Electrical impedance tomography (EIT) is a technique in which images representing the cross-sectional distribution of electrical impedance within a threedimensional object are reconstructed from measurements on the object surface. In this work, some developments of image reconstruction algorithms aimed at increasing the value of this technique in the field of medical diagnosis are studied. The electrical properties of biological tissue and the possibilities for medical applications of EIT are first reviewed. The physical and mathematical basis for EIT is then. examined with particular regard for the assumptions required. Following a review of published work on image reconstruction methods, a set of specifications thought useful to advance the utility of EIT as a clinical imaging modality is proposed, together with an approach to image reconstruction designed to fulfil these specifications. A series of computer simulations of the image reconstruction problem is then used to investigate the performance of this reconstruction approach on simple, known, impedance distributions, and to develop the method to the stage of a complete reconstruction algorithm. The algorithm is then tested on a series of data sets produced by measurements on a physical phantom, and on a set of measurements made on a volunteer human subject.

A Constrained Optimisation technique is described for the reconstruction of temporal resistivity images. The approach solves the Inverse problem by optimising a cost function under constraints, in the form of normalised boundary potentials. Mathematical models have been developed for two different data collection methods for the chosen criterion. Both of these models express the reconstructed image in terms of one dimensional (I-D) Lagrange multiplier functions. The reconstruction problem becomes one of estimating these 1-D functions from the normalised boundary potentials. These models are based on a cost criterion of the minimisation of the variance between the reconstructed resistivity distribution and the true resistivity distribution. The methods presented In this research extend the algorithms previously developed for X-ray systems. Computational efficiency is enhanced by exploiting the structure of the associated system matrices. The structure of the system matrices was preserved in the Electrical Impedance Tomography (EIT) implementations by applying a weighting due to non-linear current distribution during the backprojection of the Lagrange multiplier functions. In order to obtain the best possible reconstruction it is important to consider the effects of noise in the boundary data. This is achieved by using a fast algorithm which matches the statistics of the error in the approximate inverse of the associated system matrix with the statistics of the noise error in the boundary data. This yields the optimum solution with the available boundary data. Novel approaches have been developed to produce the Lagrange multiplier functions. Two alternative methods are given for the design of VLSI implementations of hardware accelerators to improve computational efficiencies. These accelerators are designed to implement parallel geometries and are modelled using a verification description language to assess their performance capabilities.

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Alzheimer’s disease is the most common form of dementia and is classified as a progressive neurodegenerative disease that impairs memory and cognition. Definitive diagnosis requires access to brain tissue and clinicians rely primarily on behavioural observation. Few specific, reliable, and well-characterized quantitative tools are in development. The accumulation of misfolded amyloid-beta protein in the brain is one of the hallmark pathological features of Alzheimer’s disease. Molecular imaging strategies have focused on measuring the amount of cerebral amyloid-beta. Antibody-mediated molecular imaging of amyloid-beta offers a promising strategy to measure specific types of amyloid-beta pathology in the central nervous system. This work characterizes the attempted translation of 4 anti-amyloid-beta antibodies from histological tools to live animal positron emission tomography imaging contrast agents. Several mass transfer properties of the classical anti-amyloid-beta antibody 6E10 were measured as a function of age in the TgCRND8 mouse model of Alzheimer’s disease. 6E10 was used to extensively label amyloid-beta plaques after direct injection into the cortex of TgCRND8 mice. 6E10 was subsequently covalently modified with poly(ethylene glycol) (PEG) in order to increase the blood concentration and promote higher brain uptake of the compound. PEG-modification of 6E10 enabled differentiation of TgCRND8 mice from wild type control mice using live animal imaging. Three additional antibodies were screened in a similar fashion; two of these antibodies targeted parenchymal amyloid-beta plaques and one targeted vascular amyloid-beta deposits. One of the antibodies that targeted parenchymal amyloid-beta plaques and the antibody that targeted vascular amyloid-beta were used to differentiate between TgCRND8 and wild type control mice using live animal imaging. This work demonstrates the successful use of 3 anti-amyloid-beta antibodies to detect amyloid-beta pathology using non-invasive imaging techniques and presents a credible framework for translating promising antibodies into contrast agents.

