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24 paper(s) to start with

preprint2017arXiv

Evaluation of Electric and Magnetic Fields Distribution and SAR Induced in 3D Models of Water Containers by Radiofrequency Radiation and Their Relationship to the Non-Thermal Effects of Microwaves

The research works on the biological effects of electromagnetic (EM) radiation have increased globally. Computer simulation models were developed to assess exposure of square, rectangular, pyramidal, and cylindrical water containers to microwave radiation at 300, 900, and 2,400 MHz. The development of the models included determination of EM field distribution and the resulting specific absorption rate (SAR) in the stored water. These models employed CST STUDIO SUITE 2014 package to solve EM field equations by applying the finite-difference time-domain (FDTD) method. The effect of frequency, packaging shape, and polarization on SAR induced in water was determined. High electric field and point SAR were obtained over the whole azimuth and elevation angles range in the pyramidal container model. The highest values of SAR were induced in water at the sharp edges of the four water container models. The order of the effect on total SAR and maximum point SAR is cylindrical < square < rectangular < pyramidal model at 300, 900, and 2,400 MHz for both vertical and horizontal polarizations. It can be concluded that the variation in the packaging shape of the containers, polarization, irradiat

preprint2016arXiv

Effects of non-physiological blood pressure artefacts on measures of cerebral autoregulation

Cerebral autoregulation refers to regulation mechanisms that aim to maintain cerebral blood flow approximately constant. It is often assessed by autoregulation index (ARI), which uses arterial blood pressure and cerebral blood flow velocity time series to produce a ten-scale index of autoregulation performance (0 denoting the absence of and 9 the strongest autoregulation). Unfortunately, data are rarely free from various artefacts. Here, we consider four of the most common non-physiological blood pressure artefacts (saturation, square wave, reduced pulse pressure and impulse) and study their effects on ARI for a range of different artefact sizes. We show that a sufficiently large saturation and square wave always result in ARI reaching the maximum value of 9. The pulse pressure reduction and impulse artefact lead to a more diverse behaviour. Finally, we characterised the critical size of artefacts, defined as the minimum artefact size that, on average, leads to a 10\% deviation of ARI

preprint2016arXiv

Voxel-Based Dose Prediction with Multi-Patient Atlas Selection for Automated Radiotherapy Treatment Planning

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography (CT) planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mea

preprint2016arXiv

MusculoSkeletal Modeling Using Kinect Data For Telerehabilitation

Balance, gait and postural control are some of the key factors in determining the overall stability of an individual. Several highend and costly solutions exist to perform movement analysis in clinical settings. OpenSim is a tool which uses 39 marker positions, obtained from such highend solutions like VICON or equivalent multicamera setup, for the analysis of inverse kinematics and inverse dynamics. However, an affordable solution for deriving musculoskeletal joint kinematics parameters using a low cost Kinect device is of immense importance. In this paper, we initially study the feasibility of using OpenSim tool on 20 joint locations of human being, obtained from Kinect data. Next, we analyze the various joint forces and torques experienced during a Single Limb Stance (SLS) exercise performed by healthy subjects in normal, overweight and obese categories. Results indicate that a subset of parameters related to forces and torque in hip, lumber and pelvis are the most important ones that contribute significantly in maintaining static balance in SLS. Statistical analysis demonstrates that the pelvis list and tilt moments are the key biomarkers for maintaining the statibility in SLS,

preprint2016arXiv

Probing Brain Oxygenation Wave-forms with Near Infrared Spectroscopy (NIRS)

The technique of near infrared spectroscopy (NIRS) allows to measure the oxygenation of the brain tissue. The particular problems involved in detecting regional brain oxygenation (rSO2) are discussed. The dominant chromophore (light absorber) in tissue is water. Only in the NIR light region of 650-1000 nm, the overall absorption is sufficiently low, and the NIR light can be detected across a thick layer of tissues, among them the skin, the scull and the brain. In this region, there are many absorbing light chromophores, but only three are important as far as the oxygenation is concerned. They are the hemoglobin (HbO2), the deoxy-hemoglobin (Hb) and cytochrome oxidase (CtOx). The devices that were used in our experiments were : Somanetics INVOS Brain Oximeter (IBO) and Toomim's HEG spectrophotometer. The performances of both devices were compared including their merits and drawbacks. The IBO use for research has two drawbacks: the sampling rate is too small and the readings are limited to only two significant digits. The HEG device does not have these drawbacks, but is not developed sufficiently at this time to measure rSO2. We have measured the HEG readings and compared them wi

preprint2016arXiv

PDM (Probes Distance Meter), Distance Measuring Instrument by Using Ultrasonic Propagation between Probes

