Electrical conductivity imaging via contactless measurements

A New Method of Haemorrhagic Stroke Detection Via Deep Magnetic Induction Tomography

Hemorrhage imaging is one of the most common applications of magnetic induction tomography (MIT). Depth and the mass of stroke stimulated (MSS) are the most important issues that need to be solved for this application. Transcranial magnetic stimulation (TMS) is a technique belonging to the deep brain stimulation (DBS) field, which aims at overcoming human diseases such as depression. TMS coils, namely, circular, figure-8, and H-coils, play an important role in TMS. Among these, H-coils individually focus on the issues of achieving effective stimulation of deep region. MIT and TMS mechanisms are similar. Herein, for the first time, improved TMS coils, including figure-8 and H-coils, are applied as MIT excitation coils to study the possibility of achieving the mass of stroke stimulated and deep detection through MIT. In addition, the configurations of the detection coils are varied to analyze their influence and determine the optimal coils array. Finally, MIT is used to detect haemorrhagic stroke occurring in humans, and the application of deep MIT to the haemorrhagic stroke problem is computationally explored. Results show that among the various coils, the improved H-coils have MSS and depth characteristics that enable the detection of deep strokes through MIT. Although the detecting depth of the figure-8 coil is weaker, its surface signal is good. The deep MIT technique can be applied to haemorrhagic detection, providing a critical base for deeper research.

Design and characterization of an electromagnetic probe for distinguishing morphological differences in soft tissues

We present a method for designing and optimizing an in-house designed electromagnetic probe for distinguishing morphological differences in biological tissues. The probe comprises concentric multi-wound coils, the inner being the primary coil and the outer being the detector coil. A time-varying voltage is imposed on the primary coil, resulting in an induced current in the detector coil. For highly conductive samples, eddy currents are induced in the sample and inductively couple with the electromagnetic probe. However, in weakly conducting samples, the primary coupling mechanism is found to be capacitive though there can be a non-negligible inductive component. Both the mutual inductive coupling and the capacitive coupling between the sample and the probe are detected as a change in the induced voltage of the detector coil using lock-in detection. The induced voltage in the detector coil is influenced more by the morphological structure of the specimen rather than by changes in electrical conductivity within different regions of the sample. The instrument response of the lock-in amplifier is also examined with simulated input voltage signals to relate its output to specific changes in inductive and capacitive coupling, in order to relate sample characteristics to a single voltage output. A circuit element model is used to interpret the experimental measurements. It is found that the sensitivity of the measurement for a given set of probe characteristics (resistances, inductances, and capacitances) can be optimized by adding a small amount of capacitance in the external circuit in parallel with the detector coil. Illustrative measurements are presented on animal (porcine and bovine) tissue and on human liver tissue containing a metastatic tumor to demonstrate the capabilities of the probe and measurement method in distinguishing different tissue types despite having similar electrical conductivities. Since biological tissues are multi-scale, heterogeneous materials comprising regions of differing conductivity, permittivity, and morphological structure, the electromagnetic method presented here has the potential to examine structural variations in tissue undergoing physical changes due to healing or disease.

Contactless electrical conductivity measurement of metallic submicron-grain material: Application to the study of aluminum with severe plastic deformation

We measured the electrical conductivity σ of aluminum specimen consisting of submicron-grains by observing the AC magnetic susceptibility resulting from the eddy current. By using a commercial platform for magnetic measurement, contactless measurement of the relative electrical conductivity σn of a nonmagnetic metal is possible over a wide temperature (T) range. By referring to σ at room temperature, obtained by the four-terminal method, σn(T) was transformed into σ(T). This approach is useful for cylinder specimens, in which the estimation of the radius and/or volume is difficult. An experiment in which aluminum underwent accumulative roll bonding, which is a severe plastic deformation process, validated this method of evaluating σ as a function of the fraction of high-angle grain boundaries.

