L'ablation des tissus par hyperthermie locale guidée par IRM est une technique prometteuse pour le traitement du cancer et des arythmies cardiaques. L'IRM permet d'extraire en temps réel des informations anatomiques et thermiques des tissus. Cette thèse a pour objectif d'améliorer et d'étendre la méthodologie existante pour des interventions sur des organes mobiles comme le rein, le foie et le coeur. La première partie a été consacrée à l'introduction de l'imagerie rapide (jusqu'à 10-15 Hz) pour le guidage de l'intervention par IRM en temps réel. L'utilisation de cartes graphiques (GPGPU) a permis une accélération des calculs afin de satisfaire la contrainte de temps réel. Une précision, de l'ordre de 1°C dans les organes abdominaux et de 2-3°C dans le coeur, a été obtenue. Basé sur ces avancées, de nouveaux développements méthodologiques ont été proposés dans une seconde partie de cette thèse. L'estimation du mouvement basée sur une approche variationnelle a été améliorée pour gérer la présence de structures non persistantes et de fortes variations d'intensité dans les images. Un critère pour évaluer la qualité du mouvement estimé a été proposé et utilisé pour auto-calibrer notre algorithme d'estimation du mouvement. La méthode de correction des artefacts de thermométrie liés au mouvement, jusqu'ici restreinte aux mouvements périodiques, a été étendue à la gestion de mouvements spontanés. Enfin, un nouveau filtre temporel a été développé pour la réduction du bruit sur les cartographies de température. La procédure interventionnelle apparaît maintenant suffisamment mature pour le traitement des organes abdominaux et pour le transfert vers la clinique. Concernant le traitement des arythmies cardiaques, les méthodes ont été évaluées sur des sujets sains et dans le ventricule gauche. Par conséquent, la faisabilité de l'intervention dans les oreillettes mais aussi en présence d'arythmie devra être abordée. / MR-guided thermal ablation is a promising technique for the treatment of cancer and atrial fibrillation. MRI provides both anatomical and temperature information. The objective of this thesis is to extend and improve existing techniques for such interventions in mobile organs such as the kidney, the liver and the heart. A first part of this work focuses on the use of fast MRI (up to 10-15 Hz) for guiding the intervention in real time. This study demonstrated the potential of GPGPU programming as a solution to guarantee the real time condition for both MR-reconstruction and MR-thermometry. A precision in the range of 1°C and 2-3°C was obtained in abdominal organs and in the heart, respectively. Based on these advances, new methodological developments have been carried out in a second part of this thesis. New variational approaches have proposed to address the problem of motion estimation in presence of structures appearing transient and high intensity variations in images. A novel quality criterion to assess the motion estimation is proposed and used to autocalibrate our motion estimation algorithm. The correction of motion related magnetic susceptibility variation was extended to treat the special case of spontaneous motion. Finally, a novel temporal filter is proposed to reduce the noise of MR-thermometry measurements while controlling the bias introduced by the filtering process. As a conclusion, all main obstacles for MR-guided HIFU-ablation of abdominal organs have been addressed in in-vivo and ex-vivo studies, therefore clinical studies will now be realized. However, although promising results have been obtained for MR-guided RF-ablation in the heart, its feasibility in the atrium and in presence of arrhythmia still remains to be investigated.

The aim of the Master's thesis was to study contemporary methods for human pulse detection from standard video and suggest a method, which can be used to detect the pulse. Approaches of detecting miniature changes between frames of a video are presented. Position changes of the feature points or changes in colour of some part of an image are detected. It capitalize on the fact that those changes are caused by the pulse of blood. The method for color changes magnification is selected as a base for pulse detector. Face regions of interest are analyzed to detect frequency of changes of intensity between frames. 1D signal is gained and its analysis leads to heart rate. Approach to create heat map of frequency changes is also presented.

Accurate virtual platforms allow for crucial, early, and inexpensive assessments about the viability and hardware constraints of software/hardware applications. The growth of multicore architectures in both number of cores and relevance in the industry, in turn, demands the emergence of faster and more efficient virtual platforms to make the benefits of single core simulation and emulation available to their multicore successors whilst maintaining accuracy, development costs, time, and efficiency at acceptable levels. The goal of this thesis is to find optimal virtual platforms to perform hardware design space exploration for multi-core architectures running filtering functions, particularly, a discrete signal filtering Matlab algorithm used for oil surveying applications running on an ARM Cortex-A53 quadcore CPU. In addition to the filtering algorithm, the PARSEC benchmark suite was also used to test platform compliance under workloads with diverse characteristics. Upon reviewing multiple virtual platforms, the gem5 simulator and the QEMU emulator were chosen to be tested due to their ubiquitousness, prominence and flexibility. A Raspberry Pi Model B was used as reference to measure how closely these tools can model a commonly used embedded platform. The results show that each of the virtual platforms is best suited for different scenarios. The QEMU emulator with KVM support yielded the best performance, albeit requiring access to a host with the same architecture as the target, and not guaranteeing timing accuracy. The most accurate setup was the gem5 simulator using a simplified cache system and an Out-of-Order detailed ARM CPU model.