The innovation process is always required to produce more advanced technology and increasing productivity. PDM (Probes Distance Meter) comes as a technological innovation in measurement, PDM is a digital distance measuring instrument uses a pair of probes. PDM consists of ultrasonic transducers, a microcontroller, and screen which shows the measurement result. PDM utilizes ultrasonic wave principle by using two probes as reference points. A microcontroller is used for performing calculation that uses the distance equation. Innovation and Excellence of PDM are simple, ergonomic, modern, and able to show the measurement result automatically. PDM has additional features those are the storage media to save the measurement result with a micro-SD card, sound generation, and braille for the blinds. Those tools are expected to be suitable for common people, academics, or technicians to perform the measurement. The results from the laboratory testing show that the prototype of PDM has resolution of 1 cm, full scale of 200 cm, 11.1% repeatability, 77.6% accuracy, and a nonlinearity parameter of 0.16%. PDM is in development and it is potential to be a model of digital measuring instrument in

preprint2016arXiv

Detecting and characterizing high frequency oscillations in epilepsy - A case study of big data analysis

We develop a framework to uncover and analyze dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive data sets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high frequency oscillations (HFOs) from a big database of rat EEG recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.

preprint2016arXiv

Photon counting spectroscopic CT with dynamic beam attenuator

Purpose: Photon counting (PC) computed tomography (CT) can provide material selective CT imaging at lowest patient dose but it suffers from suboptimal count rate. A dynamic beam attenuator (DBA) can help with count rate by modulating x-ray beam intensity such that the low attenuating areas of the patient receive lower exposure, and detector behind these areas is not overexposed. However, DBA may harden the beam and cause artifacts and errors. This work investigates positive and negative effects of using DBA in PCCT. Methods: A simple PCCT with single energy bin, spectroscopic PCCT with 2 and 5 energy bins, and conventional energy integrating CT with and without DBA were simulated and investigated using 120kVp tube voltage and 14mGy air dose. The DBAs were modeled as made from soft tissue (ST) equivalent material, iron (Fe), and holmium (Ho) K-edge material. A cylindrical CT phantom and chest phantom with iodine and CaCO3 contrast elements were used. Image artifacts and quantification errors in general and material decomposed CT were determined. Results: Simple PCCT exhibited major image artifacts and quantification errors when DBAs were used. The artifacts and errors were decreased

preprint2016arXiv

Reproducibility of Retinal Thickness Measurements across Spectral-Domain Optical Coherence Tomography Devices using Iowa Reference Algorithm

PURPOSE: Establishing and obtaining consistent quantitative indices of retinal thickness from a variety of clinically used Spectral-Domain Optical Coherence Tomography scanners. DESIGN: Retinal images from five Spectral-Domain Optical Coherence Tomography scanners were used to determine total retinal thickness with scanner-specific correction factors establishing consistency of thickness measurement across devices. PARTICIPANTS: 55 Fovea-centered Spectral-Domain Optical Coherence Tomography volumes from eleven subjects were analyzed, obtained from Cirrus HD-OCT, RS-3000, Heidelberg Spectralis, RTVue and Topcon2000, seven subjects with retinal diseases and four normal controls. METHOD: The Iowa Reference Algorithm measured total retinal thickness. Nonlinear model of total retinal thickness measurement comparisons was derived and used for device-specific comparisons. Bland-Altman plots and pairwise predictive equations yielded pairwise scanner-specific differences. Mendel test determined whether measurement biases were constant for each scanner pair. RESULTS: Mendel test revealed that all pairwise scanner differences of total retinal thickness were constant across the cohort (p=0.992

preprint2016arXiv

B-spline parameterization of spatial response in a monolithic scintillation camera