A method to solve the forward problem in magnetic induction tomography based on the weakly coupled field approximation

Magnetic induction tomography (MIT) is a noninvasive modality for imaging the complex conductivity (kappa = sigma + jomegaepsilon) or the magnetic permeability (mu) of a target under investigation. Because MIT employs noncontact coils for excitation and detection, MIT may be suitable for imaging biological tissues. In medical applications where high resolutions are sought, image reconstruction is a time and memory consuming task because the associated inverse problem is nonlinear and ill-posed. The time and memory constraints are mainly imposed by the solution of the forward problem within the iterative image reconstruction procedure. This paper investigates the application of a weakly coupled approximation to the solution of the forward problem and examines the accuracy against the computation time and memory gained in adopting this approximation. Initially, an analytical solution for mutual impedance change of a coil pair due to a large planar conductive object is presented based on a full wave theory and used to demonstrate a 10 MHz frequency excitation as an acceptable upper frequency limit under which the approximation is valid. Subsequently, a numerical impedance method adopting the approximation is presented. Here the impedance method is used to solve the forward problem, which employs electrical circuit analogues to mesh the target into a network that can be solved using circuit analysis and sparse matrix technique. The error due to the approximation is further estimated numerically with the impedance method against a commercial finite-element package (commercial FE solver, COMSOL) and results show at 10 MHz excitation a 0.4% of tolerance is achieved for conductivities in the range <0.5 S/m. The results also show the method can be applied for low conductivity medical applications and is computationally efficient compared to equivalent finite-element methods.

EEG/MEG source imaging: methods, challenges, and open issues

We present the four key areas of research-preprocessing, the volume conductor, the forward problem, and the inverse problem-that affect the performance of EEG and MEG source imaging. In each key area we identify prominent approaches and methodologies that have open issues warranting further investigation within the community, challenges associated with certain techniques, and algorithms necessitating clarification of their implications. More than providing definitive answers we aim to identify important open issues in the quest of source localization.

A multi-channel magnetic induction tomography measurement system for human brain model imaging

This paper proposes a multi-channel magnetic induction tomography measurement system for biological conductivity imaging in a human brain model. A hemispherical glass bowl filled with a salt solution is used as the human brain model; meanwhile, agar blocks of different conductivity are placed in the solution to simulate the intracerebral hemorrhage. The excitation and detection coils are fixed co-axially, and the axial gradiometer is used as the detection coil in order to cancel the primary field. On the outer surface of the glass bowl, 15 sensor units are arrayed in two circles as measurement parts, and a single sensor unit for cancelling the phase drift is placed beside the glass bowl. The phase sensitivity of our system is 0.204 degrees /S m(-1) with the excitation frequency of 120 kHz and the phase noise is in the range of -0.03 degrees to +0.05 degrees . Only the coaxial detection coil is available for each excitation coil; therefore, 15 phase data are collected in each measurement turn. Finally, the two-dimensional images of conductivity distribution are obtained using an interpolation algorithm. The frequency-varying experiment indicates that the imaging quality becomes better as the excitation frequency is increased.

Reconstruction artefacts in magnetic induction tomography due to patient's movement during data acquisition

Magnetic induction tomography (MIT) attempts to obtain the distribution of passive electrical properties inside the body. Eddy currents are induced in the body using an array of transmitter coils and the magnetic fields of these currents are measured by receiver coils. In clinical usage, the relative position of the coils to the body can change during data acquisition because of the expected/unexpected movements of the patient. Especially in respiration monitoring these movements will inevitably cause artefacts in the reconstructed images. In this paper, this effect was investigated for both state and frequency differential variants of MIT. It was found that a slight shift of the body in the transverse plane causes spurious perturbations on the surface. In reconstructions, this artefact on the surface propagates towards the centre in an oscillatory manner. It was observed that the movement can corrupt all the valuable information in state differential MIT, while frequency differential MIT seems more robust against movement effects. A filtering strategy is offered in order to decrease the movement artefacts in the images. To this end, monitoring of the patient's movement during data acquisition is required.

Low-frequency magnetic subsurface imaging: reconstructing conductivity images of biological tissues via magnetic measurements

A new data acquisition system has been developed. This system measures the external magnetic fields due to induced currents in the body at a relatively low operation frequency of 50 kHz . Data is obtained by scanning a 2-D area on the body surface. For each transmitter position, a single sample (averaged) of the field distribution is used for image reconstruction. The Steepest Descent Algorithm is used to solve the inverse problem related to the field profiles. High-resolution images of agar blocks and an anesthetized leech are presented. The system sensitivity is measured as 13.2 mV/(S/m) using saline solution phantoms and as 155 V/S using resistors. The signal to noise ratio in the measurements is calculated to be 35.44 dB. The linearity in the measurements is explored using saline solutions in the biological conductivity range. The nonlinearity is measured to be 3.96% of the full scale. The nonlinearity is found to be 0.12% when resistor phantoms are used. The spatial resolution in the conductivity images is measured as 9.36 mm for a 7.5-mm-diameter cylindrical agar object. The results show that it is possible to distinguish two bars separated 14.4 mm from each other.

