A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Formation and Thermal Stability of Gold-Silica Nanohybrids: Insight into the Mechanism and Morphology by Electron Tomography

Gold-silica hybrids are appealing in different fields of applications like catalysis, sensorics, drug delivery, and biotechnology. In most cases, the morphology and distribution of the heterounits play significant roles in their functional behavior. Methods of synthesizing these hybrids, with variable ordering of the heterounits, are replete; however, a complete characterization in three dimensions could not be achieved yet. A simple route to the synthesis of Au-decorated SiO2 spheres is demonstrated and a study on the 3D ordering of the heterounits by scanning transmission electron microscopy (STEM) tomography is presentedat the final stage, intermediate stages of formation, and after heating the hybrid. The final hybrid evolves from a soft self-assembled structure of Au nanoparticles. The hybrid shows good thermal stability up to 400 degrees C, beyond which the Au particles start migrating inside the SiO2 matrix. This study provides an insight in the formation mechanism and thermal stability of the structures which are crucial factors for designing and applying such hybrids in fields of catalysis and biotechnology. As the method is general, it can be applied to make similar hybrids based on SiO2 by tuning the reaction chemistry as needed.

Diffraction tomography from intensity measurements: an evolutionary stochastic search to invert experimental data

We develop iterative diffraction tomography algorithms, which are similar to the distorted Born algorithms, for inverting scattered intensity data. Within the Born approximation, the unknown scattered field is expressed as a multiplicative perturbation to the incident field. With this, the forward equation becomes stable, which helps us compute nearly oscillation-free solutions that have immediate bearing on the accuracy of the Jacobian computed for use in a deterministic Gauss-Newton (GN) reconstruction. However, since the data are inherently noisy and the sensitivity of measurement to refractive index away from the detectors is poor, we report a derivative-free evolutionary stochastic scheme, providing strictly additive updates in order to bridge the measurement-prediction misfit, to arrive at the refractive index distribution from intensity transport data. The superiority of the stochastic algorithm over the GN scheme for similar settings is demonstrated by the reconstruction of the refractive index profile from simulated and experimentally acquired intensity data. (C) 2014 Optical Society of America

Basis pursuit deconvolution for improving model-based reconstructed images in photoacoustic tomography

The model-based image reconstruction approaches in photoacoustic tomography have a distinct advantage compared to traditional analytical methods for cases where limited data is available. These methods typically deploy Tikhonov based regularization scheme to reconstruct the initial pressure from the boundary acoustic data. The model-resolution for these cases represents the blur induced by the regularization scheme. A method that utilizes this blurring model and performs the basis pursuit deconvolution to improve the quantitative accuracy of the reconstructed photoacoustic image is proposed and shown to be superior compared to other traditional methods via three numerical experiments. Moreover, this deconvolution including the building of an approximate blur matrix is achieved via the Lanczos bidagonalization (least-squares QR) making this approach attractive in real-time. (C) 2014 Optical Society of America

Incoherence-based optimal selection of independent measurements in diffuse optical tomography

An optimal measurement selection strategy based on incoherence among rows (corresponding to measurements) of the sensitivity (or weight) matrix for the near infrared diffuse optical tomography is proposed. As incoherence among the measurements can be seen as providing maximum independent information into the estimation of optical properties, this provides high level of optimization required for knowing the independency of a particular measurement on its counterparts. The proposed method was compared with the recently established data-resolution matrix-based approach for optimal choice of independent measurements and shown, using simulated and experimental gelatin phantom data sets, to be superior as it does not require an optimal regularization parameter for providing the same information. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

Born-ratio type data normalization improves quantitation in photoacoustic tomography

In this report, we present a Born-ratio type of data normalization for reconstruction of initial acoustic pressure distribution in photoacoustic tomography (PAT). The normalized Born-ratio type of data is obtained as a ratio of photoacoustic pressure obtained with tissue sample in a coupling medium to the one obtained using purely coupling medium. It is shown that this type of data normalization improves the quantitation (intrinsic contrast) of the reconstructed images in comparison to the traditional techniques (unnormalized) that are currently available in PAT. Studies are carried out using various tissue samples. The robustness of the proposed method is studied at various noise levels added to the collected data. The improvement in quantitation can enable accurate estimation of pathophysiological parameter (optical absorption coefficient, a) of tissue sample under investigation leading to better sensitivity in PAT.

