by Lo Kwok Tung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves [71-74]

Yao, Yupei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 58-60). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

Current methods for assessing the health of insects and their colonies are carried out by researchers making dissections on individual insects (which inevitably kills them) or making visual inspections of colonies and then documenting their observations. For colonies, researchers look for behavioural signs which indicate healthy individuals where foragers are regularly bringing in resources or in weak colonies, where there are fewer foragers working with a more lethargic and less purposeful manner. These methods are prone to large errors and they kill many insects in the process. The research detailed in this thesis addresses the subjective and destructive nature of these methods. This thesis also describes new methods using x-ray CT to develop and adopt protocols to accurately study insects non-invasively. Chapter one covers the current literature on tomography and some background on the different CT methods. Chapter two gives a thorough description of the new methods being developed to study insects non-invasively and details techniques that can be adopted by researchers who require non-invasive approaches to their work. Chapter three describes in detail three examples of research that has been conducted on locusts, ladybirds and butterflies to non-invasively study aspects of their morphology. The methods described maintain the integrity of the specimens for future use if so required. Chapter four covers a specific example of a fine detail study on plasticity of the honeybee brain using X-ray MicroCT and discusses the potential for live scanning to observe brain plasticity in insects. Chapter five extends the work from chapter two to show the usefulness of CT for studying insect behaviour by documenting and describing previously unreported honeybee storage behaviour. Chapter six draws conclusions from the other chapters and discusses future research.

MEMS technology has led to the development of new uncooled infrared imaging detectors. One type of these MEMS detectors consist of arrays of bi-metallic photomechanical pixels that tilt as a function of temperature associated with infrared radiation from the scene. The main advantage of these detectors is the optical readout system that measures the tilt of the beams based on the intensity of the reflected light. This removes the need for electronic readout at each of the sensing elements and reduces the fabrication cost and complexity of sensor design, as well as eliminates the electronic noise at the detector. The optical readout accuracy is sensitive to the uniformity of individual pixels on the array. The hypothesis of the present research is that direct measurements of the height change corresponding to tilt through holographic interferometry will reduce the need for high pixel uniformity. Measurements of displacements for a vacuum packaged detector with nominal responsivity of 2.4nm/K are made with a Linnik interferometer employing the four phase step technique. The interferometer can measure real-time, full-field height variations across the array. In double-exposure mode, the current height map is subtracted from a reference image so that the change in deflection is measured. A software algorithm locates each mirror on the array, extracts the measured deflection at the tip of a mirror, and uses that measurement to form a pixel of a thermogram in real-time. A blackbody target projector with temperature controllable to 0.001K is used to test the thermal resolution of the imaging system. The achieved minimum temperature resolution is better than 0.25K. The double exposure technique removes mirror non-uniformity as a source of noise. A lower than nominal measured responsivity of around 1.5nm/K combined with noise from the measurements made with the interferometric optical readout system limit the potential minimum temperature resolution. Improvements need to be made both in the holographic setup and in the MEMS detector to achieve the target temperature resolution of 0.10K.

<p> <b>INTRODUCTION:</b> Accurate body composition assessment is crucial for determining health consequences due to excess body fat (BF). While several techniques exist there are few that are accurate, non-invasive, fast, and comfortable for subjects. The Three Dimensional (3D) body scanner is a new body composition assessment method that might serve as another option for investigators and practitioners. The purpose of this study was to determine the accuracy of the 3D body scanner at measuring body composition using dual energy x-ray absorptiometry (DXA) and Air displacement plethysmography (Bod Pod) as criterion measures. The 3D body scanner was evaluated on its ability to work with differences in normal versus overweight subjects as determined by BMI. Also, a new prediction equation was created and compared to that of an existing equation used by the 3D body scanner developed by the Department of Defense (DoD).</p><p> <b>METHODS:</b> Eighty-Five male subjects (21.70 &plusmn; 2.28 yr old; 81.00 &plusmn; 12.21 kg; 25.37 &plusmn; 3.40 kg/m²) completed all body composition assessment techniques on the same day. Tests preformed included: DXA, Bod Pod, and 3D body scanning. Subjects did not eat or drink 2 hr previous to testing and did not exercise 4 hr previous to testing. Data was analyzed using SPSS version 17.0. Bland-Altmand plots, Pearson correlations, and a oneway ANOVA comparing means were performed. A prediction equation (3D MU) was created using a stepwise regression based on correlation to DXA.</p><p> <b>RESULTS:</b> Mean comparison of body composition techniques were as follows: DXA BF 16.30 &plusmn; 4.67; Bod Pod 12.17&plusmn; 7.19; DoD 13.53 &plusmn; 6.43; 3D MU 16.49 &plusmn; 4.16. 3D MU had a SEE=3.09 over the entire sample compared to DoD SEE=3.67 and Bod Pod SEE=2.45. Although body volumes of Bod Pod and 3D Scanner were highly correlated (r = 0.984; p =0.001), the 3D Scanner underestimated body volume. Improvement in making consistent estimations of head, hand, and feet are necessary for the 3D body scanner to be used for body composition assessment.</p><p> <b>CONCLUSION:</b> Although the 3D body scanner shows promise as a method of evaluating BF, more work is needed before it can be considered an acceptable laboratory method of assessment. A 3D MU prediction equation was created that appears to be more accurate for young men than the current DoD equation. 3D body scanning shows potential as a method for determining body composition in overweight subjects.</p><p>

