58 resultados para Eit
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Electromagnetically induced transparency (EIT) is an important tool for controlling light propagation and nonlinear wave mixing in atomic gases with potential applications ranging from quantum computing to table top tests of general relativity. Here we consider EIT in an atomic Bose-Einstein condensate (BEC) trapped in a double-well potential. A weak probe laser propagates through one of the wells and interacts with atoms in a three-level Lambda configuration. The well through which the probe propagates is dressed by a strong control laser with Rabi frequency Omega(mu), as in standard EIT systems. Tunneling between the wells at the frequency g provides a coherent coupling between identical electronic states in the two wells, which leads to the formation of interwell dressed states. The macroscopic interwell coherence of the BEC wave function results in the formation of two ultranarrow absorption resonances for the probe field that are inside of the ordinary EIT transparency window. We show that these new resonances can be interpreted in terms of the interwell dressed states and the formation of a type of dark state involving the control laser and the interwell tunneling. To either side of these ultranarrow resonances there is normal dispersion with very large slope controlled by g. We discuss prospects for observing these ultranarrow resonances and the corresponding regions of high dispersion experimentally.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Química - IQ
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A direct reconstruction algorithm for complex conductivities in W-2,W-infinity(Omega), where Omega is a bounded, simply connected Lipschitz domain in R-2, is presented. The framework is based on the uniqueness proof by Francini (2000 Inverse Problems 6 107-19), 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.
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Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.
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Borges JB, Suarez-Sipmann F, Bohm SH, Tusman G, Melo A, Maripuu E, Sandstrom M, Park M, Costa EL, Hedenstierna G, Amato M. Regional lung perfusion estimated by electrical impedance tomography in a piglet model of lung collapse. J Appl Physiol 112: 225-236, 2012. First published September 29, 2011; doi: 10.1152/japplphysiol.01090.2010.-The assessment of the regional match between alveolar ventilation and perfusion in critically ill patients requires simultaneous measurements of both parameters. Ideally, assessment of lung perfusion should be performed in real-time with an imaging technology that provides, through fast acquisition of sequential images, information about the regional dynamics or regional kinetics of an appropriate tracer. We present a novel electrical impedance tomography (EIT)-based method that quantitatively estimates regional lung perfusion based on first-pass kinetics of a bolus of hypertonic saline contrast. Pulmonary blood flow was measured in six piglets during control and unilateral or bilateral lung collapse conditions. The first-pass kinetics method showed good agreement with the estimates obtained by single-photon-emission computerized tomography (SPECT). The mean difference (SPECT minus EIT) between fractional blood flow to lung areas suffering atelectasis was -0.6%, with a SD of 2.9%. This method outperformed the estimates of lung perfusion based on impedance pulsatility. In conclusion, we describe a novel method based on EIT for estimating regional lung perfusion at the bedside. In both healthy and injured lung conditions, the distribution of pulmonary blood flow as assessed by EIT agreed well with the one obtained by SPECT. The method proposed in this study has the potential to contribute to a better understanding of the behavior of regional perfusion under different lung and therapeutic conditions.
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The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.
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This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.