Intense Acoustic Burst Ultrasound Modulated Optical Tomography for Elasticity Mapping of Soft Biological Tissue Mimicking Phantom: A Laser Speckle Contrast Analysis Study

This report addresses the assessment of variation in elastic property of soft biological tissues non-invasively using laser speckle contrast measurement. The experimental as well as the numerical (Monte-Carlo simulation) studies are carried out. In this an intense acoustic burst of ultrasound (an acoustic pulse with high power within standard safety limits), instead of continuous wave, is employed to induce large modulation of the tissue materials in the ultrasound insonified region of interest (ROI) and it results to enhance the strength of the ultrasound modulated optical signal in ultrasound modulated optical tomography (UMOT) system. The intensity fluctuation of speckle patterns formed by interference of light scattered (while traversing through tissue medium) is characterized by the motion of scattering sites. The displacement of scattering particles is inversely related to the elastic property of the tissue. We study the feasibility of laser speckle contrast analysis (LSCA) technique to reconstruct a map of the elastic property of a soft tissue-mimicking phantom. We employ source synchronized parallel speckle detection scheme to (experimentally) measure the speckle contrast from the light traversing through ultrasound (US) insonified tissue-mimicking phantom. The measured relative image contrast (the ratio of the difference of the maximum and the minimum values to the maximum value) for intense acoustic burst is 86.44 % in comparison to 67.28 % for continuous wave excitation of ultrasound. We also present 1-D and 2-D image of speckle contrast which is the representative of elastic property distribution.

Effect of amplitude correlations on coherence in the local field potential

Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors-phase consistency as well as amplitude covariation across trials-but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over-or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.

Analogous stress and electric field driven structural transformation and decrease in polarization coherence on poling around the morphotropic phase boundary in BiScO3-PbTiO3

The nature of the stress and electric field driven structural and microstructural transformations in the morphotropic phase boundary (MPB) compositions of the high Curie point piezoelectric system BiScO3-PbTiO3 has been examined by ex situ based techniques. Using a powder poling technique, which is based on the concept of exploiting the irreversible structural change that occurs after the application of a strong electric field and stress independently, it was possible to ascertain that both moderate stress and electric field induce identical structural transformation-a fraction of the monoclinic phase transforms irreversibly to the tetragonal phase. Moreover, analysis of the dielectric response before and after poling revealed a counterintuitive phenomenon of poling induced decrease in the spatial coherence of polarization for compositions around the MPB and not so for compositions far away from the MPB range. Exploiting the greater sensitivity of this technique, we demonstrate that the criticality associated with the interferroelectric transition spans a wider composition range than what is conventionally reported in the literature based on bulk x-ray/neutron powder diffraction techniques.

A Gold Sensors Array for Imaging The Real Tissue Phantom in Electrical Impedance Tomography

Surface electrodes in Electrical Impedance Tomography (EIT) phantoms usually reduce the SNR of the boundary potential data due to their design and development errors. A novel gold sensors array with high geometric precision is developed for EIT phantoms to improve the resistivity image quality. Gold thin films are deposited on a flexible FR4 sheet using electro-deposition process to make a sixteen electrode array with electrodes of identical geometry. A real tissue gold electrode phantom is developed with chicken tissue paste and the fat cylinders as the inhomogeneity. Boundary data are collected using a USB based high speed data acquisition system in a LabVIEW platform for different inhomogeneity positions. Resistivity images are reconstructed using EIDORS and compared with identical stainless steel electrode systems. Image contrast parameters are calculated from the resistivity matrix and the reconstructed images are evaluated for both the phantoms. Image contrast and image resolution of resistivity images are improved with gold electrode array.

