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<p> Image segmentation entails the partitioning of an image domain, usually two or three dimensions, so that each partition or segment has some meaning that is relevant to the application at hand. Accurate image segmentation is a crucial challenge in many disciplines, including medicine, computer vision, and geology. In some applications, heterogeneous pixel intensities; noisy, ill-defined, or diffusive boundaries; and irregular shapes with high variability can make it challenging to meet accuracy requirements. Various segmentation approaches tackle such challenges by casting the segmentation problem as an energy-minimization problem, and solving it using efficient optimization algorithms. These approaches are broadly classified as either region-based or edge (surface)-based depending on the features on which they operate. </p><p> The focus of this dissertation is on the development of a surface-based energy model, the design of efficient formulations of optimization frameworks to incorporate such energy, and the solution of the energy-minimization problem using graph cuts. This dissertation utilizes a set of four papers whose motivation is the efficient extraction of the left atrium wall from the late gadolinium enhancement magnetic resonance imaging (LGE-MRI) image volume. This dissertation utilizes these energy formulations for other applications, including contact lens segmentation in the optical coherence tomography (OCT) data and the extraction of geologic features in seismic data. </p><p> Chapters 2 through 5 (papers 1 through 4) explore building a surface-based image segmentation model by progressively adding components to improve its accuracy and robustness. The first paper defines a parametric search space and its discrete formulation in the form of a multilayer three-dimensional mesh model within which the segmentation takes place. It includes a generative intensity model, and we optimize using a graph formulation of the <i> surface net</i> problem. The second paper proposes a Bayesian framework with a Markov random field (MRF) prior that gives rise to another class of surface nets, which provides better segmentation with smooth boundaries. The third paper presents a maximum a posteriori (MAP)-based surface estimation framework that relies on a generative image model by incorporating global shape priors, in addition to the MRF, within the Bayesian formulation. Thus, the resulting surface not only depends on the learned model of shapes,but also accommodates the test data irregularities through smooth deviations from these priors. Further, the paper proposes a new shape parameter estimation scheme, in closed form, for segmentation as a part of the optimization process. Finally, the fourth paper (under review at the time of this document) presents an extensive analysis of the MAP framework and presents improved mesh generation and generative intensity models. It also performs a thorough analysis of the segmentation results that demonstrates the effectiveness of the proposed method qualitatively, quantitatively, and clinically. </p><p> Chapter 6, consisting of unpublished work, demonstrates the application of an MRF-based Bayesian framework to segment coupled surfaces of contact lenses in optical coherence tomography images. This chapter also shows an application related to the extraction of geological structures in seismic volumes. Due to the large sizes of seismic volume datasets, we also present fast, approximate surface-based energy minimization strategies that achieve better speed-ups and memory consumption.</p>

<p> Amyloid-&beta; (A&beta;) peptide is generated after sequential cleavage of the constitutively expressed amyloid precursor protein (APP) by &gamma; and &beta; secretases, and is recognized as the primary causative agent underlying the neuropathogenesis of Alzheimer&rsquo;sDisease (AD). Once generated, monomeric A&beta; demonstrates a high propensity to aggregate into toxic A&beta; oligomers (A&beta;O) of various sizes, which eventually accumulate in the brain in the form of amyloid plaques. Mutations in either the gene for APP or one or both of its processing genes, presenilin-1 (PS1) and presenilin-2 (PS2) of the secretases complex leading to accumulation of A&beta; and early-onset familial AD. Late onset AD is modulated by mutations in the gene for apolipoprotein E (apo-E), with the isoform apo-E4 leading to an approximate eight-fold increase in risk for AD, and by environmental and life style factors. The Alzheimer&rsquo;s disease process develops over decades, with substantial neurological loss occurring before a clinical diagnosis of dementia can be rendered. A major roadblock to the management of AD is the inability to definitively diagnose AD until post-mortem examination. It is therefore imperative to develop methods that permit safe, early detection and monitoring of disease progression. Magnetic resonance imaging (MRI) is a non-invasive way to detect and monitor AD progression and therapy, but so far MRI contrast has been obtained only using Gd(III) based contrast agents. Fluorene compounds have garnered attention as amyloid imaging agents. Our lab has developed a spin labeled fluorene (SLF) compound that contains a fluorene moiety with known affinity for A&beta; and a pyrroline nitroxyl spin-label moiety. We hypothesized that the SLF compound will specifically coat assemblies of amyloid beta in the brain and, by establishing a boundary of magnetic field inhomogeneity, produce MRI contrast in tissues with elevated levels of the A&beta; peptide. I found that labeling of brain specimens with the SLF compound produces negative contrast in samples from AD model mice whereas no negative contrast is seen in specimens harvested from wild-type mice. Injection of SLF into live mice resulted in good brain penetration, with the compound able to generate contrast 24-hr post injection. (Abstract shortened by ProQuest.)</p>

<p> The proposed project presents a methodology to detect how susceptible or resistant certain bacteria are to an applied antibiotic. This detection is achieved by calculating the area of Zone of Inhibition (ZOI) regions present in the petri dish and comparing the results to the prescribed standards. The ZOI regions are empty areas formed around an antibiotic disc when placed on a petri dish containing a sample of the bacterial culture. Digital image processing techniques are employed to automate the process of ZOI detection. Experimental results show that the proposed project is successful in detecting ZOI regions of various shapes, such as perfectly circular, irregular, and overlapping. The experimental results also show that the accuracy of detection is typically over 95%, and it remains above 90%, even when the image is degraded by additive Gaussian noise.</p><p>

