<p>Optical coherence tomography (OCT) is a non-invasive optical imaging modality that provides micron-scale resolution of tissue micro-structure over depth ranges of several millimeters. This imaging technique has had a profound effect on the field of ophthalmology, wherein it has become the standard of care for the diagnosis of many retinal pathologies. Applications of OCT in the anterior eye, as well as for imaging of coronary arteries and the gastro-intestinal tract, have also shown promise, but have not yet achieved widespread clinical use.</p><p>The usable imaging depth of OCT systems is most often limited by one of three factors: optical attenuation, inherent imaging range, or depth-of-focus. The first of these, optical attenuation, stems from the limitation that OCT only detects singly-scattered light. Thus, beyond a certain penetration depth into turbid media, essentially all of the incident light will have been multiply scattered, and can no longer be used for OCT imaging. For many applications (especially retinal imaging), optical attenuation is the most restrictive of the three imaging depth limitations. However, for some applications, especially anterior segment, cardiovascular (catheter-based) and GI (endoscopic) imaging, the usable imaging depth is often not limited by optical attenuation, but rather by the inherent imaging depth of the OCT systems. This inherent imaging depth, which is specific to only Fourier Domain OCT, arises due to two factors: sensitivity fall-off and the complex conjugate ambiguity. Finally, due to the trade-off between lateral resolution and axial depth-of-focus inherent in diffractive optical systems, additional depth limitations sometimes arises in either high lateral resolution or extended depth OCT imaging systems. The depth-of-focus limitation is most apparent in applications such as adaptive optics (AO-) OCT imaging of the retina, and extended depth imaging of the ocular anterior segment.</p><p>In this dissertation, techniques for extending the imaging range of OCT systems are developed. These techniques include the use of a high spectral purity swept source laser in a full-field OCT system, as well as the use of a peculiar phenomenon known as coherence revival to resolve the complex conjugate ambiguity in swept source OCT. In addition, a technique for extending the depth of focus of OCT systems by using a polarization-encoded, dual-focus sample arm is demonstrated. Along the way, other related advances are also presented, including the development of techniques to reduce crosstalk and speckle artifacts in full-field OCT, and the use of fast optical switches to increase the imaging speed of certain low-duty cycle swept source OCT systems. Finally, the clinical utility of these techniques is demonstrated by combining them to demonstrate high-speed, high resolution, extended-depth imaging of both the anterior and posterior eye simultaneously and in vivo.</p> / Dissertation

Articular cartilage provides a low-friction surface during normal joint motion and distributes forces to the underlying bone. The extracellular matrix (ECM) composition of healthy cartilage has previously been shown to be an excellent predictor of its mechanical properties. Changes in ECM composition and loss of mechanical function are known to occur with degenerative conditions such as osteoarthritis. Identifying differences in the composition-function relationships of cartilage under different anabolic, catabolic, and homeostatic conditions may thus be a useful approach for identifying factors (e.g. ECM content, distribution, and structure) which are critical to mechanical function. In addition, diagnostic tools capable of monitoring changes in the cartilage ECM may increase our understanding of the effects of ECM changes on composition-functions relationships. The goals of this work were to investigate composition-function relationships in healthy, degraded, and engineered cartilage and to develop a microcomputed tomography-based approach to analyze changes in matrix composition and morphology in articular cartilage. In healthy explants, compressive and shear properties were dependent on both sGAG and collagen content. In contrast, the compressive properties of IL-1stimulated cartilage were dependent on sGAG but not collagen content. To assess changes in sGAG content, EPIC-microcomputed tomography, a 3D contrast-enhanced microcomputed tomography technique was developed. EPIC-microcomputed tomography attenuation was found to be an excellent predictor of sGAG content in IL-1-stimulated cartilage explants and engineered cartilage. In addition, analytical approaches were developed to use EPIC-microcomputed tomography for the in situ analysis of cartilage morphology. EPIC-microcomputed tomography was also used to analyze spatial differences in sGAG accumulation in bilayer engineered cartilage for comparison with the local strain profile. This work underscores the significance of ECM composition and structure in regulating cartilage mechanical properties and validates the use of EPIC-microcomputed tomography as a diagnostic for monitoring sGAG content and potentially for assessing mechanical function in models of degeneration and regeneration.