A framework for parameterization of the light response functions (LRFs) in a scintillation camera is presented. It is based on approximation of the measured or simulated photosensor response with weighted sums of uniform cubic B-splines or their tensor products. The LRFs represented in this way are smooth, computationally inexpensive to evaluate and require much less computer memory than non-parametric alternatives. The parameters are found in a straightforward way by the linear least squares method. Several techniques that allow to reduce the storage and processing power requirements were developed. A software library for fitting simulated and measured light response with spline functions was developed and integrated into an open source software package ANTS2 designed for simulation and data processing for Anger camera type detectors.

preprint2016arXiv

Accelerated High-Resolution Photoacoustic Tomography via Compressed Sensing

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue. A particular example is the planar Fabry-Perot (FP) scanner, which yields high-resolution images but takes several minutes to sequentially map the photoacoustic field on the sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: First, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP scanner and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic nume

preprint2016arXiv

Impact of non-stationary optical illumination on image reconstruction in optoacoustic tomography

Optoacoustic tomography (OAT), also known as photoacoustic tomography, is a rapidly emerging hybrid imaging technique that possesses great potential for a wide range of biomedical imaging applications. In OAT, a laser is employed to illuminate the tissue of interest and acoustic signals are produced via the photoacoustic effect. From these data, an estimate of the distribution of the absorbed optical energy density within the tissue is reconstructed, referred to as the object function. This quantity is defined, in part, by the distribution of light fluence within the tissue that is established by the laser source. When performing three-dimensional imaging of large objects, such as a female human breast, it can be difficult to achieve a relatively uniform coverage of light fluence within the volume of interest when the position of the laser source is fixed. To circumvent this, researchers have proposed illumination schemes in which the relative position of the laser source and ultrasound probe is fixed, and both are rotated together to acquire a tomographic data set. A problem with this rotating-illumination scheme is that the tomographic data are inconsistent; namely, the acoustic

preprint2016arXiv

Cold Atmospheric Plasma discharged in Water and its Potential Use in Cancer Therapy

Cold atmospheric plasma (CAP) has been emerged as a novel technology for cancer treatment. CAP can directly treat cells and tissue but such direct application is limited to skin or can be invoked as a supplement during open surgery. In this study we report indirect plasma treatment using CAP discharged in DI water using three gases as carriers (argon, helium and nitrogen). Plasma stimulated water was applied to human breast cancer cell line (MDA-MB-231). MTT assay tests showed that using argon plasma had the strongest effect on inducing apoptosis in cultured human breast cancer cells. This result is attributed to the elevated production of the reactive oxygen species and reactive nitrogen species in water in the case of argon plasma.

preprint2016arXiv

Electroencephalography (EEG) Forward Modeling via H(div) Finite Element Sources with Focal Interpolation

The goal of this study is to develop focal, accurate and robust finite element method (FEM) based approaches which can predict the electric potential on the surface of the computational domain given its structure and internal primary source current distribution. While conducting an EEG evaluation, the placement of source currents to the geometrically complex grey matter compartment is a challenging but necessary task to avoid forward errors attributable to tissue conductivity jumps. Here, this task is approached via a mathematically rigorous formulation, in which the current field is modeled via divergence conforming H(div) basis functions. Both linear and quadratic functions are used while the potential field is discretized via the standard linear Lagrangian (nodal) basis. The resulting model includes dipolar sources which are interpolated into a random set of positions and orientations utilizing two alternative approaches: the position based optimization (PBO) and the mean position/orientation (MPO) method. These results demonstrate that the present dipolar approach can reach or even surpass, at least in some respects, the accuracy of two classical reference methods, the partial

preprint2016arXiv

Quantitative photoacoustic tomography using forward and adjoint Monte Carlo models of radiance

Forward and adjoint Monte Carlo (MC) models of radiance are proposed for use in model-based quantitative photoacoustic tomography. A 2D radiance MC model using a harmonic angular basis is introduced and validated against analytic solutions for the radiance in heterogeneous media. A gradient-based optimisation scheme is then used to recover 2D absorption and scattering coefficients distributions from simulated photoacoustic measurements. It is shown that the functional gradients, which are a challenge to compute efficiently using MC models, can be calculated directly from the coefficients of the harmonic angular basis used in the forward and adjoint models. This work establishes a framework for transport-based quantitative photoacoustic tomography that can fully exploit emerging highly parallel computing architectures.