Optimum receiver array design for magnetic induction tomography

Magnetic induction tomography (MIT) is an imaging modality that aims at mapping the distribution of the electrical conductivity inside the body. Eddy currents are induced in the body by magnetic induction and the resulting fields are measured by an array of receiver coils. In MIT, the location of the receivers affects the quality of the image reconstruction. In this paper, a fast deterministic algorithm was applied to obtain optimum receiver array designs for a given specific excitation. The design strategy is based on the iterative exclusion of receiver locations, which yield poor conductivity information, from the space spanning all possible locations until a feasible design is reached. The applicability of "regionally focused" MIT designs that increase the image resolution at a particular region was demonstrated. Currently used design geometries and the corresponding reconstructed images were compared to the images obtained by optimized designs. The eigenvalue analysis of the Hessian matrix showed that the algorithm tends to maintain identical conductivity information content sensed by the receivers. Although the method does not guarantee finding the optimum design globally, the results demonstrate the practical usability of this algorithm in MIT experimental designs.

Absolute conductivity reconstruction in magnetic induction tomography using a nonlinear method

Magnetic induction tomography (MIT) attempts to image the electrical and magnetic characteristics of a target using impedance measurement data from pairs of excitation and detection coils. This inverse eddy current problem is nonlinear and also severely ill posed so regularization is required for a stable solution. A regularized Gauss-Newton algorithm has been implemented as a nonlinear, iterative inverse solver. In this algorithm, one needs to solve the forward problem and recalculate the Jacobian matrix for each iteration. The forward problem has been solved using an edge based finite element method for magnetic vector potential A and electrical scalar potential V, a so called A, A - V formulation. A theoretical study of the general inverse eddy current problem and a derivation, paying special attention to the boundary conditions, of an adjoint field formula for the Jacobian is given. This efficient formula calculates the change in measured induced voltage due to a small perturbation of the conductivity in a region. This has the advantage that it involves only the inner product of the electric fields when two different coils are excited, and these are convenient computationally. This paper also shows that the sensitivity maps change significantly when the conductivity distribution changes, demonstrating the necessity for a nonlinear reconstruction algorithm. The performance of the inverse solver has been examined and results presented from simulated data with added noise.

A multifrequency magnetic induction tomography system using planar gradiometers: data collection and calibration

We developed a 14-channel multifrequency magnetic induction tomography system (MF-MIT) for biomedical applications. The excitation field is produced by a single coil and 14 planar gradiometers are used for signal detection. The object under measurement was rotated (16 steps per turn) to obtain a full data set for image reconstruction. We make measurements at frequencies from 50 kHz to 1 MHz using a single frequency excitation signal or a multifrequency signal containing several frequencies in this range. We used two acquisition boards giving a total of eight synchronous channels at a sample rate of 5 MS s(-1) per channel. The real and imaginary parts of DeltaB/B(0) were calculated using coherent demodulation at all injected frequencies. Calibration, averaging and drift cancellation techniques were used before image reconstruction. A plastic tank filled with saline (D = 19 cm) and with conductive and/or paramagnetic perturbations was measured for calibration and test purposes. We used a FEM model and an eddy current solver to evaluate the experimental results and to reconstruct the images. Measured equivalent input noise voltage for each channel was 2 nV Hz(-1/2). Using coherent demodulation, with an integration time of 20 ms, the measured STD for the magnitude was 7 nV(rms) (close to the theoretical value only taking into account the amplifier's thermal noise). For long acquisition times the drift in the signal produced a bigger effect than the input noise (typical STD was 10 nV with a maximum of 35 nV at one channel) but this effect was reduced using a drift cancellation technique based on averaging. We were able to image a 2 S m(-1) agar sphere (D = 4 cm) inside the tank filled with saline of 1 S m(-1).

Contactless bio-impedance monitoring technique for brain cryosurgery in a 3D head model

A contactless induced-current bio-impedance system for monitoring brain cryosurgery procedure was modeled and numerically simulated, where the excitation coil was also performing as the measuring, or pick-up coil. A segmented three-dimensional (3D) MRI database was used for building the volume conductor geometry, and the numerical finite-volume method was employed for solving the forward problem for calculating the scalar potential distribution and the second-order voltage change on the pick-up coil. Several coil configurations were considered, varying in their relative positioning to the 3D head model. For each case, the sensitivity of the measured voltage change on the excitation coil to the volume of a frozen lesion was calculated. The highest sensitivity (1.1 x 10(-5) relative voltage change per mm3 of frozen tissue) was obtained for a coil arrangement where its closest segment to the volume conductor is at the maximum distance away from the frozen region position. The simulated system signal-to-carrier ratio was O(10(-8)).