HCN channels enhance spike phase coherence and regulate the phase of spikes and LFPs in the theta-frequency range

What are the implications for the existence of subthreshold ion channels, their localization profiles, and plasticity on local field potentials (LFPs)? Here, we assessed the role of hyperpolarization-activated cyclic-nucleotide-gated (HCN) channels in altering hippocampal theta-frequency LFPs and the associated spike phase. We presented spatiotemporally randomized, balanced theta-modulated excitatory and inhibitory inputs to somatically aligned, morphologically realistic pyramidal neuron models spread across a cylindrical neuropil. We computed LFPs from seven electrode sites and found that the insertion of an experimentally constrained HCN-conductance gradient into these neurons introduced a location- dependent lead in the LFP phase without significantly altering its amplitude. Further, neurons fired action potentials at a specific theta phase of the LFP, and the insertion of HCN channels introduced large lags in this spike phase and a striking enhancement in neuronal spike-phase coherence. Importantly, graded changes in either HCN conductance or its half-maximal activation voltage resulted in graded changes in LFP and spike phases. Our conclusions on the impact of HCN channels on LFPs and spike phase were invariant to changes in neuropil size, to morphological heterogeneity, to excitatory or inhibitory synaptic scaling, and to shifts in the onset phase of inhibitory inputs. Finally, we selectively abolished the inductive lead in the impedance phase introduced by HCN channels without altering neuronal excitability and found that this inductive phase lead contributed significantly to changes in LFP and spike phase. Our results uncover specific roles for HCN channels and their plasticity in phase-coding schemas and in the formation and dynamic reconfiguration of neuronal cell assemblies.

Ultrasound-modulated optical tomography: direct recovery of elasticity distribution from experimentally measured intensity autocorrelation

Based on an ultrasound-modulated optical tomography experiment, a direct, quantitative recovery of Young's modulus (E) is achieved from the modulation depth (M) in the intensity autocorrelation. The number of detector locations is limited to two in orthogonal directions, reducing the complexity of the data gathering step whilst ensuring against an impoverishment of the measurement, by employing ultrasound frequency as a parameter to vary during data collection. The M and E are related via two partial differential equations. The first one connects M to the amplitude of vibration of the scattering centers in the focal volume and the other, this amplitude to E. A (composite) sensitivity matrix is arrived at mapping the variation of M with that of E and used in a (barely regularized) Gauss-Newton algorithm to iteratively recover E. The reconstruction results showing the variation of E are presented. (C) 2015 Optical Society of America

A new approach to depict bone surfaces in finger imaging using photoacoustic tomography

Imaging the vasculature close around the finger joints is of interest in the field of rheumatology. Locally increased vasculature in the synovial membrane of these joints can be a marker for rheumatoid arthritis. In previous work we showed that part of the photoacoustically induced ultrasound from the epidermis reflects on the bone surface within the finger. These reflected signals could be wrongly interpreted as new photoacoustic sources. In this work we show that a conventional ultrasound reconstruction algorithm, that considers the skin as a collection of ultrasound transmitters and the PA tomography probe as the detector array, can be used to delineate bone surfaces of a finger. This can in the future assist in the localization of the joint gaps. This can provide us with a landmark to localize the region of the inflamed synovial membrane. We test the approach on finger mimicking phantoms.

Photoacoustic tomography of the human finger: towards the assessment of inflammatory joint diseases

Inflammatory arthritis is often manifested in finger joints. The growth of new or withdrawal of old blood vessels can be a sensitive marker for these diseases. Photoacoustic (PA) imaging has great potential in this respect since it allows the sensitive and highly resolved visualization of blood. We systematically investigated PA imaging of finger vasculature in healthy volunteers using a newly developed PA tomographic system. We present the PA results which show excellent detail of the vasculature. Vessels with diameters ranging between 100 mu m and 1.5 mm are visible along with details of the skin, including the epidermis and the subpapillary plexus. The focus of all the studies is at the proximal and distal interphalangeal joints, and in the context of ultimately visualizing the inflamed synovial membrane in patients. This work is important in laying the foundation for detailed research into PA imaging of the phalangeal vasculature in patients suffering from rheumatoid arthritis.