Cardiovascular diseases is a leading cause of death worldwide and improvement of the corresponding screening tool is the best way to deal with this clinical problem. In this thesis we attempted to develop a framework of ultrasound high frame rate vector flow imaging (VFI) by emphasizing on the design of corresponding flow detector and flow estimator. We believe that the high temporal resolution and the complex blood flow visualization ability of high frame rate VFI enables it to be further developed as a reliable flow imaging modality for cardiological examination. In order to achieve high temporal resolution, fast data acquisition algorithm was applied in the framework. Doppler signals acquired using this acquisition algorithm have two unique characteristics comparing with conventional data acquisition algorithm: (1) widen spectral bandwidth and (2) greater clutter to blood signal ratio. These signal characteristics give rise to unique signal processing. In addition, complex blood flow pattern, which is common in cardiological examination, induces extra challenges in implementing high frame rate VFI. In this thesis, flow detector which is adaptive to different flow scenarios and high dynamic range 2D flow estimator were presented. The proposed flow detector employes K-means++ clustering algorithm to classify clutter components from acquired Doppler signals. As a performance analysis, Field II simulation studies were performed by a parabolic flow phantom (flow velocity: 10mm/s to 200mm/s; tissue motion: 10mm/s; beam-flow angle: 60?). The post-filtered Doppler power map and BCR were used as qualitative and quantitativemeasures of detectors performance. Analyzed result has indicated that, as compared with clutter downmixing detector and eigen-based detector, the proposed flow detector could classify and suppress clutter component more effectively. Results also suggested that the proposed flow detector is more adaptive to slow flow scenarios where existing flow detectors failed to distinguish between blood and clutter components. For the proposed flow estimator, it was characterized by the interpolation of speckle tracking results in Lagrangian reference frame. The estimation bias and RMS error were calculated for different flow scenarios (flow velocity: 100mm/s to 500mm/s; beam-flow angle: 15? to 60?). It was found that the proposed flow estimator provides higher dynamic range than conventional speckle tracking-based flow estimator. Nonetheless, it is also observed that the estimation variances and errors increases in slow flow scenarios. In order to demonstrate the medical potential of the proposed high frame rate VFI framework. A carotid bifurcation simulation model with realistic blood flow pattern calculated using computational fluid dynamic software was applied in the performance evaluation study. In the VFI image obtained, complex blood flow pattern was readily visualized. In contrast, conventional ultrasound flow imaging was only able to estimate axial velocity map and thus lead to many ambiguities in analyzing the complex blood flow pattern. It proved that ultrasound high frame rate VFI has the potential to be further developed into a new cardiological examination technique. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Surface-Assisted Laser Desorption/Ionization Mass Spectrometry (SALDI-MS) is an analytical technique enabling direct chemical analysis of solid samples. Analytes could be desorbed/ionized upon nitrogen laser irradiation from a SALDI substrate-coated sample, then analyzed by MS. The substrate is involved in the transfer of laser energy to the analytes, and eventually assists the desorption/ionization of analytes. The analytical performance of SALDI-MS, such as detection sensitivity, is dependent on different parameters of the substrate, such as size, morphology and form. In this thesis, the effects of several substrate parameters on the SALDI process were investigated. SALDI-MS based Imaging Mass Spectrometry (IMS) method was also developed using efficient SALDI substrate identified in the fundamental studies. IMS is a chemical-specific mapping technique which allows parallel mapping of multiple analytes in solid samples. The desorption mechanism of SALDI is investigated using two groups of substrate, the carbon allotropes and the noble metal nanoparticles. Ion desorption efficiency and internal energy transfer were probed and correlated in carbon-based SALDI. It was found that the ion desorption efficiency and internal energy transfer was in opposite order. Substrate that transferred more internal energy to ions did not show higher ion desorption efficiency. This result could not be explained by the Thermal Desorption model which was a generally believed mechanism of the SALDI desorption process. A non-thermal model, the Phase Transition model is proposed to account for the SALDI desorption process. The Phase Transition model suggests that the substrate is melted/ restructured upon laser irradiation, and this will assist ion desorption. The Phase Transition model is