preprint2016arXiv

Simultaneous multi-slice reconstruction by Regularized Nonlinear Inversion

Increasing imaging speed is of utmost importance in in-vivo magnetic resonance imaging (MRI). With simultaneous multi-slice (SMS) MRI we can simultaneously acquire several slices of an object, which allows for higher undersampling factors compared to single- or conventional multi-slice measurements by exploiting axial coil sensitivity information. In this thesis, we give a short introduction to the physical principles of MRI, cover the basics of a FLASH based SMS MRI sequence and perform tests to verify its accuracy: We check the fidelity of the slice distance as well as the flip angle and confirm the square-root-like signal-to-noise ratio benefit of SMS compared to conventional multi-slice experiments. A g-factor analysis is used to determine a favorable Cartesian undersampling scheme for multi-slice data. Common reconstruction strategies for SMS MRI make use of previously estimated coil sensitivities to solve a linear equation. Here, we propose a new method of SMS MRI based on Regularized Nonlinear Inversion (NLINV): SMS-NLINV. This method does not require a priori knowledge about the coil sensitivities and is attractive especially for real-time imaging where coil sensitivities m

preprint2016arXiv

Flexible and compact hybrid metasurfaces for enhanced ultra high field in vivo magnetic resonance imaging

Developments in metamaterials and related structures such as metasurfaces have opened up new possibilities in designing materials and devices with unique properties. The main progress related to electromagnetic waves applications was done in optical and microwave spectra. Here we report about a new hybrid metasurface structure, comprising a two-dimensional metamaterial surface and a very high permittivity dielectric substrate that was designed to enhance the performance of an ultra-high field MRI scanner. This new flexible and compact resonant structure is the first one which can be integrated into a multi-element close-fitting receive coil array used for all clinical MRI. We successfully demonstrated the operation of the metasurface in acquiring vivo human brain images and spectra with enhanced local sensitivity on a commercial 7 Tesla system. These experimental findings prove the feasibility of real clinical applications of metasurfaces in MRI.

preprint2016arXiv

Visualizing electromagnetic vacuum by MRI

Based upon Maxwell's equations, it has long been established that oscillating electromagnetic (EM) fields incident upon a metal surface decay exponentially inside the conductor, leading to a virtual EM vacuum at sufficient depths. Magnetic resonance imaging (MRI) utilizes radiofrequency (r.f.) EM fields to produce images. Here we present the first visualization of an EM vacuum inside a bulk metal strip by MRI, amongst several novel findings. We uncover unexpected MRI intensity patterns arising from two orthogonal pairs of faces of a metal strip, and derive formulae for their intensity ratios, revealing differing effective elemental volumes (voxels) underneath these faces. Further, we furnish chemical shift imaging (CSI) results that discriminate different faces (surfaces) of a metal block according to their distinct nuclear magnetic resonance (NMR) chemical shifts, which holds much promise for monitoring surface chemical reactions noninvasively. Bulk metals are ubiquitous, and MRI is a premier noninvasive diagnostic tool. Combining the two, the emerging field of bulk metal MRI can be expected to grow in importance. The fundamental nature of results presented here may impactbulk

preprint2016arXiv

Information limits of optical microscopy: application to fluorescently labelled tissue section

The article demonstrates some less known principles of image build-up in diffractive microscopy and their usage in analysis unravelling the smallest localized information about the original object - an electromagnetic centroid. In fluorescence, the electromagnetic centroid is naturally at the position of the fluorophore. The usage of an information-entropic variable - a point divergence gain - is demonstrated for finding the most localized position of the object's representation, generally of the size of a voxel (3D pixel). These spatial pixels can be qualitatively classified and used for reconstruction of the 3D structures with precision comparable with electron microscopy.

preprint2016arXiv

Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals of Wearable Piezo-Electric Bands