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Die Elektrische Impedanztomographie soll als kostengünstige und nebenwirkungsfreie Tomographiemethode in der medizinischen Diagnostik, z. B. in der Mammographie dienen. Mit der EIT läßt sich Krebsgewebe von gesundem Gewebe unterscheiden, da es eine signifikant erhöhte Leitfähigkeit aufweist. Damit kann die EIT als Ergänzung zu den klassischen Diagnoseverfahren dienen. So ist z.B. bei jungen Frauen mit einem dichteren Fettgewebe die Identifizierung eines Mammakarzinoms mit der Röntgentomographie nicht immer möglich. Ziel dieser Arbeit war es, einen Prototypen für die Impedanztomographie zu entwickeln und mögliche Anwendungen zu testen. Der Tomograph ist in Zusammenarbeit mit Dr. K.H.Georgi gebaut worden. Der Tomograph erlaubt es niederohmige, Wechselströme an Elektroden auf der Körperoberfläche einzuspeisen. Die Potentiale können an diesen Elektroden programmierbar vorgegeben werden. Weitere hochohmige Elektroden dienen zur Potentialmessung. Um den Hautwiderstand zu überbrücken, werden Wechselstromfrequenzen von 20-100 kHz eingesetzt. Mit der Möglichkeit der Messung von Strom und Potential auf unterschiedlichen Elektroden kann man das Problem des nur ungenau bekannten Hautwiderstandes umgehen. Prinzipiell ist es mit dem Mainzer EIT System möglich, 100 Messungen in der Sekunde durchzuführen. Auf der Basis von mit dem Mainzer EIT gewonnenen Daten sollten unterschiedliche Rekonstruktionsalgorithmen getestet und weiterentwickelt werden. In der Vergangenheit sind verschiedene Rekonstruktionsalgorithmen für das mathematisch schlecht gestellte EIT Problem betrachtet worden. Sie beruhen im Wesentlichen auf zwei Strategien: Die Linearisierung und iterative Lösung des Problems und Gebietserkennungsmethoden. Die iterativen Verfahren wurden von mir dahingehend modifiziert, dass Leitfähigkeitserhöhungen und Leitfähigkeitserniedrigungen gleichberechtigt behandelt werden können. Für den modifizierten Algorithmus wurden zwei verschiedene Rekonstruktionsalgorithmen programmiert und mit synthetischen Daten getestet. Zum einen die Rekonstruktion über die approximative Inverse, zum anderen eine Rekonstruktion mit einer Diskretisierung. Speziell für die Rekonstruktion mittels Diskretisierung wurde eine Methode entwickelt, mit der zusätzliche Informationen in der Rekonstruktion berücksichtigt werden können, was zu einer Verbesserung der Rekonstruktion beiträgt. Der Gebietserkennungsalgorithmus kann diese Zusatzinformationen liefern. In der Arbeit wurde ein neueres Verfahren für die Gebietserkennung derart modifiziert, dass eine Rekonstruktion auch für getrennte Strom- und Spannungselektroden möglich wurde. Mit Hilfe von Differenzdaten lassen sich ausgezeichnete Rekonstruktionen erzielen. Für die medizinischen Anwendungen sind aber Absolutmessungen nötig, d.h. ohne Leermessung. Der erwartende Effekt einer Inhomogenität in der Leitfähigkeit ist sehr klein und als Differenz zweier grosser Zahlen sehr schwierig zu bestimmen. Die entwickelten Algorithmen kommen auch gut mit Absolutdaten zurecht.
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The subject of this thesis is in the area of Applied Mathematics known as Inverse Problems. Inverse problems are those where a set of measured data is analysed in order to get as much information as possible on a model which is assumed to represent a system in the real world. We study two inverse problems in the fields of classical and quantum physics: QCD condensates from tau-decay data and the inverse conductivity problem. Despite a concentrated effort by physicists extending over many years, an understanding of QCD from first principles continues to be elusive. Fortunately, data continues to appear which provide a rather direct probe of the inner workings of the strong interactions. We use a functional method which allows us to extract within rather general assumptions phenomenological parameters of QCD (the condensates) from a comparison of the time-like experimental data with asymptotic space-like results from theory. The price to be paid for the generality of assumptions is relatively large errors in the values of the extracted parameters. Although we do not claim that our method is superior to other approaches, we hope that our results lend additional confidence to the numerical results obtained with the help of methods based on QCD sum rules. EIT is a technology developed to image the electrical conductivity distribution of a conductive medium. The technique works by performing simultaneous measurements of direct or alternating electric currents and voltages on the boundary of an object. These are the data used by an image reconstruction algorithm to determine the electrical conductivity distribution within the object. In this thesis, two approaches of EIT image reconstruction are proposed. The first is based on reformulating the inverse problem in terms of integral equations. This method uses only a single set of measurements for the reconstruction. The second approach is an algorithm based on linearisation which uses more then one set of measurements. A promising result is that one can qualitatively reconstruct the conductivity inside the cross-section of a human chest. Even though the human volunteer is neither two-dimensional nor circular, such reconstructions can be useful in medical applications: monitoring for lung problems such as accumulating fluid or a collapsed lung and noninvasive monitoring of heart function and blood flow.
