distribution and the velocity of the ultrasonic pulse. Then, by
applying a Wiener filter to the measured data, we reduce the problem to imaging
the conductivity from an internal electric current density. We first introduce
an optimal control method for solving such a problem. A new direct
reconstruction scheme involving a partial differential equation is then
proposed based on viscosity-type regularization to a transport equation
satisfied by the current density field. We prove that solving such an equation
yields the true conductivity distribution as the regularization parameter
approaches zero. We also test both schemes numerically in the presence of
measurement noise, quantify their stability and resolution, and compare their
performance
A mathematical model and inversion procedure for Magneto-Acousto-Electric Tomography (MAET)
Magneto-Acousto-Electric Tomography (MAET), also known as the Lorentz force
or Hall effect tomography, is a novel hybrid modality designed to be a
high-resolution alternative to the unstable Electrical Impedance Tomography. In
the present paper we analyze existing mathematical models of this method, and
propose a general procedure for solving the inverse problem associated with
MAET. It consists in applying to the data one of the algorithms of
Thermo-Acoustic tomography, followed by solving the Neumann problem for the
Laplace equation and the Poisson equation.
For the particular case when the region of interest is a cube, we present an
explicit series solution resulting in a fast reconstruction algorithm. As we
show, both analytically and numerically, MAET is a stable technique yilelding
high-resolution images even in the presence of significant noise in the data
A mathematical and numerical framework for ultrasonically-induced Lorentz force electrical impedance tomography
We provide a mathematical analysis and a numerical framework for Lorentz force electrical conductivity imaging. Ultrasonic vibration of a tissue in the presence of a static magnetic field induces an electrical current by the Lorentz force. This current can be detected by electrodes placed around the tissue; it is proportional to the velocity of the ultrasonic pulse, but depends nonlinearly on the conductivity distribution. The imaging problem is to reconstruct the conductivity distribution from measurements of the induced current. To solve this nonlinear inverse problem, we first make use of a virtual potential to relate explicitly the current measurements to the conductivity distribution and the velocity of the ultrasonic pulse. Then, by applying a Wiener filter to the measured data, we reduce the problem to imaging the conductivity from an internal electric current density. We first introduce an optimal control method for solving such a problem. A new direct reconstruction scheme involving a partial differential equation is then proposed based on viscosity-type regularization to a transport equation satisfied by the current density field. We prove that solving such an equation yields the true conductivity distribution as the regularization parameter approaches zero. We also test both schemes numerically in the presence of measurement noise, quantify their stability and resolution, and compare their performance. © 2014 Elsevier Masson SAS
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Design and simulation of superconducting Lorentz Force Electrical Impedance Tomography (LFEIT)
Quantitative thermo-acoustic imaging: An exact reconstruction formula
This paper aims to mathematically advance the field of quantitative
thermo-acoustic imaging. Given several electromagnetic data sets, we establish
for the first time an analytical formula for reconstructing the absorption
coefficient from thermal energy measurements. Since the formula involves
derivatives of the given data up to the third order, it is unstable in the
sense that small measurement noises may cause large errors. However, in the
presence of measurement noise, the obtained formula, together with a noise
regularization technique, provides a good initial guess for the true absorption
coefficient. We finally correct the errors by deriving a reconstruction formula
based on the least square solution of an optimal control problem and prove that
this optimization step reduces the errors occurring and enhances the
resolution
DICOM for EIT
With EIT starting to be used in routine clinical practice [1], it important that the clinically relevant information is portable between hospital data management systems. DICOM formats are widely used clinically and cover many imaging modalities, though not specifically EIT. We describe how existing DICOM specifications, can be repurposed as an interim solution, and basis from which a consensus EIT DICOM âSupplementâ (an extension to the standard) can be writte
Torso shape detection to improve lung monitoring
Two methodologies are proposed to detect the patient-specific boundary of the chest, aiming to produce a more accurate forward model for EIT analysis. Thus, a passive resistive and an inertial prototypes were prepared to characterize and reconstruct the shape of multiple phantoms. Preliminary results show how the passive device generates a minimum scatter between the reconstructed image and the actual shap
Estimation of thorax shape for forward modelling in lungs EIT
The thorax models for pre-term babies are developed based on the CT scans from new-borns and their effect on image reconstruction is evaluated in comparison with other available models
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