supported by the morphological change of carbon substrates after SALDI and high initial velocity of ions desorbed by carbon-based SALDI (> 1,000 ms-1). SALDI-MS is useful for small molecule analysis due to the relatively clean background in the low mass region. SALDI-IMS is developed and applied to the imaging of spatial distribution of small molecules in forensic and biological samples. Gold nanoparticles (AuNPs) was selected as the substrate from several other noble metal NPs. A solvent-free method, argon ion sputtering, was employed for coating AuNPs on sample surface prior to SALDI-IMS analysis. Fine details of the samples, such as the fine pattern of latent fingerprints and handwriting on questioned documents can be preserved and imaged reliably by avoiding the use of solvent. Fatty acids, drugs and ink components can be imaged in forensic samples including latent fingerprints, banknotes and checks. The solvent-free SALDI-IMS method was also applied to image the distribution of metabolites in intact animal tissues. Spatial distributions of neurotransmitters, nucleobases and fatty acids can be imaged from mouse brain and tumor tissue sections. / published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

Magnetic resonance (MR) is a well-known non-invasive technique that provides spectra (by MR spectroscopy, MRS) and images (by magnetic resonance imaging, MRI) of the examined tissue with detailed metabolic, structural, and functional information. This doctoral work is focused on advanced methodologies and applications of MRS for probing cellular and molecular changes in vivo. A single-voxel diffusion-weighted (DW) MRS method was first developed for monitoring the size changes of intramyocellular lipid droplets in vivo. This DWMRS technique was then utilized for exploring the vascular origins of the functional blood-oxygen-level-dependent (BOLD) signal. Magnetic resonance spectroscopic imaging (MRSI) enables simultaneous MRS acquisition in multiple voxels. However, MRSI is conventionally time-consuming. Therefore, a compressed sensing (CS) method was proposed in this thesis to accelerate the acquisition speed of the in vivo MRSI. It holds the potential for promoting the realization of multiple-voxel DW-MRS experiments, though the latter is still constrained by hardware in the present. The single-voxel DW-MRS method for probing lipid diffusion was first developed and evaluated in oil and muscle phantoms. The experimental sequence was demonstrated to be sensitive to diffusion restriction and free of significant artifacts. Experiments were then performed in rat hindlimb muscles in vivo. The restricted lipid diffusion behavior was characterized by apparent diffusion coefficient (ADC) changes and utilized for quantifying the sizes of intramyocellular lipid (IMCL) droplets in normal, fasting, diabetic and obese rats. The sizes of IMCL droplets reflect their vital roles in muscle energy metabolism. The IMCL droplet size estimated by ADC here was closely correlated with that measured by transmission electron microscopy. IMCL ADC was sensitive to metabolic alterations, decreasing in the fasting and diabetic groups while increasing in the obese group. These results clearly demonstrate DW MRS as a new means to examine the dynamics of IMCL metabolism in vivo. The DW-MRS technique was then utilized to characterize water ADC during neuronal activation to explore the vascular origins of the BOLD signal in rat brains. MRS experiments with acoustic stimulation were performed with a dynamic point-resolved spectroscopy (PRESS) acquisition on conditions with or without the diffusion gradient for blood suppression in the same voxel and same experimental session, which enabled the simultaneous T2/T2*/diffusion measurements. The T2*% changes with and without diffusion gradient showed no significant difference, while the spin echo (SE)-BOLD% (T2%) change significantly decreased after applying the diffusion gradient, suggesting an intravascular component in the SE-BOLD signal. This intravascular component was not venous blood, as the T2* of this component was comparable with the T2* of the brain tissue. These results provide new insights into the vascular origins of BOLD signals. A CS approach was developed to accelerate in vivo magnetic resonance spectroscopic imaging (MRSI) which enables multi-voxel MRS measurements. The CS undersampling was performed by acquiring a pseudo-random and density-varying subset of phase encodings. The proposed CS approach preserved the spectral and spatial resolution, while substantially reduced the number of phase encodings with accelerations up to seven fold for phantom and up to six fold for in vivo rat brains. