Pyramidal flux in an anisotropic diffusion scheme for enhancing structures in 3D images

Pyramid based methods in image processing provide a helpful framework for accelerating the propagation of information over large spatial domains, increasing the efficiency for large scale applications. Combined with an anisotropic diffusion scheme tailored to preserve the boundaries at a given level, an efficient way for enhancing large structures in 3D images is presented. In our approach, the partial differential equation defining the evolution of the intensity in the image is solved in an explicit scheme at multiple resolutions in an ascending-descending cycle. Intensity 'flux' between distant voxels is allowed, while preserving borders relative to the scale. Experiments have been performed both with phantoms and with real data from 3D Transrectal Ultrasound Imaging. The effectiveness of the method to remove speckle noise and to enhance large structures such as the prostate has been demonstrated. For instance, using two scales reduces the computation time by 87% as compared to a single scale. Furthermore, we show that the boundaries of the prostate are mainly preserved, by comparing with manually outlined edges

Application of diffusion techniques to the segmentation of Mr 3D images for virtual colonoscopy

Master'sMASTER OF ENGINEERIN

New MR imaging techniques in epilepsy

This thesis is concerned with the application of three magnetic resonance (MR) techniques in epilepsy: i.) Fluid attenuated inversion recovery prepared (FLAIR) imaging, ii.) diffusion imaging including diffusion tensor imaging (DTI) and iii.) serial and high resolution imaging of the hippocampus. I assessed the clinical value of fast FLAIR in epilepsy in a study involving 128 patients and of 3D FLAIR in a study involving 10 patients. The conspicuity of neocortical lesions and hippocampal sclerosis was increased. New lesions were detected in 5% of patients. The extent of low grade tumours was best assessed on 3D fast FLAIR images. Fast FLAIR was inferior to standard MR techniques for identifying and heterotopia. I applied newly developed, experimental diffusion imaging techniques. In eight studies using different diffusion imaging techniques involving a total of 50 patients and 54 control subjects I investigated the mobility of water molecules in the human epileptic brain in vivo. I used spin echo diffusion imaging in two studies, echo planar imaging (EPI) based DTI in four studies and EPI diffusion imaging in a patient during focal status epilepticus. Finally, in a preliminary study I attempted to use EPI diffusion imaging as a contrast to visualise transient changes associated with frequent lateralizing spikes. Our findings were: i.) diffusion is increased in hippocampal sclerosis suggesting a loss of structural organization and expansion of the extracellular space, ii.) displaying the directionality (anisotropy) of diffusion is superior to standard imaging to visualise tracts, iii.) anisotropy is reduced in the pyramidal tract in patients with hemiparesis and iv.) in the optic radiation in patients with hemianopia after temporal lobectomy suggesting wallerian degeneration, v.) both developmental and acquired structural abnormalities have a lower anisotropy than normal white matter, vi.) diffusion abnormalities in blunt head trauma are widespread and may include regions which are normal on standard imaging, indicating micro structural damage suggestive of diffuse axonal injury, vii.) focal status epilepticus can be associated with a reduced difflision in the affected cortex, viii.) diffusion imaging may be useful as a contrast for event-related (spike triggered) functional MR imaging. With serial MRI I demonstrated hippocampal volume loss in a patient after generalized status epilepticus and with high resolution imaging of an anatomical specimen and a control subject I showed hippocampal layers on MR images. The results presented in this thesis emphasised the flexibility of MR imaging and its ability to demonstrate abnormalities in vivo. FLAIR imaging is now part of the clinical work up of patients with epilepsy. Diffusion imaging has been shown to be superior to standard imaging to visualise tracts which has far-reaching implications for neurological applications. Diffusion imaging also provides an exciting window to study cerebral micro structure in vivo. Serial imaging allows for the first time the visualisation of temporal changes and high resolution imaging has the prospect of demonstrating hippocampal layers in vivo. MR imaging is a constantly progressing technique. It is hoped that this thesis will help to formulate hypotheses for new MR experiments to study the relationship of dysfunction and structural abnormalities