Sensitivity of EEG and MEG measurements to tissue conductivity

Monitoring the electrical activity inside the human brain using electrical and magnetic field measurements requires a mathematical head model. Using this model the potential distribution in the head and magnetic fields outside the head are computed for a given source distribution. This is called the forward problem of the electro-magnetic source imaging. Accurate representation of the source distribution requires a realistic geometry and an accurate conductivity model. Deviation from the actual head is one of the reasons for the localization errors. In this study, the mathematical basis for the sensitivity of voltage and magnetic field measurements to perturbations from the actual conductivity model is investigated. Two mathematical expressions are derived relating the changes in the potentials and magnetic fields to conductivity perturbations. These equations show that measurements change due to secondary sources at the perturbation points. A finite element method (FEM) based formulation is developed for computing the sensitivity of measurements to tissue conductivities efficiently. The sensitivity matrices are calculated for both a concentric spheres model of the head and a realistic head model. The rows of the sensitivity matrix show that the sensitivity of a voltage measurement is greater to conductivity perturbations on the brain tissue in the vicinity of the dipole, the skull and the scalp beneath the electrodes. The sensitivity values for perturbations in the skull and brain conductivity are comparable and they are, in general, greater than the sensitivity for the scalp conductivity. The effects of the perturbations on the skull are more pronounced for shallow dipoles, whereas, for deep dipoles, the measurements are more sensitive to the conductivity of the brain tissue near the dipole. The magnetic measurements are found to be more sensitive to perturbations near the dipole location. The sensitivity to perturbations in the brain tissue is much greater when the primary source is tangential and it decreases as the dipole depth increases. The resultant linear system of equations can be used to update the initially assumed conductivity distribution for the head. They may be further exploited to image the conductivity distribution of the head from EEG and/or MEG measurements. This may be a fast and promising new imaging modality.

Text Influenced Molecular Indexing (TIMI): a literature database mining approach that handles text and chemistry

We present an application of a novel methodology called Text Influenced Molecular Indexing (TIMI) to mine the information in the scientific literature. TIMI is an extension of two existing methodologies: (1) Latent Semantic Structure Indexing (LaSSI), a method for calculating chemical similarity using two-dimensional topological descriptors, and (2) Latent Semantic Indexing (LSI), a method for generating correlations between textual terms. The singular value decomposition (SVD) of a feature/object matrix is the fundamental mathematical operation underlying LSI, LaSSI, and TIMI and is used in the identification of associations between textual and chemical descriptors. We present the results of our studies with a database containing 11,571 PubMed/MEDLINE abstracts which show the advantages of merging textual and chemical descriptors over using either text or chemistry alone. Our work demonstrates that searching text-only databases limits retrieved documents to those that explicitly mention compounds by name in the text. Similarly, searching chemistry-only databases can only retrieve those documents that have chemical structures in them. TIMI, however, enables search and retrieval of documents with textual, chemical, and/or text- and chemistry-based queries. Thus, the TIMI system offers a powerful new approach to uncovering the contextual scientific knowledge sought by the medical research community.

Electrical conductivity imaging via contactless measurements: an experimental study

A data-acquisition system has been developed to image electrical conductivity of biological tissues via contactless measurements. This system uses magnetic excitation to induce currents inside the body and measures the resulting magnetic fields. The data-acquisition system is constructed using a PC-controlled lock-in amplifier instrument. A magnetically coupled differential coil is used to scan conducting phantoms by a computer controlled scanning system. A 10000-turn differential coil system with circular receiver coils of radii 15 mm is used as a magnetic sensor. The transmitter coil is a 100-turn circular coil of radius 15 mm and is driven by a sinusoidal current of 200 mA (peak). The linearity of the system is 7.2% full scale. The sensitivity of the system to conducting tubes when the sensor-body distance is 0.3 cm is 21.47 mV/(S/m). It is observed that it is possible to detect a conducting tube of average conductivity (0.2 S/m) when the body is 6 cm from the sensor. The system has a signal-to-noise ratio of 34 dB and thermal stability of 33.4 mV/degrees C. Conductivity images are reconstructed using the steepest-descent algorithm. Images obtained from isolated conducting tubes show that it is possible to distinguish two tubes separated 17 mm from each other. The images of different phantoms are found to be a good representation of the actual conductivity distribution. The field profiles obtained by scanning a biological tissue show the potential of this methodology for clinical applications.