Doctor of Philosophy

dissertationThis dissertation presents original research that improves the ability of magnetic resonance imaging (MRI) to measure temperature in aqueous tissue using the proton resonance frequency (PRF) shift and T1 measurements in fat tissue in order to monitor focused ultrasound (FUS) treatments. The inherent errors involved in measuring the longitudinal relaxation time T1 using the variable flip angle method with a two-dimensional (2D) acquisition are presented. The edges of the slice profile can contribute a significant amount of signal for large flip angles at steady state, which causes significant errors in the T1 estimate. Only a narrow range of flip angle combinations provided accurate T1 estimates. Respiration motion causes phase artifacts, which lead to errors when measuring temperature changes using the PRF method. A respiration correction method for 3D imaging temperature of the breast is presented. Free induction decay (FID) navigators were used to measure and correct phase offsets induced by respiration. The precision of PRF temperature measurements within the breast was improved by an average factor of 2.1 with final temperature precision of approximately 1 °C. Locating the position of the ultrasound focus in MR coordinates of an ultrasound transducer with multiple degrees of freedom can be difficult. A rapid method for predicting the position using 3 tracker coils with a special MRI pulse iv sequence is presented. The Euclidean transformation of the coil's current positions to their calibration positions was used to predict the current focus position. The focus position was predicted to within approximately 2.1 mm in less than 1 s. MRI typically has tradeoffs between imaging field of view and spatial and temporal resolution. A method for acquiring a large field of view with high spatial and temporal resolution is presented. This method used a multiecho pseudo-golden angle stack of stars imaging sequence to acquire the large field of view with high spatial resolution and k-space weighted image contrast (KWIC) to increase the temporal resolution. The pseudo-golden angle allowed for removal of artifacts introduced by the KWIC reconstruction algorithm. The multiple echoes allowed for high readout bandwidth to reduce blurring due to off resonance and chemical shift as well as provide separate water/fat images, estimates of the initial signal magnitude M(0), T2 * time constant, and combination of echo phases. The combined echo phases provided significant improvement to the PRF temperature precision, and ranged from ~0.3-1.0 °C within human breast. M(0) and T2 * values can possibly be used as a measure of temperature in fat

Efficient image-based rendering

Recent advancements in real-time ray tracing and deep learning have significantly enhanced the realism of computer-generated images. However, conventional 3D computer graphics (CG) can still be time-consuming and resource-intensive, particularly when creating photo-realistic simulations of complex or animated scenes. Image-based rendering (IBR) has emerged as an alternative approach that utilizes pre-captured images from the real world to generate realistic images in real-time, eliminating the need for extensive modeling. Although IBR has its advantages, it faces challenges in providing the same level of control over scene attributes as traditional CG pipelines and accurately reproducing complex scenes and objects with different materials, such as transparent objects. This thesis endeavors to address these issues by harnessing the power of deep learning and incorporating the fundamental principles of graphics and physical-based rendering. It offers an efficient solution that enables interactive manipulation of real-world dynamic scenes captured from sparse views, lighting positions, and times, as well as a physically-based approach that facilitates accurate reproduction of the view dependency effect resulting from the interaction between transparent objects and their surrounding environment. Additionally, this thesis develops a visibility metric that can identify artifacts in the reconstructed IBR images without observing the reference image, thereby contributing to the design of an effective IBR acquisition pipeline. Lastly, a perception-driven rendering technique is developed to provide high-fidelity visual content in virtual reality displays while retaining computational efficiency.Jüngste Fortschritte im Bereich Echtzeit-Raytracing und Deep Learning haben den Realismus computergenerierter Bilder erheblich verbessert. Konventionelle 3DComputergrafik (CG) kann jedoch nach wie vor zeit- und ressourcenintensiv sein, insbesondere bei der Erstellung fotorealistischer Simulationen von komplexen oder animierten Szenen. Das bildbasierte Rendering (IBR) hat sich als alternativer Ansatz herauskristallisiert, bei dem vorab aufgenommene Bilder aus der realen Welt verwendet werden, um realistische Bilder in Echtzeit zu erzeugen, so dass keine umfangreiche Modellierung erforderlich ist. Obwohl IBR seine Vorteile hat, ist es eine Herausforderung, das gleiche Maß an Kontrolle über Szenenattribute zu bieten wie traditionelle CG-Pipelines und komplexe Szenen und Objekte mit unterschiedlichen Materialien, wie z.B. transparente Objekte, akkurat wiederzugeben. In dieser Arbeit wird versucht, diese Probleme zu lösen, indem die Möglichkeiten des Deep Learning genutzt und die grundlegenden Prinzipien der Grafik und des physikalisch basierten Renderings einbezogen werden. Sie bietet eine effiziente Lösung, die eine interaktive Manipulation von dynamischen Szenen aus der realen Welt ermöglicht, die aus spärlichen Ansichten, Beleuchtungspositionen und Zeiten erfasst wurden, sowie einen physikalisch basierten Ansatz, der eine genaue Reproduktion des Effekts der Sichtabhängigkeit ermöglicht, der sich aus der Interaktion zwischen transparenten Objekten und ihrer Umgebung ergibt. Darüber hinaus wird in dieser Arbeit eine Sichtbarkeitsmetrik entwickelt, mit der Artefakte in den rekonstruierten IBR-Bildern identifiziert werden können, ohne das Referenzbild zu betrachten, und die somit zur Entwicklung einer effektiven IBR-Erfassungspipeline beiträgt. Schließlich wird ein wahrnehmungsgesteuertes Rendering-Verfahren entwickelt, um visuelle Inhalte in Virtual-Reality-Displays mit hoherWiedergabetreue zu liefern und gleichzeitig die Rechenleistung zu erhalten

