Digital Morphometry : A Taxonomy Of Morphological Filters And Feature Parameters With Application To Alzheimer\u27s Disease Research

In this thesis the expression digital morphometry collectively describes all those procedures used to obtain quantitative measurements of objects within a two-dimensional digital image. Quantitative measurement is a two-step process: the application of geometrical transformations to extract the features of interest, and then the actual measurement of these features. With regard to the first step the morphological filters of mathematical morphology provide a wealth of suitable geometric transfomations. Traditional radiometric and spatial enhancement techniques provide an additional source of transformations. The second step is more classical (e.g. Underwood, 1970; Bookstein, 1978; and Weibull, 1980); yet here again mathematical morphology is applicable - morphologically derived feature parameters. This thesis focuses on mathematical morphology for digital morphometry. In particular it proffers a taxonomy of morphological filters and investigates the morphologically derived feature parameters (Minkowski functionals) for digital images sampled on a square grid. As originally conceived by Georges Matheron, mathematical morphology concerns the analysis of binary images by means of probing with structuring elements [typically convex geometric shapes] (Dougherty, 1993, preface). Since its inception the theory has been extended to grey-level images and most recently to complete lattices. It is within the very general framework of the complete lattice that the taxonomy of morphological filters is presented. Examples are provided to help illustrate the behaviour of each type of filter. This thesis also introduces DIMPAL (Mehnert, 1994) - a PC-based image processing and analysis language suitable for researching and developing algorithms for a wide range of image processing applications. Though DIMPAL was used to produce the majority of the images in this thesis it was principally written to provide an environment in which to investigate the application of mathematical morphology to Alzheimer\u27s disease research. Alzheimer\u27s disease is a form of progressive dementia associated with the degeneration of the brain. It is the commonest type of dementia and probably accounts for half the dementia of old age (Forsythe, 1990, p. 21 ). Post mortem examination of the brain reveals the presence of characteristic neuropathologic lesions; namely neuritic plaques and neurofibrillary tangles. They occur predominantly in the cerebral cortex and hippocampus. Quantitative studies of the distribution of plaques and tangles in normally aged and Alzheimer brains are hampered by the enormous amount of time and effort required to count and measure these lesions. Here in a morphological algorithm is proposed for the automatic segmentation and measurement of neuritic plaques from light micrographs of post mortem brain tissue

Morphological erosions and openings: fast algorithms based on anchors

Several efficient algorithms for computing erosions and openings have been proposed recently. They improve on VAN HERK's algorithm in terms of number of comparisons for large structuring elements. In this paper we introduce a theoretical framework of anchors that aims at a better understanding of the process involved in the computation of erosions and openings. It is shown that the knowledge of opening anchors of a signal f is sufficient to perform both the erosion and the opening of f. Then we propose an algorithm for one-dimensional erosions and openings which exploits opening anchors. This algorithm improves on the fastest algorithms available in literature by approximately 30% in terms of computation speed, for a range of structuring element sizes and image content

Biomass-derived carbon materials for energy storage applications

Energy storage systems are an essential link in the implementation of renewable energies and in the development of electric vehicles, which are needed to reduce our dependence on fossil fuels and the emission of greenhouse gases. Various technologies have been proposed for energy storage based on different working principles, including lithium-ion batteries, emerging sodium-ion batteries and electric-double layer capacitors. Besides the quest for improving key aspects such as energy and power densities, current research efforts are devoted to foster the manufacturing of more environmentally friendly devices using sustainable materials. Carbon-based electrodes hold considerable promise in such terms due to their low cost, tailorable morphology and microstructure, and the possibility of processing them by direct carbonization of eco-friendly and naturally-available biomass resources. The main goal of this thesis is to develop carbon materials from biomass resources and study their applications as electrode for lithium-ion batteries, sodium-ion batteries and electric-double layer capacitors. En route towards that goal, it also aims at expanding our understanding of the microstructural changes of biomass-derived carbons with varying processing conditions and their effect on the electrochemical performance for each of these technologies. The first part of this work reports on the synthesis of graphitized carbon materials from biomass resources by means of an Fe catalyst, and the study of their electrochemical performance as anode materials for lithium-ion batteries (LIBs). Peak carbonization temperatures between 850 °C and 2000 ºC were covered to study the effect of crystallinity, surface and microstructural parameters on the anodic behavior, focusing on the first-cycle Coulombic efficiency, reversible specific capacity and rate performance. Reversible capacities of Fe-catalyzed biomass-derived carbons were compared to non-catalyzed hard carbon and soft carbons materials heated up to 2800 ºC. Moreover, in-situ characterization experiments were carried out to advance our understanding of the mechanisms responsible for catalytic graphitization. The second part of this work reports a comprehensive study on the structural evolution of hard carbons from biomass resources as a function of carbonization temperature (800 - 2000 ºC), and its correlation with electrochemical properties as anode materials for sodium-ion batteries (SIBs). Synchrotron X-ray total scattering experiments were performed and the associated atomic pair distribution function (PDF) extracted from the data to access quantitative information on local atomic arrangement in these amorphous materials at the nanoscale, as well as its evolution with increasing processing temperature. Then, electrochemical properties and the storage mechanisms involved on Na ions insertion into hard carbon structures at each characteristic potential regions were elucidated and correlated with microstructural properties. Finally, the third part of this work reports on the synthesis of nanostructured porous graphene-like materials from biomass resources using an explosion-assisted activation strategy by nitrate compounds and Ni as a graphitization catalyst. The thermal behavior during carbonization as well as the resulting microstructural and surface properties were evaluated at two different processing temperatures, 300 and 1000 ºC. Finally, their application as electrode materials for electric-double layer capacitors (EDLCs) and LIBs is investigated, with a view to their performance under high charge/discharge specific current densities experiments.Premio Extraordinario de Doctorado U