Multi-Oriented Windowed Harmonic Phase Reconstruction for Robust Cardiac Strain Imaging

The purpose of this work is to develop a method for direct estimation of the cardiac strain tensor by extending the harmonic phase reconstruction on tagged magnetic resonance images to obtain more precise and robust measurements. The extension relies on the reconstruction of the local phase of the image by means of the windowed Fourier transform and the acquisition of an overdetermined set of stripe orientations in order to avoid the phase interferences from structures outside the myocardium and the instabilities arising from the application of a gradient operator. Results have shown that increasing the number of acquired orientations provides a signi cant improvement in the reproducibility of the strain measurements and that the acquisition of an extended set of orientations also improves the reproducibility when compared with acquiring repeated samples from a smaller set of orientations. Additionally, biases in local phase estimation when using the original harmonic phase formulation are greatly diminished by the one here proposed. The ideas here presented allow the design of new methods for motion sensitive magnetic resonance imaging, which could simultaneously improve the resolution, robustness and accuracy of motion estimates

On motion in dynamic magnetic resonance imaging: Applications in cardiac function and abdominal diffusion

La imagen por resonancia magnética (MRI), hoy en día, representa una potente herramienta para el diagnóstico clínico debido a su flexibilidad y sensibilidad a un amplio rango de propiedades del tejido. Sus principales ventajas son su sobresaliente versatilidad y su capacidad para proporcionar alto contraste entre tejidos blandos. Gracias a esa versatilidad, la MRI se puede emplear para observar diferentes fenómenos físicos dentro del cuerpo humano combinando distintos tipos de pulsos dentro de la secuencia. Esto ha permitido crear distintas modalidades con múltiples aplicaciones tanto biológicas como clínicas. La adquisición de MR es, sin embargo, un proceso lento, lo que conlleva una solución de compromiso entre resolución y tiempo de adquisición (Lima da Cruz, 2016; Royuela-del Val, 2017). Debido a esto, la presencia de movimiento fisiológico durante la adquisición puede conllevar una grave degradación de la calidad de imagen, así como un incremento del tiempo de adquisición, aumentando así tambien la incomodidad del paciente. Esta limitación práctica representa un gran obstáculo para la viabilidad clínica de la MRI. En esta Tesis Doctoral se abordan dos problemas de interés en el campo de la MRI en los que el movimiento fisiológico tiene un papel protagonista. Éstos son, por un lado, la estimación robusta de parámetros de rotación y esfuerzo miocárdico a partir de imágenes de MR-Tagging dinámica para el diagnóstico y clasificación de cardiomiopatías y, por otro, la reconstrucción de mapas del coeficiente de difusión aparente (ADC) a alta resolución y con alta relación señal a ruido (SNR) a partir de adquisiciones de imagen ponderada en difusión (DWI) multiparamétrica en el hígado.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

A robust sequential hypothesis testing method for brake squeal localisation

This contribution deals with the in situ detection and localisation of brake squeal in an automobile. As brake squeal is emitted from regions known a priori, i.e., near the wheels, the localisation is treated as a hypothesis testing problem. Distributed microphone arrays, situated under the automobile, are used to capture the directional properties of the sound field generated by a squealing brake. The spatial characteristics of the sampled sound field is then used to formulate the hypothesis tests. However, in contrast to standard hypothesis testing approaches of this kind, the propagation environment is complex and time-varying. Coupled with inaccuracies in the knowledge of the sensor and source positions as well as sensor gain mismatches, modelling the sound field is difficult and standard approaches fail in this case. A previously proposed approach implicitly tried to account for such incomplete system knowledge and was based on ad hoc likelihood formulations. The current paper builds upon this approach and proposes a second approach, based on more solid theoretical foundations, that can systematically account for the model uncertainties. Results from tests in a real setting show that the proposed approach is more consistent than the prior state-of-the-art. In both approaches, the tasks of detection and localisation are decoupled for complexity reasons. The localisation (hypothesis testing) is subject to a prior detection of brake squeal and identification of the squeal frequencies. The approaches used for the detection and identification of squeal frequencies are also presented. The paper, further, briefly addresses some practical issues related to array design and placement. (C) 2019 Author(s)

