Rapid 3D Phase Contrast Magnetic Resonance Angiography through High-Moment Velocity Encoding and 3D Parallel Imaging

abstract: Phase contrast magnetic resonance angiography (PCMRA) is a non-invasive imaging modality that is capable of producing quantitative vascular flow velocity information. The encoding of velocity information can significantly increase the imaging acquisition and reconstruction durations associated with this technique. The purpose of this work is to provide mechanisms for reducing the scan time of a 3D phase contrast exam, so that hemodynamic velocity data may be acquired robustly and with a high sensitivity. The methods developed in this work focus on the reduction of scan duration and reconstruction computation of a neurovascular PCMRA exam. The reductions in scan duration are made through a combination of advances in imaging and velocity encoding methods. The imaging improvements are explored using rapid 3D imaging techniques such as spiral projection imaging (SPI), Fermat looped orthogonally encoded trajectories (FLORET), stack of spirals and stack of cones trajectories. Scan durations are also shortened through the use and development of a novel parallel imaging technique called Pretty Easy Parallel Imaging (PEPI). Improvements in the computational efficiency of PEPI and in general MRI reconstruction are made in the area of sample density estimation and correction of 3D trajectories. A new method of velocity encoding is demonstrated to provide more efficient signal to noise ratio (SNR) gains than current state of the art methods. The proposed velocity encoding achieves improved SNR through the use of high gradient moments and by resolving phase aliasing through the use measurement geometry and non-linear constraints.Dissertation/ThesisPh.D. Bioengineering 201

Light field image processing: an overview

Light field imaging has emerged as a technology allowing to capture richer visual information from our world. As opposed to traditional photography, which captures a 2D projection of the light in the scene integrating the angular domain, light fields collect radiance from rays in all directions, demultiplexing the angular information lost in conventional photography. On the one hand, this higher dimensional representation of visual data offers powerful capabilities for scene understanding, and substantially improves the performance of traditional computer vision problems such as depth sensing, post-capture refocusing, segmentation, video stabilization, material classification, etc. On the other hand, the high-dimensionality of light fields also brings up new challenges in terms of data capture, data compression, content editing, and display. Taking these two elements together, research in light field image processing has become increasingly popular in the computer vision, computer graphics, and signal processing communities. In this paper, we present a comprehensive overview and discussion of research in this field over the past 20 years. We focus on all aspects of light field image processing, including basic light field representation and theory, acquisition, super-resolution, depth estimation, compression, editing, processing algorithms for light field display, and computer vision applications of light field data

Development of radiofrequency pulses for fast and motion-robust brain MRI

This thesis is based on three projects and the three scientific articles that were the result of each project. Each project deals with various kinds of technical software development in the field of magnetic resonance imaging (MRI). The projects are in many ways very different, encompassing several acquisition and reconstruction strategies. However, there are at least two common denominators. The first is the projects shared the same goal of producing fast and motion robust methods. The second common denominator is that all the projects were carried out with a particular focus on the radiofrequency (RF) pulses used. The first project combined the acceleration method simultaneous multi-slice (SMS) with the acquisition method called PROPELLER. This combination was utilized to acquire motion-corrected thin-sliced reformattable T2-weighted and T1-FLAIR image volumes, thereby producing a motion robust alternative to 3D sequences. The second project analyzed the effect of the excitation RF pulse on T1-weighted images acquired with 3D echo planar imaging (EPI). It turned out that an RF pulse that reduced magnetization transfer (MT) effects significantly increased the gray/white matter contrast. The 3D EPI sequence was then used to rapidly image tumor patients after gadolinium enhancement. The third project combined PROPELLER’s retrospective motion correction with the prospective motion correction of an intelligent marker (the WRAD). With this combination, sharp T1-FLAIR images were acquired during large continuous head movements

Development of Methodologies for Diffusion-weighted Magnetic Resonance Imaging at High Field Strength