Alzheimer’s disease is the most common form of dementia and is classified as a progressive neurodegenerative disease that impairs memory and cognition. Definitive diagnosis requires access to brain tissue and clinicians rely primarily on behavioural observation. Few specific, reliable, and well-characterized quantitative tools are in development. The accumulation of misfolded amyloid-beta protein in the brain is one of the hallmark pathological features of Alzheimer’s disease. Molecular imaging strategies have focused on measuring the amount of cerebral amyloid-beta. Antibody-mediated molecular imaging of amyloid-beta offers a promising strategy to measure specific types of amyloid-beta pathology in the central nervous system. This work characterizes the attempted translation of 4 anti-amyloid-beta antibodies from histological tools to live animal positron emission tomography imaging contrast agents. Several mass transfer properties of the classical anti-amyloid-beta antibody 6E10 were measured as a function of age in the TgCRND8 mouse model of Alzheimer’s disease. 6E10 was used to extensively label amyloid-beta plaques after direct injection into the cortex of TgCRND8 mice. 6E10 was subsequently covalently modified with poly(ethylene glycol) (PEG) in order to increase the blood concentration and promote higher brain uptake of the compound. PEG-modification of 6E10 enabled differentiation of TgCRND8 mice from wild type control mice using live animal imaging. Three additional antibodies were screened in a similar fashion; two of these antibodies targeted parenchymal amyloid-beta plaques and one targeted vascular amyloid-beta deposits. One of the antibodies that targeted parenchymal amyloid-beta plaques and the antibody that targeted vascular amyloid-beta were used to differentiate between TgCRND8 and wild type control mice using live animal imaging. This work demonstrates the successful use of 3 anti-amyloid-beta antibodies to detect amyloid-beta pathology using non-invasive imaging techniques and presents a credible framework for translating promising antibodies into contrast agents.

Thesis (M.S.)--University of Hawaii at Manoa, 2007. / Includes bibliographical references (leaves 50-51). / viii, 51 leaves, bound ill. (some col.) 29 cm

A pose estimation method is proposed for measuring the position and orientation of a biopsy needle. The technique is to be used as a touchless needle guide system for guidance of percutaneous procedures with 4D ultrasound. A pair of uncalibrated, light-weight USB cameras are used as inputs. A database is prepared offline, using both the needle line estimated from camera-captured images and the true needle line recorded from an independent tracking device. A nonparametric learning algorithm determines the best fit model from the database. This model can then be used in real-time to estimate the true position of the needle with inputs from only the camera images. Simulation results confirm the feasibility of the method and show how a small, accurately made database can provide satisfactory results. In a series of tests with cameras, we achieved an average error of 2.4mm in position and 2.61° in orientation. The system is also extended to real ultrasound imaging, as the two miniature cameras capture images of the needle in air and the ultrasound system captures a volume as the needle moves through the workspace. A new database is created with the estimated 3D position of the needle from the ultrasound volume and the 2D position and orientation of the needle calculated from the camera images. This study achieved an average error of 0.94 mm in position and 3.93° in orientation.

Title page, contents and summary only. The complete thesis in print form is available from the University of Adelaide Library. / "In early arthritis, it is important to make a diagnosis before structural damage has occurred, with early disease modifying therapy effective in improving long term outcomes. The first part of this thesis addresses the deficiency in our current knowledge of standardisation and reproducibility of ultrasound (US) findings. Chapter 2 describes a standardised protocol developed for assessing the metacarphphalangeal (MCP) joints and novel measurements of synovial inflammation. Chapter 3 compares early arthritis subjects to a control group, and showed significantly more US synovitis and abnormally increased measurements, with extensor tenosynovitis (ET) and power Doppler (PD_ positivity highly specific to the early arthritis group. Chapter 4 validates HRUS findings in a subset of subjects using MRI as the reference standard..Chapter 5 presents longitudinal data which suggests that clnical swelling and PD positivity at the MCP joints were the most sensitive to change as a reseult of disease-modifying therapy. Chapter 6 validates an US assessment tooldevelopedbadsed on “sentinel joints” whilst factors that may hemp to differentiate subjects with polyarthralgias from those with early RA are identified in chapter 7. The results of this study suggest that early RA needs to be redefined in the light of our US findings. The prognostic value of early US abnormalities will contlinue to be investigated." -- from Abstract. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1317258 / Thesis (Ph.D.) -- University of Adelaide, School of Medicine, 2008

Most EIT machine operates at high frequencies above 10 kHz. Biological systems demonstrate dispersions of electrical impedance characteristics at very low frequencies below 2 kHz due to the presence of membrane surrounding the cells and diffusion polarisation effects. A study was made on the feasibility of the use of low frequencies in a range of 1.12 Hz to 4.55 kHz in EIT. One high frequency of 77.712 kHz similar to that normally used in common EIT was also used as a comparison. The impedance measurements employed a four-terminal method using the BULFIS, an ultra low frequency impedance spectrometer and used conducting and insulating material as the objects/phantoms. The results show that the conductance and capacitance of a metal object disperses at frequency range of 0.1 -10 kHz, which is consistent to the electrical properties of a double layer forming at the metal-electrolyte interface similar to the electrical properties of a membrane. The reconstructed images reveal that at low frequencies the conducting and the insulating bodies were indistinguishable. They appear differently at high frequencies above 4.55 kHz indicating that the use of multi frequency instrumentation in EIT covering the very low frequency range provides information that instrumentation restricted to frequencies above 10 kHz does not supply. While the internal structure of the double layers could not be delineated, the presence of the double layers could be readily detected by the behaviour of the images as the frequency was varied. This has potential for EIT because it might allow the detection of structures from the variation of the images with frequency. This variation with frequency does not occur at the higher frequencies more usually used for EIT.

No description available.