In the paper a new position signal filtering method with position prediction is presented along with test results using a simulation tool. The complete active heave compensation system performance with input signal filtering is also shown. The control system uses an input acceleration signal taken from the motion reference unit, which usually contains noise that is not acceptable for the position controller. Currently, a Kalman filter is used which is okay to use for certain conditions. The filter works similarly to how it is used for autonomous applications where two input positions are necessary, one from position sensors and another one taken from the model. The challenge is that there is no physical wave model available for the Kalman filter used for offshore position control and the waves are not predictable. It was found that a Kalman filter with a special signal prediction instead of the model input can be used. This position prediction helps to avoid system delays and the potential of missing the signal for a short period of the time.

This work deals with digital signal processing in the field of adaptive filtering. Fundamental basics of adaptive filtering are described and primary aim is to create executable laboratory examples, using adaptive filtering, in LabView programming language. These laboratory examples are intended to be used by students fo studying and during laboratory lessons. Objective is to connect the examples with external devices, such as microphone. A microphone is used as an user's speech input acquiring interface. In the thesis is depicted Wiener's filter and problem of adaptive filtering is discussed. Contemporary adaptive algorithms are described and their applications as well. Most mentioned is the LMS algorithm and it's forms. Laboratory examples use following concepts: Adaptive Echo Cancellation, Active Noise Control and System Identification. Each of these examples is solely executable (need for LabView or Run-time engine), consisting also of theory with diagrams. Examples therefore are usable even without manual.

This thesis deals with the filter algorithm design, implementing mathematical model to improve algorithm performance. Designed algorithms are implemented in a control unit of the experimental vehicle (filters signal used in the closed-loop controller). The improvement of the position estimation using Kalman Filter is demonstrated on the experimental vehicle. In the next part the design process of algorithm developing for dsPIC microcontroller using Matlab is described.

[ES] En la actualidad, cada vez existen más y más tareas que necesitamos exportar y automatizar en dispositivos portables de bajo consumo que se alimentan de baterías, en los cuales es imprescindible realizar un uso "optimo" de la energía disponible con la finalidad de no drenarlas rápidamente.En la sección primera de esta tesis, "Filtros de señales de audio digital", "optimizamos" las implementaciones de diferentes filtros, tanto generales como específicos, para aplicaciones de sonido digital diseñados e implantados en plataformas basadas en las arquitecturas ARM®. Como filtros generales, trabajamos con los filtros FIR, IIR y Parallel IIR, siendo este tipo de filtros implementados a bajo nivel con instrucciones vectoriales NEON®. Finalmente, se implementa un filtro de separación de señales conocido como "Beamforming", el cual plantea después de su estudio, la problemática de realizar una factorización QR de una matriz relativamente grande en tiempo real, lo cual nos lleva a desarrollar diferentes técnicas de "aceleración" de los cálculos de la misma. En la segunda parte, "Rellenado de mapa de profundidad de una escena", describimos el proceso de rellenado de un mapa de profundidad de una escena capturada a partir del uso de la imagen RGB y de un mapa de profundidad disperso donde únicamente tenemos valores de profundidad en los bordes de los objetos que componen la escena. Estos algoritmos de "rellenado" del mapa de profundidad, también han sido diseñados e implantados en dispositivos basados en la arquitectura ARM®. / [CA] Actualment, cada vegada existixen més i més tasques que tenen la necessitat d'exportar i automatitzar a dispositius portables de baix consum que s'alimenten amb bateríes, als quals es imprescindible realitzar un ús "óptim" de l'energia disponible amb la finalitat de no drenar-les ràpidament. Part I: Filtres de senyals d'àudio digital En aquesta secció "optimitzarem" les implementacions de diferents filtres, tant generals com específics, empreats a aplicacions de so digital disenyats e implantats a plataformes basades a les arquitectures ARM®. Com a filtres generals, treballem amb els filtres FIR, IIR y Parallel IIR, sent aquests tipus de filtres implementats a baix nivell amb instruccions vectorials NEON®. Finalment, s'implementa un filtro de separació de senyals conegut com "Beamforming", el qual planteja després del seu estudi, la problem`atica de realitzar una factorizació QR d'una matriu relativament gran en temps real, i açó ens porta a desenvolupar diferents tècniques "d'acceleració" dels càlculs de la mateixa. Part II: Emplenat del mapa de profunditat d'una escena A la secció d'image per computador, descrivim el procés d'emplenat d'un mapa de profunditat d'una escena capturada fent servir l'image RGB i un mapa de profunditat dispers on únicament tenim valors de profunditat als bordes dels objetes que composen l'escena. Aquests algoritmes "d'emplenat" del mapa de profunditat, també han sigut disenyats e implantats a dispositius basats en l'arquitectura ARM®. / [EN] Currently, there are more and more tasks that we need to export and automate in low-consumption mobile devices that are powered by batteries, in which it is essential to make an "optimum" use of the available energy in order to do not drain them quickly. Part I: Filters of digital audio signals In this section we "optimize" the implementations of different filters, both general and specific, for digital sound applications designed and implemented on platforms based on the ARM®. As general filters, we work with the FIR, IIR and Parallel IIR filters, these types of filters being implemented at a low level with NEON®vector instructions. Finally, a signal separation filter known as "Beamforming" is implemented, which set out after its study, the problem of performing a QR factorization of a relatively large matrix in real time, which leads us to develop different techniques of "acceleration" of the calculations of it. Part II: Filling the depth map of a scene In the computer image section, we describe the process of filling in a depth map of a captured scene using RGB image and a sparse depth map where we only have depth values at the edges of the objects that make up the scene. These depth map "filling" algorithms have also been designed and implemented in devices based on the ARM® architecture. / Alventosa Rueda, FJ. (2022). Algoritmos de imagen y sonido digital con restricciones de tiempo real [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181573 / TESIS