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Die vorliegende Arbeit untersucht das inverse Hindernisproblem der zweidimensionalen elektrischen Impedanztomographie (EIT) mit Rückstreudaten. Wir präsentieren und analysieren das mathematische Modell für Rückstreudaten, diskutieren das inverse Problem für einen einzelnen isolierenden oder perfekt leitenden Einschluss und stellen zwei Rekonstruktionsverfahren für das inverse Hindernisproblem mit Rückstreudaten vor. Ziel des inversen Hindernisproblems der EIT ist es, Inhomogenitäten (sogenannte Einschlüsse) der elektrischen Leitfähigkeit eines Körpers aus Strom-Spannungs-Messungen an der Körperoberfläche zu identifizieren. Für die Messung von Rückstreudaten ist dafür nur ein Paar aus an der Körperoberfläche nahe zueinander angebrachten Elektroden nötig, das zur Datenerfassung auf der Oberfläche entlang bewegt wird. Wir stellen ein mathematisches Modell für Rückstreudaten vor und zeigen, dass Rückstreudaten die Randwerte einer außerhalb der Einschlüsse holomorphen Funktion sind. Auf dieser Grundlage entwickeln wir das Konzept des konvexen Rückstreuträgers: Der konvexe Rückstreuträger ist eine Teilmenge der konvexen Hülle der Einschlüsse und kann daher zu deren Auffindung dienen. Wir stellen einen Algorithmus zur Berechnung des konvexen Rückstreuträgers vor und demonstrieren ihn an numerischen Beispielen. Ferner zeigen wir, dass ein einzelner isolierender Einschluss anhand seiner Rückstreudaten eindeutig identifizierbar ist. Der Beweis dazu beruht auf dem Riemann'schen Abbildungssatz für zweifach zusammenhängende Gebiete und dient als Grundlage für einen Rekonstruktionsalgorithmus, dessen Leistungsfähigkeit wir an verschiedenen Beispielen demonstrieren. Ein perfekt leitender Einschluss ist hingegen nicht immer aus seinen Rückstreudaten rekonstruierbar. Wir diskutieren, in welchen Fällen die eindeutige Identifizierung fehlschlägt und zeigen Beispiele für unterschiedliche perfekt leitende Einschlüsse mit gleichen Rückstreudaten.
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Il presente lavoro di tesi presenta la progettazione, realizzazione e applicazione di un setup sperimentale miniaturizzato per la ricostruzione di immagine, con tecnica di Tomografia ad Impedenza Elettrica (EIT). Il lavoro descritto nel presente elaborato costituisce uno studio di fattibilità preliminare per ricostruire la posizione di piccole porzioni di tessuto (ordine di qualche millimetro) o aggregati cellulari dentro uno scaffold in colture tissutali o cellulari 3D. Il setup disegnato incorpora 8 elettrodi verticali disposti alla periferia di una camera di misura circolare del diametro di 10 mm. Il metodo di analisi EIT è stato svolto utilizzando i) elettrodi conduttivi per tutta l’altezza della camera (usati nel modello EIT bidimensionale e quasi-bidimensionale) e ii) elettrodi per deep brain stimulation (conduttivi esclusivamente su un ridotto volume in punta e posti a tre diverse altezze: alto, centro e basso) usati nel modello EIT tridimensionale. Il metodo ad elementi finiti (FEM) è stato utilizzato per la soluzione sia del problema diretto che del problema inverso, con la ricostruzione della mappa di distribuzione della conduttività entro la camera di misura. Gli esperimenti svolti hanno permesso di ricostruire la mappa di distribuzione di conduttività relativa a campioni dell’ordine del millimetro di diametro. Tali dimensioni sono compatibili con quelle dei campioni oggetto di studio in ingegneria tissutale e, anche, con quelle tipiche dei sistemi organ-on-a-chip. Il metodo EIT sviluppato, il prototipo del setup realizzato e la trattazione statistica dei dati sono attualmente in fase di implementazione in collaborazione con il gruppo del Professor David Holder, Dept. Medical Physics and Bioengineering, University College London (UCL), United Kingdom.