Physiologically, the thoracic (THO) and abdominal (ABD) movement signals, captured using wearable piezo-electric bands, provide information about various types of apnea, including central sleep apnea (CSA) and obstructive sleep apnea (OSA). However, the use of piezo-electric wearables in detecting sleep apnea events has been seldom explored in the literature. This study explored the possibility of identifying sleep apnea events, including OSA and CSA, by solely analyzing {one or both the THO and ABD signals. An adaptive non-harmonic model was introduced to model the THO and ABD signals, which allows us to design features for sleep apnea events. To confirm the suitability of the extracted features, a support vector machine was applied to classify three categories -- normal and hypopnea, OSA, and CSA. According to a database of} 34 subjects, the overall classification accuracies were on average $75.9\%\pm 11.7\%$ and $73.8\%\pm 4.4\%$, respectively, based on the cross validation. When the features determined from the THO and ABD signals were combined, the overall classification accuracy became $81.8\%\pm 9.4\%$. These features were applied for designing a state machine for online apn

preprint2016arXiv

Existence of Millisecond-order Stable States in Time-Varying Phase Synchronization Measure in EEG Signals

In this paper, we have developed a new measure of understanding the temporal evolution of phase synchronization for EEG signals using cross-electrode information. From this measure it is found that there exists a small number of well-defined phase-synchronized states, each of which is stable for few milliseconds during the execution of a face perception task. We termed these quasi-stable states as synchrostates. We used k-means clustering algorithms to estimate the optimal number of synchrostates from 100 trials of EEG signals over 128 channels. Our results show that these synchrostates exist consistently in all the different trials. It is also found that from the onset of the stimulus, switching between these synchrostates results in well-behaved temporal sequence with repeatability which may be indicative of the dynamics of the cognitive process underlying that task. Therefore these synchrostates and their temporal switching sequences may be used as a new measure of the stability of phase synchrony and information exchange between different regions of a human brain.

preprint2016arXiv

Influence of Collimation and Detector length on CT exposures measured in a 60cm long body phantom

Background: Data fitting approaches to modeling allow for parametric formulae that may not reveal the physical quantities involved and their influence on the function being studied. In this paper the author models the approach to equilibrium function by a method that allows the physical quantities to be defined beforehand, allows their influence to be studied, and can be used to predict how each physical quantity affects approach to equilibrium. Methods: An ordinary differential equation (ODE) is used to model the approach to equilibrium function for the case where collimation is changed at fixed detector size. A parallel model is used to study the approach to equilibrium as a function of detector size for fixed collimation. Both models are validated by experimental measurements in a 60cm body phantom. Influence of detector size is simulated by using leaded sleeves of varying sizes wrapped around a 100mm pencil chamber. This creates sleeve gaps of 10 - 60mm around the chamber. A 100mm detector size is the pencil chamber without a leaded sleeve. Results: Model accurately describes the experimental data for the cases studied. Except for the smallest collimation of 5mm, linear regress

preprint2016arXiv

Using Brain Connectivity Measure of EEG Synchrostates for Discriminating Typical and Autism Spectrum Disorder

In this paper we utilized the concept of stable phase synchronization topography - synchrostates - over the scalp derived from EEG recording for formulating brain connectivity network in Autism Spectrum Disorder (ASD) and typically-growing children. A synchronization index is adapted for forming the edges of the connectivity graph capturing the stability of each of the synchrostates. Such network is formed for 11 ASD and 12 control group children. Comparative analyses of these networks using graph theoretic measures show that children with autism have a different modularity of such networks from typical children. This result could pave the way to a new modality for possible identification of ASD from non-invasively recorded EEG data.

preprint2016arXiv

Ptychographic X-ray computed tomography of extended colloidal networks in food emulsions

As a main structural level in colloidal food materials, extended colloidal networks are important for texture and rheology. By obtaining the 3D microstructure of the network, macroscopic mechanical properties of the material can be inferred. However, this approach is hampered by the lack of suitable non-destructive 3D imaging techniques with submicron resolution. We present results of quantitative ptychographic X-ray computed tomography applied to a palm kernel oil based oil-in-water emulsion. The measurements were carried out at ambient pressure and temperature. The 3D structure of the extended colloidal network of fat globules was obtained with a resolution of around 300 nm. Through image analysis of the network structure, the fat globule size distribution was computed and compared to previous findings. In further support, the reconstructed electron density values were within 4% of reference values.

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