<p> Duchenne&rsquo;s Muscular Dystrophy is a debilitating disease that affects skeletal and cardiac muscle of 1 in 5000 male births. In the last thirty years, the gene responsible for the encoding of Dystrophin has been identified, sequenced and the variations of mutations described. There remains a void in the successful treatment of the disease although corticosteroid use has proven useful in delaying progression. Novel therapies are produced in the categories of virus-mediated gene delivery and stem cells, but evaluating their efficacy is hindered by an inability to contemporaneously assess the changes in muscle. The purpose of this pilot study was to characterize the changes in skeletal and cardiac muscle in a clinically advanced population of dogs affected with Duchenne Muscular Dystrophy. Using traditional sequences, delayed gadolinium enhancement, novel sequences and spectroscopy, changes in the investigated muscle were characterized. By establishing the differences between affected and unaffected dogs, the long-term goal of this body of work is to characterize these changes longitudinally and design a non-invasive method for tissue assessment as novel treatments are trialed.</p><p>

<p> Visual knowledge plays an important role in many highly skilled applications, such as medical diagnosis, geospatial image analysis and pathology diagnosis. Medical practitioners are able to interpret and reason about diagnostic images based on not only primitive-level image features such as color, texture, and spatial distribution but also their experience and tacit knowledge which are seldom articulated explicitly. This reasoning process is dynamic and closely related to real-time human cognition. Due to a lack of visual knowledge management and sharing tools, it is difficult to capture and transfer such tacit and hard-won expertise to novices. Moreover, many mission-critical applications require the ability to process such tacit visual knowledge in real time. Precisely how to index this visual knowledge computationally and systematically still poses a challenge to the computing community.</p><p> My dissertation research results in novel computational approaches for highthroughput visual knowledge analysis and retrieval from large-scale databases using latest technologies in big data ecosystems. To provide a better understanding of visual reasoning, human gaze patterns are qualitatively measured spatially and temporally to model observers&rsquo; cognitive process. These gaze patterns are then indexed in a NoSQL distributed database as a visual knowledge repository, which is accessed using various unique retrieval methods developed through this dissertation work. To provide meaningful retrievals in real time, deep-learning methods for automatic annotation of visual activities and streaming similarity comparisons are developed under a gaze-streaming framework using Apache Spark. </p><p> This research has several potential applications that offer a broader impact among the scientific community and in the practical world. First, the proposed framework can be adapted for different domains, such as fine arts, life sciences, etc. with minimal effort to capture human reasoning processes. Second, with its real-time visual knowledge search function, this framework can be used for training novices in the interpretation of domain images, by helping them learn experts&rsquo; reasoning processes. Third, by helping researchers to understand human visual reasoning, it may shed light on human semantics modeling. Finally, integrating reasoning process with multimedia data, future retrieval of media could embed human perceptual reasoning for database search beyond traditional content-based media retrievals.</p><p>

Diagnosing the severity of blunt trauma injuries is difficult and involves the use of diagnostic radiological scanning. The primary diagnostic radiology modality used for assessing these injuries is computed tomography (CT). CT delivers more radiation dose than other diagnostic scanning modalities. Trauma patients are at an increased risk of radiation induced cancer because of the cumulative dose effects from multiple scanning procedures. Current methods for estimating effective dose, the quantity used to describe the whole body health detriment from radiation, involves the use of published conversion coefficients and procedure specific machine parameters such as dose-length-product based on computed tomography dose index and scan length. Other methods include the use of Monte Carlo simulations based upon the specific machine geometry and radiation source. Unless the requisite machine information is known, the only means of estimating the effective dose is through the use of generic estimates that are published by scientific radiation committees and have a wide range of values. This research addressed a knowledge gap in assigning effective doses from computed tomography when machine parameters knowledge is either unknown or incomplete. The research involved the development of a new method of estimating the effective dose from CT through the use of regression models incorporating the use of patient parameters as opposed to machine specific parameters. This new method was experimentally verified using two adult anthropomorphic phantoms and optically stimulated luminescent dosimeters. The new method was then compared against a real patient population undergoing similar computed tomography scanning procedures. Utilizing statistical procedures, the new method was tested for repeatability and bias against the current conversion coefficient method. The analysis of the new method verifies that the estimation ability is similar to recent research indicating that the older conversion coefficient methods can underestimate the effective dose to the patient by up to 40%. The new method can be used as a retrospective tool for effective dose estimation from CT trauma protocols for a patient population with physical characteristics similar to the U.S. Army Soldier population.