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Today label-free bioimaging has been leading to widespread and fast-growing applications, which demands for a more efficient way to keep up such momentum. To this end, the research in this thesis will study the techniques of efficiency improvement for advanced label-free bioimaging, including the time efficiency, cost efficiency and information efficiency. Optical coherence tomography (OCT) is one of the most valuable label-free bioimaging modalities to provide noninvasive cross-sectional assessment of biological tissue. In many occasions, these applications demand for three dimensional (3D) imaging at video-rate in order to perform real-time diagnoses, which can be overcome by MHz-OCT. Here we demonstrate inertia-free all-optical ultrahigh-speed swept-source optical coherence tomography (OCT) based on amplified optical time-stretch (AOT). More importantly, the key significance of AOT-OCT is its broadband amplification stage, which greatly enhances the detection sensitivity compared with the prior attempts to employ optical time-stretch to OCT. We report an AOT-OCT system which is operated at an A-scan rate of multi-megahertz with high sensitivity (>80 dB) and perform time-stretch-based OCT of biological tissue in vivo. Moreover, using a more stable and coherent mode-locked fiber laser, we can achieve better performance without the compromise of averaging for supercontinuum-generation-based AOT-OCT system. It represents a major step forward in utilizing AOT as an alternative for achieving practical time-efficient OCT imaging at multi-MHz speed. For the further development of this ultrahigh-speed OCT, we present a theoretical analysis of the AOT-OCT system. The spectral resolution, coherence length and sensitivity of AOT-OCT system have been discussed in detail. By theoretical model of the noise sources based on Raman amplifier, we also quantify how the input signal, amplifier gain, A-scan rate affect the sensitivity of AOT-OCT imaging. These simulation results are expected to be valuable for optimizing the design of AOT-OCT. We also investigate in cost-effective implementation to realize efficient optical time-stretch process based on dispersive fiber. We explore and demonstrate the feasibility of using the standard telecommunication single-mode fibers as few-mode fibers (FMFs) for optical time-stretch confocal microscopy in the 1m range. It can provide sufficiently high dispersion-to-loss ratios for practical time-stretch imaging at 1 m, without the needs for high-cost specialty 1 m single mode fiber. In addition, Coherent anti-Stokes Raman scattering (CARS) microscopy is another attractive efficient tool for label-free biochemical-specific imaging, which can bypass laborious steps of preparing and staining in routine standard histopathology. Here we further explore ultrabroadband hyperspectral multiplex (HM-CARS) to perform chemoselective histological imaging with efficient information in fingerprint region. In order to unravel the congested CARS spectra, we employ phase-retrieval algorithm based on Kramers–Kronig (KK) transform and principal component analysis (PCA) to display the key cellular structures with components distribution. All these research efforts are aiming at improving the efficiency, from theory to implementation, for label-free bioimaging technology such as OCT and CARS. These schemes demonstrate great potential to realize powerful label-free bioimaging with high efficiency, including ultrafast 3D OCT imaging at video-rate, cost-effective optical time-stretch imaging and HM-CARS imaging with richness of biological fingerprint information. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Diffusion weighted magnetic resonance images offer unique insights into the neural networks of in vivo human brain. In this study, we investigate estimation and statistical analysis of multi-compartment models in high angular resolution diffusion imaging (HARDI) involving the Rician noise model. In particular, we address four important issues in multi-compartment diffusion model estimation, namely, the modelling of Rician noise in diffusion weighted (DW) images, the automatic determination of the number of compartments in the diffusion signal, the application of spatial prior on multi-compartment models, and the evaluation of parameter indeterminacy in diffusion models. We propose an expectation maximization (EM) algorithm to estimate the parameters of a multi-compartment model by maximizing the Rician likelihood of the diffusion signal. We introduce a novel scheme for automatically selecting the number of compartments, via a sparsity-inducing prior on the compartment weights. A non-local weighted maximum likelihood estimator is proposed to improve estimation accuracy utilizing repetitive patterns in the image. Experimental results show that the proposed algorithm improves estimation accuracy in low signal-to-noise-ratio scenarios, and it provides better model selection than several alternative strategies. In addition, we derive the Cram´er-Rao Lower Bound (CRLB) of the maximum Rician likelihood estimator for the balland-stick model and general differentiable diffusion models. The CRLB provides a general theoretical tool for comparing diffusion models and examining parameter indeterminacy in the maximum likelihood estimation problem. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