The aim of this project was to compare and evaluate other, non-EPI, diffusion-weighted MRI (DWI) sequences, through imaging experiments, on a phantom and in vivo, (using a 0.95 T system) and computer simulations, and to develop improved DWI methodology which could be implemented on standard hardware. Pulsed gradient spin echo (PGSE) and diffusion-weighted STEAM are slow multiple shot sequences, with measurement times of several minutes. Both sequences are highly sensitive to patient motion, but motion artifact was virtually eliminated using navigator echo phase correction and EGG triggering when diffusion-sensitisation was in the phase-encoding direction. It was demonstrated that both sequences can provide high quality images and allow accurate and straightforward diffusion-coefficient measurement when an imaging time period in the region of 20-30 minutes is available and when diffusion-sensitisation is required in one or two directions. A third direction of diffusion-sensitisation may be feasible if more sophisticated immobilisation or phase correction techniques are employed. A choice between PGSE or STEAM for a given application should take account of the Ti and T2 values of the imaged tissues, since a higher SNR might be provided by STEAM when the T1T2 ratio is high. A diffusion-weighted CE-FAST sequence was implemented with the novel modification of acquisition of a navigator gradient-echo, which was shown to reduce motion artifact when diffusion-sensitisation was in the phase-encoding direction. However, it has been demonstrated by other workers that unknown signal losses due to motion-induced phase incoherence between signal components may remain. The SNR (normalised with respect to the square root of the imaging time) in the phantom and in white matter was similar to that obtained using PGSE, but an advantage of CE- FAST is that it can be performed in a fraction of the measurement time of PGSE. Diffusion-sensitivity was much higher than in other sequences and the diffusion- attenuation was found to agree with an analysis presented in the literature. However, a major disadvantage of the technique, which precludes its use for many DWI applications, is the requirement of accurate knowledge of Ti, T2 and flip angle in order to calculate the diffusion coefficient or tensor. Prior to a study of diffusion-weighted snapshot FLASH, the effects of magnetisation evolution during snapshot FLASH acquisition on image quality and parameter measurement accuracy were first investigated, through phantom experiments and computer simulations, in the context of a r2-weighted snapshot FLASH sequence. It was demonstrated that magnetisation evolution effects can lead to significant error in parameter measurement, but that this error can be eliminated by using crusher gradients to prevent evolved magnetisation from contributing to the acquired signal. However, qualitative effects are not entirely eliminated, since a significant degree of edge blurring may remain, and there is a 50% loss of SNR inherent to the crusher gradient technique. It was then shown, theoretically and experimentally, that in diffusion-weighted snapshot FLASH, the crusher gradient technique not only addresses the problem of magnetisation evolution, but also eliminates the effect of phase shifts arising during the diffusion-preparation sequence.

<p> <b>Introduction:</b> Endovascular chemotherapy treatment allows localized delivery adjacent to the target tumor; allowing an increased dosage and decreased leakage to other areas. It also allows for the opportunity to filter chemotherapy escaping the target tumor and entering the bloodstream. The ChemoFilter - a temporarily deployable, endovascular device will do just that; reducing systemic toxicity thus reducing adverse side effects from chemotherapy treatment. This will allow further increased dosage, increased tumor suppression, and increased tolerance to treatment. ChemoFilter has successfully filtered the chemotherapeutic Doxorubicin, but had yet to be tested in other chemotherapeutics. This study evaluates binding with new chemotherapeutics: Cisplatin, Carboplatin, and a cocktail comprised of Cisplatin and Doxorubicin.</p><p> <b>Materials and Methods:</b> ChemoFilter prototypes based on: 1.) Genomic DNA and 2.) Dowex (ion-exchange) resin, were evaluated for their ability to bind chemotherapy in vitro in phosphate-buffered saline (PBS). ChemoFilter was tested free in solution and encapsulated in nylon or polyester mesh packets of various dimensions. Concentrations were quantified using inductively coupled plasma mass spectrometry (IPC-MS), ultraviolet-visible spectrophotometry (UV-Vis), or fluorospectrometry. ¹¹C, ¹³C, and/or ¹⁴C radiolabeling Carboplatin began for in vitro and in vivo ChemoFilter quantification. In vitro quantification can include scintillation and/or gamma counting. In vivo may include Positron Emission Tomography (PET) imaging, Hyperpolarized ¹³C Magnetic Resonance Imaging (MRI), and/or Magnetic Resonance Spectroscopy (MRS) for real-time visualization. Reactions were verified using High Performance Liquid Chromatography (HPLC) for chemical species identification.</p><p> <b>Results and Discussion:</b> Results indicate significant and nearly complete, ~99% (p&lt;0.01) clearance of Cisplatin using the DNA ChemoFilter sequestered in Nylon mesh, quantified with gold standard ICP-MS (evidenced at 214 and 265 nm). The Ion-exchange ChemoFilter has significant clearance, within seconds, of both Doxorubicin and Cisplatin mixed in a cocktail solution. However, it appears some Cisplatin is binding to the Nylon Mesh itself. Size, shape, and material of the mesh have been optimized. A potential mechanism for ¹¹C, ¹³C, or ¹⁴C radiolabeling of Carboplatin has been developed and early results have been successful. ChemoFilter works much more efficiently when sequestered in nylon packets of specific geometries. Significant improvements have been made to ChemoFilter, moving the device closer to clinical trials.</p>