Extension to pv optics to include front electrode design in solar cells

Proper optical designing of solar cells and modules is of paramount importance towards achieving high photovoltaic conversion efficiencies. Modeling softwares such as PV OPTICS, BIRANDY and SUNRAYS have been created to aid such optical designing of cells and modules; but none of these modeling packages take the front metal electrode architecture of a solar cell into account. A new model, has been developed to include the front metal electrode architecture to finished solar cells for optical calculations. This has been implemented in C++ in order to add a new module to PV OPTICS (NREL’s photovoltaic modeling tool) to include front metallization patterns for optical design and simulation of solar cells. This new addition also calculates the contribution of light that diffuses out of the illuminated (non-metallized) regions to the solar cell current. It also determines the optical loss caused by the absorption in the front metal and separates metallic losses due to front and back contacts. This added capability also performs the following functions: calculates the total current that can be generated in a solar cell due to optical absorption in each region, including the region beneath the front metal electrodes for the radiation spectrum of AM 1.5, calculates various losses in the solar cell due to front electrode shading, metal absorption, and reflectance, makes a plot of how light is absorbed in the metal as well as silicon under the shaded region in the solar cell. Although Finite Difference Time Domain (FDTD) is the numerical technique of choice to solve Maxwell’s equations for a propagating electromagnetic wave, it is both time consuming and very demanding on the computer processors. Furthermore, for complicated geometric structures, FDTD poses various limitations. Hence, ray tracing has been chosen as the means of implementing this new model. This new software has been used to carry out a detailed investigation on the effect of various parameters of the front electrode architecture on the performance of alkaline anisotropically texture etched (100) oriented single crystal silicon solar cells. These parameters include: the thickness of the silicon absorber layer, the texture height, width of the front metal fingers, height of the front metal fingers, and the effect of encapsulation of a solar cell in a module. The results show that the front metal architecture used in commercial silicon solar cells has minimal effect on its performance. A decline in the total current derived from the cell encapsulated in a module is also observed. This has helped to narrow down the design variables of commercial silicon solar cells with the standard front electrode grid of fingers and busbars to only the electrical transport

Nano-Optics-Enabled High-Efficiency Solar Cells

Glancing angle coupling of light into dielectric media is a desirable feature that can benefit the performance of solar cells. At a highly refractive dielectric interface, however, the transmission angle is limited small (e.g., ~15 deg for air/Si) by Snell’s law. In this thesis, we propose a new method of light coupling that overcomes the conventional limits of refractive transmission. A vertical dipole structure is designed to enable glancing propagation into high-index media, enhancing light absorption and carrier collection for a given thickness of active medium. A vertical-dipole nano-optic structure was introduced to a conventional finished silicon cell (~16% efficiency). The vertical dipoles reradiate incident light into oblique directions inside the active medium (Si). The glancing propagation along the junction interface results in a synergistic, uncompromised improvement of cell performance (i.e., enhancing photocarrier generation without sacrificing carrier transport) and demonstrates 20% cell efficiency. We have further studied low-voltage, broadband photocarrier multiplication in a graphene/SiO2/Si structure and demonstrate external quantum efficiency 146-200% (internal quantum efficiency 218-384%) as measured with photocurrent in UV-to-NIR (325-850nm). The self-induced electric field (~106 V/cm) in 2D electron gas enables impact ionization at low bias (< 2V), in a way promising and compatible with photovoltaic operation

3D reconstruction of coronary arteries from angiographic sequences for interventional assistance

Introduction -- Review of literature -- Research hypothesis and objectives -- Methodology -- Results and discussion -- Conclusion and future perspectives

A NOVEL MICROFABRICATION TECHNIQUE FOR DEVELOPMENT OF A 3D PYRAMIDAL POROUS MEMBRANE

Ph.DDOCTOR OF PHILOSOPH

FiberBlender: A Realistic Computer Model of Nerve Bundles for Simulating and Validating the Acquisition of Diffusion Tensor Imaging