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Metallic films with narrow and deep subwavelength gratings or holes having a converging-diverging channel (CDC) can exhibit enhanced transmission resonances for wavelengths larger than the periodicity of the grating or hole. Using the finite element method, it is shown that by varying the gap size at the throat of a CDC, the spectral locations of the transmission resonance bands can be shifted close to each other and have high transmittance in a very narrow energy band. Additionally, the transmission of light can be influenced by the presence of the externally applied magnetic field H. The spectral locations of the transmission peak resonances depend on the magnitude and the direction of H. The transmission peaks have blue-shift with the increase in H. A new multilayer thermal emitter has been analyzed in the visible wavelength range. The proposed emitter has large temporal and spatial coherence extending into the far field. The thermal emitter is made up of a cavity that is surrounded by a thin silver grating having a CDC on one side and a one-dimensional (1D) photonic crystal (PhC) on the other side. The large coherence length is achieved by making use of the coherence properties of the surface waves. Due to the nature of surface waves the new multilayer structure can attain the spectral and directional control of emission with only ppolarization. The resonance condition inside the cavity is extremely sensitive to the wavelength, which would then lead to high emission in a very narrow wavelength band. In addition a new tunable plasmonic crystal (tPLC) was proposed, where the plasmonic or polaritonic mode of a metallic array can be combined with the photonic mode of a hole array in a dielectric slab for achieving negative refraction and still posses an extra degree of freedom for tuning the tPLC as a superlens to operate at different frequencies. The tunability of the single planar tPLC slab is demonstrated numerically for subwavelength imaging (FWHM 0.38[lambda]~ 0.42[lambda]) by just varying the fluid in the hole array, thereby enabling the realization of ultracompact tunable superlens and paving the way for a new class of lens. An aggressive pursuit for decreasing the minimum feature size in high bandgap materials has lead to various challenges in nanofabrication. However, it is difficult to achieve critical dimensions at sub-wavelength scale using traditional optical lithography. A new technique to create submicron patterns on hard-to-machine materials like silicon carbide (SiC) and borosilicate glass with a laser beam is demonstrated. Here the principle of optical near-field enhancement between the spheres and substrate when irradiated by a laser beam has been used for obtaining the patterning.

This dissertation describes a new topology analysis tool for a skeletal based geometric modeling system for conceptual design. Skeletal modeling is an approach to creating solid models in which the engineer designs with lower dimensional primitives such as points, lines, and triangles. The skeleton is then "skinned over" to create the surfaces of the three-dimensional object. In this research, convolution surfaces are used to provide the flesh to the skeleton. Convolution surfaces are generated by convolving a kernel function with a geometric field function to create an implicit surface. Certain properties of convolution surfaces make them attractive for skeletal modeling, including: (1) providing analytic solutions for various geometry primitives (including points, line segments, and triangles); (2) generating smooth surfaces; and (3) providing well-behaved blending. We assume that engineering designers expect the topology of a skeletal model to be identical to that of the underlying skeleton. However, the topology of convolution surfaces can change arbitrarily, making it difficult to predict the topology of the generated surface from knowledge of the topology of the skeleton. To address this issue, we apply Morse theory to analyze the topology of convolution surfaces by detecting the critical points of the surfaces. We developed an efficient and intelligent algorithm to find the critical points (CPs) by analyzing the skeleton. The critical points provide valuable information about the topology of the convolution surfaces. By tracking the CPs, we know where and what kind of topology changes happen when the threshold value reaches the critical value at the CP. Topology matching is done in two steps: (1) global topology is tested by comparing the Betti numbers (number of component, loops, and voids) of the skeleton and the generated convolution surfaces; (2) with matched Betti numbers, local topology is tested by comparing the location of each loop and void area between the skeleton and surfaces. If the topology does not match, appropriate heuristics for determining parameter values of the convolution surfaces are applied to force the surface topology to match that of the skeleton. A recommend threshold value is then provided to generate the topology matched convolution surfaces.