Laminar optical tomography (LOT) is an optical imaging technique capable of making depth-resolved measurements of absorption and fluorescence contrast in scattering tissue. LOT was first demonstrated in 2004 by Hillman et al [1]. The technique combines a non-contact laser scanning geometry, similar to a low magnification confocal microscope, with the imaging principles of diffuse optical tomography (DOT). This thesis describes the development and application of a second generation LOT system, which acquires both fluorescence and multi-wavelength measurements simultaneously and is better suited for in vivo measurements. Chapter 1 begins by reviewing the interactions of light with tissue that form the foundation of optical imaging. A range of related optical imaging techniques and the basic principles of LOT imaging are then described. In Chapter 2, the development of the new LOT imaging system is described including the implementation of a series of interfaces to allow clinical imaging. System performance is then evaluated on a range of imaging phantoms. Chapter 3 describes two in vivo imaging applications explored using the second generation LOT system, first in a clinical setting where skin lesions were imaged, and then in a laboratory setting where LOT imaging was performed on exposed rat cortex. The final chapter provides a brief summary and describes future directions for LOT. LOT has the potential to find applications in medical diagnostics, surgical guidance, and in-situ monitoring owing to its sensitivity to absorption and fluorescence contrast as well as its ability to provide depth sensitive measures. Optical techniques can characterize blood volume and oxygenation, two important biological parameters, through measurements at different wavelengths. Fluorescence measurements, either from autofluorescence or fluorescent dyes, have shown promise for identifying and analyzing lesions in various epithelial tissues including skin [2, 3], colon [4], esophagus [5, 6], oral mucosa [7, 8], and cervix [9]. The desire to capture these types of measurements with LOT motivated much of the work presented here.

This thesis explores two mathematical routes that make the transition from some severely ill-posed parameter reconstruction problems to better-posed versions of them. The general introduction starts by defining what we mean by an inverse problem and its theoretical analysis. We then provide motivations that come from the field of medical imaging. The first part consists in the analysis of an inverse problem involving the Boltzmann transport equation, with applications in Optical Tomography. There we investigate the reconstruction of the spatially-dependent part of the scattering kernel, from knowledge of angularly averaged outgoing traces of transport solutions and isotropic boundary sources. We study this problem in the stationary regime first, then in the time-harmonic regime. In particular we show, using techniques from functional analysis and stationary phase, that this inverse problem is severely ill-posed in the former setting, whereas it is mildly ill-posed in the latter. In this case, we deduce that making the measurements depend on modulation frequency allows to improve the stability of reconstructions. In the second part, we investigate the inverse problem of reconstructing a tensor-valued conductivity (or diffusion) coefficient in a second-order elliptic partial differential equation, from knowledge of internal measurements of power density type. This problem finds applications in the medical imaging modalities of Electrical Impedance Tomography and Optical Tomography, and the fact that one considers power densities is justified in practice by assuming a coupling of this physical model with ultrasound waves, a coupling assumption that is characteristic of so-called hybrid medical imaging methods. Starting from the famous Calderon's problem (i.e. the same parameter reconstruction problem from knowledge of boundary fluxes of solutions), and recalling its lack of injectivity and severe instability, we show how going from Dirichlet-to-Neumann data to considering the power density operator leads to reconstruction of the full conductivity tensor via explicit inversion formulas. Moreover, such reconstruction algorithms only require the loss of either zero or one derivative from the power density functionals to the unknown, depending on what part of the tensor one wants to reconstruct. The inversion formulas are worked out with the help of linear algebra and differential geometry, in particular calculus with the Euclidean connection. The practical pay-off of such theoretical improvements in injectivity and stability is twofold: (i) the lack of injectivity of Calderà³n's problem, no longer existing when using power density measurements, implies that future medical imaging modalities such as hybrid methods may make anisotropic properties of human tissues more accessible; (ii) the improvements in stability for both problems in transport and conductivity may yield practical improvements in the resolution of images of the reconstructed coefficients.