Diffusion-weighted imaging of small animals at high field strengths is a challenging prospect due to its extreme sensitivity to motion. Periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) was introduced at 9.4T as an imaging method that is robust to motion and distortion. Proton density (PD)-weighted and T2-weighted PROPELLER data were generally superior to that acquired with single-shot, Cartesian and echo planar imaging-based methods in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio and resistance to artifacts. Simulations and experiments revealed that PROPELLER image quality was dependent on the field strength and echo times specified. In particular, PD-weighted imaging at high field led to artifacts that reduced image contrast. In PROPELLER, data are acquired in progressively rotated blades in k-space and combined on a Cartesian grid. PROPELLER with echo truncation at low spatial frequencies (PETALS) was conceived as a postprocessing method that improved contrast by reducing the overlap of k-space data from different blades with different echo times. Where the addition of diffusion weighting gradients typically leads to catastrophic motion artifacts in multi-shot sequences, diffusion-weighted PROPELLER enabled the acquisition of high quality, motion-robust data. Applications in the healthy mouse brain and abdomen at 9.4T and in stroke patients at 3T are presented. PROPELLER increases the minimum scan time by approximately 50%. Consequently, methods were explored to reduce the acquisition time. Two k-space undersampling regimes were investigated by examining image fidelity as a function of degree of undersampling. Undersampling by acquiring fewer k-space blades was shown to be more robust to motion and artifacts than undersampling by expanding the distance between successive phase encoding steps. To improve the consistency of undersampled data, the non-uniform fast Fourier transform was employed. It was found that acceleration factors of up to two could be used with minimal visual impact on image fidelity. To reduce the number of scans required for isotropic diffusion weighting, the use of rotating diffusion gradients was investigated, exploiting the rotational symmetry of the PROPELLER acquisition. Fixing the diffusion weighting direction to the individual rotating blades yielded geometry and anisotropy-dependent diffusion measurements. However, alternating the orientations of diffusion weighting with successive blades led to more accurate measurements of the apparent diffusion coefficient while halving the overall acquisition time. Optimized strategies are proposed for the use of PROPELLER in rapid high resolution imaging at high field strength

Techniques in Optical Coherence and Resonance for Sensing

Optical sensors are ubiquitous for their precision and non-contact acquisition, and have enjoyed widespread use in applications such as biosensing, environmental monitoring, and security. Despite their sensitivity, many of these sensors rely on costly laboratory instrumentation, and are not adaptable to the ever-growing volume of consumer detectors and optics that are readily available, making their application limited to benchtop analytics. This work leverages plasmonic resonances and optical coherence phenomena to make modifications upon traditional sensing formats that improve their sensitivity when deployed in off-the-shelf optical systems. In particular, we demonstrate that label-free plasmonic sensors can be combined with electrochemical impedance spectroscopic biosensors to tackle the problem of specificity in label-free sesning, demonstrate the novel use case for the plasmonic detection of thermal infrared radiation, and show that plasmonic imaging is conducive to the characterization of nanometric thin liquid films. Moreover, we show that by introducing limited dispersion to Fourier transform spectroscopy, we can efficiently use camera detector formats and imaging systems to implement a high resolution scan-less Fourier transform spectrometer. By improving the figures of merit for sensor devices, we aim to translate traditional analytical sensing instrumentation from the laboratory benchtop into the consumer marketplace, and to spearhead a host of new applications