The use of distributed sensor arrays in electrical and electromagnetic imaging

Electrical methods for exploring the earth, such as direct current resistivity, induced polarization and electromagnetism are used for numerous exploration, engineering and environmental applications. Common to all these applications is the desire to obtain the clearest possible image of the target. This thesis analyses and develops methods for improving signal to noise ratio for electrical methodsThe ability to recover subsurface information from electrical exploration methods is dependent on the limits of signal detection which is strongly influenced by instrumentation and the conductivity structure of the Earth. Multiple sensors can be used to collect data efficiently over a survey area. Such multi-receiver arrays can improve the signal-to-noise ratio. However, the use of multiple sensors can also be exploited to improve the signal fidelity from each sensor, which may then translate to more accurate geological models and/or greater depth of investigation. In this thesis a two step algorithm for the removal of harmonic noise and atmospheric transients is presented. The first step is the removal of harmonic noise from each sensor using a non-linear single value decomposition (SVD) inversion technique to model a modulated sinusoid to narrow band noise sources. The second step is spherics attenuation using an iterative technique of signal stripping then removing residual coherent noise across the array combined with robust statistical measures in the tacking process. I show that this approach can recover signals otherwise buried in noise and that under certain conditions, signal to noise ratio can be improved by more than 46 dB. The algorithms designed here are applicable to any type of electrical or time domain electromagnetic survey conducted with a multi-receiver array

Systems and methods for physiological signal enhancement and biometric extraction using non-invasive optical sensors

A system and method for signal processing to remove unwanted noise components including: (i) wavelength-independent motion artifacts such as tissue, bone and skin effects, and (ii) wavelength-dependent motion artifact/noise components such as venous blood pulsation and movement due to various sources including muscle pump, respiratory pump and physical perturbation. Disclosed are methods, analytics, and their uses for reliable perfusion monitoring, arterial oxygen saturation monitoring, heart rate monitoring during daily activities and in hospital settings and for extraction of physiological parameters such as respiration information, hemodynamic parameters, venous capacity, and fluid responsiveness. The system and methods disclosed are extendable to include monitoring platforms for perfusion, hypoxia, arrhythmia detection, airway obstruction detection and sleep disorders including apnea.Board of Regents, University of Texas Syste

A Robust and Self-Paced BCI System Based on a Four Class SSVEP Paradigm: Algorithms and Protocols for a High-Transfer-Rate Direct Brain Communication

In this paper, we present, with particular focus on the adopted processing and identification chain and protocol-related solutions, a whole self-paced brain-computer interface system based on a 4-class steady-state visual evoked potentials (SSVEPs) paradigm. The proposed system incorporates an automated spatial filtering technique centred on the common spatial patterns (CSPs) method, an autoscaled and effective signal features extraction which is used for providing an unsupervised biofeedback, and a robust self-paced classifier based on the discriminant analysis theory. The adopted operating protocol is structured in a screening, training, and testing phase aimed at collecting user-specific information regarding best stimulation frequencies, optimal sources identification, and overall system processing chain calibration in only a few minutes. The system, validated on 11 healthy/pathologic subjects, has proven to be reliable in terms of achievable communication speed (up to 70 bit/min) and very robust to false positive identifications

Adaptive phase-shifting algorithm for temporal phase evaluation

Most standard temporal phase-shifting algorithms evaluate the phase by computing a windowed Fourier transform (WFT) of the intensity signal at the carrier frequency of the system. However, displacement of the specimen during image acquisition may cause the peak of the transform to shift away from the carrier frequency, leading to phase errors and even unwrapping failure. We present a novel TPS method that searches for the peak of the WFT and evaluates the phase at that frequency instead of at the carrier frequency. The performance of this method is compared with that of standard algorithms by using numerical simulations. Experimental results from highspeed speckle interferometry studies of carbon fiber panels are also presented

A 0.35 μm CMOS 17-bit@40-kS/s cascade 2-1 ΣΔ modulator with programmable gain and programmable chopper stabilization

This paper describes a 0.35μm CMOS chopper-stabilized Switched-Capacitor 2-1 cascade ΣDelta; modulator for automotive sensor interfaces. For a better fitting to the characteristics of different sensor outputs, the modulator includes a programmable set of gains (x0.5, x1, x2, and x4) and a programmable set of chopper frequencies (fs/16, fs/8, fs/4 and fs/2). It has also been designed to operate within the restrictive environmental conditions of automotive electronics (-40°C, 175°C). The modulator architecture has been selected after an exhaustive comparison among multiple ΣΔM topologies in terms of resolution, speed and power dissipation. The design of the modulator building blocks is based upon a top-down CAD methodology which combines simulation and statistical optimization at different levels of the modulator hierarchy. The circuit is clocked at 5.12MHz and consumes, all together, 14.7mW from a single 3.3-V supply. Experimental measurements result in 99.77dB of Dynamic Range (DR), which combined with the gain programmability leads to an overall DR of 112dB. This puts the presented design beyond the state-of-the-art according with the existing bibliography