Ultra-Shallow Imaging Using 2D & 3D Seismic Reflection Methods

The research presented in this dissertation focuses on the survey design, acquisition, processing, and interpretation of ultra-shallow seismic reflection (USR) data in two and three dimensions. The application of 3D USR methods to image multiple reflectors less than 20 m deep, including the top of the saturated zone (TSZ), a paleo-channel, and bedrock, are presented using conventional acquisition methods and a new automated method of acquiring 3D data using hydraulically planted geophones. Processing techniques that focus on near-surface problems, such as intersecting reflection hyperbolae caused by large vertical velocity changes and processing pitfalls, are also discussed. The application of AVO analysis of 2D USR data collected during a pumping test yielded amplitude variations related to the thickness of the partially saturated zone that correlated spatially and with changes in pumping. USR methods were also used to image the TSZ less than one meter deep, the shallowest TSZ reflection to date

Bathymetric uncertainty model for the L-3 Klein 5410 sidescan sonar

The L-3 Klein 5410 sidescan sonar system acquires acoustic backscatter imagery and bathymetry data. A bathymetry uncertainty model was developed for this sonar to predict its performance against hydrographic standards set by the International Hydrographic Organization (IHO). Elements of the model not specific to this sonar were adapted from existing uncertainty models, and the remainder was calculated by comparing the 5410 bathymetry with a reference surface obtained from multibeam echosounder data. The sonar\u27s angular uncertainty was solved for different bottom types with best results obtained over sandy bottoms, where, after removal of some system biases, the bathymetry met standards for hydrographic surveys Order 1 from 30° to 75° from nadir. The model predicts that the total propagated uncertainty at 20-m altitude meets IHO standards over a swath width equal to seven times the water-depth, with a central gap one water-depth wide for an ideal 5410

Fast, Three-Dimensional Fluorescence Imaging of Living Cells

This thesis focuses on multi-plane fluorescence microscopy for fast live-cell imaging. To improve the performance of multi-plane microscopy, I developed new image analysis methods. I used these methods to measure and analyze the movements of cardiomyocytesand Dictyostelium discoideum cells.The multi-plane setup is based on a conventional wide-field microscope using a custom multiple beam-splitter in the detection path. This prism creates separate images of eight distinct focal planes in the sample. Since 3D volume is imaged without scanning, three-dimensional imaging at a very high speed becomes possible. However, as in conventional wide-field microscopy, the "missing cone" of spatial frequencies along the optical axis in the optical transfer function (OTF) prevents optical sectioning in such a microscope. This is in stark contrast to other truly three-dimensional imaging modalities like confocal and light-sheet microscopy. In order to overcome the lack of optical sectioning, I developed a new deconvolution method. Deconvolution describes methods that restore or sharpen an image based on physical assumptions and knowledge of the imaging process. Deconvolution methods have been widely used to sharpen images of microscopes and telescopes. The recently developed SUPPOSe algorithm is a deconvolution algorithm that uses a set of numerous virtual point sources. It tries to reconstruct an image by distributing these point sources in space and optimizing their positions so that the resulting image reproduces as good as possible the measured data. SUPPOSe has never been used for 3D images. Compared to other algorithms, this method has superior performance when the number of pixels is increased by interpolation. In this work, I extended the method to work also with 3D image data. The 3D-SUPPOSe program is suitable for analyzing data of our multi-plane setup. The multi-plane setup has only eight vertically aligned image planes. Furthermore, for accurate reconstruction of 3D images, I studied a method of correcting each image plane's relative brightness constituting an image, and I also developed a method of measuring the movement of point emitters in 3D space. Using these methods, I measured and analyzed the beating motion of cardiomyocytes and the chemotaxis of Dicyosteilium discoidem. Cardiomyocytes are the cells of the heart muscle and consist of repetitive sarcomeres. These cells are characterized by fast and periodic movements, and so far the dynamics of these cells was studied only with two-dimensional imaging. In this thesis, the beating motion was analyzed by tracing the spatial distribution of the so-called z-discs, one of the constituent components of cardiomyocytes. I found that the vertical distribution of $\alpha$-actinine-2 in a single z-disc changed very rapidly, which may serve as a starting point for a better understanding the motion of cardiomyocytes. \textit{Dictyostelium discoideum} is a well established single cell model organism that migrates along the gradient of a chemoattractant. One has conducted much research to understand the mechanism of chemotaxis, and many efforts have been made to understand the role of actin in the chemotactic motion. By suppressing the motor protein, myosin, a cell line was created that prevented the formation of normal actin filaments. In these myosin null cells, F-actin moves in a flow-like behaviour and induces cell movement. In this study, I imaged the actin dynamics, and I analyzed the flow using the newly created deconvolution and flow estimation methods. As a result of the analysis, the spatio-temporal correlation between pseudo-pod formation and dynamics and actin flow was investigated.2022-01-2

Pulse patency and oxygenation sensing system development to detect g-induced loss of consciousness

A fighter pilots greatest strength is the weakness of his or her opponent. Commonly, this strength comes down to the maneuverability of the aircraft, particularly the ability to out-climb. Since the 1980\u27s, the thrust produced by these engines have the ability to drain the pilots head of blood causing a state of unconsciousness due to the overwhelming forces of gravity for upwards of 30 seconds; often times having fatal outcomes. This thesis explores the feasibility of detecting of blood flow by means of arterial wall expansion (pulse patency) and blood oxygenation using a microprocessor to continually monitor the signals from this two part sensor where by insight into the development of a g-induced loss of consciousness sensing system can be developed. Results indicate greater than 90% accuracy pulse patency detection using an accelerometer. Simulation and physical models were used as well as human testing to develop a blood oxygenation and pulse patency sensor, or BOPS