published_or_final_version / Medicine / Master / Doctor of Medicine

The work covered in this thesis deals with the problem of automatically registering 3D images acquired from different medical imaging modalities. The approach taken is to develop generic measures of image registration derived from the co-occurence of values in the two images. The development of statistical alignment measures is reviewed. The registration problem is then expressed in terms of entropy and developed using tools from information theory. The problem of the optimization of the registration process in the different types of algorithms is identified as important and the power of Genetic Algorithms is applied. The application of image registration techniques, implemented during this thesis, in complex situations is evaluated. The cases of patients with brain ischemia and brain tumour residual disease are elaborated. This is accomplished with the formation of Groupwares where the tacit knowledge, owned by the individual specialists that take part in the collaboration, is exposed and made explicit in the process of the evaluation of the findings, provided by the fused images. This is performed in a high performance computer network that has been developed between the Department of Medicine and the University Hospital. / Η παρούσα εργασία ασχολείται με το πρόβλημα της αυτοματοποιημένης προσαρμογής και σύντηξης τρισδιάστατων απεικονίσεων από διαφορετικές ιατρικές απεικονιστικές μεθοδολογίες.

In many medical imaging modalities, as photons travel from the emission source to the detector, they are scattered by the biological tissue. Often this scatter is viewed as a phenomenon that degrades image quality, and most research is focused on designing methods for either discarding the scattered photons or correcting for scatter. However, the scattered photons also carry information about the tissue that they pass through, which can perhaps be extracted. In this research, we investigate methods to retrieve information from the scattered photons in two specific medical imaging modalities: diffuse optical tomography (DOT) and single photon emission computed tomography (SPECT). To model the scattering of photons in biological tissue, we investigate using the Neumann-series form of the radiative transport equation (RTE). Since the scattering phenomenon are different in DOT and SPECT, the models are individually designed for each modality. In the DOT study, we use the developed photon-propagation model to investigate signal detectability in tissue. To study this detectability, we demonstrate the application of a surrogate figure of merit, based on Fisher information, which approximates the Bayesian ideal observer performance. In the SPECT study, our aim is to determine if only the SPECT emission data acquired in list-mode (LM) format, including the scattered-photon data, can be used to compute the tissue-attenuation map. We first propose a path-based formalism to process scattered photon data, and follow it with deriving expressions for the Fisher information that help determine the information content of LM data. We then derive a maximum-likelihood expectation-maximization algorithm that can jointly reconstruct the activity and attenuation map using LM SPECT emission data. While the DOT study can provide a boost in transition of DOT to clinical imaging, the SPECT study will provide insights on whether it is worth exposing the patient to extra X-ray radiation dose in order to obtain an attenuation map. Finally, although the RTE can be used to model light propagation in tissues, it is computationally intensive and therefore time consuming. To increase the speed of computation in the DOT study, we develop software to implement the RTE on parallel computing architectures, specifically the NVIDIA graphics processing units (GPUs).

X-Ray Diffraction Contrast Tomography (DCT) is a recently developed, non-destructive synchrotron imaging technique which characterizes microstructure and grain orientation in polycrystalline materials in three dimensions (3D). By combining it with propagation based phase contrast tomography (PCT) it is for the first lime possible to observe in situ the 3D propagation behavior of short fatigue cracks (SFCs) within a set of fully characterized grains (orientation and shape). The combined approach, termed 3D X-ray Tomography of short cracks and Microstructure (3DXTSM), has been developed on the metastable beta titanium alloy "Beta21S". A large part of this work deals with the development of the 3DXTSM methodology. In the combined dataset, each point on the 3D fracture surface can be associated with a multidimensional data structure containing variables describing the grain orientation, the local fracture surface normal and the propagation history. The method uses a surface mesh composed of triangles that describes the crack (in other words: the fracture surface) in the last propagation state measured. Grain orientations, crack fronts, local growth rates and grain boundaries can be visualized by assigning colors to this mesh. The data structure can be interrogated in a number of different ways. Tools for extracting pole figures and pole density distribution functions have been implemented. An algorithm was developed that is capable of measuring the 3D local growth rate of a crack containing branches. The accuracy of the grain boundaries as reconstructed with OCT was evaluated and the elastic constants of Beta21S were determined.

No description available.