The aim of this master’s thesis is to create a multiband stop derived from Lynn filters for suppressing mains hum and baseline variation (drift). The first part of the thesis is focused on brief theoretical introduction to the distortion types affecting ECG signal and twelve lead connection. The following practical part describes free realizations of ECG filter and ECG signal filtration. The filter has been tested both on distorted and on non-distorted signal. Finally filters’ error rate was computed from CSE database signals.

Motion artefacts due to cardiac and respiratory motion present a daily challenge in cardiac Magnetic Resonance Imaging (MRI), and many different motion correction procedures are used in clinical routine imaging. To reduce motion artefacts further, patients are required to hold their breath during parts of the data acquisition, which is physically straining – especially when done repetitively. Self-Gating (SG) is a method that extracts cardiac and respiratory motion information from the MRI data in the form of signals, called SG signals, and uses them to divide the data into the specific cardiac and respiratory phases it was acquired from. This method both avoids motion artefacts and allow for free-breathing acquisition. This project’s goal was to find a method for extracting cardiac and respiratory SG signals from MRI data. The data was acquired with a golden angle radial acquisition method for 3-dimensional (3D) scans. Extraction of the raw signal was tested for both raw k-space data and high temporal resolution image series, where the images were reconstructed using a sliding window reconstruction. Filters were then applied to isolate the cardiac and respiratory information, to create separate cardiac and respiratory SG signals. Thereafter trigger points marking the beginning of the cardiac and respiratory cycles were generated. The trigger points were compared against ECG and respiratory trigger points provided by the MR scanner. The conclusion was that the SG signals based on k-space data was functional on the scans from the evaluated subjects and the most effective choice of the two options, but image based SG signals may prove to be functional after further studies. / Rörelseartefakter på grund av hjärt- och respirationsrörelser är idag vardagliga utmaningar inom magnetresonanstomografi (MR) av hjärtat, och många olika metoder används för att eliminera rörelseartefakterna. Patienterna behöver dessutom hålla andan under delar av dataupptagningen, vilket är fysiskt ansträngande – speciellt när det sker upprepade gånger. Self-Gating (SG) är en metod som extraherar information hjärt- och respirationsrytm från MR-datan i form av signaler, kallade SG signaler, och använder dem för att dela in datan i de specifika hjärt- respektive respirationsfaser som var när datan upptogs. Denna metod både undviker rörelseartefakter och tillåter fri andning under dataupptagningen. Målet med det här projektet var att hitta en metod för att extrahera SG signaler för hjärt- och respirationsrytm från MR-data. Datan samlades in med en golden angle radial-upptagning för 3- dimensionella (3D) scanningar. Extraheringen av den råa signalen testades på både rå k-space data och på bildserier av 3D-bilder med hög tidsupplösning, där bilderna var rekonstruerade med en sliding window rekonstruktion. Därefter applicerades filter för att isolera hjärt- och respirationsinformationen, för att få separata SG signaler med endast hjärt- respektive respirationsrytmer. Till slut genererades triggerpunkter för att markera början av hjärt- respektive respirationscyklerna. Dessa jämfördes med triggerpunkter uppmätta med EKG och andningskudde i magnetkameran. Slutsatsen för projektet var att SG signalerna som baserades på k-space data var funktionell för de scanningar som testades och det mest effektiva alternativet, men SG signalerna som baserades på bilder kan visa sig fungera efter mer studier.