Computational aberration correction in optical coherence tomography with phase-unstable systems

La tomografía de coherence óptica (OCT) es una técnica usada ampliamente en medicina, pero al tratarse de una técnica óptica es susceptible la aberraciones ópticas que degradan la calidad de la imagen, lo que dificulta la visualización de estructuras finas con alta resolución. Este trabajo presenta una técnica computacional para corregir aberraciones en OCT, cuya operación es compatible con muchos tipos de sistemas estandarés, y se muestran resultados en imagen del ojo, la via area y la piel.Optical coherence tomography (OCT) is an imaging technique widely use in medicine. OCT is an optical technique, therefore it is prone to optical aberrations that degrade image quality, making it difficult to visualize fine structures with high resolution.This work presents SHARP, a computational technique for correction of aberrations in OCT, that is compatible with most standard systems, and we present results in eye, airway and skin imagin

Multi-resolution Active Models for Image Segmentation

Image segmentation refers to the process of subdividing an image into a set of non-overlapping regions. Image segmentation is a critical and essential step to almost all higher level image processing and pattern recognition approaches, where a good segmentation relieves higher level applications from considering irrelevant and noise data in the image. Image segmentation is also considered as the most challenging image processing step due to several reasons including spatial discontinuity of the region of interest and the absence of a universally accepted criteria for image segmentation. Among the huge number of segmentation approaches, active contour models or simply snakes receive a great attention in the literature. Where the contour/boundary of the region of interest is defined as the set of pixels at which the active contour reaches its equilibrium state. In general, two forces control the movement of the snake inside the image, internal force that prevents the snake from stretching and bending and external force that pulls the snake towards the desired object boundaries. One main limitation of active contour models is their sensitivity to image noise. Specifically, noise sensitivity leads the active contour to fail to properly converge, getting caught on spurious image features, preventing the iterative solver from taking large steps towards the final contour. Additionally, active contour initialization forms another type of limitation. Where, especially in noisy images, the active contour needs to be initialized relatively close to the object of interest, otherwise the active contour will be pulled by other non-real/spurious image features. This dissertation, aiming to improve the active model-based segmentation, introduces two models for building up the external force of the active contour. The first model builds up a scale-based-weighted gradient map from all resolutions of the undecimated wavelet transform, with preference given to coarse gradients over fine gradients. The undecimated wavelet transform, due to its near shift-invariance and the absence of down-sampling properties, produces well-localized gradient maps at all resolutions of the transform. Hence, the proposed final weighted gradient map is able to better drive the snake towards its final equilibrium state. Unlike other multiscale active contour algorithms that define a snake at each level of the hierarchy, our model defines a single snake with the external force field is simultaneously built based on gradient maps from all scales. The second model proposes the incorporation of the directional information, revealed by the dual tree complex wavelet transform (DT CWT), into the external force field of the active contour. At each resolution of the transform, a steerable set of convolution kernels is created and used for external force generation. In the proposed model, the size and the orientation of the kernels depend on the scale of the DT CWT and the local orientation statistics of each pixel. Experimental results using nature, synthetic and Optical Coherent Tomography (OCT) images reflect the superiority of the proposed models over the classical and the state-of-the-art models

X-ray imaging of failure and degradation mechanisms of lithium-ion batteries

Lithium-ion batteries are becoming increasingly energy and power dense, and are required to operate in demanding applications and under challenging conditions. Both safety and performance of lithium-ion batteries need to be improved to meet the needs of the current demand, and are inextricably linked to their microstructure and mechanical design. However, there is little understanding of the complex, multi-length scale, structural dynamics that occur inside cells during operation and failure. From the evolving particle microstructure during operation to the rapid breakdown of active materials during failure, the plethora of dynamic phenomena is not well understood. In this thesis, both ex-situ and operando X-ray imaging, and computed tomography, in combination with image-based modelling and quantification are used to characterise battery materials and components in 3D. Degradation mechanisms are investigated across multiple length-scales, from the electrode particle to the full cell architecture, and direct comparisons between materials in their fresh and failed states are made. Rapid structural evolution that occurs during operation and failure is captured using high-speed synchrotron X-ray imaging, and quantified by correlating sequential tomograms. Consistent degradation mechanisms that occur over fractions of a second are identified and are shown to contribute significantly towards uncontrolled and catastrophic failure, and previously unexplored interplay between the mechanical design of cells and their safety and performance is described. The experiments reported here assess the thermal and mechanical responses of cells to extreme operating and environmental conditions. The interaction between the dynamic architecture of active materials and the mechanical designs of commercial cells are revealed, highlighting the importance of the engineering design of commercial lithium-ion batteries and their efficacy to mitigate failure. These insights are expected to influence the future design of safer and more reliable lithium-ion batteries