X-ray scatter in cone-beam computed tomography (CBCT) is known to reduce image quality by introducing image artifacts, reducing contrast, and limiting computed tomography (CT) number accuracy. The extent of the effect of x-ray scatter on CBCT image quality is determined by the shape and magnitude of the scatter distribution in the projections. A method to allay the effects of scatter is imperative to enable application of CBCT to solve a wider domain of clinical problems. The work contained herein proposes such a method. A characterization of the scatter distribution through the use of a validated Monte Carlo (MC) model is carried out. The effects of imaging parameters and compensators on the scatter distribution are investigated. The spectral frequency components of the scatter distribution in CBCT projection sets are analyzed using Fourier analysis and found to reside predominately in the low frequency domain. The exact frequency extents of the scatter distribution are explored for different imaging configurations and patient geometries. Based on the Fourier analysis it is hypothesized the scatter distribution can be represented by a finite sum of sine and cosine functions. The fitting of MC scatter distribution estimates enables the reduction of the MC computation time by diminishing the number of photon tracks required by over three orders of magnitude. The fitting method is incorporated into a novel scatter correction method using an algorithm that simultaneously combines multiple MC scatter simulations. Running concurrent MC simulations while simultaneously fitting the results allows for the physical accuracy and flexibility of MC methods to be maintained while enhancing the overall efficiency. CBCT projection set scatter estimates, using the algorithm, are computed on the order of 1-2 minutes instead of hours or days. Resulting scatter corrected reconstructions show a reduction in artifacts and improvement in tissue contrast and voxel value accuracy.

X-ray scatter in cone-beam computed tomography (CBCT) is known to reduce image quality by introducing image artifacts, reducing contrast, and limiting computed tomography (CT) number accuracy. The extent of the effect of x-ray scatter on CBCT image quality is determined by the shape and magnitude of the scatter distribution in the projections. A method to allay the effects of scatter is imperative to enable application of CBCT to solve a wider domain of clinical problems. The work contained herein proposes such a method. A characterization of the scatter distribution through the use of a validated Monte Carlo (MC) model is carried out. The effects of imaging parameters and compensators on the scatter distribution are investigated. The spectral frequency components of the scatter distribution in CBCT projection sets are analyzed using Fourier analysis and found to reside predominately in the low frequency domain. The exact frequency extents of the scatter distribution are explored for different imaging configurations and patient geometries. Based on the Fourier analysis it is hypothesized the scatter distribution can be represented by a finite sum of sine and cosine functions. The fitting of MC scatter distribution estimates enables the reduction of the MC computation time by diminishing the number of photon tracks required by over three orders of magnitude. The fitting method is incorporated into a novel scatter correction method using an algorithm that simultaneously combines multiple MC scatter simulations. Running concurrent MC simulations while simultaneously fitting the results allows for the physical accuracy and flexibility of MC methods to be maintained while enhancing the overall efficiency. CBCT projection set scatter estimates, using the algorithm, are computed on the order of 1-2 minutes instead of hours or days. Resulting scatter corrected reconstructions show a reduction in artifacts and improvement in tissue contrast and voxel value accuracy.

The understanding of multiphase flow properties is essential for the exploitation of hydrocarbon reserves in a reservoir; these properties in turn are dependent on the geometric properties and connectivity of the pore space. The determination of the pore size distribution in carbonate reservoirs remains challenging; carbonates exhibit complex pore structures comprising length scales from nanometers to several centimeters. A major challenge to the accurate evaluation of these reservoirs is accounting for pore scale heterogeneity on multiple scales. This is the topic of this thesis. Conventionally, this micron scale information is achieved either by building stochastic models using 2D images or by combining log and laboratory data to classify pore types and their behaviour. None of these capture the true 3D connectivity vital for flow characterisation. We present here an approach to build realistic 3D network models across a range of scales to improve property estimation through employment of X-ray micro-Computed Tomography (μCT) and Focussed Ion Beam Tomography (FIBT). The submicron, or microporous, regions are delineated through a differential imaging technique undertaken on x-ray CT providing a qualitative description of microporosity. Various 3-Phase segmentation methods are then applied for quantitative characterisation of those regions utilising the attenuation coefficient values from the 3D tomographic images. X-ray micro-CT is resolution limited and can not resolve the detailed geometrical features of the submicron pores. FIB tomography is used to image the 3D pore structure of submicron pores down to a scale of tens of nanometers. We describe the experimental development and subsequent image processing including issues and difficulties resolved at various stages. The developed methodology is implemented on cores from producing wackstone and grainstone reservoirs. Pore network models are generated to characterise the 3D interconnectivity of pores. We perform the simulations of petrophysical properties (permeability and formation resistivity) directly on the submicron scale image data. Simulated drainage capillary pressure curves are matched with the experimental data. We also present some preliminary results for the integration of multiscale pore information to build dual-scale network models. The integration of multiscale data allows one to select appropriate effective medium theories to incorporate sub-micron structure into property calculations at macro scale giving a more realistic estimation of properties.