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Introduction Electrical impedance tomography (EIT) has been shown to be able to distinguish both ventilation and perfusion. With adequate filtering the regional distributions of both ventilation and perfusion and their relationships could be analysed. Several methods of separation have been suggested previously, including breath holding, electrocardiograph (ECG) gating and frequency filtering. Many of these methods require interventions inappropriate in a clinical setting. This study therefore aims to extend a previously reported frequency filtering technique to a spontaneously breathing cohort and assess the regional distributions of ventilation and perfusion and their relationship. Methods Ten healthy adults were measured during a breath hold and while spontaneously breathing in supine, prone, left and right lateral positions. EIT data were analysed with and without filtering at the respiratory and heart rate. Profiles of ventilation, perfusion and ventilation/perfusion related impedance change were generated and regions of ventilation and pulmonary perfusion were identified and compared. Results Analysis of the filtration technique demonstrated its ability to separate the ventilation and cardiac related impedance signals without negative impact. It was, therefore, deemed suitable for use in this spontaneously breathing cohort. Regional distributions of ventilation, perfusion and the combined ΔZV/ΔZQ were calculated along the gravity axis and anatomically in each position. Along the gravity axis, gravity dependence was seen only in the lateral positions in ventilation distribution, with the dependent lung being better ventilated regardless of position. This gravity dependence was not seen in perfusion. When looking anatomically, differences were only apparent in the lateral positions. The lateral position ventilation distributions showed a difference in the left lung, with the right lung maintaining a similar distribution in both lateral positions. This is likely caused by more pronounced anatomical changes in the left lung when changing positions. Conclusions The modified filtration technique was demonstrated to be effective in separating the ventilation and perfusion signals in spontaneously breathing subjects. Gravity dependence was seen only in ventilation distribution in the left lung in lateral positions, suggesting gravity based shifts in anatomical structures. Gravity dependence was not seen in any perfusion distributions.
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ABSTRACT Varying pulmonary shunt fractions during the respiratory cycle cause oxygen oscillations during mechanical ventilation. In artificially damaged lungs, cyclical recruitment of atelectasis is responsible for varying shunt according to published evidence. We introduce a complimentary hypothesis that cyclically varying shunt in healthy lungs is caused by cyclical redistribution of pulmonary perfusion. Administration of crystalloid or colloid infusions would decrease oxygen oscillations if our hypothesis was right. Therefore, n = 14 mechanically ventilated healthy pigs were investigated in 2 groups: crystalloid (fluid) versus no-fluid administration. Additional volume interventions (colloid infusion, blood withdrawal) were carried out in each pig. Intra-aortal PaO(2) oscillations were recorded using fluorescence quenching technique. Phase shift of oxygen oscillations during altered inspiratory to expiratory (I:E) ventilation ratio and electrical impedance tomography (EIT) served as control methods to exclude that recruitment of atelectasis is responsible for oxygen oscillations. In hypovolemia relevant oxygen oscillations could be recorded. Fluid and volume state changed PaO(2) oscillations according to our hypothesis. Fluid administration led to a mean decline of 105.3 mmHg of the PaO(2) oscillations amplitude (P < 0.001). The difference of the amplitudes between colloid administration and blood withdrawal was 62.4 mmHg in pigs not having received fluids (P = 0.0059). Fluid and volume state also changed the oscillation phase during altered I:E ratio. EIT excluded changes of regional ventilation (i.e., recruitment of atelectasis) to be responsible for these oscillations. In healthy pigs, cyclical redistribution of pulmonary perfusion can explain the size of respiratory-dependent PaO(2) oscillations.
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Our understanding of regional filling of the lung and regional ventilation distribution is based on studies using stepwise inhalation of radiolabelled tracer gases, magnetic resonance imaging and positron emission tomography. We aimed to investigate whether these differences in ventilation distribution at different end-expiratory levels (EELs) and tidal volumes (V (T)s) held also true during tidal breathing. Electrical impedance tomography (EIT) measurements were performed in ten healthy adults in the right lateral position. Five different EELs with four different V (T)s at each EEL were tested in random order, resulting in 19 combinations. There were no measurements for the combination of the highest EEL/highest V (T). EEL and V (T) were controlled by visual feedback based on airflow. The fraction of ventilation directed to different slices of the lung (VENT(RL1)-VENT(RL8)) and the rate of the regional filling of each slice versus the total lung were analysed. With increasing EEL but normal tidal volume, ventilation was preferentially distributed to the dependent lung and the filling of the right and left lung was more homogeneous. With increasing V (T) and maintained normal EEL (FRC), ventilation was preferentially distributed to the dependent lung and regional filling became more inhomogeneous (p < 0.05). We could demonstrate that regional and temporal ventilation distribution during tidal breathing was highly influenced by EEL and V (T).