X-ray Bragg Projection Ptychography for nano-materials

Progress in nanotechnology critically relies on high resolution probing tools, and X-ray coherent diffraction imaging (CDI) is certainly an attractive method for exploring science at such small scales. Thus, the aim of this PhD is to study structural properties of nano-materials using X-ray CDI, with a special motivation to combine Bragg CDI with ptychography. The former has ability to retrieve the complex density and strain maps of nano-meso crystalline objects, and the latter uses translational diversity to produce quantitative maps of the complex transmission function of non-crystalline objects. As both techniques promote highly sensitive phase-contrast properties, the thesis exploits their agreement to reveal the morphology of domain structures in metallic thin films. Additionally, it is demonstrated that Bragg-ptychography is an evolutionary improvement to probe the structure of ’highly’ strained crystals, with respect to its Bragg-CDI counterpart. However, the adaptation of ptychography to the Bragg geometry is not without difficulties and comes with more experimental cost. Therefore, the effects of experimental uncertainties, e.g., scan positions undetermination, partial coherence, and time-varying probes are assessed throughout the thesis and corrected for by implementation of suitable refinement methods. Furthermore, it is shown how the set-up at beamline 34-ID-C at the Advanced Photon Source, used for the experimental measurements can be optimized for better ptychographical reconstructions

Atomic-scale and three-dimensional transmission electron microscopy of nanoparticle morphology

The burgeoning field of nanotechnology motivates comprehensive elucidation of nanoscale materials. This thesis addresses transmission electron microscope characterisation of nanoparticle morphology, concerning specifically the crystal- lographic status of novel intermetallic GaPd2 nanocatalysts and advancement of electron tomographic methods for high-fidelity three-dimensional analysis. Going beyond preceding analyses, high-resolution annular dark-field imaging is used to verify successful nano-sizing of the intermetallic compound GaPd2. It also reveals catalytically significant and crystallographically intriguing deviations from the bulk crystal structure. So-called ‘non-crystallographic’ five-fold twinned nanoparticles are observed, adding a new perspective in the long standing debate over how such morphologies may be achieved. The morphological complexity of the GaPd2 nanocatalysts, and many cognate nanoparticle systems, demands fully three-dimensional analysis. It is illustrated how image processing techniques applied to electron tomography reconstructions can facilitate more facile and objective quantitative analysis (‘nano-metrology’). However, the fidelity of the analysis is limited ultimately by artefacts in the tomographic reconstruction. Compressed sensing, a new sampling theory, asserts that many signals can be recovered from far fewer measurements than traditional theories dictate are necessary. Compressed sensing is applied here to electron tomographic reconstruction, and is shown to yield far higher fidelity reconstructions than conventional algorithms. Reconstruction from extremely limited data, more robust quantitative analysis and novel three-dimensional imaging are demon- strated, including the first three-dimensional imaging of localised surface plasmon resonances. Many aspects of transmission electron microscopy characterisation may be enhanced using a compressed sensing approach

Inferring structures, free energy differences, and kinetic rates of biological macromolecular assemblies by integrative modeling

Biological macromolecular assemblies play crucial roles in most cellular processes. The determination of their structures, thermodynamics, and kinetics is essential to understand their function, evolution, modulation, and design. Determining such models, however, remains challenging. One particularly powerful approach to constructing models in general is integrative modeling. Integrative modeling aims to maximize the accuracy, precision, and completeness of models, by simultaneously utilizing all available information, including experimental data, physical principles, statistical analyses, and other prior models. The goal of this thesis is to expand the scope of integrative modeling to the inference of spatial, thermodynamic, and kinetic aspects of macromolecular assemblies. In Chapter I, I introduce the integrative modeling framework for spatiotemporal modeling of biological macromolecular assemblies. In Chapter II, I demonstrate how the synergy between multi-chemistry cross-linking mass spectrometry and integrative modeling can map the structural dynamics of macromolecular assemblies, by application to the human Cop9 signalosome complex. In Chapter III, I present a method for determining structures, free energy differences, and kinetic rates of macromolecular assemblies along their functional cycle, mainly from negative stain electron microscopy (EM). We apply the method to the yeast Hsp90 to estimate the free energy differences and kinetic parameters along its nucleotide hydrolysis cycle, which includes open and closed states of Hsp90. In Chapter IV, I describe a validation of stochastic sampling in integrative modeling. The remaining chapters describe applications of integrative modeling to assemblies of various sizes and scales, using various sources of information, thus illustrating the flexibility of the integrative modeling approach. Specifically, I apply integrative modeling to the human ECM29-Proteasome assembly under oxidative stress (Chapter V), the yeast nuclear pore complex (NPC) cytoplasmic mRNA export platform (Chapter VI), the major membrane ring component of the yeast NPC (Chapter VII), the entire yeast NPC (Chapter VIII), and the reconstruction of 3D structures of MET antibodies (Chapter IX)

Microscopy Conference 2017 (MC 2017) - Proceedings

Das Dokument enthält die Kurzfassungen der Beiträge aller Teilnehmer an der Mikroskopiekonferenz "MC 2017", die vom 21. bis 25.08.2017, in Lausanne stattfand