Diffusion Tensor Imaging (DTI) is a powerful medical imaging technique that provides a unique method to investigate the structure and connectivity of neural pathways. DTI is a special magnetic resonance imaging (MRI) modality that combines the principles of magnetic resonance with molecular diffusion to trace the motion of water molecules. In the central nervous system, where nerve fibers are packed in highly-directional bundles, these molecules diffuse along the orientation of the fibers. Hence, characterizing the motion of water with DTI delivers a non-invasive in vivo technique to capture the connectivity of nerves themselves. Despite its promises and successful clinical applications for nearly thirty years, problems with validation and interpretation of measurements still persist. Most validation studies attempt to generate ground-truth data from animal models, phantoms, and computer models. This dissertation proposes a novel validation system, FiberBlender, capable of reproducing three-dimensional fiber structures and simulating the diffusion of water molecules to generate ground-truth synthetic DTI data. In particular FiberBlender contributes to: (i) creating more biologically accurate representations of fiber bundles with the inclusion of myelin and glial cells, (ii) examining the effect of demyelination and gliosis on DTI measurements, (iii) optimizing acquisition sequences, and (iv) evaluating the performance of multi-tensor models for the study of crossing fibers. FiberBlender strays away from the “one size fits all” approach taken by previous studies and uses computer algorithms in conjunction with some limited manual operations to produce brain-like geometries that take into account the random spatial location of axons and correct distributions of axon diameters, myelin to axon radius, and myelin to glia ratio. In this way no two models are the same and the system is capable of generating structures that can potentially represent any region of the brain and encompass the heterogeneity between human subjects. This feature is essential for optimization as the performance of DTI acquisition sequences may vary among subjects and the type of scanner used. In addition to better accuracy, the system offers a high degree of flexibility as the geometry can be modified to simulate events that cause drastic changes to the fiber structure. Specially, this dissertation looks at demyelination (an extensive loss of myelin volume), gliosis (a proliferation of glial cells), and axon compaction (a condensation of axons due to a loss of total brain volume) to determine their effects on the observed DTI signal. Simulation results confirm that axon compaction and partial remyelination have similar characteristics. Results also show that some standard clinically used acquisition sequences are incapable of capturing the effects of demyelination, gliosis and compaction when performing longitudinal studies. A novel sequence optimization technique based on Shannon entropy and mutual information is proposed to better capture demyelination. Optimized sequences are tested on a number of non-identical models to confirm their validity and can be used to improve the quality of DTI diagnostics. Finally this work looks at crossing fibers for the validation of multi-tensor models in their ability to characterize crossing diffusion profiles. The performance of multi-tensor models from CHARMED, Q-ball and spherical deconvolution that are widely used in both research and clinical settings are evaluated against ground-truth data generated with FiberBlender. The study is performed on a number of different crossing geometries and preliminary results show that the CHARMED model is the most comprehensive approach

Flow and thermal transport in additively manufactured metal lattices based on novel unit-cell topologies

The emergence of metal Additive Manufacturing (AM) over the last two decades has opened venues to mitigate the challenges associated with stochastic open-cell metal foams manufactured through the traditional foaming process. Regular lattices with user-defined unit cell topologies have been reported to exhibit better mechanical properties in comparison to metal foams which extend their applicability to multifunctional heat exchangers subjected to both thermal and mechanical loads. The current study aims at investigating the thermal-hydraulic characteristics of promising novel unit cell topologies realizable through AM technologies. Experimental investigation was conducted on four different topologies, viz (a) Octet, (b) Face-diagonal (FD) cube, (c) Tetrakaidecahedron, and (d) Cube, printed in single-cell thick sandwich type configuration in 420 stainless steel via Binder Jetting technology at same intended porosity. The effective thermal conductivity of the samples was found to be strongly dependent on the lattice porosity, however, no significant dependence on the unit-cell topology was demonstrated. Face-diagonal cube lattice exhibited the highest heat transfer coefficient and pressure drop, and consequently provided the lowest thermal-hydraulic performance. A procedure to incorporate the manufacturing-induced random roughness effects in the samples during numerical modelling is introduced. The numerical simulations were conducted on samples exhibiting the roughness profiles having statistically same mean roughness as the additively manufactured coupons and the results were compared to that obtained from the intended smooth-profiled CAD models that were fed into the printing machines. The analysis showed that inclusion of roughness effects in computational models can significantly improve the thermal performance predictions. Through this study, we demonstrate that additively manufactured ordered lattices exhibit superior thermal transport characteristics and future developmental efforts would require extensive experimentations to characterize their thermal and flow performance as well as local surface quality and AM-induced defect recognition. Experimental findings would also need to be supported by computational efforts where configurations which closely mimic the real AM parts could be modeled. A combined experimental-numerical framework is recommended for advancements in metal additive manufacturing-enabled enhanced heat transfer concepts