Artistic Path Space Editing of Physically Based Light Transport

Die Erzeugung realistischer Bilder ist ein wichtiges Ziel der Computergrafik, mit Anwendungen u.a. in der Spielfilmindustrie, Architektur und Medizin. Die physikalisch basierte Bildsynthese, welche in letzter Zeit anwendungsübergreifend weiten Anklang findet, bedient sich der numerischen Simulation des Lichttransports entlang durch die geometrische Optik vorgegebener Ausbreitungspfade; ein Modell, welches für übliche Szenen ausreicht, Photorealismus zu erzielen. Insgesamt gesehen ist heute das computergestützte Verfassen von Bildern und Animationen mit wohlgestalteter und theoretisch fundierter Schattierung stark vereinfacht. Allerdings ist bei der praktischen Umsetzung auch die Rücksichtnahme auf Details wie die Struktur des Ausgabegeräts wichtig und z.B. das Teilproblem der effizienten physikalisch basierten Bildsynthese in partizipierenden Medien ist noch weit davon entfernt, als gelöst zu gelten. Weiterhin ist die Bildsynthese als Teil eines weiteren Kontextes zu sehen: der effektiven Kommunikation von Ideen und Informationen. Seien es nun Form und Funktion eines Gebäudes, die medizinische Visualisierung einer Computertomografie oder aber die Stimmung einer Filmsequenz -- Botschaften in Form digitaler Bilder sind heutzutage omnipräsent. Leider hat die Verbreitung der -- auf Simulation ausgelegten -- Methodik der physikalisch basierten Bildsynthese generell zu einem Verlust intuitiver, feingestalteter und lokaler künstlerischer Kontrolle des finalen Bildinhalts geführt, welche in vorherigen, weniger strikten Paradigmen vorhanden war. Die Beiträge dieser Dissertation decken unterschiedliche Aspekte der Bildsynthese ab. Dies sind zunächst einmal die grundlegende Subpixel-Bildsynthese sowie effiziente Bildsyntheseverfahren für partizipierende Medien. Im Mittelpunkt der Arbeit stehen jedoch Ansätze zum effektiven visuellen Verständnis der Lichtausbreitung, die eine lokale künstlerische Einflussnahme ermöglichen und gleichzeitig auf globaler Ebene konsistente und glaubwürdige Ergebnisse erzielen. Hierbei ist die Kernidee, Visualisierung und Bearbeitung des Lichts direkt im alle möglichen Lichtpfade einschließenden "Pfadraum" durchzuführen. Dies steht im Gegensatz zu Verfahren nach Stand der Forschung, die entweder im Bildraum arbeiten oder auf bestimmte, isolierte Beleuchtungseffekte wie perfekte Spiegelungen, Schatten oder Kaustiken zugeschnitten sind. Die Erprobung der vorgestellten Verfahren hat gezeigt, dass mit ihnen real existierende Probleme der Bilderzeugung für Filmproduktionen gelöst werden können

Compressive Sensing for Microwave and Millimeter-Wave Array Imaging

PhDCompressive Sensing (CS) is a recently proposed signal processing technique that has already found many applications in microwave and millimeter-wave imaging. CS theory guarantees that sparse or compressible signals can be recovered from far fewer measure- ments than those were traditionally thought necessary. This property coincides with the goal of personnel surveillance imaging whose priority is to reduce the scanning time as much as possible. Therefore, this thesis investigates the implementation of CS techniques in personnel surveillance imaging systems with different array configurations. The first key contribution is the comparative study of CS methods in a switched array imaging system. Specific attention has been paid to situations where the array element spacing does not satisfy the Nyquist criterion due to physical limitations. CS methods are divided into the Fourier transform based CS (FT-CS) method that relies on conventional FT and the direct CS (D-CS) method that directly utilizes classic CS formulations. The performance of the two CS methods is compared with the conventional FT method in terms of resolution, computational complexity, robustness to noise and under-sampling. Particularly, the resolving power of the two CS methods is studied under various cir- cumstances. Both numerical and experimental results demonstrate the superiority of CS methods. The FT-CS and D-CS methods are complementary techniques that can be used together for optimized efficiency and image reconstruction. The second contribution is a novel 3-D compressive phased array imaging algorithm based on a more general forward model that takes antenna factors into consideration. Imaging results in both range and cross-range dimensions show better performance than the conventional FT method. Furthermore, suggestions on how to design the sensing con- figurations for better CS reconstruction results are provided based on coherence analysis. This work further considers the near-field imaging with a near-field focusing technique integrated into the CS framework. Simulation results show better robustness against noise and interfering targets from the background. The third contribution presents the effects of array configurations on the performance of the D-CS method. Compressive MIMO array imaging is first derived and demonstrated with a cross-shaped MIMO array. The switched array, MIMO array and phased array are then investigated together under the compressive imaging framework. All three methods have similar resolution due to the same effective aperture. As an alternative scheme for the switched array, the MIMO array is able to achieve comparable performance with far fewer antenna elements. While all three array configurations are capable of imaging with sub-Nyquist element spacing, the phased array is more sensitive to this element spacing factor. Nevertheless, the phased array configuration achieves the best robustness against noise at the cost of higher computational complexity. The final contribution is the design of a novel low-cost beam-steering imaging system using a flat Luneburg lens. The idea is to use a switched array at the focal plane of the Luneburg lens to control the beam-steering. By sequentially exciting each element, the lens forms directive beams to scan the region of interest. The adoption of CS for image reconstruction enables high resolution and also data under-sampling. Numerical simulations based on mechanically scanned data are conducted to verify the proposed imaging system.China Scholarship Council Engineering and Physical Sciences Research Council (EPSRC) funding (EP/I034548/1)